HBASE-13665 Fix docs and site building on branch-1
This commit is contained in:
Nick Dimiduk
parent
95f1fe52ed
commit
33fe79cf6f
177
pom.xml
177
pom.xml
|
|
@ -837,14 +837,21 @@
|
|||
</executions>
|
||||
<configuration>
|
||||
<transformationSets>
|
||||
<!-- For asciidoc -->
|
||||
<transformationSet>
|
||||
<!--Reaching up and over into common sub-module for hbase-default.xml-->
|
||||
<dir>${basedir}/hbase-common/src/main/resources/</dir>
|
||||
<includes>
|
||||
<include>hbase-default.xml</include>
|
||||
</includes>
|
||||
<stylesheet>${basedir}/src/main/xslt/configuration_to_docbook_section.xsl</stylesheet>
|
||||
<outputDir>${basedir}/target/docbkx</outputDir>
|
||||
<stylesheet>${basedir}/src/main/xslt/configuration_to_asciidoc_chapter.xsl</stylesheet>
|
||||
<fileMappers>
|
||||
<fileMapper implementation="org.codehaus.plexus.components.io.filemappers.RegExpFileMapper">
|
||||
<pattern>^(.*)\.xml$</pattern>
|
||||
<replacement>$1.adoc</replacement>
|
||||
</fileMapper>
|
||||
</fileMappers>
|
||||
<outputDir>${basedir}/target/asciidoc</outputDir>
|
||||
</transformationSet>
|
||||
</transformationSets>
|
||||
</configuration>
|
||||
|
|
@ -881,62 +888,6 @@
|
|||
<suppressionsLocation>hbase/checkstyle-suppressions.xml</suppressionsLocation>
|
||||
</configuration>
|
||||
</plugin>
|
||||
<!--Build the documentation. We build it twice. Once as a single page and then
|
||||
again as multipage.-->
|
||||
<plugin>
|
||||
<groupId>com.agilejava.docbkx</groupId>
|
||||
<artifactId>docbkx-maven-plugin</artifactId>
|
||||
<version>2.0.15</version>
|
||||
<inherited>false</inherited>
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>org.docbook</groupId>
|
||||
<artifactId>docbook-xml</artifactId>
|
||||
<version>4.4</version>
|
||||
<scope>runtime</scope>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
<configuration>
|
||||
<sourceDirectory>${basedir}/src/main/docbkx</sourceDirectory>
|
||||
<xincludeSupported>true</xincludeSupported>
|
||||
<useIdAsFilename>true</useIdAsFilename>
|
||||
<sectionAutolabelMaxDepth>100</sectionAutolabelMaxDepth>
|
||||
<sectionAutolabel>true</sectionAutolabel>
|
||||
<sectionLabelIncludesComponentLabel>true</sectionLabelIncludesComponentLabel>
|
||||
<htmlCustomization>${basedir}/src/main/docbkx/customization.xsl</htmlCustomization>
|
||||
<tocMaxDepth>2</tocMaxDepth>
|
||||
<insertXrefPageNumber>yes</insertXrefPageNumber>
|
||||
<chunkerOutputEncoding>UTF-8</chunkerOutputEncoding>
|
||||
</configuration>
|
||||
<executions>
|
||||
<execution>
|
||||
<id>multipage</id>
|
||||
<goals>
|
||||
<goal>generate-html</goal>
|
||||
</goals>
|
||||
<phase>pre-site</phase>
|
||||
<configuration>
|
||||
<navigShowtitles>true</navigShowtitles>
|
||||
<chunkedOutput>true</chunkedOutput>
|
||||
<imgSrcPath>../images/</imgSrcPath>
|
||||
<htmlStylesheet>../css/freebsd_docbook.css</htmlStylesheet>
|
||||
<targetDirectory>${basedir}/target/docbkx/book</targetDirectory>
|
||||
</configuration>
|
||||
</execution>
|
||||
<execution>
|
||||
<id>onepage</id>
|
||||
<goals>
|
||||
<goal>generate-html</goal>
|
||||
</goals>
|
||||
<phase>pre-site</phase>
|
||||
<configuration>
|
||||
<imgSrcPath>images/</imgSrcPath>
|
||||
<htmlStylesheet>css/freebsd_docbook.css</htmlStylesheet>
|
||||
<targetDirectory>${basedir}/target/docbkx/</targetDirectory>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-resources-plugin</artifactId>
|
||||
|
|
@ -962,18 +913,37 @@
|
|||
</configuration>
|
||||
</execution>
|
||||
<execution>
|
||||
<id>copy-docbkx</id>
|
||||
<id>copy-htaccess</id>
|
||||
<goals>
|
||||
<goal>copy-resources</goal>
|
||||
</goals>
|
||||
<phase>site</phase>
|
||||
<phase>post-site</phase>
|
||||
<configuration>
|
||||
<outputDirectory>target/site</outputDirectory>
|
||||
<outputDirectory>${basedir}/target/site</outputDirectory>
|
||||
<resources>
|
||||
<resource>
|
||||
<directory>${basedir}/target/docbkx</directory>
|
||||
<directory>${basedir}/src/main/site/resources/</directory>
|
||||
<includes>
|
||||
<include>**/**</include>
|
||||
<include>.htaccess</include>
|
||||
</includes>
|
||||
</resource>
|
||||
</resources>
|
||||
</configuration>
|
||||
</execution>
|
||||
<!-- needed to make the redirect above work -->
|
||||
<execution>
|
||||
<id>copy-empty-book-dir</id>
|
||||
<goals>
|
||||
<goal>copy-resources</goal>
|
||||
</goals>
|
||||
<phase>post-site</phase>
|
||||
<configuration>
|
||||
<outputDirectory>${basedir}/target/site</outputDirectory>
|
||||
<resources>
|
||||
<resource>
|
||||
<directory>${basedir}/src/main/site/resources/</directory>
|
||||
<includes>
|
||||
<include>book/**</include>
|
||||
</includes>
|
||||
</resource>
|
||||
</resources>
|
||||
|
|
@ -1008,6 +978,12 @@
|
|||
<artifactId>velocity</artifactId>
|
||||
<version>1.7</version>
|
||||
</dependency>
|
||||
<!-- For building docs from asciidoctor -->
|
||||
<!--<dependency>
|
||||
<groupId>org.asciidoctor</groupId>
|
||||
<artifactId>asciidoctor-maven-plugin</artifactId>
|
||||
<version>1.5.2</version>
|
||||
</dependency>-->
|
||||
</dependencies>
|
||||
<configuration>
|
||||
<siteDirectory>${basedir}/src/main/site</siteDirectory>
|
||||
|
|
@ -1015,6 +991,81 @@
|
|||
<outputEncoding>UTF-8</outputEncoding>
|
||||
</configuration>
|
||||
</plugin>
|
||||
<!-- For AsciiDoc docs building -->
|
||||
<plugin>
|
||||
<groupId>org.asciidoctor</groupId>
|
||||
<artifactId>asciidoctor-maven-plugin</artifactId>
|
||||
<version>1.5.2</version>
|
||||
<inherited>false</inherited>
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>org.asciidoctor</groupId>
|
||||
<artifactId>asciidoctorj-pdf</artifactId>
|
||||
<version>1.5.0-alpha.6</version>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
<configuration>
|
||||
<outputDirectory>target/site</outputDirectory>
|
||||
<doctype>book</doctype>
|
||||
<imagesDir>images</imagesDir>
|
||||
<sourceHighlighter>coderay</sourceHighlighter>
|
||||
<attributes>
|
||||
<docVersion>${project.version}</docVersion>
|
||||
</attributes>
|
||||
</configuration>
|
||||
<executions>
|
||||
<execution>
|
||||
<id>output-html</id>
|
||||
<phase>site</phase>
|
||||
<goals>
|
||||
<goal>process-asciidoc</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<attributes>
|
||||
<stylesheet>hbase.css</stylesheet>
|
||||
</attributes>
|
||||
<backend>html5</backend>
|
||||
</configuration>
|
||||
</execution>
|
||||
<execution>
|
||||
<id>output-pdf</id>
|
||||
<phase>site</phase>
|
||||
<goals>
|
||||
<goal>process-asciidoc</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<backend>pdf</backend>
|
||||
<attributes>
|
||||
<pagenums/>
|
||||
<toc/>
|
||||
<idprefix/>
|
||||
<idseparator>-</idseparator>
|
||||
</attributes>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<artifactId>maven-antrun-plugin</artifactId>
|
||||
<version>${maven.antrun.version}</version>
|
||||
<inherited>false</inherited>
|
||||
<!-- Rename the book.pdf generated by asciidoctor -->
|
||||
<executions>
|
||||
<execution>
|
||||
<id>rename-pdf</id>
|
||||
<phase>post-site</phase>
|
||||
<configuration>
|
||||
<target name="rename file">
|
||||
<move file="${project.basedir}/target/site/book.pdf" tofile="${project.basedir}/target/site/apache_hbase_reference_guide.pdf" />
|
||||
<move file="${project.basedir}/target/site/book.pdfmarks" tofile="${project.basedir}/target/site/apache_hbase_reference_guide.pdfmarks" />
|
||||
</target>
|
||||
</configuration>
|
||||
<goals>
|
||||
<goal>run</goal>
|
||||
</goals>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<groupId>org.jacoco</groupId>
|
||||
<artifactId>jacoco-maven-plugin</artifactId>
|
||||
|
|
|
|||
|
|
@ -0,0 +1,161 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[appendix_acl_matrix]]
|
||||
== Access Control Matrix
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
:toc: left
|
||||
:source-language: java
|
||||
|
||||
The following matrix shows the permission set required to perform operations in HBase.
|
||||
Before using the table, read through the information about how to interpret it.
|
||||
|
||||
.Interpreting the ACL Matrix Table
|
||||
The following conventions are used in the ACL Matrix table:
|
||||
|
||||
=== Scopes
|
||||
Permissions are evaluated starting at the widest scope and working to the narrowest scope.
|
||||
|
||||
A scope corresponds to a level of the data model. From broadest to narrowest, the scopes are as follows:
|
||||
|
||||
.Scopes
|
||||
* Global
|
||||
* Namespace (NS)
|
||||
* Table
|
||||
* Column Family (CF)
|
||||
* Column Qualifier (CQ)
|
||||
* Cell
|
||||
|
||||
For instance, a permission granted at table level dominates any grants done at the Column Family, Column Qualifier, or cell level. The user can do what that grant implies at any location in the table. A permission granted at global scope dominates all: the user is always allowed to take that action everywhere.
|
||||
|
||||
=== Permissions
|
||||
Possible permissions include the following:
|
||||
|
||||
.Permissions
|
||||
* Superuser - a special user that belongs to group "supergroup" and has unlimited access
|
||||
* Admin (A)
|
||||
* Create \(C)
|
||||
* Write (W)
|
||||
* Read \(R)
|
||||
* Execute (X)
|
||||
|
||||
For the most part, permissions work in an expected way, with the following caveats:
|
||||
|
||||
Having Write permission does not imply Read permission.::
|
||||
It is possible and sometimes desirable for a user to be able to write data that same user cannot read. One such example is a log-writing process.
|
||||
The [systemitem]+hbase:meta+ table is readable by every user, regardless of the user's other grants or restrictions.::
|
||||
This is a requirement for HBase to function correctly.
|
||||
`CheckAndPut` and `CheckAndDelete` operations will fail if the user does not have both Write and Read permission.::
|
||||
`Increment` and `Append` operations do not require Read access.::
|
||||
The `superuser`, as the name suggests has permissions to perform all possible operations.::
|
||||
And for the operations marked with *, the checks are done in post hook and only subset of results satisfying access checks are returned back to the user.::
|
||||
|
||||
The following table is sorted by the interface that provides each operation.
|
||||
In case the table goes out of date, the unit tests which check for accuracy of permissions can be found in _hbase-server/src/test/java/org/apache/hadoop/hbase/security/access/TestAccessController.java_, and the access controls themselves can be examined in _hbase-server/src/main/java/org/apache/hadoop/hbase/security/access/AccessController.java_.
|
||||
|
||||
.ACL Matrix
|
||||
[cols="1,1,1", frame="all", options="header"]
|
||||
|===
|
||||
| Interface | Operation | Permissions
|
||||
| Master | createTable | superuser\|global\(C)\|NS\(C)
|
||||
| | modifyTable | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | deleteTable | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | truncateTable | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | addColumn | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | modifyColumn | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)\|column(A)\|column\(C)
|
||||
| | deleteColumn | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)\|column(A)\|column\(C)
|
||||
| | enableTable | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | disableTable | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | disableAclTable | Not allowed
|
||||
| | move | superuser\|global(A)\|NS(A)\|TableOwner\|table(A)
|
||||
| | assign | superuser\|global(A)\|NS(A)\|TableOwner\|table(A)
|
||||
| | unassign | superuser\|global(A)\|NS(A)\|TableOwner\|table(A)
|
||||
| | regionOffline | superuser\|global(A)\|NS(A)\|TableOwner\|table(A)
|
||||
| | balance | superuser\|global(A)
|
||||
| | balanceSwitch | superuser\|global(A)
|
||||
| | shutdown | superuser\|global(A)
|
||||
| | stopMaster | superuser\|global(A)
|
||||
| | snapshot | superuser\|global(A)\|NS(A)\|TableOwner\|table(A)
|
||||
| | listSnapshot | superuser\|global(A)\|SnapshotOwner
|
||||
| | cloneSnapshot | superuser\|global(A)
|
||||
| | restoreSnapshot | superuser\|global(A)\|SnapshotOwner & (NS(A)\|TableOwner\|table(A))
|
||||
| | deleteSnapshot | superuser\|global(A)\|SnapshotOwner
|
||||
| | createNamespace | superuser\|global(A)
|
||||
| | deleteNamespace | superuser\|global(A)
|
||||
| | modifyNamespace | superuser\|global(A)
|
||||
| | getNamespaceDescriptor | superuser\|global(A)\|NS(A)
|
||||
| | listNamespaceDescriptors* | superuser\|global(A)\|NS(A)
|
||||
| | flushTable | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | getTableDescriptors* | superuser\|global(A)\|global\(C)\|NS(A)\|NS\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | getTableNames* | superuser\|TableOwner\|Any global or table perm
|
||||
| | setUserQuota(global level) | superuser\|global(A)
|
||||
| | setUserQuota(namespace level) | superuser\|global(A)
|
||||
| | setUserQuota(Table level) | superuser\|global(A)\|NS(A)\|TableOwner\|table(A)
|
||||
| | setTableQuota | superuser\|global(A)\|NS(A)\|TableOwner\|table(A)
|
||||
| | setNamespaceQuota | superuser\|global(A)
|
||||
| Region | openRegion | superuser\|global(A)
|
||||
| | closeRegion | superuser\|global(A)
|
||||
| | flush | superuser\|global(A)\|global\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | split | superuser\|global(A)\|TableOwner\|TableOwner\|table(A)
|
||||
| | compact | superuser\|global(A)\|global\(C)\|TableOwner\|table(A)\|table\(C)
|
||||
| | getClosestRowBefore | superuser\|global\(R)\|NS\(R)\|TableOwner\|table\(R)\|CF\(R)\|CQ\(R)
|
||||
| | getOp | superuser\|global\(R)\|NS\(R)\|TableOwner\|table\(R)\|CF\(R)\|CQ\(R)
|
||||
| | exists | superuser\|global\(R)\|NS\(R)\|TableOwner\|table\(R)\|CF\(R)\|CQ\(R)
|
||||
| | put | superuser\|global(W)\|NS(W)\|table(W)\|TableOwner\|CF(W)\|CQ(W)
|
||||
| | delete | superuser\|global(W)\|NS(W)\|table(W)\|TableOwner\|CF(W)\|CQ(W)
|
||||
| | batchMutate | superuser\|global(W)\|NS(W)\|TableOwner\|table(W)\|CF(W)\|CQ(W)
|
||||
| | checkAndPut | superuser\|global(RW)\|NS(RW)\|TableOwner\|table(RW)\|CF(RW)\|CQ(RW)
|
||||
| | checkAndPutAfterRowLock | superuser\|global\(R)\|NS\(R)\|TableOwner\|Table\(R)\|CF\(R)\|CQ\(R)
|
||||
| | checkAndDelete | superuser\|global(RW)\|NS(RW)\|TableOwner\|table(RW)\|CF(RW)\|CQ(RW)
|
||||
| | checkAndDeleteAfterRowLock | superuser\|global\(R)\|NS\(R)\|TableOwner\|table\(R)\|CF\(R)\|CQ\(R)
|
||||
| | incrementColumnValue | superuser\|global(W)\|NS(W)\|TableOwner\|table(W)\|CF(W)\|CQ(W)
|
||||
| | append | superuser\|global(W)\|NS(W)\|TableOwner\|table(W)\|CF(W)\|CQ(W)
|
||||
| | appendAfterRowLock | superuser\|global(W)\|NS(W)\|TableOwner\|table(W)\|CF(W)\|CQ(W)
|
||||
| | increment | superuser\|global(W)\|NS(W)\|TableOwner\|table(W)\|CF(W)\|CQ(W)
|
||||
| | incrementAfterRowLock | superuser\|global(W)\|NS(W)\|TableOwner\|table(W)\|CF(W)\|CQ(W)
|
||||
| | scannerOpen | superuser\|global\(R)\|NS\(R)\|TableOwner\|table\(R)\|CF\(R)\|CQ\(R)
|
||||
| | scannerNext | superuser\|global\(R)\|NS\(R)\|TableOwner\|table\(R)\|CF\(R)\|CQ\(R)
|
||||
| | scannerClose | superuser\|global\(R)\|NS\(R)\|TableOwner\|table\(R)\|CF\(R)\|CQ\(R)
|
||||
| | bulkLoadHFile | superuser\|global\(C)\|TableOwner\|table\(C)\|CF\(C)
|
||||
| | prepareBulkLoad | superuser\|global\(C)\|TableOwner\|table\(C)\|CF\(C)
|
||||
| | cleanupBulkLoad | superuser\|global\(C)\|TableOwner\|table\(C)\|CF\(C)
|
||||
| Endpoint | invoke | superuser\|global(X)\|NS(X)\|TableOwner\|table(X)
|
||||
| AccessController | grant(global level) | global(A)
|
||||
| | grant(namespace level) | global(A)\|NS(A)
|
||||
| | grant(table level) | global(A)\|NS(A)\|TableOwner\|table(A)\|CF(A)\|CQ(A)
|
||||
| | revoke(global level) | global(A)
|
||||
| | revoke(namespace level) | global(A)\|NS(A)
|
||||
| | revoke(table level) | global(A)\|NS(A)\|TableOwner\|table(A)\|CF(A)\|CQ(A)
|
||||
| | getUserPermissions(global level) | global(A)
|
||||
| | getUserPermissions(namespace level) | global(A)\|NS(A)
|
||||
| | getUserPermissions(table level) | global(A)\|NS(A)\|TableOwner\|table(A)\|CF(A)\|CQ(A)
|
||||
| RegionServer | stopRegionServer | superuser\|global(A)
|
||||
| | mergeRegions | superuser\|global(A)
|
||||
| | rollWALWriterRequest | superuser\|global(A)
|
||||
| | replicateLogEntries | superuser\|global(W)
|
||||
|===
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,395 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[appendix_contributing_to_documentation]]
|
||||
== Contributing to Documentation
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
:toc: left
|
||||
:source-language: java
|
||||
|
||||
The Apache HBase project welcomes contributions to all aspects of the project, including the documentation.
|
||||
|
||||
In HBase, documentation includes the following areas, and probably some others:
|
||||
|
||||
* The link:http://hbase.apache.org/book.html[HBase Reference
|
||||
Guide] (this book)
|
||||
* The link:http://hbase.apache.org/[HBase website]
|
||||
* The link:http://wiki.apache.org/hadoop/Hbase[HBase
|
||||
Wiki]
|
||||
* API documentation
|
||||
* Command-line utility output and help text
|
||||
* Web UI strings, explicit help text, context-sensitive strings, and others
|
||||
* Log messages
|
||||
* Comments in source files, configuration files, and others
|
||||
* Localization of any of the above into target languages other than English
|
||||
|
||||
No matter which area you want to help out with, the first step is almost always to download (typically by cloning the Git repository) and familiarize yourself with the HBase source code.
|
||||
The only exception in the list above is the HBase Wiki, which is edited online.
|
||||
For information on downloading and building the source, see <<developer,developer>>.
|
||||
|
||||
=== Getting Access to the Wiki
|
||||
|
||||
The HBase Wiki is not well-maintained and much of its content has been moved into the HBase Reference Guide (this guide). However, some pages on the Wiki are well maintained, and it would be great to have some volunteers willing to help out with the Wiki.
|
||||
To request access to the Wiki, register a new account at link:https://wiki.apache.org/hadoop/Hbase?action=newaccount[https://wiki.apache.org/hadoop/Hbase?action=newaccount].
|
||||
Contact one of the HBase committers, who can either give you access or refer you to someone who can.
|
||||
|
||||
=== Contributing to Documentation or Other Strings
|
||||
|
||||
If you spot an error in a string in a UI, utility, script, log message, or elsewhere, or you think something could be made more clear, or you think text needs to be added where it doesn't currently exist, the first step is to file a JIRA.
|
||||
Be sure to set the component to `Documentation` in addition any other involved components.
|
||||
Most components have one or more default owners, who monitor new issues which come into those queues.
|
||||
Regardless of whether you feel able to fix the bug, you should still file bugs where you see them.
|
||||
|
||||
If you want to try your hand at fixing your newly-filed bug, assign it to yourself.
|
||||
You will need to clone the HBase Git repository to your local system and work on the issue there.
|
||||
When you have developed a potential fix, submit it for review.
|
||||
If it addresses the issue and is seen as an improvement, one of the HBase committers will commit it to one or more branches, as appropriate.
|
||||
|
||||
.Procedure: Suggested Work flow for Submitting Patches
|
||||
This procedure goes into more detail than Git pros will need, but is included in this appendix so that people unfamiliar with Git can feel confident contributing to HBase while they learn.
|
||||
|
||||
. If you have not already done so, clone the Git repository locally.
|
||||
You only need to do this once.
|
||||
. Fairly often, pull remote changes into your local repository by using the `git pull` command, while your master branch is checked out.
|
||||
. For each issue you work on, create a new branch.
|
||||
One convention that works well for naming the branches is to name a given branch the same as the JIRA it relates to:
|
||||
+
|
||||
----
|
||||
$ git checkout -b HBASE-123456
|
||||
----
|
||||
|
||||
. Make your suggested changes on your branch, committing your changes to your local repository often.
|
||||
If you need to switch to working on a different issue, remember to check out the appropriate branch.
|
||||
. When you are ready to submit your patch, first be sure that HBase builds cleanly and behaves as expected in your modified branch.
|
||||
If you have made documentation changes, be sure the documentation and website builds by running `mvn clean site`.
|
||||
+
|
||||
NOTE: Before you use the `site` target the very first time, be sure you have built HBase at least once, in order to fetch all the Maven dependencies you need.
|
||||
+
|
||||
----
|
||||
$ mvn clean install -DskipTests # Builds HBase
|
||||
----
|
||||
+
|
||||
----
|
||||
$ mvn clean site -DskipTests # Builds the website and documentation
|
||||
----
|
||||
+
|
||||
If any errors occur, address them.
|
||||
|
||||
. If it takes you several days or weeks to implement your fix, or you know that the area of the code you are working in has had a lot of changes lately, make sure you rebase your branch against the remote master and take care of any conflicts before submitting your patch.
|
||||
+
|
||||
----
|
||||
|
||||
$ git checkout HBASE-123456
|
||||
$ git rebase origin/master
|
||||
----
|
||||
|
||||
. Generate your patch against the remote master.
|
||||
Run the following command from the top level of your git repository (usually called `hbase`):
|
||||
+
|
||||
----
|
||||
$ git format-patch --stdout origin/master > HBASE-123456.patch
|
||||
----
|
||||
+
|
||||
The name of the patch should contain the JIRA ID.
|
||||
Look over the patch file to be sure that you did not change any additional files by accident and that there are no other surprises.
|
||||
When you are satisfied, attach the patch to the JIRA and click the btn:[Patch Available] button.
|
||||
A reviewer will review your patch.
|
||||
If you need to submit a new version of the patch, leave the old one on the JIRA and add a version number to the name of the new patch.
|
||||
|
||||
. After a change has been committed, there is no need to keep your local branch around.
|
||||
Instead you should run `git pull` to get the new change into your master branch.
|
||||
|
||||
=== Editing the HBase Website
|
||||
|
||||
The source for the HBase website is in the HBase source, in the _src/main/site/_ directory.
|
||||
Within this directory, source for the individual pages is in the _xdocs/_ directory, and images referenced in those pages are in the _images/_ directory.
|
||||
This directory also stores images used in the HBase Reference Guide.
|
||||
|
||||
The website's pages are written in an HTML-like XML dialect called xdoc, which has a reference guide at link:http://maven.apache.org/archives/maven-1.x/plugins/xdoc/reference/xdocs.html.
|
||||
You can edit these files in a plain-text editor, an IDE, or an XML editor such as XML Mind XML Editor (XXE) or Oxygen XML Author.
|
||||
|
||||
To preview your changes, build the website using the +mvn clean site
|
||||
-DskipTests+ command.
|
||||
The HTML output resides in the _target/site/_ directory.
|
||||
When you are satisfied with your changes, follow the procedure in <<submit_doc_patch_procedure,submit doc patch procedure>> to submit your patch.
|
||||
|
||||
=== HBase Reference Guide Style Guide and Cheat Sheet
|
||||
|
||||
The HBase Reference Guide is written in Asciidoc and built using link:http://asciidoctor.org[AsciiDoctor]. The following cheat sheet is included for your reference. More nuanced and comprehensive documentation is available at link:http://asciidoctor.org/docs/user-manual/.
|
||||
|
||||
.AsciiDoc Cheat Sheet
|
||||
[cols="1,1,a",options="header"]
|
||||
|===
|
||||
| Element Type | Desired Rendering | How to do it
|
||||
| A paragraph | a paragraph | Just type some text with a blank line at the top and bottom.
|
||||
| Add line breaks within a paragraph without adding blank lines | Manual line breaks | This will break + at the plus sign. Or prefix the whole paragraph with a line containing '[%hardbreaks]'
|
||||
| Give a title to anything | Colored italic bold differently-sized text | .MyTitle (no space between the period and the words) on the line before the thing to be titled
|
||||
| In-Line Code or commands | monospace | \`text`
|
||||
| In-line literal content (things to be typed exactly as shown) | bold mono | \*\`typethis`*
|
||||
| In-line replaceable content (things to substitute with your own values) | bold italic mono | \*\_typesomething_*
|
||||
| Code blocks with highlighting | monospace, highlighted, preserve space |
|
||||
........
|
||||
[source,java]
|
||||
----
|
||||
myAwesomeCode() {
|
||||
}
|
||||
----
|
||||
........
|
||||
| Code block included from a separate file | included just as though it were part of the main file |
|
||||
................
|
||||
[source,ruby]
|
||||
----
|
||||
include\::path/to/app.rb[]
|
||||
----
|
||||
................
|
||||
| Include only part of a separate file | Similar to Javadoc | See link:http://asciidoctor.org/docs/user-manual/#by-tagged-regions
|
||||
| Filenames, directory names, new terms | italic | \_hbase-default.xml_
|
||||
| External naked URLs | A link with the URL as link text |
|
||||
----
|
||||
link:http://www.google.com
|
||||
----
|
||||
|
||||
| External URLs with text | A link with arbitrary link text |
|
||||
----
|
||||
link:http://www.google.com[Google]
|
||||
----
|
||||
|
||||
| Create an internal anchor to cross-reference | not rendered |
|
||||
----
|
||||
[[anchor_name]]
|
||||
----
|
||||
| Cross-reference an existing anchor using its default title| an internal hyperlink using the element title if available, otherwise using the anchor name |
|
||||
----
|
||||
<<anchor_name>>
|
||||
----
|
||||
| Cross-reference an existing anchor using custom text | an internal hyperlink using arbitrary text |
|
||||
----
|
||||
<<anchor_name,Anchor Text>>
|
||||
----
|
||||
| A block image | The image with alt text |
|
||||
----
|
||||
image::sunset.jpg[Alt Text]
|
||||
----
|
||||
(put the image in the src/main/site/resources/images directory)
|
||||
| An inline image | The image with alt text, as part of the text flow |
|
||||
----
|
||||
image:sunset.jpg [Alt Text]
|
||||
----
|
||||
(only one colon)
|
||||
| Link to a remote image | show an image hosted elsewhere |
|
||||
----
|
||||
image::http://inkscape.org/doc/examples/tux.svg[Tux,250,350]
|
||||
----
|
||||
(or `image:`)
|
||||
| Add dimensions or a URL to the image | depends | inside the brackets after the alt text, specify width, height and/or link="http://my_link.com"
|
||||
| A footnote | subscript link which takes you to the footnote |
|
||||
----
|
||||
Some text.footnote:[The footnote text.]
|
||||
----
|
||||
| A note or warning with no title | The admonition image followed by the admonition |
|
||||
----
|
||||
NOTE:My note here
|
||||
----
|
||||
|
||||
----
|
||||
WARNING:My warning here
|
||||
----
|
||||
| A complex note | The note has a title and/or multiple paragraphs and/or code blocks or lists, etc |
|
||||
........
|
||||
.The Title
|
||||
[NOTE]
|
||||
====
|
||||
Here is the note text. Everything until the second set of four equals signs is part of the note.
|
||||
----
|
||||
some source code
|
||||
----
|
||||
====
|
||||
........
|
||||
| Bullet lists | bullet lists |
|
||||
----
|
||||
* list item 1
|
||||
----
|
||||
(see http://asciidoctor.org/docs/user-manual/#unordered-lists)
|
||||
| Numbered lists | numbered list |
|
||||
----
|
||||
. list item 2
|
||||
----
|
||||
(see http://asciidoctor.org/docs/user-manual/#ordered-lists)
|
||||
| Checklists | Checked or unchecked boxes |
|
||||
Checked:
|
||||
----
|
||||
- [*]
|
||||
----
|
||||
Unchecked:
|
||||
----
|
||||
- [ ]
|
||||
----
|
||||
| Multiple levels of lists | bulleted or numbered or combo |
|
||||
----
|
||||
. Numbered (1), at top level
|
||||
* Bullet (2), nested under 1
|
||||
* Bullet (3), nested under 1
|
||||
. Numbered (4), at top level
|
||||
* Bullet (5), nested under 4
|
||||
** Bullet (6), nested under 5
|
||||
- [x] Checked (7), at top level
|
||||
----
|
||||
| Labelled lists / variablelists | a list item title or summary followed by content |
|
||||
----
|
||||
Title:: content
|
||||
|
||||
Title::
|
||||
content
|
||||
----
|
||||
| Sidebars, quotes, or other blocks of text | a block of text, formatted differently from the default | Delimited using different delimiters, see link:http://asciidoctor.org/docs/user-manual/#built-in-blocks-summary. Some of the examples above use delimiters like \...., ----,====.
|
||||
........
|
||||
[example]
|
||||
====
|
||||
This is an example block.
|
||||
====
|
||||
|
||||
[source]
|
||||
----
|
||||
This is a source block.
|
||||
----
|
||||
|
||||
[note]
|
||||
====
|
||||
This is a note block.
|
||||
====
|
||||
|
||||
[quote]
|
||||
____
|
||||
This is a quote block.
|
||||
____
|
||||
........
|
||||
|
||||
If you want to insert literal Asciidoc content that keeps being interpreted, when in doubt, use eight dots as the delimiter at the top and bottom.
|
||||
| Nested Sections | chapter, section, sub-section, etc |
|
||||
----
|
||||
= Book (or chapter if the chapter can be built alone, see the leveloffset info below)
|
||||
|
||||
== Chapter (or section if the chapter is standalone)
|
||||
|
||||
=== Section (or subsection, etc)
|
||||
|
||||
==== Subsection
|
||||
----
|
||||
|
||||
and so on up to 6 levels (think carefully about going deeper than 4 levels, maybe you can just titled paragraphs or lists instead). Note that you can include a book inside another book by adding the `:leveloffset:+1` macro directive directly before your include, and resetting it to 0 directly after. See the _book.adoc_ source for examples, as this is how this guide handles chapters. *Don't do it for prefaces, glossaries, appendixes, or other special types of chapters.*
|
||||
|
||||
| Include one file from another | Content is included as though it were inline |
|
||||
|
||||
----
|
||||
include::[/path/to/file.adoc]
|
||||
----
|
||||
|
||||
For plenty of examples. see _book.adoc_.
|
||||
| A table | a table | See http://asciidoctor.org/docs/user-manual/#tables. Generally rows are separated by newlines and columns by pipes
|
||||
| Comment out a single line | A line is skipped during rendering |
|
||||
`+//+ This line won't show up`
|
||||
| Comment out a block | A section of the file is skipped during rendering |
|
||||
----
|
||||
////
|
||||
Nothing between the slashes will show up.
|
||||
////
|
||||
----
|
||||
| Highlight text for review | text shows up with yellow background |
|
||||
----
|
||||
Test between #hash marks# is highlighted yellow.
|
||||
----
|
||||
|===
|
||||
|
||||
|
||||
=== Auto-Generated Content
|
||||
|
||||
Some parts of the HBase Reference Guide, most notably <<config.files,config.files>>, are generated automatically, so that this area of the documentation stays in sync with the code.
|
||||
This is done by means of an XSLT transform, which you can examine in the source at _src/main/xslt/configuration_to_asciidoc_chapter.xsl_.
|
||||
This transforms the _hbase-common/src/main/resources/hbase-default.xml_ file into an Asciidoc output which can be included in the Reference Guide.
|
||||
Sometimes, it is necessary to add configuration parameters or modify their descriptions.
|
||||
Make the modifications to the source file, and they will be included in the Reference Guide when it is rebuilt.
|
||||
|
||||
It is possible that other types of content can and will be automatically generated from HBase source files in the future.
|
||||
|
||||
|
||||
=== Images in the HBase Reference Guide
|
||||
|
||||
You can include images in the HBase Reference Guide. It is important to include an image title if possible, and alternate text always.
|
||||
This allows screen readers to navigate to the image and also provides alternative text for the image.
|
||||
The following is an example of an image with a title and alternate text. Notice the double colon.
|
||||
|
||||
[source,asciidoc]
|
||||
----
|
||||
.My Image Title
|
||||
image::sunset.jpg[Alt Text]
|
||||
----
|
||||
|
||||
Here is an example of an inline image with alternate text. Notice the single colon. Inline images cannot have titles. They are generally small images like GUI buttons.
|
||||
|
||||
[source,asciidoc]
|
||||
----
|
||||
image:sunset.jpg[Alt Text]
|
||||
----
|
||||
|
||||
|
||||
When doing a local build, save the image to the _src/main/site/resources/images/_ directory.
|
||||
When you link to the image, do not include the directory portion of the path.
|
||||
The image will be copied to the appropriate target location during the build of the output.
|
||||
|
||||
When you submit a patch which includes adding an image to the HBase Reference Guide, attach the image to the JIRA.
|
||||
If the committer asks where the image should be committed, it should go into the above directory.
|
||||
|
||||
=== Adding a New Chapter to the HBase Reference Guide
|
||||
|
||||
If you want to add a new chapter to the HBase Reference Guide, the easiest way is to copy an existing chapter file, rename it, and change the ID (in double brackets) and title. Chapters are located in the _src/main/asciidoc/_chapters/_ directory.
|
||||
|
||||
Delete the existing content and create the new content.
|
||||
Then open the _src/main/asciidoc/book.adoc_ file, which is the main file for the HBase Reference Guide, and copy an existing `include` element to include your new chapter in the appropriate location.
|
||||
Be sure to add your new file to your Git repository before creating your patch.
|
||||
|
||||
When in doubt, check to see how other files have been included.
|
||||
|
||||
=== Common Documentation Issues
|
||||
|
||||
The following documentation issues come up often.
|
||||
Some of these are preferences, but others can create mysterious build errors or other problems.
|
||||
|
||||
[qanda]
|
||||
Isolate Changes for Easy Diff Review.::
|
||||
Be careful with pretty-printing or re-formatting an entire XML file, even if the formatting has degraded over time. If you need to reformat a file, do that in a separate JIRA where you do not change any content. Be careful because some XML editors do a bulk-reformat when you open a new file, especially if you use GUI mode in the editor.
|
||||
|
||||
Syntax Highlighting::
|
||||
The HBase Reference Guide uses `coderay` for syntax highlighting. To enable syntax highlighting for a given code listing, use the following type of syntax:
|
||||
+
|
||||
........
|
||||
[source,xml]
|
||||
----
|
||||
<name>My Name</name>
|
||||
----
|
||||
........
|
||||
+
|
||||
Several syntax types are supported. The most interesting ones for the HBase Reference Guide are `java`, `xml`, `sql`, and `bash`.
|
||||
|
||||
|
|
@ -0,0 +1,355 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
== HFile format
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
:toc: left
|
||||
:source-language: java
|
||||
|
||||
This appendix describes the evolution of the HFile format.
|
||||
|
||||
[[hfilev1]]
|
||||
=== HBase File Format (version 1)
|
||||
|
||||
As we will be discussing changes to the HFile format, it is useful to give a short overview of the original (HFile version 1) format.
|
||||
|
||||
[[hfilev1.overview]]
|
||||
==== Overview of Version 1
|
||||
|
||||
An HFile in version 1 format is structured as follows:
|
||||
|
||||
.HFile V1 Format
|
||||
image::hfile.png[HFile Version 1]
|
||||
|
||||
==== Block index format in version 1
|
||||
|
||||
The block index in version 1 is very straightforward.
|
||||
For each entry, it contains:
|
||||
|
||||
. Offset (long)
|
||||
. Uncompressed size (int)
|
||||
. Key (a serialized byte array written using Bytes.writeByteArray)
|
||||
.. Key length as a variable-length integer (VInt)
|
||||
.. Key bytes
|
||||
|
||||
|
||||
The number of entries in the block index is stored in the fixed file trailer, and has to be passed in to the method that reads the block index.
|
||||
One of the limitations of the block index in version 1 is that it does not provide the compressed size of a block, which turns out to be necessary for decompression.
|
||||
Therefore, the HFile reader has to infer this compressed size from the offset difference between blocks.
|
||||
We fix this limitation in version 2, where we store on-disk block size instead of uncompressed size, and get uncompressed size from the block header.
|
||||
|
||||
[[hfilev2]]
|
||||
=== HBase file format with inline blocks (version 2)
|
||||
|
||||
Note: this feature was introduced in HBase 0.92
|
||||
|
||||
==== Motivation
|
||||
|
||||
We found it necessary to revise the HFile format after encountering high memory usage and slow startup times caused by large Bloom filters and block indexes in the region server.
|
||||
Bloom filters can get as large as 100 MB per HFile, which adds up to 2 GB when aggregated over 20 regions.
|
||||
Block indexes can grow as large as 6 GB in aggregate size over the same set of regions.
|
||||
A region is not considered opened until all of its block index data is loaded.
|
||||
Large Bloom filters produce a different performance problem: the first get request that requires a Bloom filter lookup will incur the latency of loading the entire Bloom filter bit array.
|
||||
|
||||
To speed up region server startup we break Bloom filters and block indexes into multiple blocks and write those blocks out as they fill up, which also reduces the HFile writer's memory footprint.
|
||||
In the Bloom filter case, "filling up a block" means accumulating enough keys to efficiently utilize a fixed-size bit array, and in the block index case we accumulate an "index block" of the desired size.
|
||||
Bloom filter blocks and index blocks (we call these "inline blocks") become interspersed with data blocks, and as a side effect we can no longer rely on the difference between block offsets to determine data block length, as it was done in version 1.
|
||||
|
||||
HFile is a low-level file format by design, and it should not deal with application-specific details such as Bloom filters, which are handled at StoreFile level.
|
||||
Therefore, we call Bloom filter blocks in an HFile "inline" blocks.
|
||||
We also supply HFile with an interface to write those inline blocks.
|
||||
|
||||
Another format modification aimed at reducing the region server startup time is to use a contiguous "load-on-open" section that has to be loaded in memory at the time an HFile is being opened.
|
||||
Currently, as an HFile opens, there are separate seek operations to read the trailer, data/meta indexes, and file info.
|
||||
To read the Bloom filter, there are two more seek operations for its "data" and "meta" portions.
|
||||
In version 2, we seek once to read the trailer and seek again to read everything else we need to open the file from a contiguous block.
|
||||
|
||||
[[hfilev2.overview]]
|
||||
==== Overview of Version 2
|
||||
|
||||
The version of HBase introducing the above features reads both version 1 and 2 HFiles, but only writes version 2 HFiles.
|
||||
A version 2 HFile is structured as follows:
|
||||
|
||||
.HFile Version 2 Structure
|
||||
image:hfilev2.png[HFile Version 2]
|
||||
|
||||
==== Unified version 2 block format
|
||||
|
||||
In the version 2 every block in the data section contains the following fields:
|
||||
|
||||
. 8 bytes: Block type, a sequence of bytes equivalent to version 1's "magic records". Supported block types are:
|
||||
.. DATA – data blocks
|
||||
.. LEAF_INDEX – leaf-level index blocks in a multi-level-block-index
|
||||
.. BLOOM_CHUNK – Bloom filter chunks
|
||||
.. META – meta blocks (not used for Bloom filters in version 2 anymore)
|
||||
.. INTERMEDIATE_INDEX – intermediate-level index blocks in a multi-level blockindex
|
||||
.. ROOT_INDEX – root>level index blocks in a multi>level block index
|
||||
.. FILE_INFO – the ``file info'' block, a small key>value map of metadata
|
||||
.. BLOOM_META – a Bloom filter metadata block in the load>on>open section
|
||||
.. TRAILER – a fixed>size file trailer.
|
||||
As opposed to the above, this is not an HFile v2 block but a fixed>size (for each HFile version) data structure
|
||||
.. INDEX_V1 – this block type is only used for legacy HFile v1 block
|
||||
. Compressed size of the block's data, not including the header (int).
|
||||
+
|
||||
Can be used for skipping the current data block when scanning HFile data.
|
||||
. Uncompressed size of the block's data, not including the header (int)
|
||||
+
|
||||
This is equal to the compressed size if the compression algorithm is NONE
|
||||
. File offset of the previous block of the same type (long)
|
||||
+
|
||||
Can be used for seeking to the previous data/index block
|
||||
. Compressed data (or uncompressed data if the compression algorithm is NONE).
|
||||
|
||||
The above format of blocks is used in the following HFile sections:
|
||||
|
||||
Scanned block section::
|
||||
The section is named so because it contains all data blocks that need to be read when an HFile is scanned sequentially.
|
||||
Also contains leaf block index and Bloom chunk blocks.
|
||||
Non-scanned block section::
|
||||
This section still contains unified-format v2 blocks but it does not have to be read when doing a sequential scan.
|
||||
This section contains "meta" blocks and intermediate-level index blocks.
|
||||
|
||||
We are supporting "meta" blocks in version 2 the same way they were supported in version 1, even though we do not store Bloom filter data in these blocks anymore.
|
||||
|
||||
==== Block index in version 2
|
||||
|
||||
There are three types of block indexes in HFile version 2, stored in two different formats (root and non-root):
|
||||
|
||||
. Data index -- version 2 multi-level block index, consisting of:
|
||||
.. Version 2 root index, stored in the data block index section of the file
|
||||
.. Optionally, version 2 intermediate levels, stored in the non%root format in the data index section of the file. Intermediate levels can only be present if leaf level blocks are present
|
||||
.. Optionally, version 2 leaf levels, stored in the non%root format inline with data blocks
|
||||
. Meta index -- version 2 root index format only, stored in the meta index section of the file
|
||||
. Bloom index -- version 2 root index format only, stored in the ``load-on-open'' section as part of Bloom filter metadata.
|
||||
|
||||
==== Root block index format in version 2
|
||||
|
||||
This format applies to:
|
||||
|
||||
. Root level of the version 2 data index
|
||||
. Entire meta and Bloom indexes in version 2, which are always single-level.
|
||||
|
||||
A version 2 root index block is a sequence of entries of the following format, similar to entries of a version 1 block index, but storing on-disk size instead of uncompressed size.
|
||||
|
||||
. Offset (long)
|
||||
+
|
||||
This offset may point to a data block or to a deeper>level index block.
|
||||
|
||||
. On-disk size (int)
|
||||
. Key (a serialized byte array stored using Bytes.writeByteArray)
|
||||
+
|
||||
. Key (VInt)
|
||||
. Key bytes
|
||||
|
||||
|
||||
A single-level version 2 block index consists of just a single root index block.
|
||||
To read a root index block of version 2, one needs to know the number of entries.
|
||||
For the data index and the meta index the number of entries is stored in the trailer, and for the Bloom index it is stored in the compound Bloom filter metadata.
|
||||
|
||||
For a multi-level block index we also store the following fields in the root index block in the load-on-open section of the HFile, in addition to the data structure described above:
|
||||
|
||||
. Middle leaf index block offset
|
||||
. Middle leaf block on-disk size (meaning the leaf index block containing the reference to the ``middle'' data block of the file)
|
||||
. The index of the mid-key (defined below) in the middle leaf-level block.
|
||||
|
||||
|
||||
|
||||
These additional fields are used to efficiently retrieve the mid-key of the HFile used in HFile splits, which we define as the first key of the block with a zero-based index of (n – 1) / 2, if the total number of blocks in the HFile is n.
|
||||
This definition is consistent with how the mid-key was determined in HFile version 1, and is reasonable in general, because blocks are likely to be the same size on average, but we don't have any estimates on individual key/value pair sizes.
|
||||
|
||||
|
||||
|
||||
When writing a version 2 HFile, the total number of data blocks pointed to by every leaf-level index block is kept track of.
|
||||
When we finish writing and the total number of leaf-level blocks is determined, it is clear which leaf-level block contains the mid-key, and the fields listed above are computed.
|
||||
When reading the HFile and the mid-key is requested, we retrieve the middle leaf index block (potentially from the block cache) and get the mid-key value from the appropriate position inside that leaf block.
|
||||
|
||||
==== Non-root block index format in version 2
|
||||
|
||||
This format applies to intermediate-level and leaf index blocks of a version 2 multi-level data block index.
|
||||
Every non-root index block is structured as follows.
|
||||
|
||||
. numEntries: the number of entries (int).
|
||||
. entryOffsets: the ``secondary index'' of offsets of entries in the block, to facilitate a quick binary search on the key (numEntries + 1 int values). The last value is the total length of all entries in this index block.
|
||||
For example, in a non-root index block with entry sizes 60, 80, 50 the ``secondary index'' will contain the following int array: {0, 60, 140, 190}.
|
||||
. Entries.
|
||||
Each entry contains:
|
||||
+
|
||||
. Offset of the block referenced by this entry in the file (long)
|
||||
. On>disk size of the referenced block (int)
|
||||
. Key.
|
||||
The length can be calculated from entryOffsets.
|
||||
|
||||
|
||||
==== Bloom filters in version 2
|
||||
|
||||
In contrast with version 1, in a version 2 HFile Bloom filter metadata is stored in the load-on-open section of the HFile for quick startup.
|
||||
|
||||
. A compound Bloom filter.
|
||||
+
|
||||
. Bloom filter version = 3 (int). There used to be a DynamicByteBloomFilter class that had the Bloom filter version number 2
|
||||
. The total byte size of all compound Bloom filter chunks (long)
|
||||
. Number of hash functions (int
|
||||
. Type of hash functions (int)
|
||||
. The total key count inserted into the Bloom filter (long)
|
||||
. The maximum total number of keys in the Bloom filter (long)
|
||||
. The number of chunks (int)
|
||||
. Comparator class used for Bloom filter keys, a UTF>8 encoded string stored using Bytes.writeByteArray
|
||||
. Bloom block index in the version 2 root block index format
|
||||
|
||||
|
||||
==== File Info format in versions 1 and 2
|
||||
|
||||
The file info block is a serialized link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/io/HbaseMapWritable.html[HbaseMapWritable] (essentially a map from byte arrays to byte arrays) with the following keys, among others.
|
||||
StoreFile-level logic adds more keys to this.
|
||||
|
||||
[cols="1,1", frame="all"]
|
||||
|===
|
||||
|hfile.LASTKEY| The last key of the file (byte array)
|
||||
|hfile.AVG_KEY_LEN| The average key length in the file (int)
|
||||
|hfile.AVG_VALUE_LEN| The average value length in the file (int)
|
||||
|===
|
||||
|
||||
File info format did not change in version 2.
|
||||
However, we moved the file info to the final section of the file, which can be loaded as one block at the time the HFile is being opened.
|
||||
Also, we do not store comparator in the version 2 file info anymore.
|
||||
Instead, we store it in the fixed file trailer.
|
||||
This is because we need to know the comparator at the time of parsing the load-on-open section of the HFile.
|
||||
|
||||
==== Fixed file trailer format differences between versions 1 and 2
|
||||
|
||||
The following table shows common and different fields between fixed file trailers in versions 1 and 2.
|
||||
Note that the size of the trailer is different depending on the version, so it is ``fixed'' only within one version.
|
||||
However, the version is always stored as the last four-byte integer in the file.
|
||||
|
||||
.Differences between HFile Versions 1 and 2
|
||||
[cols="1,1", frame="all"]
|
||||
|===
|
||||
| Version 1 | Version 2
|
||||
| |File info offset (long)
|
||||
| Data index offset (long)| loadOnOpenOffset (long) /The offset of the sectionthat we need toload when opening the file./
|
||||
| | Number of data index entries (int)
|
||||
| metaIndexOffset (long) /This field is not being used by the version 1 reader, so we removed it from version 2./ | uncompressedDataIndexSize (long) /The total uncompressed size of the whole data block index, including root-level, intermediate-level, and leaf-level blocks./
|
||||
| | Number of meta index entries (int)
|
||||
| | Total uncompressed bytes (long)
|
||||
| numEntries (int) | numEntries (long)
|
||||
| Compression codec: 0 = LZO, 1 = GZ, 2 = NONE (int) | Compression codec: 0 = LZO, 1 = GZ, 2 = NONE (int)
|
||||
| | The number of levels in the data block index (int)
|
||||
| | firstDataBlockOffset (long) /The offset of the first first data block. Used when scanning./
|
||||
| | lastDataBlockEnd (long) /The offset of the first byte after the last key/value data block. We don't need to go beyond this offset when scanning./
|
||||
| Version: 1 (int) | Version: 2 (int)
|
||||
|===
|
||||
|
||||
|
||||
|
||||
==== getShortMidpointKey(an optimization for data index block)
|
||||
|
||||
Note: this optimization was introduced in HBase 0.95+
|
||||
|
||||
HFiles contain many blocks that contain a range of sorted Cells.
|
||||
Each cell has a key.
|
||||
To save IO when reading Cells, the HFile also has an index that maps a Cell's start key to the offset of the beginning of a particular block.
|
||||
Prior to this optimization, HBase would use the key of the first cell in each data block as the index key.
|
||||
|
||||
In HBASE-7845, we generate a new key that is lexicographically larger than the last key of the previous block and lexicographically equal or smaller than the start key of the current block.
|
||||
While actual keys can potentially be very long, this "fake key" or "virtual key" can be much shorter.
|
||||
For example, if the stop key of previous block is "the quick brown fox", the start key of current block is "the who", we could use "the r" as our virtual key in our hfile index.
|
||||
|
||||
There are two benefits to this:
|
||||
|
||||
* having shorter keys reduces the hfile index size, (allowing us to keep more indexes in memory), and
|
||||
* using something closer to the end key of the previous block allows us to avoid a potential extra IO when the target key lives in between the "virtual key" and the key of the first element in the target block.
|
||||
|
||||
This optimization (implemented by the getShortMidpointKey method) is inspired by LevelDB's ByteWiseComparatorImpl::FindShortestSeparator() and FindShortSuccessor().
|
||||
|
||||
[[hfilev3]]
|
||||
=== HBase File Format with Security Enhancements (version 3)
|
||||
|
||||
Note: this feature was introduced in HBase 0.98
|
||||
|
||||
[[hfilev3.motivation]]
|
||||
==== Motivation
|
||||
|
||||
Version 3 of HFile makes changes needed to ease management of encryption at rest and cell-level metadata (which in turn is needed for cell-level ACLs and cell-level visibility labels). For more information see <<hbase.encryption.server,hbase.encryption.server>>, <<hbase.tags,hbase.tags>>, <<hbase.accesscontrol.configuration,hbase.accesscontrol.configuration>>, and <<hbase.visibility.labels,hbase.visibility.labels>>.
|
||||
|
||||
[[hfilev3.overview]]
|
||||
==== Overview
|
||||
|
||||
The version of HBase introducing the above features reads HFiles in versions 1, 2, and 3 but only writes version 3 HFiles.
|
||||
Version 3 HFiles are structured the same as version 2 HFiles.
|
||||
For more information see <<hfilev2.overview,hfilev2.overview>>.
|
||||
|
||||
[[hvilev3.infoblock]]
|
||||
==== File Info Block in Version 3
|
||||
|
||||
Version 3 added two additional pieces of information to the reserved keys in the file info block.
|
||||
|
||||
[cols="1,1", frame="all"]
|
||||
|===
|
||||
| hfile.MAX_TAGS_LEN | The maximum number of bytes needed to store the serialized tags for any single cell in this hfile (int)
|
||||
| hfile.TAGS_COMPRESSED | Does the block encoder for this hfile compress tags? (boolean). Should only be present if hfile.MAX_TAGS_LEN is also present.
|
||||
|===
|
||||
|
||||
When reading a Version 3 HFile the presence of `MAX_TAGS_LEN` is used to determine how to deserialize the cells within a data block.
|
||||
Therefore, consumers must read the file's info block prior to reading any data blocks.
|
||||
|
||||
When writing a Version 3 HFile, HBase will always include `MAX_TAGS_LEN ` when flushing the memstore to underlying filesystem and when using prefix tree encoding for data blocks, as described in <<compression,compression>>.
|
||||
|
||||
When compacting extant files, the default writer will omit `MAX_TAGS_LEN` if all of the files selected do not themselves contain any cells with tags.
|
||||
|
||||
See <<compaction,compaction>> for details on the compaction file selection algorithm.
|
||||
|
||||
[[hfilev3.datablock]]
|
||||
==== Data Blocks in Version 3
|
||||
|
||||
Within an HFile, HBase cells are stored in data blocks as a sequence of KeyValues (see <<hfilev1.overview,hfilev1.overview>>, or link:http://www.larsgeorge.com/2009/10/hbase-architecture-101-storage.html[Lars George's
|
||||
excellent introduction to HBase Storage]). In version 3, these KeyValue optionally will include a set of 0 or more tags:
|
||||
|
||||
[cols="1,1", frame="all"]
|
||||
|===
|
||||
| Version 1 & 2, Version 3 without MAX_TAGS_LEN | Version 3 with MAX_TAGS_LEN
|
||||
2+| Key Length (4 bytes)
|
||||
2+| Value Length (4 bytes)
|
||||
2+| Key bytes (variable)
|
||||
2+| Value bytes (variable)
|
||||
| | Tags Length (2 bytes)
|
||||
| | Tags bytes (variable)
|
||||
|===
|
||||
|
||||
If the info block for a given HFile contains an entry for `MAX_TAGS_LEN` each cell will have the length of that cell's tags included, even if that length is zero.
|
||||
The actual tags are stored as a sequence of tag length (2 bytes), tag type (1 byte), tag bytes (variable). The format an individual tag's bytes depends on the tag type.
|
||||
|
||||
Note that the dependence on the contents of the info block implies that prior to reading any data blocks you must first process a file's info block.
|
||||
It also implies that prior to writing a data block you must know if the file's info block will include `MAX_TAGS_LEN`.
|
||||
|
||||
[[hfilev3.fixedtrailer]]
|
||||
==== Fixed File Trailer in Version 3
|
||||
|
||||
The fixed file trailers written with HFile version 3 are always serialized with protocol buffers.
|
||||
Additionally, it adds an optional field to the version 2 protocol buffer named encryption_key.
|
||||
If HBase is configured to encrypt HFiles this field will store a data encryption key for this particular HFile, encrypted with the current cluster master key using AES.
|
||||
For more information see <<hbase.encryption.server,hbase.encryption.server>>.
|
||||
|
||||
:numbered:
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,47 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[asf]]
|
||||
== HBase and the Apache Software Foundation
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
:toc: left
|
||||
:source-language: java
|
||||
|
||||
HBase is a project in the Apache Software Foundation and as such there are responsibilities to the ASF to ensure a healthy project.
|
||||
|
||||
[[asf.devprocess]]
|
||||
=== ASF Development Process
|
||||
|
||||
See the link:http://www.apache.org/dev/#committers[Apache Development Process page] for all sorts of information on how the ASF is structured (e.g., PMC, committers, contributors), to tips on contributing and getting involved, and how open-source works at ASF.
|
||||
|
||||
[[asf.reporting]]
|
||||
=== ASF Board Reporting
|
||||
|
||||
Once a quarter, each project in the ASF portfolio submits a report to the ASF board.
|
||||
This is done by the HBase project lead and the committers.
|
||||
See link:http://www.apache.org/foundation/board/reporting[ASF board reporting] for more information.
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,170 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[casestudies]]
|
||||
= Apache HBase Case Studies
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
[[casestudies.overview]]
|
||||
== Overview
|
||||
|
||||
This chapter will describe a variety of performance and troubleshooting case studies that can provide a useful blueprint on diagnosing Apache HBase cluster issues.
|
||||
|
||||
For more information on Performance and Troubleshooting, see <<performance>> and <<trouble>>.
|
||||
|
||||
[[casestudies.schema]]
|
||||
== Schema Design
|
||||
|
||||
See the schema design case studies here: <<schema.casestudies>>
|
||||
|
||||
[[casestudies.perftroub]]
|
||||
== Performance/Troubleshooting
|
||||
|
||||
[[casestudies.slownode]]
|
||||
=== Case Study #1 (Performance Issue On A Single Node)
|
||||
|
||||
==== Scenario
|
||||
|
||||
Following a scheduled reboot, one data node began exhibiting unusual behavior.
|
||||
Routine MapReduce jobs run against HBase tables which regularly completed in five or six minutes began taking 30 or 40 minutes to finish.
|
||||
These jobs were consistently found to be waiting on map and reduce tasks assigned to the troubled data node (e.g., the slow map tasks all had the same Input Split). The situation came to a head during a distributed copy, when the copy was severely prolonged by the lagging node.
|
||||
|
||||
==== Hardware
|
||||
|
||||
.Datanodes:
|
||||
* Two 12-core processors
|
||||
* Six Enerprise SATA disks
|
||||
* 24GB of RAM
|
||||
* Two bonded gigabit NICs
|
||||
|
||||
.Network:
|
||||
* 10 Gigabit top-of-rack switches
|
||||
* 20 Gigabit bonded interconnects between racks.
|
||||
|
||||
==== Hypotheses
|
||||
|
||||
===== HBase "Hot Spot" Region
|
||||
|
||||
We hypothesized that we were experiencing a familiar point of pain: a "hot spot" region in an HBase table, where uneven key-space distribution can funnel a huge number of requests to a single HBase region, bombarding the RegionServer process and cause slow response time.
|
||||
Examination of the HBase Master status page showed that the number of HBase requests to the troubled node was almost zero.
|
||||
Further, examination of the HBase logs showed that there were no region splits, compactions, or other region transitions in progress.
|
||||
This effectively ruled out a "hot spot" as the root cause of the observed slowness.
|
||||
|
||||
===== HBase Region With Non-Local Data
|
||||
|
||||
Our next hypothesis was that one of the MapReduce tasks was requesting data from HBase that was not local to the DataNode, thus forcing HDFS to request data blocks from other servers over the network.
|
||||
Examination of the DataNode logs showed that there were very few blocks being requested over the network, indicating that the HBase region was correctly assigned, and that the majority of the necessary data was located on the node.
|
||||
This ruled out the possibility of non-local data causing a slowdown.
|
||||
|
||||
===== Excessive I/O Wait Due To Swapping Or An Over-Worked Or Failing Hard Disk
|
||||
|
||||
After concluding that the Hadoop and HBase were not likely to be the culprits, we moved on to troubleshooting the DataNode's hardware.
|
||||
Java, by design, will periodically scan its entire memory space to do garbage collection.
|
||||
If system memory is heavily overcommitted, the Linux kernel may enter a vicious cycle, using up all of its resources swapping Java heap back and forth from disk to RAM as Java tries to run garbage collection.
|
||||
Further, a failing hard disk will often retry reads and/or writes many times before giving up and returning an error.
|
||||
This can manifest as high iowait, as running processes wait for reads and writes to complete.
|
||||
Finally, a disk nearing the upper edge of its performance envelope will begin to cause iowait as it informs the kernel that it cannot accept any more data, and the kernel queues incoming data into the dirty write pool in memory.
|
||||
However, using `vmstat(1)` and `free(1)`, we could see that no swap was being used, and the amount of disk IO was only a few kilobytes per second.
|
||||
|
||||
===== Slowness Due To High Processor Usage
|
||||
|
||||
Next, we checked to see whether the system was performing slowly simply due to very high computational load. `top(1)` showed that the system load was higher than normal, but `vmstat(1)` and `mpstat(1)` showed that the amount of processor being used for actual computation was low.
|
||||
|
||||
===== Network Saturation (The Winner)
|
||||
|
||||
Since neither the disks nor the processors were being utilized heavily, we moved on to the performance of the network interfaces.
|
||||
The DataNode had two gigabit ethernet adapters, bonded to form an active-standby interface. `ifconfig(8)` showed some unusual anomalies, namely interface errors, overruns, framing errors.
|
||||
While not unheard of, these kinds of errors are exceedingly rare on modern hardware which is operating as it should:
|
||||
|
||||
----
|
||||
|
||||
$ /sbin/ifconfig bond0
|
||||
bond0 Link encap:Ethernet HWaddr 00:00:00:00:00:00
|
||||
inet addr:10.x.x.x Bcast:10.x.x.255 Mask:255.255.255.0
|
||||
UP BROADCAST RUNNING MASTER MULTICAST MTU:1500 Metric:1
|
||||
RX packets:2990700159 errors:12 dropped:0 overruns:1 frame:6 <--- Look Here! Errors!
|
||||
TX packets:3443518196 errors:0 dropped:0 overruns:0 carrier:0
|
||||
collisions:0 txqueuelen:0
|
||||
RX bytes:2416328868676 (2.4 TB) TX bytes:3464991094001 (3.4 TB)
|
||||
----
|
||||
|
||||
These errors immediately lead us to suspect that one or more of the ethernet interfaces might have negotiated the wrong line speed.
|
||||
This was confirmed both by running an ICMP ping from an external host and observing round-trip-time in excess of 700ms, and by running `ethtool(8)` on the members of the bond interface and discovering that the active interface was operating at 100Mbs/, full duplex.
|
||||
|
||||
----
|
||||
|
||||
$ sudo ethtool eth0
|
||||
Settings for eth0:
|
||||
Supported ports: [ TP ]
|
||||
Supported link modes: 10baseT/Half 10baseT/Full
|
||||
100baseT/Half 100baseT/Full
|
||||
1000baseT/Full
|
||||
Supports auto-negotiation: Yes
|
||||
Advertised link modes: 10baseT/Half 10baseT/Full
|
||||
100baseT/Half 100baseT/Full
|
||||
1000baseT/Full
|
||||
Advertised pause frame use: No
|
||||
Advertised auto-negotiation: Yes
|
||||
Link partner advertised link modes: Not reported
|
||||
Link partner advertised pause frame use: No
|
||||
Link partner advertised auto-negotiation: No
|
||||
Speed: 100Mb/s <--- Look Here! Should say 1000Mb/s!
|
||||
Duplex: Full
|
||||
Port: Twisted Pair
|
||||
PHYAD: 1
|
||||
Transceiver: internal
|
||||
Auto-negotiation: on
|
||||
MDI-X: Unknown
|
||||
Supports Wake-on: umbg
|
||||
Wake-on: g
|
||||
Current message level: 0x00000003 (3)
|
||||
Link detected: yes
|
||||
----
|
||||
|
||||
In normal operation, the ICMP ping round trip time should be around 20ms, and the interface speed and duplex should read, "1000MB/s", and, "Full", respectively.
|
||||
|
||||
==== Resolution
|
||||
|
||||
After determining that the active ethernet adapter was at the incorrect speed, we used the `ifenslave(8)` command to make the standby interface the active interface, which yielded an immediate improvement in MapReduce performance, and a 10 times improvement in network throughput:
|
||||
|
||||
On the next trip to the datacenter, we determined that the line speed issue was ultimately caused by a bad network cable, which was replaced.
|
||||
|
||||
[[casestudies.perf.1]]
|
||||
=== Case Study #2 (Performance Research 2012)
|
||||
|
||||
Investigation results of a self-described "we're not sure what's wrong, but it seems slow" problem. http://gbif.blogspot.com/2012/03/hbase-performance-evaluation-continued.html
|
||||
|
||||
[[casestudies.perf.2]]
|
||||
=== Case Study #3 (Performance Research 2010))
|
||||
|
||||
Investigation results of general cluster performance from 2010.
|
||||
Although this research is on an older version of the codebase, this writeup is still very useful in terms of approach. http://hstack.org/hbase-performance-testing/
|
||||
|
||||
[[casestudies.max.transfer.threads]]
|
||||
=== Case Study #4 (max.transfer.threads Config)
|
||||
|
||||
Case study of configuring `max.transfer.threads` (previously known as `xcievers`) and diagnosing errors from misconfigurations. http://www.larsgeorge.com/2012/03/hadoop-hbase-and-xceivers.html
|
||||
|
||||
See also <<dfs.datanode.max.transfer.threads>>.
|
||||
|
|
@ -0,0 +1,111 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[community]]
|
||||
= Community
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
== Decisions
|
||||
|
||||
.Feature Branches
|
||||
|
||||
Feature Branches are easy to make.
|
||||
You do not have to be a committer to make one.
|
||||
Just request the name of your branch be added to JIRA up on the developer's mailing list and a committer will add it for you.
|
||||
Thereafter you can file issues against your feature branch in Apache HBase JIRA.
|
||||
Your code you keep elsewhere -- it should be public so it can be observed -- and you can update dev mailing list on progress.
|
||||
When the feature is ready for commit, 3 +1s from committers will get your feature merged.
|
||||
See link:http://search-hadoop.com/m/asM982C5FkS1[HBase, mail # dev - Thoughts
|
||||
about large feature dev branches]
|
||||
|
||||
[[patchplusonepolicy]]
|
||||
.Patch +1 Policy
|
||||
|
||||
The below policy is something we put in place 09/2012.
|
||||
It is a suggested policy rather than a hard requirement.
|
||||
We want to try it first to see if it works before we cast it in stone.
|
||||
|
||||
Apache HBase is made of link:https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel[components].
|
||||
Components have one or more <<owner,OWNER>>s.
|
||||
See the 'Description' field on the link:https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel[components] JIRA page for who the current owners are by component.
|
||||
|
||||
Patches that fit within the scope of a single Apache HBase component require, at least, a +1 by one of the component's owners before commit.
|
||||
If owners are absent -- busy or otherwise -- two +1s by non-owners will suffice.
|
||||
|
||||
Patches that span components need at least two +1s before they can be committed, preferably +1s by owners of components touched by the x-component patch (TODO: This needs tightening up but I think fine for first pass).
|
||||
|
||||
Any -1 on a patch by anyone vetos a patch; it cannot be committed until the justification for the -1 is addressed.
|
||||
|
||||
[[hbase.fix.version.in.jira]]
|
||||
.How to set fix version in JIRA on issue resolve
|
||||
|
||||
Here is how link:http://search-hadoop.com/m/azemIi5RCJ1[we agreed] to set versions in JIRA when we resolve an issue.
|
||||
If trunk is going to be 0.98.0 then:
|
||||
|
||||
* Commit only to trunk: Mark with 0.98
|
||||
* Commit to 0.95 and trunk : Mark with 0.98, and 0.95.x
|
||||
* Commit to 0.94.x and 0.95, and trunk: Mark with 0.98, 0.95.x, and 0.94.x
|
||||
* Commit to 89-fb: Mark with 89-fb.
|
||||
* Commit site fixes: no version
|
||||
|
||||
[[hbase.when.to.close.jira]]
|
||||
.Policy on when to set a RESOLVED JIRA as CLOSED
|
||||
|
||||
We link:http://search-hadoop.com/m/4cIKs1iwXMS1[agreed] that for issues that list multiple releases in their _Fix Version/s_ field, CLOSE the issue on the release of any of the versions listed; subsequent change to the issue must happen in a new JIRA.
|
||||
|
||||
[[no.permanent.state.in.zk]]
|
||||
.Only transient state in ZooKeeper!
|
||||
|
||||
You should be able to kill the data in zookeeper and hbase should ride over it recreating the zk content as it goes.
|
||||
This is an old adage around these parts.
|
||||
We just made note of it now.
|
||||
We also are currently in violation of this basic tenet -- replication at least keeps permanent state in zk -- but we are working to undo this breaking of a golden rule.
|
||||
|
||||
[[community.roles]]
|
||||
== Community Roles
|
||||
|
||||
[[owner]]
|
||||
.Component Owner/Lieutenant
|
||||
|
||||
Component owners are listed in the description field on this Apache HBase JIRA link:https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel[components] page.
|
||||
The owners are listed in the 'Description' field rather than in the 'Component Lead' field because the latter only allows us list one individual whereas it is encouraged that components have multiple owners.
|
||||
|
||||
Owners or component lieutenants are volunteers who are (usually, but not necessarily) expert in their component domain and may have an agenda on how they think their Apache HBase component should evolve.
|
||||
|
||||
. Owners will try and review patches that land within their component's scope.
|
||||
. If applicable, if an owner has an agenda, they will publish their goals or the design toward which they are driving their component
|
||||
|
||||
If you would like to be volunteer as a component owner, just write the dev list and we'll sign you up.
|
||||
Owners do not need to be committers.
|
||||
|
||||
[[hbase.commit.msg.format]]
|
||||
== Commit Message format
|
||||
|
||||
We link:http://search-hadoop.com/m/Gwxwl10cFHa1[agreed] to the following SVN commit message format:
|
||||
[source]
|
||||
----
|
||||
HBASE-xxxxx <title>. (<contributor>)
|
||||
----
|
||||
If the person making the commit is the contributor, leave off the '(<contributor>)' element.
|
||||
|
|
@ -0,0 +1,459 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[compression]]
|
||||
== Compression and Data Block Encoding In HBase(((Compression,Data BlockEncoding)))
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
NOTE: Codecs mentioned in this section are for encoding and decoding data blocks or row keys.
|
||||
For information about replication codecs, see <<cluster.replication.preserving.tags,cluster.replication.preserving.tags>>.
|
||||
|
||||
Some of the information in this section is pulled from a link:http://search-hadoop.com/m/lL12B1PFVhp1/v=threaded[discussion] on the HBase Development mailing list.
|
||||
|
||||
HBase supports several different compression algorithms which can be enabled on a ColumnFamily.
|
||||
Data block encoding attempts to limit duplication of information in keys, taking advantage of some of the fundamental designs and patterns of HBase, such as sorted row keys and the schema of a given table.
|
||||
Compressors reduce the size of large, opaque byte arrays in cells, and can significantly reduce the storage space needed to store uncompressed data.
|
||||
|
||||
Compressors and data block encoding can be used together on the same ColumnFamily.
|
||||
|
||||
.Changes Take Effect Upon Compaction
|
||||
If you change compression or encoding for a ColumnFamily, the changes take effect during compaction.
|
||||
|
||||
Some codecs take advantage of capabilities built into Java, such as GZip compression. Others rely on native libraries. Native libraries may be available as part of Hadoop, such as LZ4. In this case, HBase only needs access to the appropriate shared library.
|
||||
|
||||
Other codecs, such as Google Snappy, need to be installed first.
|
||||
Some codecs are licensed in ways that conflict with HBase's license and cannot be shipped as part of HBase.
|
||||
|
||||
This section discusses common codecs that are used and tested with HBase.
|
||||
No matter what codec you use, be sure to test that it is installed correctly and is available on all nodes in your cluster.
|
||||
Extra operational steps may be necessary to be sure that codecs are available on newly-deployed nodes.
|
||||
You can use the <<compression.test,compression.test>> utility to check that a given codec is correctly installed.
|
||||
|
||||
To configure HBase to use a compressor, see <<compressor.install,compressor.install>>.
|
||||
To enable a compressor for a ColumnFamily, see <<changing.compression,changing.compression>>.
|
||||
To enable data block encoding for a ColumnFamily, see <<data.block.encoding.enable,data.block.encoding.enable>>.
|
||||
|
||||
.Block Compressors
|
||||
* none
|
||||
* Snappy
|
||||
* LZO
|
||||
* LZ4
|
||||
* GZ
|
||||
|
||||
.Data Block Encoding Types
|
||||
Prefix::
|
||||
Often, keys are very similar. Specifically, keys often share a common prefix and only differ near the end. For instance, one key might be `RowKey:Family:Qualifier0` and the next key might be `RowKey:Family:Qualifier1`.
|
||||
+
|
||||
In Prefix encoding, an extra column is added which holds the length of the prefix shared between the current key and the previous key.
|
||||
Assuming the first key here is totally different from the key before, its prefix length is 0.
|
||||
+
|
||||
The second key's prefix length is `23`, since they have the first 23 characters in common.
|
||||
+
|
||||
Obviously if the keys tend to have nothing in common, Prefix will not provide much benefit.
|
||||
+
|
||||
The following image shows a hypothetical ColumnFamily with no data block encoding.
|
||||
+
|
||||
.ColumnFamily with No Encoding
|
||||
image::data_block_no_encoding.png[]
|
||||
+
|
||||
Here is the same data with prefix data encoding.
|
||||
+
|
||||
.ColumnFamily with Prefix Encoding
|
||||
image::data_block_prefix_encoding.png[]
|
||||
|
||||
Diff::
|
||||
Diff encoding expands upon Prefix encoding.
|
||||
Instead of considering the key sequentially as a monolithic series of bytes, each key field is split so that each part of the key can be compressed more efficiently.
|
||||
+
|
||||
Two new fields are added: timestamp and type.
|
||||
+
|
||||
If the ColumnFamily is the same as the previous row, it is omitted from the current row.
|
||||
+
|
||||
If the key length, value length or type are the same as the previous row, the field is omitted.
|
||||
+
|
||||
In addition, for increased compression, the timestamp is stored as a Diff from the previous row's timestamp, rather than being stored in full.
|
||||
Given the two row keys in the Prefix example, and given an exact match on timestamp and the same type, neither the value length, or type needs to be stored for the second row, and the timestamp value for the second row is just 0, rather than a full timestamp.
|
||||
+
|
||||
Diff encoding is disabled by default because writing and scanning are slower but more data is cached.
|
||||
+
|
||||
This image shows the same ColumnFamily from the previous images, with Diff encoding.
|
||||
+
|
||||
.ColumnFamily with Diff Encoding
|
||||
image::data_block_diff_encoding.png[]
|
||||
|
||||
Fast Diff::
|
||||
Fast Diff works similar to Diff, but uses a faster implementation. It also adds another field which stores a single bit to track whether the data itself is the same as the previous row. If it is, the data is not stored again.
|
||||
+
|
||||
Fast Diff is the recommended codec to use if you have long keys or many columns.
|
||||
+
|
||||
The data format is nearly identical to Diff encoding, so there is not an image to illustrate it.
|
||||
|
||||
|
||||
Prefix Tree::
|
||||
Prefix tree encoding was introduced as an experimental feature in HBase 0.96.
|
||||
It provides similar memory savings to the Prefix, Diff, and Fast Diff encoder, but provides faster random access at a cost of slower encoding speed.
|
||||
+
|
||||
Prefix Tree may be appropriate for applications that have high block cache hit ratios. It introduces new 'tree' fields for the row and column.
|
||||
The row tree field contains a list of offsets/references corresponding to the cells in that row. This allows for a good deal of compression.
|
||||
For more details about Prefix Tree encoding, see link:https://issues.apache.org/jira/browse/HBASE-4676[HBASE-4676].
|
||||
+
|
||||
It is difficult to graphically illustrate a prefix tree, so no image is included. See the Wikipedia article for link:http://en.wikipedia.org/wiki/Trie[Trie] for more general information about this data structure.
|
||||
|
||||
=== Which Compressor or Data Block Encoder To Use
|
||||
|
||||
The compression or codec type to use depends on the characteristics of your data. Choosing the wrong type could cause your data to take more space rather than less, and can have performance implications.
|
||||
|
||||
In general, you need to weigh your options between smaller size and faster compression/decompression. Following are some general guidelines, expanded from a discussion at link:http://search-hadoop.com/m/lL12B1PFVhp1[Documenting Guidance on compression and codecs].
|
||||
|
||||
* If you have long keys (compared to the values) or many columns, use a prefix encoder.
|
||||
FAST_DIFF is recommended, as more testing is needed for Prefix Tree encoding.
|
||||
* If the values are large (and not precompressed, such as images), use a data block compressor.
|
||||
* Use GZIP for [firstterm]_cold data_, which is accessed infrequently.
|
||||
GZIP compression uses more CPU resources than Snappy or LZO, but provides a higher compression ratio.
|
||||
* Use Snappy or LZO for [firstterm]_hot data_, which is accessed frequently.
|
||||
Snappy and LZO use fewer CPU resources than GZIP, but do not provide as high of a compression ratio.
|
||||
* In most cases, enabling Snappy or LZO by default is a good choice, because they have a low performance overhead and provide space savings.
|
||||
* Before Snappy became available by Google in 2011, LZO was the default.
|
||||
Snappy has similar qualities as LZO but has been shown to perform better.
|
||||
|
||||
[[hadoop.native.lib]]
|
||||
=== Making use of Hadoop Native Libraries in HBase
|
||||
|
||||
The Hadoop shared library has a bunch of facility including compression libraries and fast crc'ing. To make this facility available to HBase, do the following. HBase/Hadoop will fall back to use alternatives if it cannot find the native library versions -- or fail outright if you asking for an explicit compressor and there is no alternative available.
|
||||
|
||||
If you see the following in your HBase logs, you know that HBase was unable to locate the Hadoop native libraries:
|
||||
[source]
|
||||
----
|
||||
2014-08-07 09:26:20,139 WARN [main] util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
|
||||
----
|
||||
If the libraries loaded successfully, the WARN message does not show.
|
||||
|
||||
Lets presume your Hadoop shipped with a native library that suits the platform you are running HBase on.
|
||||
To check if the Hadoop native library is available to HBase, run the following tool (available in Hadoop 2.1 and greater):
|
||||
[source]
|
||||
----
|
||||
$ ./bin/hbase --config ~/conf_hbase org.apache.hadoop.util.NativeLibraryChecker
|
||||
2014-08-26 13:15:38,717 WARN [main] util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
|
||||
Native library checking:
|
||||
hadoop: false
|
||||
zlib: false
|
||||
snappy: false
|
||||
lz4: false
|
||||
bzip2: false
|
||||
2014-08-26 13:15:38,863 INFO [main] util.ExitUtil: Exiting with status 1
|
||||
----
|
||||
Above shows that the native hadoop library is not available in HBase context.
|
||||
|
||||
To fix the above, either copy the Hadoop native libraries local or symlink to them if the Hadoop and HBase stalls are adjacent in the filesystem.
|
||||
You could also point at their location by setting the `LD_LIBRARY_PATH` environment variable.
|
||||
|
||||
Where the JVM looks to find native librarys is "system dependent" (See `java.lang.System#loadLibrary(name)`). On linux, by default, is going to look in _lib/native/PLATFORM_ where `PLATFORM` is the label for the platform your HBase is installed on.
|
||||
On a local linux machine, it seems to be the concatenation of the java properties `os.name` and `os.arch` followed by whether 32 or 64 bit.
|
||||
HBase on startup prints out all of the java system properties so find the os.name and os.arch in the log.
|
||||
For example:
|
||||
[source]
|
||||
----
|
||||
...
|
||||
2014-08-06 15:27:22,853 INFO [main] zookeeper.ZooKeeper: Client environment:os.name=Linux
|
||||
2014-08-06 15:27:22,853 INFO [main] zookeeper.ZooKeeper: Client environment:os.arch=amd64
|
||||
...
|
||||
----
|
||||
So in this case, the PLATFORM string is `Linux-amd64-64`.
|
||||
Copying the Hadoop native libraries or symlinking at _lib/native/Linux-amd64-64_ will ensure they are found.
|
||||
Check with the Hadoop _NativeLibraryChecker_.
|
||||
|
||||
|
||||
Here is example of how to point at the Hadoop libs with `LD_LIBRARY_PATH` environment variable:
|
||||
[source]
|
||||
----
|
||||
$ LD_LIBRARY_PATH=~/hadoop-2.5.0-SNAPSHOT/lib/native ./bin/hbase --config ~/conf_hbase org.apache.hadoop.util.NativeLibraryChecker
|
||||
2014-08-26 13:42:49,332 INFO [main] bzip2.Bzip2Factory: Successfully loaded & initialized native-bzip2 library system-native
|
||||
2014-08-26 13:42:49,337 INFO [main] zlib.ZlibFactory: Successfully loaded & initialized native-zlib library
|
||||
Native library checking:
|
||||
hadoop: true /home/stack/hadoop-2.5.0-SNAPSHOT/lib/native/libhadoop.so.1.0.0
|
||||
zlib: true /lib64/libz.so.1
|
||||
snappy: true /usr/lib64/libsnappy.so.1
|
||||
lz4: true revision:99
|
||||
bzip2: true /lib64/libbz2.so.1
|
||||
----
|
||||
Set in _hbase-env.sh_ the LD_LIBRARY_PATH environment variable when starting your HBase.
|
||||
|
||||
=== Compressor Configuration, Installation, and Use
|
||||
|
||||
[[compressor.install]]
|
||||
==== Configure HBase For Compressors
|
||||
|
||||
Before HBase can use a given compressor, its libraries need to be available.
|
||||
Due to licensing issues, only GZ compression is available to HBase (via native Java libraries) in a default installation.
|
||||
Other compression libraries are available via the shared library bundled with your hadoop.
|
||||
The hadoop native library needs to be findable when HBase starts.
|
||||
See
|
||||
|
||||
.Compressor Support On the Master
|
||||
|
||||
A new configuration setting was introduced in HBase 0.95, to check the Master to determine which data block encoders are installed and configured on it, and assume that the entire cluster is configured the same.
|
||||
This option, `hbase.master.check.compression`, defaults to `true`.
|
||||
This prevents the situation described in link:https://issues.apache.org/jira/browse/HBASE-6370[HBASE-6370], where a table is created or modified to support a codec that a region server does not support, leading to failures that take a long time to occur and are difficult to debug.
|
||||
|
||||
If `hbase.master.check.compression` is enabled, libraries for all desired compressors need to be installed and configured on the Master, even if the Master does not run a region server.
|
||||
|
||||
.Install GZ Support Via Native Libraries
|
||||
|
||||
HBase uses Java's built-in GZip support unless the native Hadoop libraries are available on the CLASSPATH.
|
||||
The recommended way to add libraries to the CLASSPATH is to set the environment variable `HBASE_LIBRARY_PATH` for the user running HBase.
|
||||
If native libraries are not available and Java's GZIP is used, `Got brand-new compressor` reports will be present in the logs.
|
||||
See <<brand.new.compressor,brand.new.compressor>>).
|
||||
|
||||
[[lzo.compression]]
|
||||
.Install LZO Support
|
||||
|
||||
HBase cannot ship with LZO because of incompatibility between HBase, which uses an Apache Software License (ASL) and LZO, which uses a GPL license.
|
||||
See the link:http://wiki.apache.org/hadoop/UsingLzoCompression[Using LZO
|
||||
Compression] wiki page for information on configuring LZO support for HBase.
|
||||
|
||||
If you depend upon LZO compression, consider configuring your RegionServers to fail to start if LZO is not available.
|
||||
See <<hbase.regionserver.codecs,hbase.regionserver.codecs>>.
|
||||
|
||||
[[lz4.compression]]
|
||||
.Configure LZ4 Support
|
||||
|
||||
LZ4 support is bundled with Hadoop.
|
||||
Make sure the hadoop shared library (libhadoop.so) is accessible when you start HBase.
|
||||
After configuring your platform (see <<hbase.native.platform,hbase.native.platform>>), you can make a symbolic link from HBase to the native Hadoop libraries.
|
||||
This assumes the two software installs are colocated.
|
||||
For example, if my 'platform' is Linux-amd64-64:
|
||||
[source,bourne]
|
||||
----
|
||||
$ cd $HBASE_HOME
|
||||
$ mkdir lib/native
|
||||
$ ln -s $HADOOP_HOME/lib/native lib/native/Linux-amd64-64
|
||||
----
|
||||
Use the compression tool to check that LZ4 is installed on all nodes.
|
||||
Start up (or restart) HBase.
|
||||
Afterward, you can create and alter tables to enable LZ4 as a compression codec.:
|
||||
----
|
||||
hbase(main):003:0> alter 'TestTable', {NAME => 'info', COMPRESSION => 'LZ4'}
|
||||
----
|
||||
|
||||
[[snappy.compression.installation]]
|
||||
.Install Snappy Support
|
||||
|
||||
HBase does not ship with Snappy support because of licensing issues.
|
||||
You can install Snappy binaries (for instance, by using +yum install snappy+ on CentOS) or build Snappy from source.
|
||||
After installing Snappy, search for the shared library, which will be called _libsnappy.so.X_ where X is a number.
|
||||
If you built from source, copy the shared library to a known location on your system, such as _/opt/snappy/lib/_.
|
||||
|
||||
In addition to the Snappy library, HBase also needs access to the Hadoop shared library, which will be called something like _libhadoop.so.X.Y_, where X and Y are both numbers.
|
||||
Make note of the location of the Hadoop library, or copy it to the same location as the Snappy library.
|
||||
|
||||
[NOTE]
|
||||
====
|
||||
The Snappy and Hadoop libraries need to be available on each node of your cluster.
|
||||
See <<compression.test,compression.test>> to find out how to test that this is the case.
|
||||
|
||||
See <<hbase.regionserver.codecs,hbase.regionserver.codecs>> to configure your RegionServers to fail to start if a given compressor is not available.
|
||||
====
|
||||
|
||||
Each of these library locations need to be added to the environment variable `HBASE_LIBRARY_PATH` for the operating system user that runs HBase.
|
||||
You need to restart the RegionServer for the changes to take effect.
|
||||
|
||||
[[compression.test]]
|
||||
.CompressionTest
|
||||
|
||||
You can use the CompressionTest tool to verify that your compressor is available to HBase:
|
||||
|
||||
----
|
||||
|
||||
$ hbase org.apache.hadoop.hbase.util.CompressionTest hdfs://host/path/to/hbase snappy
|
||||
----
|
||||
|
||||
[[hbase.regionserver.codecs]]
|
||||
.Enforce Compression Settings On a RegionServer
|
||||
|
||||
You can configure a RegionServer so that it will fail to restart if compression is configured incorrectly, by adding the option hbase.regionserver.codecs to the _hbase-site.xml_, and setting its value to a comma-separated list of codecs that need to be available.
|
||||
For example, if you set this property to `lzo,gz`, the RegionServer would fail to start if both compressors were not available.
|
||||
This would prevent a new server from being added to the cluster without having codecs configured properly.
|
||||
|
||||
[[changing.compression]]
|
||||
==== Enable Compression On a ColumnFamily
|
||||
|
||||
To enable compression for a ColumnFamily, use an `alter` command.
|
||||
You do not need to re-create the table or copy data.
|
||||
If you are changing codecs, be sure the old codec is still available until all the old StoreFiles have been compacted.
|
||||
|
||||
.Enabling Compression on a ColumnFamily of an Existing Table using HBaseShell
|
||||
====
|
||||
----
|
||||
|
||||
hbase> disable 'test'
|
||||
hbase> alter 'test', {NAME => 'cf', COMPRESSION => 'GZ'}
|
||||
hbase> enable 'test'
|
||||
----
|
||||
====
|
||||
|
||||
.Creating a New Table with Compression On a ColumnFamily
|
||||
====
|
||||
----
|
||||
|
||||
hbase> create 'test2', { NAME => 'cf2', COMPRESSION => 'SNAPPY' }
|
||||
----
|
||||
====
|
||||
|
||||
.Verifying a ColumnFamily's Compression Settings
|
||||
====
|
||||
----
|
||||
|
||||
hbase> describe 'test'
|
||||
DESCRIPTION ENABLED
|
||||
'test', {NAME => 'cf', DATA_BLOCK_ENCODING => 'NONE false
|
||||
', BLOOMFILTER => 'ROW', REPLICATION_SCOPE => '0',
|
||||
VERSIONS => '1', COMPRESSION => 'GZ', MIN_VERSIONS
|
||||
=> '0', TTL => 'FOREVER', KEEP_DELETED_CELLS => 'fa
|
||||
lse', BLOCKSIZE => '65536', IN_MEMORY => 'false', B
|
||||
LOCKCACHE => 'true'}
|
||||
1 row(s) in 0.1070 seconds
|
||||
----
|
||||
====
|
||||
|
||||
==== Testing Compression Performance
|
||||
|
||||
HBase includes a tool called LoadTestTool which provides mechanisms to test your compression performance.
|
||||
You must specify either `-write` or `-update-read` as your first parameter, and if you do not specify another parameter, usage advice is printed for each option.
|
||||
|
||||
.+LoadTestTool+ Usage
|
||||
====
|
||||
----
|
||||
|
||||
$ bin/hbase org.apache.hadoop.hbase.util.LoadTestTool -h
|
||||
usage: bin/hbase org.apache.hadoop.hbase.util.LoadTestTool <options>
|
||||
Options:
|
||||
-batchupdate Whether to use batch as opposed to separate
|
||||
updates for every column in a row
|
||||
-bloom <arg> Bloom filter type, one of [NONE, ROW, ROWCOL]
|
||||
-compression <arg> Compression type, one of [LZO, GZ, NONE, SNAPPY,
|
||||
LZ4]
|
||||
-data_block_encoding <arg> Encoding algorithm (e.g. prefix compression) to
|
||||
use for data blocks in the test column family, one
|
||||
of [NONE, PREFIX, DIFF, FAST_DIFF, PREFIX_TREE].
|
||||
-encryption <arg> Enables transparent encryption on the test table,
|
||||
one of [AES]
|
||||
-generator <arg> The class which generates load for the tool. Any
|
||||
args for this class can be passed as colon
|
||||
separated after class name
|
||||
-h,--help Show usage
|
||||
-in_memory Tries to keep the HFiles of the CF inmemory as far
|
||||
as possible. Not guaranteed that reads are always
|
||||
served from inmemory
|
||||
-init_only Initialize the test table only, don't do any
|
||||
loading
|
||||
-key_window <arg> The 'key window' to maintain between reads and
|
||||
writes for concurrent write/read workload. The
|
||||
default is 0.
|
||||
-max_read_errors <arg> The maximum number of read errors to tolerate
|
||||
before terminating all reader threads. The default
|
||||
is 10.
|
||||
-multiput Whether to use multi-puts as opposed to separate
|
||||
puts for every column in a row
|
||||
-num_keys <arg> The number of keys to read/write
|
||||
-num_tables <arg> A positive integer number. When a number n is
|
||||
speicfied, load test tool will load n table
|
||||
parallely. -tn parameter value becomes table name
|
||||
prefix. Each table name is in format
|
||||
<tn>_1...<tn>_n
|
||||
-read <arg> <verify_percent>[:<#threads=20>]
|
||||
-regions_per_server <arg> A positive integer number. When a number n is
|
||||
specified, load test tool will create the test
|
||||
table with n regions per server
|
||||
-skip_init Skip the initialization; assume test table already
|
||||
exists
|
||||
-start_key <arg> The first key to read/write (a 0-based index). The
|
||||
default value is 0.
|
||||
-tn <arg> The name of the table to read or write
|
||||
-update <arg> <update_percent>[:<#threads=20>][:<#whether to
|
||||
ignore nonce collisions=0>]
|
||||
-write <arg> <avg_cols_per_key>:<avg_data_size>[:<#threads=20>]
|
||||
-zk <arg> ZK quorum as comma-separated host names without
|
||||
port numbers
|
||||
-zk_root <arg> name of parent znode in zookeeper
|
||||
----
|
||||
====
|
||||
|
||||
.Example Usage of LoadTestTool
|
||||
====
|
||||
----
|
||||
|
||||
$ hbase org.apache.hadoop.hbase.util.LoadTestTool -write 1:10:100 -num_keys 1000000
|
||||
-read 100:30 -num_tables 1 -data_block_encoding NONE -tn load_test_tool_NONE
|
||||
----
|
||||
====
|
||||
|
||||
[[data.block.encoding.enable]]
|
||||
== Enable Data Block Encoding
|
||||
|
||||
Codecs are built into HBase so no extra configuration is needed.
|
||||
Codecs are enabled on a table by setting the `DATA_BLOCK_ENCODING` property.
|
||||
Disable the table before altering its DATA_BLOCK_ENCODING setting.
|
||||
Following is an example using HBase Shell:
|
||||
|
||||
.Enable Data Block Encoding On a Table
|
||||
====
|
||||
----
|
||||
|
||||
hbase> disable 'test'
|
||||
hbase> alter 'test', { NAME => 'cf', DATA_BLOCK_ENCODING => 'FAST_DIFF' }
|
||||
Updating all regions with the new schema...
|
||||
0/1 regions updated.
|
||||
1/1 regions updated.
|
||||
Done.
|
||||
0 row(s) in 2.2820 seconds
|
||||
hbase> enable 'test'
|
||||
0 row(s) in 0.1580 seconds
|
||||
----
|
||||
====
|
||||
|
||||
.Verifying a ColumnFamily's Data Block Encoding
|
||||
====
|
||||
----
|
||||
|
||||
hbase> describe 'test'
|
||||
DESCRIPTION ENABLED
|
||||
'test', {NAME => 'cf', DATA_BLOCK_ENCODING => 'FAST true
|
||||
_DIFF', BLOOMFILTER => 'ROW', REPLICATION_SCOPE =>
|
||||
'0', VERSIONS => '1', COMPRESSION => 'GZ', MIN_VERS
|
||||
IONS => '0', TTL => 'FOREVER', KEEP_DELETED_CELLS =
|
||||
> 'false', BLOCKSIZE => '65536', IN_MEMORY => 'fals
|
||||
e', BLOCKCACHE => 'true'}
|
||||
1 row(s) in 0.0650 seconds
|
||||
----
|
||||
====
|
||||
|
||||
:numbered:
|
||||
|
||||
ifdef::backend-docbook[]
|
||||
[index]
|
||||
== Index
|
||||
// Generated automatically by the DocBook toolchain.
|
||||
endif::backend-docbook[]
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,230 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[cp]]
|
||||
= Apache HBase Coprocessors
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
HBase coprocessors are modeled after the coprocessors which are part of Google's BigTable (http://www.scribd.com/doc/21631448/Dean-Keynote-Ladis2009, pages 66-67.). Coprocessors function in a similar way to Linux kernel modules.
|
||||
They provide a way to run server-level code against locally-stored data.
|
||||
The functionality they provide is very powerful, but also carries great risk and can have adverse effects on the system, at the level of the operating system.
|
||||
The information in this chapter is primarily sourced and heavily reused from Mingjie Lai's blog post at https://blogs.apache.org/hbase/entry/coprocessor_introduction.
|
||||
|
||||
Coprocessors are not designed to be used by end users of HBase, but by HBase developers who need to add specialized functionality to HBase.
|
||||
One example of the use of coprocessors is pluggable compaction and scan policies, which are provided as coprocessors in link:https://issues.apache.org/jira/browse/HBASE-6427[HBASE-6427].
|
||||
|
||||
== Coprocessor Framework
|
||||
|
||||
The implementation of HBase coprocessors diverges from the BigTable implementation.
|
||||
The HBase framework provides a library and runtime environment for executing user code within the HBase region server and master processes.
|
||||
|
||||
The framework API is provided in the link:https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/coprocessor/package-summary.html[coprocessor] package.
|
||||
|
||||
Two different types of coprocessors are provided by the framework, based on their scope.
|
||||
|
||||
.Types of Coprocessors
|
||||
|
||||
System Coprocessors::
|
||||
System coprocessors are loaded globally on all tables and regions hosted by a region server.
|
||||
|
||||
Table Coprocessors::
|
||||
You can specify which coprocessors should be loaded on all regions for a table on a per-table basis.
|
||||
|
||||
The framework provides two different aspects of extensions as well: _observers_ and _endpoints_.
|
||||
|
||||
Observers::
|
||||
Observers are analogous to triggers in conventional databases.
|
||||
They allow you to insert user code by overriding upcall methods provided by the coprocessor framework.
|
||||
Callback functions are executed from core HBase code when events occur.
|
||||
Callbacks are handled by the framework, and the coprocessor itself only needs to insert the extended or alternate functionality.
|
||||
|
||||
Endpoints (HBase 0.96.x and later)::
|
||||
The implementation for endpoints changed significantly in HBase 0.96.x due to the introduction of protocol buffers (protobufs) (link:https://issues.apache.org/jira/browse/HBASE-5448[HBASE-5488]). If you created endpoints before 0.96.x, you will need to rewrite them.
|
||||
Endpoints are now defined and callable as protobuf services, rather than endpoint invocations passed through as Writable blobs
|
||||
|
||||
Endpoints (HBase 0.94.x and earlier)::
|
||||
Dynamic RPC endpoints resemble stored procedures.
|
||||
An endpoint can be invoked at any time from the client.
|
||||
When it is invoked, it is executed remotely at the target region or regions, and results of the executions are returned to the client.
|
||||
|
||||
== Examples
|
||||
|
||||
An example of an observer is included in _hbase-examples/src/test/java/org/apache/hadoop/hbase/coprocessor/example/TestZooKeeperScanPolicyObserver.java_.
|
||||
Several endpoint examples are included in the same directory.
|
||||
|
||||
== Building A Coprocessor
|
||||
|
||||
Before you can build a processor, it must be developed, compiled, and packaged in a JAR file.
|
||||
The next step is to configure the coprocessor framework to use your coprocessor.
|
||||
You can load the coprocessor from your HBase configuration, so that the coprocessor starts with HBase, or you can configure the coprocessor from the HBase shell, as a table attribute, so that it is loaded dynamically when the table is opened or reopened.
|
||||
|
||||
=== Load from Configuration
|
||||
|
||||
To configure a coprocessor to be loaded when HBase starts, modify the RegionServer's _hbase-site.xml_ and configure one of the following properties, based on the type of observer you are configuring:
|
||||
|
||||
* `hbase.coprocessor.region.classes`for RegionObservers and Endpoints
|
||||
* `hbase.coprocessor.wal.classes`for WALObservers
|
||||
* `hbase.coprocessor.master.classes`for MasterObservers
|
||||
|
||||
.Example RegionObserver Configuration
|
||||
====
|
||||
In this example, one RegionObserver is configured for all the HBase tables.
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
<property>
|
||||
<name>hbase.coprocessor.region.classes</name>
|
||||
<value>org.apache.hadoop.hbase.coprocessor.AggregateImplementation</value>
|
||||
</property>
|
||||
----
|
||||
====
|
||||
|
||||
If multiple classes are specified for loading, the class names must be comma-separated.
|
||||
The framework attempts to load all the configured classes using the default class loader.
|
||||
Therefore, the jar file must reside on the server-side HBase classpath.
|
||||
|
||||
Coprocessors which are loaded in this way will be active on all regions of all tables.
|
||||
These are the system coprocessor introduced earlier.
|
||||
The first listed coprocessors will be assigned the priority `Coprocessor.Priority.SYSTEM`.
|
||||
Each subsequent coprocessor in the list will have its priority value incremented by one (which reduces its priority, because priorities have the natural sort order of Integers).
|
||||
|
||||
When calling out to registered observers, the framework executes their callbacks methods in the sorted order of their priority.
|
||||
Ties are broken arbitrarily.
|
||||
|
||||
=== Load from the HBase Shell
|
||||
|
||||
You can load a coprocessor on a specific table via a table attribute.
|
||||
The following example will load the `FooRegionObserver` observer when table `t1` is read or re-read.
|
||||
|
||||
.Load a Coprocessor On a Table Using HBase Shell
|
||||
====
|
||||
----
|
||||
hbase(main):005:0> alter 't1', METHOD => 'table_att',
|
||||
'coprocessor'=>'hdfs:///foo.jar|com.foo.FooRegionObserver|1001|arg1=1,arg2=2'
|
||||
Updating all regions with the new schema...
|
||||
1/1 regions updated.
|
||||
Done.
|
||||
0 row(s) in 1.0730 seconds
|
||||
|
||||
hbase(main):006:0> describe 't1'
|
||||
DESCRIPTION ENABLED
|
||||
{NAME => 't1', coprocessor$1 => 'hdfs:///foo.jar|com.foo.FooRegio false
|
||||
nObserver|1001|arg1=1,arg2=2', FAMILIES => [{NAME => 'c1', DATA_B
|
||||
LOCK_ENCODING => 'NONE', BLOOMFILTER => 'NONE', REPLICATION_SCOPE
|
||||
=> '0', VERSIONS => '3', COMPRESSION => 'NONE', MIN_VERSIONS =>
|
||||
'0', TTL => '2147483647', KEEP_DELETED_CELLS => 'false', BLOCKSIZ
|
||||
E => '65536', IN_MEMORY => 'false', ENCODE_ON_DISK => 'true', BLO
|
||||
CKCACHE => 'true'}, {NAME => 'f1', DATA_BLOCK_ENCODING => 'NONE',
|
||||
BLOOMFILTER => 'NONE', REPLICATION_SCOPE => '0', VERSIONS => '3'
|
||||
, COMPRESSION => 'NONE', MIN_VERSIONS => '0', TTL => '2147483647'
|
||||
, KEEP_DELETED_CELLS => 'false', BLOCKSIZE => '65536', IN_MEMORY
|
||||
=> 'false', ENCODE_ON_DISK => 'true', BLOCKCACHE => 'true'}]}
|
||||
1 row(s) in 0.0190 seconds
|
||||
----
|
||||
====
|
||||
|
||||
The coprocessor framework will try to read the class information from the coprocessor table attribute value.
|
||||
The value contains four pieces of information which are separated by the `|` character.
|
||||
|
||||
* File path: The jar file containing the coprocessor implementation must be in a location where all region servers can read it.
|
||||
You could copy the file onto the local disk on each region server, but it is recommended to store it in HDFS.
|
||||
* Class name: The full class name of the coprocessor.
|
||||
* Priority: An integer.
|
||||
The framework will determine the execution sequence of all configured observers registered at the same hook using priorities.
|
||||
This field can be left blank.
|
||||
In that case the framework will assign a default priority value.
|
||||
* Arguments: This field is passed to the coprocessor implementation.
|
||||
|
||||
.Unload a Coprocessor From a Table Using HBase Shell
|
||||
====
|
||||
----
|
||||
|
||||
hbase(main):007:0> alter 't1', METHOD => 'table_att_unset',
|
||||
hbase(main):008:0* NAME => 'coprocessor$1'
|
||||
Updating all regions with the new schema...
|
||||
1/1 regions updated.
|
||||
Done.
|
||||
0 row(s) in 1.1130 seconds
|
||||
|
||||
hbase(main):009:0> describe 't1'
|
||||
DESCRIPTION ENABLED
|
||||
{NAME => 't1', FAMILIES => [{NAME => 'c1', DATA_BLOCK_ENCODING => false
|
||||
'NONE', BLOOMFILTER => 'NONE', REPLICATION_SCOPE => '0', VERSION
|
||||
S => '3', COMPRESSION => 'NONE', MIN_VERSIONS => '0', TTL => '214
|
||||
7483647', KEEP_DELETED_CELLS => 'false', BLOCKSIZE => '65536', IN
|
||||
_MEMORY => 'false', ENCODE_ON_DISK => 'true', BLOCKCACHE => 'true
|
||||
'}, {NAME => 'f1', DATA_BLOCK_ENCODING => 'NONE', BLOOMFILTER =>
|
||||
'NONE', REPLICATION_SCOPE => '0', VERSIONS => '3', COMPRESSION =>
|
||||
'NONE', MIN_VERSIONS => '0', TTL => '2147483647', KEEP_DELETED_C
|
||||
ELLS => 'false', BLOCKSIZE => '65536', IN_MEMORY => 'false', ENCO
|
||||
DE_ON_DISK => 'true', BLOCKCACHE => 'true'}]}
|
||||
1 row(s) in 0.0180 seconds
|
||||
----
|
||||
====
|
||||
|
||||
WARNING: There is no guarantee that the framework will load a given coprocessor successfully.
|
||||
For example, the shell command neither guarantees a jar file exists at a particular location nor verifies whether the given class is actually contained in the jar file.
|
||||
|
||||
== Check the Status of a Coprocessor
|
||||
|
||||
To check the status of a coprocessor after it has been configured, use the `status` HBase Shell command.
|
||||
|
||||
----
|
||||
|
||||
hbase(main):020:0> status 'detailed'
|
||||
version 0.92-tm-6
|
||||
0 regionsInTransition
|
||||
master coprocessors: []
|
||||
1 live servers
|
||||
localhost:52761 1328082515520
|
||||
requestsPerSecond=3, numberOfOnlineRegions=3, usedHeapMB=32, maxHeapMB=995
|
||||
-ROOT-,,0
|
||||
numberOfStores=1, numberOfStorefiles=1, storefileUncompressedSizeMB=0, storefileSizeMB=0, memstoreSizeMB=0,
|
||||
storefileIndexSizeMB=0, readRequestsCount=54, writeRequestsCount=1, rootIndexSizeKB=0, totalStaticIndexSizeKB=0,
|
||||
totalStaticBloomSizeKB=0, totalCompactingKVs=0, currentCompactedKVs=0, compactionProgressPct=NaN, coprocessors=[]
|
||||
.META.,,1
|
||||
numberOfStores=1, numberOfStorefiles=0, storefileUncompressedSizeMB=0, storefileSizeMB=0, memstoreSizeMB=0,
|
||||
storefileIndexSizeMB=0, readRequestsCount=97, writeRequestsCount=4, rootIndexSizeKB=0, totalStaticIndexSizeKB=0,
|
||||
totalStaticBloomSizeKB=0, totalCompactingKVs=0, currentCompactedKVs=0, compactionProgressPct=NaN, coprocessors=[]
|
||||
t1,,1328082575190.c0491168a27620ffe653ec6c04c9b4d1.
|
||||
numberOfStores=2, numberOfStorefiles=1, storefileUncompressedSizeMB=0, storefileSizeMB=0, memstoreSizeMB=0,
|
||||
storefileIndexSizeMB=0, readRequestsCount=0, writeRequestsCount=0, rootIndexSizeKB=0, totalStaticIndexSizeKB=0,
|
||||
totalStaticBloomSizeKB=0, totalCompactingKVs=0, currentCompactedKVs=0, compactionProgressPct=NaN,
|
||||
coprocessors=[AggregateImplementation]
|
||||
0 dead servers
|
||||
----
|
||||
|
||||
== Monitor Time Spent in Coprocessors
|
||||
|
||||
HBase 0.98.5 introduced the ability to monitor some statistics relating to the amount of time spent executing a given coprocessor.
|
||||
You can see these statistics via the HBase Metrics framework (see <<hbase_metrics>> or the Web UI for a given Region Server, via the _Coprocessor Metrics_ tab.
|
||||
These statistics are valuable for debugging and benchmarking the performance impact of a given coprocessor on your cluster.
|
||||
Tracked statistics include min, max, average, and 90th, 95th, and 99th percentile.
|
||||
All times are shown in milliseconds.
|
||||
The statistics are calculated over coprocessor execution samples recorded during the reporting interval, which is 10 seconds by default.
|
||||
The metrics sampling rate as described in <<hbase_metrics>>.
|
||||
|
||||
.Coprocessor Metrics UI
|
||||
image::coprocessor_stats.png[]
|
||||
|
|
@ -0,0 +1,562 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[datamodel]]
|
||||
= Data Model
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
In HBase, data is stored in tables, which have rows and columns.
|
||||
This is a terminology overlap with relational databases (RDBMSs), but this is not a helpful analogy.
|
||||
Instead, it can be helpful to think of an HBase table as a multi-dimensional map.
|
||||
|
||||
.HBase Data Model Terminology
|
||||
|
||||
Table::
|
||||
An HBase table consists of multiple rows.
|
||||
|
||||
Row::
|
||||
A row in HBase consists of a row key and one or more columns with values associated with them.
|
||||
Rows are sorted alphabetically by the row key as they are stored.
|
||||
For this reason, the design of the row key is very important.
|
||||
The goal is to store data in such a way that related rows are near each other.
|
||||
A common row key pattern is a website domain.
|
||||
If your row keys are domains, you should probably store them in reverse (org.apache.www, org.apache.mail, org.apache.jira). This way, all of the Apache domains are near each other in the table, rather than being spread out based on the first letter of the subdomain.
|
||||
|
||||
Column::
|
||||
A column in HBase consists of a column family and a column qualifier, which are delimited by a `:` (colon) character.
|
||||
|
||||
Column Family::
|
||||
Column families physically colocate a set of columns and their values, often for performance reasons.
|
||||
Each column family has a set of storage properties, such as whether its values should be cached in memory, how its data is compressed or its row keys are encoded, and others.
|
||||
Each row in a table has the same column families, though a given row might not store anything in a given column family.
|
||||
|
||||
Column Qualifier::
|
||||
A column qualifier is added to a column family to provide the index for a given piece of data.
|
||||
Given a column family `content`, a column qualifier might be `content:html`, and another might be `content:pdf`.
|
||||
Though column families are fixed at table creation, column qualifiers are mutable and may differ greatly between rows.
|
||||
|
||||
Cell::
|
||||
A cell is a combination of row, column family, and column qualifier, and contains a value and a timestamp, which represents the value's version.
|
||||
|
||||
Timestamp::
|
||||
A timestamp is written alongside each value, and is the identifier for a given version of a value.
|
||||
By default, the timestamp represents the time on the RegionServer when the data was written, but you can specify a different timestamp value when you put data into the cell.
|
||||
|
||||
[[conceptual.view]]
|
||||
== Conceptual View
|
||||
|
||||
You can read a very understandable explanation of the HBase data model in the blog post link:http://jimbojw.com/wiki/index.php?title=Understanding_Hbase_and_BigTable[Understanding HBase and BigTable] by Jim R. Wilson.
|
||||
Another good explanation is available in the PDF link:http://0b4af6cdc2f0c5998459-c0245c5c937c5dedcca3f1764ecc9b2f.r43.cf2.rackcdn.com/9353-login1210_khurana.pdf[Introduction to Basic Schema Design] by Amandeep Khurana.
|
||||
|
||||
It may help to read different perspectives to get a solid understanding of HBase schema design.
|
||||
The linked articles cover the same ground as the information in this section.
|
||||
|
||||
The following example is a slightly modified form of the one on page 2 of the link:http://research.google.com/archive/bigtable.html[BigTable] paper.
|
||||
There is a table called `webtable` that contains two rows (`com.cnn.www` and `com.example.www`) and three column families named `contents`, `anchor`, and `people`.
|
||||
In this example, for the first row (`com.cnn.www`), `anchor` contains two columns (`anchor:cssnsi.com`, `anchor:my.look.ca`) and `contents` contains one column (`contents:html`). This example contains 5 versions of the row with the row key `com.cnn.www`, and one version of the row with the row key `com.example.www`.
|
||||
The `contents:html` column qualifier contains the entire HTML of a given website.
|
||||
Qualifiers of the `anchor` column family each contain the external site which links to the site represented by the row, along with the text it used in the anchor of its link.
|
||||
The `people` column family represents people associated with the site.
|
||||
|
||||
.Column Names
|
||||
[NOTE]
|
||||
====
|
||||
By convention, a column name is made of its column family prefix and a _qualifier_.
|
||||
For example, the column _contents:html_ is made up of the column family `contents` and the `html` qualifier.
|
||||
The colon character (`:`) delimits the column family from the column family _qualifier_.
|
||||
====
|
||||
|
||||
.Table `webtable`
|
||||
[cols="1,1,1,1,1", frame="all", options="header"]
|
||||
|===
|
||||
|Row Key |Time Stamp |ColumnFamily `contents` |ColumnFamily `anchor`|ColumnFamily `people`
|
||||
|"com.cnn.www" |t9 | |anchor:cnnsi.com = "CNN" |
|
||||
|"com.cnn.www" |t8 | |anchor:my.look.ca = "CNN.com" |
|
||||
|"com.cnn.www" |t6 | contents:html = "<html>..." | |
|
||||
|"com.cnn.www" |t5 | contents:html = "<html>..." | |
|
||||
|"com.cnn.www" |t3 | contents:html = "<html>..." | |
|
||||
|"com.example.www"| t5 | contents:html = "<html>..." | people:author = "John Doe"
|
||||
|===
|
||||
|
||||
Cells in this table that appear to be empty do not take space, or in fact exist, in HBase.
|
||||
This is what makes HBase "sparse." A tabular view is not the only possible way to look at data in HBase, or even the most accurate.
|
||||
The following represents the same information as a multi-dimensional map.
|
||||
This is only a mock-up for illustrative purposes and may not be strictly accurate.
|
||||
|
||||
[source,json]
|
||||
----
|
||||
{
|
||||
"com.cnn.www": {
|
||||
contents: {
|
||||
t6: contents:html: "<html>..."
|
||||
t5: contents:html: "<html>..."
|
||||
t3: contents:html: "<html>..."
|
||||
}
|
||||
anchor: {
|
||||
t9: anchor:cnnsi.com = "CNN"
|
||||
t8: anchor:my.look.ca = "CNN.com"
|
||||
}
|
||||
people: {}
|
||||
}
|
||||
"com.example.www": {
|
||||
contents: {
|
||||
t5: contents:html: "<html>..."
|
||||
}
|
||||
anchor: {}
|
||||
people: {
|
||||
t5: people:author: "John Doe"
|
||||
}
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
[[physical.view]]
|
||||
== Physical View
|
||||
|
||||
Although at a conceptual level tables may be viewed as a sparse set of rows, they are physically stored by column family.
|
||||
A new column qualifier (column_family:column_qualifier) can be added to an existing column family at any time.
|
||||
|
||||
.ColumnFamily `anchor`
|
||||
[cols="1,1,1", frame="all", options="header"]
|
||||
|===
|
||||
|Row Key | Time Stamp |Column Family `anchor`
|
||||
|"com.cnn.www" |t9 |`anchor:cnnsi.com = "CNN"`
|
||||
|"com.cnn.www" |t8 |`anchor:my.look.ca = "CNN.com"`
|
||||
|===
|
||||
|
||||
|
||||
.ColumnFamily `contents`
|
||||
[cols="1,1,1", frame="all", options="header"]
|
||||
|===
|
||||
|Row Key |Time Stamp |ColumnFamily `contents:`
|
||||
|"com.cnn.www" |t6 |contents:html = "<html>..."
|
||||
|"com.cnn.www" |t5 |contents:html = "<html>..."
|
||||
|"com.cnn.www" |t3 |contents:html = "<html>..."
|
||||
|===
|
||||
|
||||
|
||||
The empty cells shown in the conceptual view are not stored at all.
|
||||
Thus a request for the value of the `contents:html` column at time stamp `t8` would return no value.
|
||||
Similarly, a request for an `anchor:my.look.ca` value at time stamp `t9` would return no value.
|
||||
However, if no timestamp is supplied, the most recent value for a particular column would be returned.
|
||||
Given multiple versions, the most recent is also the first one found, since timestamps are stored in descending order.
|
||||
Thus a request for the values of all columns in the row `com.cnn.www` if no timestamp is specified would be: the value of `contents:html` from timestamp `t6`, the value of `anchor:cnnsi.com` from timestamp `t9`, the value of `anchor:my.look.ca` from timestamp `t8`.
|
||||
|
||||
For more information about the internals of how Apache HBase stores data, see <<regions.arch,regions.arch>>.
|
||||
|
||||
== Namespace
|
||||
|
||||
A namespace is a logical grouping of tables analogous to a database in relation database systems.
|
||||
This abstraction lays the groundwork for upcoming multi-tenancy related features:
|
||||
|
||||
* Quota Management (link:https://issues.apache.org/jira/browse/HBASE-8410[HBASE-8410]) - Restrict the amount of resources (ie regions, tables) a namespace can consume.
|
||||
* Namespace Security Administration (link:https://issues.apache.org/jira/browse/HBASE-9206[HBASE-9206]) - Provide another level of security administration for tenants.
|
||||
* Region server groups (link:https://issues.apache.org/jira/browse/HBASE-6721[HBASE-6721]) - A namespace/table can be pinned onto a subset of RegionServers thus guaranteeing a course level of isolation.
|
||||
|
||||
[[namespace_creation]]
|
||||
=== Namespace management
|
||||
|
||||
A namespace can be created, removed or altered.
|
||||
Namespace membership is determined during table creation by specifying a fully-qualified table name of the form:
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
<table namespace>:<table qualifier>
|
||||
----
|
||||
|
||||
.Examples
|
||||
====
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
#Create a namespace
|
||||
create_namespace 'my_ns'
|
||||
----
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
#create my_table in my_ns namespace
|
||||
create 'my_ns:my_table', 'fam'
|
||||
----
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
#drop namespace
|
||||
drop_namespace 'my_ns'
|
||||
----
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
#alter namespace
|
||||
alter_namespace 'my_ns', {METHOD => 'set', 'PROPERTY_NAME' => 'PROPERTY_VALUE'}
|
||||
----
|
||||
====
|
||||
|
||||
[[namespace_special]]
|
||||
=== Predefined namespaces
|
||||
|
||||
There are two predefined special namespaces:
|
||||
|
||||
* hbase - system namespace, used to contain HBase internal tables
|
||||
* default - tables with no explicit specified namespace will automatically fall into this namespace
|
||||
|
||||
.Examples
|
||||
====
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
#namespace=foo and table qualifier=bar
|
||||
create 'foo:bar', 'fam'
|
||||
|
||||
#namespace=default and table qualifier=bar
|
||||
create 'bar', 'fam'
|
||||
----
|
||||
====
|
||||
|
||||
== Table
|
||||
|
||||
Tables are declared up front at schema definition time.
|
||||
|
||||
== Row
|
||||
|
||||
Row keys are uninterpreted bytes.
|
||||
Rows are lexicographically sorted with the lowest order appearing first in a table.
|
||||
The empty byte array is used to denote both the start and end of a tables' namespace.
|
||||
|
||||
[[columnfamily]]
|
||||
== Column Family
|
||||
|
||||
Columns in Apache HBase are grouped into _column families_.
|
||||
All column members of a column family have the same prefix.
|
||||
For example, the columns _courses:history_ and _courses:math_ are both members of the _courses_ column family.
|
||||
The colon character (`:`) delimits the column family from the column family qualifier.
|
||||
The column family prefix must be composed of _printable_ characters.
|
||||
The qualifying tail, the column family _qualifier_, can be made of any arbitrary bytes.
|
||||
Column families must be declared up front at schema definition time whereas columns do not need to be defined at schema time but can be conjured on the fly while the table is up an running.
|
||||
|
||||
Physically, all column family members are stored together on the filesystem.
|
||||
Because tunings and storage specifications are done at the column family level, it is advised that all column family members have the same general access pattern and size characteristics.
|
||||
|
||||
== Cells
|
||||
|
||||
A _{row, column, version}_ tuple exactly specifies a `cell` in HBase.
|
||||
Cell content is uninterpreted bytes
|
||||
|
||||
== Data Model Operations
|
||||
|
||||
The four primary data model operations are Get, Put, Scan, and Delete.
|
||||
Operations are applied via link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html[Table] instances.
|
||||
|
||||
=== Get
|
||||
|
||||
link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html[Get] returns attributes for a specified row.
|
||||
Gets are executed via link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#get(org.apache.hadoop.hbase.client.Get)[Table.get].
|
||||
|
||||
=== Put
|
||||
|
||||
link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Put.html[Put] either adds new rows to a table (if the key is new) or can update existing rows (if the key already exists). Puts are executed via link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#put(org.apache.hadoop.hbase.client.Put)[Table.put] (writeBuffer) or link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#batch(java.util.List, java.lang.Object[])[Table.batch] (non-writeBuffer).
|
||||
|
||||
[[scan]]
|
||||
=== Scans
|
||||
|
||||
link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html[Scan] allow iteration over multiple rows for specified attributes.
|
||||
|
||||
The following is an example of a Scan on a Table instance.
|
||||
Assume that a table is populated with rows with keys "row1", "row2", "row3", and then another set of rows with the keys "abc1", "abc2", and "abc3". The following example shows how to set a Scan instance to return the rows beginning with "row".
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public static final byte[] CF = "cf".getBytes();
|
||||
public static final byte[] ATTR = "attr".getBytes();
|
||||
...
|
||||
|
||||
Table table = ... // instantiate a Table instance
|
||||
|
||||
Scan scan = new Scan();
|
||||
scan.addColumn(CF, ATTR);
|
||||
scan.setRowPrefixFilter(Bytes.toBytes("row"));
|
||||
ResultScanner rs = table.getScanner(scan);
|
||||
try {
|
||||
for (Result r = rs.next(); r != null; r = rs.next()) {
|
||||
// process result...
|
||||
}
|
||||
} finally {
|
||||
rs.close(); // always close the ResultScanner!
|
||||
}
|
||||
----
|
||||
|
||||
Note that generally the easiest way to specify a specific stop point for a scan is by using the link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/InclusiveStopFilter.html[InclusiveStopFilter] class.
|
||||
|
||||
=== Delete
|
||||
|
||||
link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Delete.html[Delete] removes a row from a table.
|
||||
Deletes are executed via link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#delete(org.apache.hadoop.hbase.client.Delete)[Table.delete].
|
||||
|
||||
HBase does not modify data in place, and so deletes are handled by creating new markers called _tombstones_.
|
||||
These tombstones, along with the dead values, are cleaned up on major compactions.
|
||||
|
||||
See <<version.delete,version.delete>> for more information on deleting versions of columns, and see <<compaction,compaction>> for more information on compactions.
|
||||
|
||||
[[versions]]
|
||||
== Versions
|
||||
|
||||
A _{row, column, version}_ tuple exactly specifies a `cell` in HBase.
|
||||
It's possible to have an unbounded number of cells where the row and column are the same but the cell address differs only in its version dimension.
|
||||
|
||||
While rows and column keys are expressed as bytes, the version is specified using a long integer.
|
||||
Typically this long contains time instances such as those returned by `java.util.Date.getTime()` or `System.currentTimeMillis()`, that is: [quote]_the difference, measured in milliseconds, between the current time and midnight, January 1, 1970 UTC_.
|
||||
|
||||
The HBase version dimension is stored in decreasing order, so that when reading from a store file, the most recent values are found first.
|
||||
|
||||
There is a lot of confusion over the semantics of `cell` versions, in HBase.
|
||||
In particular:
|
||||
|
||||
* If multiple writes to a cell have the same version, only the last written is fetchable.
|
||||
* It is OK to write cells in a non-increasing version order.
|
||||
|
||||
Below we describe how the version dimension in HBase currently works.
|
||||
See link:https://issues.apache.org/jira/browse/HBASE-2406[HBASE-2406] for discussion of HBase versions. link:http://outerthought.org/blog/417-ot.html[Bending time in HBase] makes for a good read on the version, or time, dimension in HBase.
|
||||
It has more detail on versioning than is provided here.
|
||||
As of this writing, the limitation _Overwriting values at existing timestamps_ mentioned in the article no longer holds in HBase.
|
||||
This section is basically a synopsis of this article by Bruno Dumon.
|
||||
|
||||
[[specify.number.of.versions]]
|
||||
=== Specifying the Number of Versions to Store
|
||||
|
||||
The maximum number of versions to store for a given column is part of the column schema and is specified at table creation, or via an `alter` command, via `HColumnDescriptor.DEFAULT_VERSIONS`.
|
||||
Prior to HBase 0.96, the default number of versions kept was `3`, but in 0.96 and newer has been changed to `1`.
|
||||
|
||||
.Modify the Maximum Number of Versions for a Column Family
|
||||
====
|
||||
This example uses HBase Shell to keep a maximum of 5 versions of all columns in column family `f1`.
|
||||
You could also use link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html[HColumnDescriptor].
|
||||
|
||||
----
|
||||
hbase> alter ‘t1′, NAME => ‘f1′, VERSIONS => 5
|
||||
----
|
||||
====
|
||||
|
||||
.Modify the Minimum Number of Versions for a Column Family
|
||||
====
|
||||
You can also specify the minimum number of versions to store per column family.
|
||||
By default, this is set to 0, which means the feature is disabled.
|
||||
The following example sets the minimum number of versions on all columns in column family `f1` to `2`, via HBase Shell.
|
||||
You could also use link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html[HColumnDescriptor].
|
||||
|
||||
----
|
||||
hbase> alter ‘t1′, NAME => ‘f1′, MIN_VERSIONS => 2
|
||||
----
|
||||
====
|
||||
|
||||
Starting with HBase 0.98.2, you can specify a global default for the maximum number of versions kept for all newly-created columns, by setting `hbase.column.max.version` in _hbase-site.xml_.
|
||||
See <<hbase.column.max.version,hbase.column.max.version>>.
|
||||
|
||||
[[versions.ops]]
|
||||
=== Versions and HBase Operations
|
||||
|
||||
In this section we look at the behavior of the version dimension for each of the core HBase operations.
|
||||
|
||||
==== Get/Scan
|
||||
|
||||
Gets are implemented on top of Scans.
|
||||
The below discussion of link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html[Get] applies equally to link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html[Scans].
|
||||
|
||||
By default, i.e. if you specify no explicit version, when doing a `get`, the cell whose version has the largest value is returned (which may or may not be the latest one written, see later). The default behavior can be modified in the following ways:
|
||||
|
||||
* to return more than one version, see link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html#setMaxVersions()[Get.setMaxVersions()]
|
||||
* to return versions other than the latest, see link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html#setTimeRange(long,%20long)[Get.setTimeRange()]
|
||||
+
|
||||
To retrieve the latest version that is less than or equal to a given value, thus giving the 'latest' state of the record at a certain point in time, just use a range from 0 to the desired version and set the max versions to 1.
|
||||
|
||||
|
||||
==== Default Get Example
|
||||
|
||||
The following Get will only retrieve the current version of the row
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public static final byte[] CF = "cf".getBytes();
|
||||
public static final byte[] ATTR = "attr".getBytes();
|
||||
...
|
||||
Get get = new Get(Bytes.toBytes("row1"));
|
||||
Result r = table.get(get);
|
||||
byte[] b = r.getValue(CF, ATTR); // returns current version of value
|
||||
----
|
||||
|
||||
==== Versioned Get Example
|
||||
|
||||
The following Get will return the last 3 versions of the row.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public static final byte[] CF = "cf".getBytes();
|
||||
public static final byte[] ATTR = "attr".getBytes();
|
||||
...
|
||||
Get get = new Get(Bytes.toBytes("row1"));
|
||||
get.setMaxVersions(3); // will return last 3 versions of row
|
||||
Result r = table.get(get);
|
||||
byte[] b = r.getValue(CF, ATTR); // returns current version of value
|
||||
List<KeyValue> kv = r.getColumn(CF, ATTR); // returns all versions of this column
|
||||
----
|
||||
|
||||
==== Put
|
||||
|
||||
Doing a put always creates a new version of a `cell`, at a certain timestamp.
|
||||
By default the system uses the server's `currentTimeMillis`, but you can specify the version (= the long integer) yourself, on a per-column level.
|
||||
This means you could assign a time in the past or the future, or use the long value for non-time purposes.
|
||||
|
||||
To overwrite an existing value, do a put at exactly the same row, column, and version as that of the cell you want to overwrite.
|
||||
|
||||
===== Implicit Version Example
|
||||
|
||||
The following Put will be implicitly versioned by HBase with the current time.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public static final byte[] CF = "cf".getBytes();
|
||||
public static final byte[] ATTR = "attr".getBytes();
|
||||
...
|
||||
Put put = new Put(Bytes.toBytes(row));
|
||||
put.add(CF, ATTR, Bytes.toBytes( data));
|
||||
table.put(put);
|
||||
----
|
||||
|
||||
===== Explicit Version Example
|
||||
|
||||
The following Put has the version timestamp explicitly set.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public static final byte[] CF = "cf".getBytes();
|
||||
public static final byte[] ATTR = "attr".getBytes();
|
||||
...
|
||||
Put put = new Put( Bytes.toBytes(row));
|
||||
long explicitTimeInMs = 555; // just an example
|
||||
put.add(CF, ATTR, explicitTimeInMs, Bytes.toBytes(data));
|
||||
table.put(put);
|
||||
----
|
||||
|
||||
Caution: the version timestamp is used internally by HBase for things like time-to-live calculations.
|
||||
It's usually best to avoid setting this timestamp yourself.
|
||||
Prefer using a separate timestamp attribute of the row, or have the timestamp as a part of the row key, or both.
|
||||
|
||||
[[version.delete]]
|
||||
==== Delete
|
||||
|
||||
There are three different types of internal delete markers.
|
||||
See Lars Hofhansl's blog for discussion of his attempt adding another, link:http://hadoop-hbase.blogspot.com/2012/01/scanning-in-hbase.html[Scanning in HBase: Prefix Delete Marker].
|
||||
|
||||
* Delete: for a specific version of a column.
|
||||
* Delete column: for all versions of a column.
|
||||
* Delete family: for all columns of a particular ColumnFamily
|
||||
|
||||
When deleting an entire row, HBase will internally create a tombstone for each ColumnFamily (i.e., not each individual column).
|
||||
|
||||
Deletes work by creating _tombstone_ markers.
|
||||
For example, let's suppose we want to delete a row.
|
||||
For this you can specify a version, or else by default the `currentTimeMillis` is used.
|
||||
What this means is _delete all cells where the version is less than or equal to this version_.
|
||||
HBase never modifies data in place, so for example a delete will not immediately delete (or mark as deleted) the entries in the storage file that correspond to the delete condition.
|
||||
Rather, a so-called _tombstone_ is written, which will mask the deleted values.
|
||||
When HBase does a major compaction, the tombstones are processed to actually remove the dead values, together with the tombstones themselves.
|
||||
If the version you specified when deleting a row is larger than the version of any value in the row, then you can consider the complete row to be deleted.
|
||||
|
||||
For an informative discussion on how deletes and versioning interact, see the thread link:http://comments.gmane.org/gmane.comp.java.hadoop.hbase.user/28421[Put w/timestamp -> Deleteall -> Put w/ timestamp fails] up on the user mailing list.
|
||||
|
||||
Also see <<keyvalue,keyvalue>> for more information on the internal KeyValue format.
|
||||
|
||||
Delete markers are purged during the next major compaction of the store, unless the `KEEP_DELETED_CELLS` option is set in the column family (See <<cf.keep.deleted>>).
|
||||
To keep the deletes for a configurable amount of time, you can set the delete TTL via the +hbase.hstore.time.to.purge.deletes+ property in _hbase-site.xml_.
|
||||
If `hbase.hstore.time.to.purge.deletes` is not set, or set to 0, all delete markers, including those with timestamps in the future, are purged during the next major compaction.
|
||||
Otherwise, a delete marker with a timestamp in the future is kept until the major compaction which occurs after the time represented by the marker's timestamp plus the value of `hbase.hstore.time.to.purge.deletes`, in milliseconds.
|
||||
|
||||
NOTE: This behavior represents a fix for an unexpected change that was introduced in HBase 0.94, and was fixed in link:https://issues.apache.org/jira/browse/HBASE-10118[HBASE-10118].
|
||||
The change has been backported to HBase 0.94 and newer branches.
|
||||
|
||||
=== Current Limitations
|
||||
|
||||
==== Deletes mask Puts
|
||||
|
||||
Deletes mask puts, even puts that happened after the delete was entered.
|
||||
See link:https://issues.apache.org/jira/browse/HBASE-2256[HBASE-2256].
|
||||
Remember that a delete writes a tombstone, which only disappears after then next major compaction has run.
|
||||
Suppose you do a delete of everything <= T.
|
||||
After this you do a new put with a timestamp <= T.
|
||||
This put, even if it happened after the delete, will be masked by the delete tombstone.
|
||||
Performing the put will not fail, but when you do a get you will notice the put did have no effect.
|
||||
It will start working again after the major compaction has run.
|
||||
These issues should not be a problem if you use always-increasing versions for new puts to a row.
|
||||
But they can occur even if you do not care about time: just do delete and put immediately after each other, and there is some chance they happen within the same millisecond.
|
||||
|
||||
[[major.compactions.change.query.results]]
|
||||
==== Major compactions change query results
|
||||
|
||||
_...create three cell versions at t1, t2 and t3, with a maximum-versions
|
||||
setting of 2. So when getting all versions, only the values at t2 and t3 will be
|
||||
returned. But if you delete the version at t2 or t3, the one at t1 will appear again.
|
||||
Obviously, once a major compaction has run, such behavior will not be the case
|
||||
anymore..._ (See _Garbage Collection_ in link:http://outerthought.org/blog/417-ot.html[Bending time in HBase].)
|
||||
|
||||
[[dm.sort]]
|
||||
== Sort Order
|
||||
|
||||
All data model operations HBase return data in sorted order.
|
||||
First by row, then by ColumnFamily, followed by column qualifier, and finally timestamp (sorted in reverse, so newest records are returned first).
|
||||
|
||||
[[dm.column.metadata]]
|
||||
== Column Metadata
|
||||
|
||||
There is no store of column metadata outside of the internal KeyValue instances for a ColumnFamily.
|
||||
Thus, while HBase can support not only a wide number of columns per row, but a heterogeneous set of columns between rows as well, it is your responsibility to keep track of the column names.
|
||||
|
||||
The only way to get a complete set of columns that exist for a ColumnFamily is to process all the rows.
|
||||
For more information about how HBase stores data internally, see <<keyvalue,keyvalue>>.
|
||||
|
||||
== Joins
|
||||
|
||||
Whether HBase supports joins is a common question on the dist-list, and there is a simple answer: it doesn't, at not least in the way that RDBMS' support them (e.g., with equi-joins or outer-joins in SQL). As has been illustrated in this chapter, the read data model operations in HBase are Get and Scan.
|
||||
|
||||
However, that doesn't mean that equivalent join functionality can't be supported in your application, but you have to do it yourself.
|
||||
The two primary strategies are either denormalizing the data upon writing to HBase, or to have lookup tables and do the join between HBase tables in your application or MapReduce code (and as RDBMS' demonstrate, there are several strategies for this depending on the size of the tables, e.g., nested loops vs.
|
||||
hash-joins). So which is the best approach? It depends on what you are trying to do, and as such there isn't a single answer that works for every use case.
|
||||
|
||||
== ACID
|
||||
|
||||
See link:http://hbase.apache.org/acid-semantics.html[ACID Semantics].
|
||||
Lars Hofhansl has also written a note on link:http://hadoop-hbase.blogspot.com/2012/03/acid-in-hbase.html[ACID in HBase].
|
||||
|
||||
ifdef::backend-docbook[]
|
||||
[index]
|
||||
== Index
|
||||
// Generated automatically by the DocBook toolchain.
|
||||
endif::backend-docbook[]
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,66 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[external_apis]]
|
||||
= Apache HBase External APIs
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
This chapter will cover access to Apache HBase either through non-Java languages, or through custom protocols.
|
||||
For information on using the native HBase APIs, refer to link:http://hbase.apache.org/apidocs/index.html[User API Reference] and the new <<hbase_apis,HBase APIs>> chapter.
|
||||
|
||||
[[nonjava.jvm]]
|
||||
== Non-Java Languages Talking to the JVM
|
||||
|
||||
Currently the documentation on this topic is in the link:http://wiki.apache.org/hadoop/Hbase[Apache HBase Wiki].
|
||||
See also the link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/thrift/package-summary.html#package_description[Thrift API Javadoc].
|
||||
|
||||
== REST
|
||||
|
||||
Currently most of the documentation on REST exists in the link:http://wiki.apache.org/hadoop/Hbase/Stargate[Apache HBase Wiki on REST] (The REST gateway used to be called 'Stargate'). There are also a nice set of blogs on link:http://blog.cloudera.com/blog/2013/03/how-to-use-the-apache-hbase-rest-interface-part-1/[How-to: Use the Apache HBase REST Interface] by Jesse Anderson.
|
||||
|
||||
To run your REST server under SSL, set `hbase.rest.ssl.enabled` to `true` and also set the following configs when you launch the REST server: (See example commands in <<jmx_config,JMX config>>)
|
||||
|
||||
[source]
|
||||
----
|
||||
hbase.rest.ssl.keystore.store
|
||||
hbase.rest.ssl.keystore.password
|
||||
hbase.rest.ssl.keystore.keypassword
|
||||
----
|
||||
|
||||
HBase ships a simple REST client, see link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/rest/client/package-summary.html[REST client] package for details.
|
||||
To enable SSL support for it, please also import your certificate into local java cacerts keystore:
|
||||
----
|
||||
keytool -import -trustcacerts -file /home/user/restserver.cert -keystore $JAVA_HOME/jre/lib/security/cacerts
|
||||
----
|
||||
|
||||
== Thrift
|
||||
|
||||
Documentation about Thrift has moved to <<thrift>>.
|
||||
|
||||
[[c]]
|
||||
== C/C++ Apache HBase Client
|
||||
|
||||
FB's Chip Turner wrote a pure C/C++ client.
|
||||
link:https://github.com/facebook/native-cpp-hbase-client[Check it out].
|
||||
|
|
@ -0,0 +1,141 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[faq]]
|
||||
== FAQ
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
=== General
|
||||
When should I use HBase?::
|
||||
See <<arch.overview>> in the Architecture chapter.
|
||||
|
||||
Are there other HBase FAQs?::
|
||||
See the FAQ that is up on the wiki, link:http://wiki.apache.org/hadoop/Hbase/FAQ[HBase Wiki FAQ].
|
||||
|
||||
Does HBase support SQL?::
|
||||
Not really. SQL-ish support for HBase via link:http://hive.apache.org/[Hive] is in development, however Hive is based on MapReduce which is not generally suitable for low-latency requests. See the <<datamodel>> section for examples on the HBase client.
|
||||
|
||||
How can I find examples of NoSQL/HBase?::
|
||||
See the link to the BigTable paper in <<other.info>>, as well as the other papers.
|
||||
|
||||
What is the history of HBase?::
|
||||
See <<hbase.history,hbase.history>>.
|
||||
|
||||
=== Upgrading
|
||||
How do I upgrade Maven-managed projects from HBase 0.94 to HBase 0.96+?::
|
||||
In HBase 0.96, the project moved to a modular structure. Adjust your project's dependencies to rely upon the `hbase-client` module or another module as appropriate, rather than a single JAR. You can model your Maven depency after one of the following, depending on your targeted version of HBase. See Section 3.5, “Upgrading from 0.94.x to 0.96.x” or Section 3.3, “Upgrading from 0.96.x to 0.98.x” for more information.
|
||||
+
|
||||
.Maven Dependency for HBase 0.98
|
||||
[source,xml]
|
||||
----
|
||||
<dependency>
|
||||
<groupId>org.apache.hbase</groupId>
|
||||
<artifactId>hbase-client</artifactId>
|
||||
<version>0.98.5-hadoop2</version>
|
||||
</dependency>
|
||||
----
|
||||
+
|
||||
.Maven Dependency for HBase 0.96
|
||||
[source,xml]
|
||||
----
|
||||
<dependency>
|
||||
<groupId>org.apache.hbase</groupId>
|
||||
<artifactId>hbase-client</artifactId>
|
||||
<version>0.96.2-hadoop2</version>
|
||||
</dependency>
|
||||
----
|
||||
+
|
||||
.Maven Dependency for HBase 0.94
|
||||
[source,xml]
|
||||
----
|
||||
<dependency>
|
||||
<groupId>org.apache.hbase</groupId>
|
||||
<artifactId>hbase</artifactId>
|
||||
<version>0.94.3</version>
|
||||
</dependency>
|
||||
----
|
||||
|
||||
|
||||
=== Architecture
|
||||
How does HBase handle Region-RegionServer assignment and locality?::
|
||||
See <<regions.arch>>.
|
||||
|
||||
=== Configuration
|
||||
How can I get started with my first cluster?::
|
||||
See <<quickstart>>.
|
||||
|
||||
Where can I learn about the rest of the configuration options?::
|
||||
See <<configuration>>.
|
||||
|
||||
=== Schema Design / Data Access
|
||||
|
||||
How should I design my schema in HBase?::
|
||||
See <<datamodel>> and <<schema>>.
|
||||
|
||||
How can I store (fill in the blank) in HBase?::
|
||||
See <<supported.datatypes>>.
|
||||
|
||||
How can I handle secondary indexes in HBase?::
|
||||
See <<secondary.indexes>>.
|
||||
|
||||
Can I change a table's rowkeys?::
|
||||
This is a very common question. You can't. See <<changing.rowkeys>>.
|
||||
|
||||
What APIs does HBase support?::
|
||||
See <<datamodel>>, <<architecture.client>>, and <<nonjava.jvm>>.
|
||||
|
||||
=== MapReduce
|
||||
|
||||
How can I use MapReduce with HBase?::
|
||||
See <<mapreduce>>.
|
||||
|
||||
=== Performance and Troubleshooting
|
||||
|
||||
How can I improve HBase cluster performance?::
|
||||
See <<performance>>.
|
||||
|
||||
How can I troubleshoot my HBase cluster?::
|
||||
See <<trouble>>.
|
||||
|
||||
=== Amazon EC2
|
||||
|
||||
I am running HBase on Amazon EC2 and...::
|
||||
EC2 issues are a special case. See <<trouble.ec2>> and <<perf.ec2>>.
|
||||
|
||||
=== Operations
|
||||
|
||||
How do I manage my HBase cluster?::
|
||||
See <<ops_mgt>>.
|
||||
|
||||
How do I back up my HBase cluster?::
|
||||
See <<ops.backup>>.
|
||||
|
||||
=== HBase in Action
|
||||
|
||||
Where can I find interesting videos and presentations on HBase?::
|
||||
See <<other.info>>.
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,641 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
= Getting Started
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
== Introduction
|
||||
|
||||
<<quickstart,Quickstart>> will get you up and running on a single-node, standalone instance of HBase, followed by a pseudo-distributed single-machine instance, and finally a fully-distributed cluster.
|
||||
|
||||
[[quickstart]]
|
||||
== Quick Start - Standalone HBase
|
||||
|
||||
This guide describes the setup of a standalone HBase instance running against the local filesystem.
|
||||
This is not an appropriate configuration for a production instance of HBase, but will allow you to experiment with HBase.
|
||||
This section shows you how to create a table in HBase using the `hbase shell` CLI, insert rows into the table, perform put and scan operations against the table, enable or disable the table, and start and stop HBase.
|
||||
Apart from downloading HBase, this procedure should take less than 10 minutes.
|
||||
|
||||
.Local Filesystem and Durability
|
||||
WARNING: _The following is fixed in HBase 0.98.3 and beyond. See link:https://issues.apache.org/jira/browse/HBASE-11272[HBASE-11272] and link:https://issues.apache.org/jira/browse/HBASE-11218[HBASE-11218]._
|
||||
|
||||
Using HBase with a local filesystem does not guarantee durability.
|
||||
The HDFS local filesystem implementation will lose edits if files are not properly closed.
|
||||
This is very likely to happen when you are experimenting with new software, starting and stopping the daemons often and not always cleanly.
|
||||
You need to run HBase on HDFS to ensure all writes are preserved.
|
||||
Running against the local filesystem is intended as a shortcut to get you familiar with how the general system works, as the very first phase of evaluation.
|
||||
See link:https://issues.apache.org/jira/browse/HBASE-3696[HBASE-3696] and its associated issues for more details about the issues of running on the local filesystem.
|
||||
|
||||
[[loopback.ip]]
|
||||
.Loopback IP - HBase 0.94.x and earlier
|
||||
NOTE: _The below advice is for hbase-0.94.x and older versions only. This is fixed in hbase-0.96.0 and beyond._
|
||||
|
||||
Prior to HBase 0.94.x, HBase expected the loopback IP address to be 127.0.0.1. Ubuntu and some other distributions default to 127.0.1.1 and this will cause problems for you. See link:http://devving.com/?p=414[Why does HBase care about /etc/hosts?] for detail
|
||||
|
||||
|
||||
.Example /etc/hosts File for Ubuntu
|
||||
====
|
||||
The following _/etc/hosts_ file works correctly for HBase 0.94.x and earlier, on Ubuntu. Use this as a template if you run into trouble.
|
||||
[listing]
|
||||
----
|
||||
127.0.0.1 localhost
|
||||
127.0.0.1 ubuntu.ubuntu-domain ubuntu
|
||||
----
|
||||
|
||||
====
|
||||
|
||||
|
||||
=== JDK Version Requirements
|
||||
|
||||
HBase requires that a JDK be installed.
|
||||
See <<java,Java>> for information about supported JDK versions.
|
||||
|
||||
=== Get Started with HBase
|
||||
|
||||
.Procedure: Download, Configure, and Start HBase
|
||||
. Choose a download site from this list of link:http://www.apache.org/dyn/closer.cgi/hbase/[Apache Download Mirrors].
|
||||
Click on the suggested top link.
|
||||
This will take you to a mirror of _HBase
|
||||
Releases_.
|
||||
Click on the folder named _stable_ and then download the binary file that ends in _.tar.gz_ to your local filesystem.
|
||||
Be sure to choose the version that corresponds with the version of Hadoop you are likely to use later.
|
||||
In most cases, you should choose the file for Hadoop 2, which will be called something like _hbase-0.98.3-hadoop2-bin.tar.gz_.
|
||||
Do not download the file ending in _src.tar.gz_ for now.
|
||||
. Extract the downloaded file, and change to the newly-created directory.
|
||||
+
|
||||
----
|
||||
|
||||
$ tar xzvf hbase-<?eval ${project.version}?>-hadoop2-bin.tar.gz
|
||||
$ cd hbase-<?eval ${project.version}?>-hadoop2/
|
||||
----
|
||||
|
||||
. For HBase 0.98.5 and later, you are required to set the `JAVA_HOME` environment variable before starting HBase.
|
||||
Prior to 0.98.5, HBase attempted to detect the location of Java if the variables was not set.
|
||||
You can set the variable via your operating system's usual mechanism, but HBase provides a central mechanism, _conf/hbase-env.sh_.
|
||||
Edit this file, uncomment the line starting with `JAVA_HOME`, and set it to the appropriate location for your operating system.
|
||||
The `JAVA_HOME` variable should be set to a directory which contains the executable file _bin/java_.
|
||||
Most modern Linux operating systems provide a mechanism, such as /usr/bin/alternatives on RHEL or CentOS, for transparently switching between versions of executables such as Java.
|
||||
In this case, you can set `JAVA_HOME` to the directory containing the symbolic link to _bin/java_, which is usually _/usr_.
|
||||
+
|
||||
----
|
||||
JAVA_HOME=/usr
|
||||
----
|
||||
+
|
||||
NOTE: These instructions assume that each node of your cluster uses the same configuration.
|
||||
If this is not the case, you may need to set `JAVA_HOME` separately for each node.
|
||||
|
||||
. Edit _conf/hbase-site.xml_, which is the main HBase configuration file.
|
||||
At this time, you only need to specify the directory on the local filesystem where HBase and ZooKeeper write data.
|
||||
By default, a new directory is created under /tmp.
|
||||
Many servers are configured to delete the contents of _/tmp_ upon reboot, so you should store the data elsewhere.
|
||||
The following configuration will store HBase's data in the _hbase_ directory, in the home directory of the user called `testuser`.
|
||||
Paste the `<property>` tags beneath the `<configuration>` tags, which should be empty in a new HBase install.
|
||||
+
|
||||
.Example _hbase-site.xml_ for Standalone HBase
|
||||
====
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<configuration>
|
||||
<property>
|
||||
<name>hbase.rootdir</name>
|
||||
<value>file:///home/testuser/hbase</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zookeeper.property.dataDir</name>
|
||||
<value>/home/testuser/zookeeper</value>
|
||||
</property>
|
||||
</configuration>
|
||||
----
|
||||
====
|
||||
+
|
||||
You do not need to create the HBase data directory.
|
||||
HBase will do this for you.
|
||||
If you create the directory, HBase will attempt to do a migration, which is not what you want.
|
||||
|
||||
. The _bin/start-hbase.sh_ script is provided as a convenient way to start HBase.
|
||||
Issue the command, and if all goes well, a message is logged to standard output showing that HBase started successfully.
|
||||
You can use the `jps` command to verify that you have one running process called `HMaster`.
|
||||
In standalone mode HBase runs all daemons within this single JVM, i.e.
|
||||
the HMaster, a single HRegionServer, and the ZooKeeper daemon.
|
||||
+
|
||||
NOTE: Java needs to be installed and available.
|
||||
If you get an error indicating that Java is not installed, but it is on your system, perhaps in a non-standard location, edit the _conf/hbase-env.sh_ file and modify the `JAVA_HOME` setting to point to the directory that contains _bin/java_ your system.
|
||||
|
||||
|
||||
[[shell_exercises]]
|
||||
.Procedure: Use HBase For the First Time
|
||||
. Connect to HBase.
|
||||
+
|
||||
Connect to your running instance of HBase using the `hbase shell` command, located in the [path]_bin/_ directory of your HBase install.
|
||||
In this example, some usage and version information that is printed when you start HBase Shell has been omitted.
|
||||
The HBase Shell prompt ends with a `>` character.
|
||||
+
|
||||
----
|
||||
|
||||
$ ./bin/hbase shell
|
||||
hbase(main):001:0>
|
||||
----
|
||||
|
||||
. Display HBase Shell Help Text.
|
||||
+
|
||||
Type `help` and press Enter, to display some basic usage information for HBase Shell, as well as several example commands.
|
||||
Notice that table names, rows, columns all must be enclosed in quote characters.
|
||||
|
||||
. Create a table.
|
||||
+
|
||||
Use the `create` command to create a new table.
|
||||
You must specify the table name and the ColumnFamily name.
|
||||
+
|
||||
----
|
||||
hbase(main):001:0> create 'test', 'cf'
|
||||
0 row(s) in 0.4170 seconds
|
||||
|
||||
=> Hbase::Table - test
|
||||
----
|
||||
|
||||
. List Information About your Table
|
||||
+
|
||||
Use the `list` command to
|
||||
+
|
||||
----
|
||||
hbase(main):002:0> list 'test'
|
||||
TABLE
|
||||
test
|
||||
1 row(s) in 0.0180 seconds
|
||||
|
||||
=> ["test"]
|
||||
----
|
||||
|
||||
. Put data into your table.
|
||||
+
|
||||
To put data into your table, use the `put` command.
|
||||
+
|
||||
----
|
||||
hbase(main):003:0> put 'test', 'row1', 'cf:a', 'value1'
|
||||
0 row(s) in 0.0850 seconds
|
||||
|
||||
hbase(main):004:0> put 'test', 'row2', 'cf:b', 'value2'
|
||||
0 row(s) in 0.0110 seconds
|
||||
|
||||
hbase(main):005:0> put 'test', 'row3', 'cf:c', 'value3'
|
||||
0 row(s) in 0.0100 seconds
|
||||
----
|
||||
+
|
||||
Here, we insert three values, one at a time.
|
||||
The first insert is at `row1`, column `cf:a`, with a value of `value1`.
|
||||
Columns in HBase are comprised of a column family prefix, `cf` in this example, followed by a colon and then a column qualifier suffix, `a` in this case.
|
||||
|
||||
. Scan the table for all data at once.
|
||||
+
|
||||
One of the ways to get data from HBase is to scan.
|
||||
Use the `scan` command to scan the table for data.
|
||||
You can limit your scan, but for now, all data is fetched.
|
||||
+
|
||||
----
|
||||
hbase(main):006:0> scan 'test'
|
||||
ROW COLUMN+CELL
|
||||
row1 column=cf:a, timestamp=1421762485768, value=value1
|
||||
row2 column=cf:b, timestamp=1421762491785, value=value2
|
||||
row3 column=cf:c, timestamp=1421762496210, value=value3
|
||||
3 row(s) in 0.0230 seconds
|
||||
----
|
||||
|
||||
. Get a single row of data.
|
||||
+
|
||||
To get a single row of data at a time, use the `get` command.
|
||||
+
|
||||
----
|
||||
hbase(main):007:0> get 'test', 'row1'
|
||||
COLUMN CELL
|
||||
cf:a timestamp=1421762485768, value=value1
|
||||
1 row(s) in 0.0350 seconds
|
||||
----
|
||||
|
||||
. Disable a table.
|
||||
+
|
||||
If you want to delete a table or change its settings, as well as in some other situations, you need to disable the table first, using the `disable` command.
|
||||
You can re-enable it using the `enable` command.
|
||||
+
|
||||
----
|
||||
hbase(main):008:0> disable 'test'
|
||||
0 row(s) in 1.1820 seconds
|
||||
|
||||
hbase(main):009:0> enable 'test'
|
||||
0 row(s) in 0.1770 seconds
|
||||
----
|
||||
+
|
||||
Disable the table again if you tested the `enable` command above:
|
||||
+
|
||||
----
|
||||
hbase(main):010:0> disable 'test'
|
||||
0 row(s) in 1.1820 seconds
|
||||
----
|
||||
|
||||
. Drop the table.
|
||||
+
|
||||
To drop (delete) a table, use the `drop` command.
|
||||
+
|
||||
----
|
||||
hbase(main):011:0> drop 'test'
|
||||
0 row(s) in 0.1370 seconds
|
||||
----
|
||||
|
||||
. Exit the HBase Shell.
|
||||
+
|
||||
To exit the HBase Shell and disconnect from your cluster, use the `quit` command.
|
||||
HBase is still running in the background.
|
||||
|
||||
|
||||
.Procedure: Stop HBase
|
||||
. In the same way that the _bin/start-hbase.sh_ script is provided to conveniently start all HBase daemons, the _bin/stop-hbase.sh_ script stops them.
|
||||
+
|
||||
----
|
||||
|
||||
$ ./bin/stop-hbase.sh
|
||||
stopping hbase....................
|
||||
$
|
||||
----
|
||||
|
||||
. After issuing the command, it can take several minutes for the processes to shut down.
|
||||
Use the `jps` to be sure that the HMaster and HRegionServer processes are shut down.
|
||||
|
||||
[[quickstart_pseudo]]
|
||||
=== Intermediate - Pseudo-Distributed Local Install
|
||||
|
||||
After working your way through <<quickstart,quickstart>>, you can re-configure HBase to run in pseudo-distributed mode.
|
||||
Pseudo-distributed mode means that HBase still runs completely on a single host, but each HBase daemon (HMaster, HRegionServer, and Zookeeper) runs as a separate process.
|
||||
By default, unless you configure the `hbase.rootdir` property as described in <<quickstart,quickstart>>, your data is still stored in _/tmp/_.
|
||||
In this walk-through, we store your data in HDFS instead, assuming you have HDFS available.
|
||||
You can skip the HDFS configuration to continue storing your data in the local filesystem.
|
||||
|
||||
.Hadoop Configuration
|
||||
[NOTE]
|
||||
====
|
||||
This procedure assumes that you have configured Hadoop and HDFS on your local system and or a remote system, and that they are running and available.
|
||||
It also assumes you are using Hadoop 2.
|
||||
Currently, the documentation on the Hadoop website does not include a quick start for Hadoop 2, but the guide at link:http://www.alexjf.net/blog/distributed-systems/hadoop-yarn-installation-definitive-guide is a good starting point.
|
||||
====
|
||||
|
||||
|
||||
. Stop HBase if it is running.
|
||||
+
|
||||
If you have just finished <<quickstart,quickstart>> and HBase is still running, stop it.
|
||||
This procedure will create a totally new directory where HBase will store its data, so any databases you created before will be lost.
|
||||
|
||||
. Configure HBase.
|
||||
+
|
||||
Edit the _hbase-site.xml_ configuration.
|
||||
First, add the following property.
|
||||
which directs HBase to run in distributed mode, with one JVM instance per daemon.
|
||||
+
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<property>
|
||||
<name>hbase.cluster.distributed</name>
|
||||
<value>true</value>
|
||||
</property>
|
||||
----
|
||||
+
|
||||
Next, change the `hbase.rootdir` from the local filesystem to the address of your HDFS instance, using the `hdfs:////` URI syntax.
|
||||
In this example, HDFS is running on the localhost at port 8020.
|
||||
+
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<property>
|
||||
<name>hbase.rootdir</name>
|
||||
<value>hdfs://localhost:8020/hbase</value>
|
||||
</property>
|
||||
----
|
||||
+
|
||||
You do not need to create the directory in HDFS.
|
||||
HBase will do this for you.
|
||||
If you create the directory, HBase will attempt to do a migration, which is not what you want.
|
||||
|
||||
. Start HBase.
|
||||
+
|
||||
Use the _bin/start-hbase.sh_ command to start HBase.
|
||||
If your system is configured correctly, the `jps` command should show the HMaster and HRegionServer processes running.
|
||||
|
||||
. Check the HBase directory in HDFS.
|
||||
+
|
||||
If everything worked correctly, HBase created its directory in HDFS.
|
||||
In the configuration above, it is stored in _/hbase/_ on HDFS.
|
||||
You can use the `hadoop fs` command in Hadoop's _bin/_ directory to list this directory.
|
||||
+
|
||||
----
|
||||
|
||||
$ ./bin/hadoop fs -ls /hbase
|
||||
Found 7 items
|
||||
drwxr-xr-x - hbase users 0 2014-06-25 18:58 /hbase/.tmp
|
||||
drwxr-xr-x - hbase users 0 2014-06-25 21:49 /hbase/WALs
|
||||
drwxr-xr-x - hbase users 0 2014-06-25 18:48 /hbase/corrupt
|
||||
drwxr-xr-x - hbase users 0 2014-06-25 18:58 /hbase/data
|
||||
-rw-r--r-- 3 hbase users 42 2014-06-25 18:41 /hbase/hbase.id
|
||||
-rw-r--r-- 3 hbase users 7 2014-06-25 18:41 /hbase/hbase.version
|
||||
drwxr-xr-x - hbase users 0 2014-06-25 21:49 /hbase/oldWALs
|
||||
----
|
||||
|
||||
. Create a table and populate it with data.
|
||||
+
|
||||
You can use the HBase Shell to create a table, populate it with data, scan and get values from it, using the same procedure as in <<shell_exercises,shell exercises>>.
|
||||
|
||||
. Start and stop a backup HBase Master (HMaster) server.
|
||||
+
|
||||
NOTE: Running multiple HMaster instances on the same hardware does not make sense in a production environment, in the same way that running a pseudo-distributed cluster does not make sense for production.
|
||||
This step is offered for testing and learning purposes only.
|
||||
+
|
||||
The HMaster server controls the HBase cluster.
|
||||
You can start up to 9 backup HMaster servers, which makes 10 total HMasters, counting the primary.
|
||||
To start a backup HMaster, use the `local-master-backup.sh`.
|
||||
For each backup master you want to start, add a parameter representing the port offset for that master.
|
||||
Each HMaster uses three ports (16010, 16020, and 16030 by default). The port offset is added to these ports, so using an offset of 2, the backup HMaster would use ports 16012, 16022, and 16032.
|
||||
The following command starts 3 backup servers using ports 16012/16022/16032, 16013/16023/16033, and 16015/16025/16035.
|
||||
+
|
||||
----
|
||||
|
||||
$ ./bin/local-master-backup.sh 2 3 5
|
||||
----
|
||||
+
|
||||
To kill a backup master without killing the entire cluster, you need to find its process ID (PID). The PID is stored in a file with a name like _/tmp/hbase-USER-X-master.pid_.
|
||||
The only contents of the file is the PID.
|
||||
You can use the `kill -9` command to kill that PID.
|
||||
The following command will kill the master with port offset 1, but leave the cluster running:
|
||||
+
|
||||
----
|
||||
|
||||
$ cat /tmp/hbase-testuser-1-master.pid |xargs kill -9
|
||||
----
|
||||
|
||||
. Start and stop additional RegionServers
|
||||
+
|
||||
The HRegionServer manages the data in its StoreFiles as directed by the HMaster.
|
||||
Generally, one HRegionServer runs per node in the cluster.
|
||||
Running multiple HRegionServers on the same system can be useful for testing in pseudo-distributed mode.
|
||||
The `local-regionservers.sh` command allows you to run multiple RegionServers.
|
||||
It works in a similar way to the `local-master-backup.sh` command, in that each parameter you provide represents the port offset for an instance.
|
||||
Each RegionServer requires two ports, and the default ports are 16020 and 16030.
|
||||
However, the base ports for additional RegionServers are not the default ports since the default ports are used by the HMaster, which is also a RegionServer since HBase version 1.0.0.
|
||||
The base ports are 16200 and 16300 instead.
|
||||
You can run 99 additional RegionServers that are not a HMaster or backup HMaster, on a server.
|
||||
The following command starts four additional RegionServers, running on sequential ports starting at 16202/16302 (base ports 16200/16300 plus 2).
|
||||
+
|
||||
----
|
||||
|
||||
$ .bin/local-regionservers.sh start 2 3 4 5
|
||||
----
|
||||
+
|
||||
To stop a RegionServer manually, use the `local-regionservers.sh` command with the `stop` parameter and the offset of the server to stop.
|
||||
+
|
||||
----
|
||||
$ .bin/local-regionservers.sh stop 3
|
||||
----
|
||||
|
||||
. Stop HBase.
|
||||
+
|
||||
You can stop HBase the same way as in the <<quickstart,quickstart>> procedure, using the _bin/stop-hbase.sh_ command.
|
||||
|
||||
|
||||
[[quickstart_fully_distributed]]
|
||||
=== Advanced - Fully Distributed
|
||||
|
||||
In reality, you need a fully-distributed configuration to fully test HBase and to use it in real-world scenarios.
|
||||
In a distributed configuration, the cluster contains multiple nodes, each of which runs one or more HBase daemon.
|
||||
These include primary and backup Master instances, multiple Zookeeper nodes, and multiple RegionServer nodes.
|
||||
|
||||
This advanced quickstart adds two more nodes to your cluster.
|
||||
The architecture will be as follows:
|
||||
|
||||
.Distributed Cluster Demo Architecture
|
||||
[cols="1,1,1,1", options="header"]
|
||||
|===
|
||||
| Node Name | Master | ZooKeeper | RegionServer
|
||||
| node-a.example.com | yes | yes | no
|
||||
| node-b.example.com | backup | yes | yes
|
||||
| node-c.example.com | no | yes | yes
|
||||
|===
|
||||
|
||||
This quickstart assumes that each node is a virtual machine and that they are all on the same network.
|
||||
It builds upon the previous quickstart, <<quickstart_pseudo>>, assuming that the system you configured in that procedure is now `node-a`.
|
||||
Stop HBase on `node-a` before continuing.
|
||||
|
||||
NOTE: Be sure that all the nodes have full access to communicate, and that no firewall rules are in place which could prevent them from talking to each other.
|
||||
If you see any errors like `no route to host`, check your firewall.
|
||||
|
||||
[[passwordless.ssh.quickstart]]
|
||||
.Procedure: Configure Passwordless SSH Access
|
||||
|
||||
`node-a` needs to be able to log into `node-b` and `node-c` (and to itself) in order to start the daemons.
|
||||
The easiest way to accomplish this is to use the same username on all hosts, and configure password-less SSH login from `node-a` to each of the others.
|
||||
|
||||
. On `node-a`, generate a key pair.
|
||||
+
|
||||
While logged in as the user who will run HBase, generate a SSH key pair, using the following command:
|
||||
+
|
||||
[source,bash]
|
||||
----
|
||||
$ ssh-keygen -t rsa
|
||||
----
|
||||
+
|
||||
If the command succeeds, the location of the key pair is printed to standard output.
|
||||
The default name of the public key is _id_rsa.pub_.
|
||||
|
||||
. Create the directory that will hold the shared keys on the other nodes.
|
||||
+
|
||||
On `node-b` and `node-c`, log in as the HBase user and create a _.ssh/_ directory in the user's home directory, if it does not already exist.
|
||||
If it already exists, be aware that it may already contain other keys.
|
||||
|
||||
. Copy the public key to the other nodes.
|
||||
+
|
||||
Securely copy the public key from `node-a` to each of the nodes, by using the `scp` or some other secure means.
|
||||
On each of the other nodes, create a new file called _.ssh/authorized_keys_ _if it does
|
||||
not already exist_, and append the contents of the _id_rsa.pub_ file to the end of it.
|
||||
Note that you also need to do this for `node-a` itself.
|
||||
+
|
||||
----
|
||||
$ cat id_rsa.pub >> ~/.ssh/authorized_keys
|
||||
----
|
||||
|
||||
. Test password-less login.
|
||||
+
|
||||
If you performed the procedure correctly, if you SSH from `node-a` to either of the other nodes, using the same username, you should not be prompted for a password.
|
||||
|
||||
. Since `node-b` will run a backup Master, repeat the procedure above, substituting `node-b` everywhere you see `node-a`.
|
||||
Be sure not to overwrite your existing _.ssh/authorized_keys_ files, but concatenate the new key onto the existing file using the `>>` operator rather than the `>` operator.
|
||||
|
||||
.Procedure: Prepare `node-a`
|
||||
|
||||
`node-a` will run your primary master and ZooKeeper processes, but no RegionServers.
|
||||
. Stop the RegionServer from starting on `node-a`.
|
||||
|
||||
. Edit _conf/regionservers_ and remove the line which contains `localhost`. Add lines with the hostnames or IP addresses for `node-b` and `node-c`.
|
||||
+
|
||||
Even if you did want to run a RegionServer on `node-a`, you should refer to it by the hostname the other servers would use to communicate with it.
|
||||
In this case, that would be `node-a.example.com`.
|
||||
This enables you to distribute the configuration to each node of your cluster any hostname conflicts.
|
||||
Save the file.
|
||||
|
||||
. Configure HBase to use `node-b` as a backup master.
|
||||
+
|
||||
Create a new file in _conf/_ called _backup-masters_, and add a new line to it with the hostname for `node-b`.
|
||||
In this demonstration, the hostname is `node-b.example.com`.
|
||||
|
||||
. Configure ZooKeeper
|
||||
+
|
||||
In reality, you should carefully consider your ZooKeeper configuration.
|
||||
You can find out more about configuring ZooKeeper in <<zookeeper,zookeeper>>.
|
||||
This configuration will direct HBase to start and manage a ZooKeeper instance on each node of the cluster.
|
||||
+
|
||||
On `node-a`, edit _conf/hbase-site.xml_ and add the following properties.
|
||||
+
|
||||
[source,xml]
|
||||
----
|
||||
<property>
|
||||
<name>hbase.zookeeper.quorum</name>
|
||||
<value>node-a.example.com,node-b.example.com,node-c.example.com</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zookeeper.property.dataDir</name>
|
||||
<value>/usr/local/zookeeper</value>
|
||||
</property>
|
||||
----
|
||||
|
||||
. Everywhere in your configuration that you have referred to `node-a` as `localhost`, change the reference to point to the hostname that the other nodes will use to refer to `node-a`.
|
||||
In these examples, the hostname is `node-a.example.com`.
|
||||
|
||||
.Procedure: Prepare `node-b` and `node-c`
|
||||
|
||||
`node-b` will run a backup master server and a ZooKeeper instance.
|
||||
|
||||
. Download and unpack HBase.
|
||||
+
|
||||
Download and unpack HBase to `node-b`, just as you did for the standalone and pseudo-distributed quickstarts.
|
||||
|
||||
. Copy the configuration files from `node-a` to `node-b`.and `node-c`.
|
||||
+
|
||||
Each node of your cluster needs to have the same configuration information.
|
||||
Copy the contents of the _conf/_ directory to the _conf/_ directory on `node-b` and `node-c`.
|
||||
|
||||
|
||||
.Procedure: Start and Test Your Cluster
|
||||
. Be sure HBase is not running on any node.
|
||||
+
|
||||
If you forgot to stop HBase from previous testing, you will have errors.
|
||||
Check to see whether HBase is running on any of your nodes by using the `jps` command.
|
||||
Look for the processes `HMaster`, `HRegionServer`, and `HQuorumPeer`.
|
||||
If they exist, kill them.
|
||||
|
||||
. Start the cluster.
|
||||
+
|
||||
On `node-a`, issue the `start-hbase.sh` command.
|
||||
Your output will be similar to that below.
|
||||
+
|
||||
----
|
||||
|
||||
$ bin/start-hbase.sh
|
||||
node-c.example.com: starting zookeeper, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-zookeeper-node-c.example.com.out
|
||||
node-a.example.com: starting zookeeper, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-zookeeper-node-a.example.com.out
|
||||
node-b.example.com: starting zookeeper, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-zookeeper-node-b.example.com.out
|
||||
starting master, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-master-node-a.example.com.out
|
||||
node-c.example.com: starting regionserver, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-regionserver-node-c.example.com.out
|
||||
node-b.example.com: starting regionserver, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-regionserver-node-b.example.com.out
|
||||
node-b.example.com: starting master, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-master-nodeb.example.com.out
|
||||
----
|
||||
+
|
||||
ZooKeeper starts first, followed by the master, then the RegionServers, and finally the backup masters.
|
||||
|
||||
. Verify that the processes are running.
|
||||
+
|
||||
On each node of the cluster, run the `jps` command and verify that the correct processes are running on each server.
|
||||
You may see additional Java processes running on your servers as well, if they are used for other purposes.
|
||||
+
|
||||
.`node-a` `jps` Output
|
||||
====
|
||||
----
|
||||
|
||||
$ jps
|
||||
20355 Jps
|
||||
20071 HQuorumPeer
|
||||
20137 HMaster
|
||||
----
|
||||
====
|
||||
+
|
||||
.`node-b` `jps` Output
|
||||
====
|
||||
----
|
||||
$ jps
|
||||
15930 HRegionServer
|
||||
16194 Jps
|
||||
15838 HQuorumPeer
|
||||
16010 HMaster
|
||||
----
|
||||
====
|
||||
+
|
||||
.`node-a` `jps` Output
|
||||
====
|
||||
----
|
||||
$ jps
|
||||
13901 Jps
|
||||
13639 HQuorumPeer
|
||||
13737 HRegionServer
|
||||
----
|
||||
====
|
||||
+
|
||||
.ZooKeeper Process Name
|
||||
[NOTE]
|
||||
====
|
||||
The `HQuorumPeer` process is a ZooKeeper instance which is controlled and started by HBase.
|
||||
If you use ZooKeeper this way, it is limited to one instance per cluster node, , and is appropriate for testing only.
|
||||
If ZooKeeper is run outside of HBase, the process is called `QuorumPeer`.
|
||||
For more about ZooKeeper configuration, including using an external ZooKeeper instance with HBase, see <<zookeeper,zookeeper>>.
|
||||
====
|
||||
|
||||
. Browse to the Web UI.
|
||||
+
|
||||
.Web UI Port Changes
|
||||
NOTE: Web UI Port Changes
|
||||
+
|
||||
In HBase newer than 0.98.x, the HTTP ports used by the HBase Web UI changed from 60010 for the
|
||||
Master and 60030 for each RegionServer to 16010 for the Master and 16030 for the RegionServer.
|
||||
|
||||
+
|
||||
If everything is set up correctly, you should be able to connect to the UI for the Master
|
||||
`http://node-a.example.com:16010/` or the secondary master at `http://node-b.example.com:16010/`
|
||||
for the secondary master, using a web browser.
|
||||
If you can connect via `localhost` but not from another host, check your firewall rules.
|
||||
You can see the web UI for each of the RegionServers at port 16030 of their IP addresses, or by
|
||||
clicking their links in the web UI for the Master.
|
||||
|
||||
. Test what happens when nodes or services disappear.
|
||||
+
|
||||
With a three-node cluster like you have configured, things will not be very resilient.
|
||||
Still, you can test what happens when the primary Master or a RegionServer disappears, by killing the processes and watching the logs.
|
||||
|
||||
|
||||
=== Where to go next
|
||||
|
||||
The next chapter, <<configuration,configuration>>, gives more information about the different HBase run modes, system requirements for running HBase, and critical configuration areas for setting up a distributed HBase cluster.
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,135 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[hbase_apis]]
|
||||
= Apache HBase APIs
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
This chapter provides information about performing operations using HBase native APIs.
|
||||
This information is not exhaustive, and provides a quick reference in addition to the link:http://hbase.apache.org/apidocs/index.html[User API Reference].
|
||||
The examples here are not comprehensive or complete, and should be used for purposes of illustration only.
|
||||
|
||||
Apache HBase also works with multiple external APIs.
|
||||
See <<external_apis>> for more information.
|
||||
|
||||
== Examples
|
||||
|
||||
.Create, modify and delete a Table Using Java
|
||||
====
|
||||
|
||||
[source,java]
|
||||
----
|
||||
package com.example.hbase.admin;
|
||||
|
||||
package util;
|
||||
|
||||
import java.io.IOException;
|
||||
|
||||
import org.apache.hadoop.conf.Configuration;
|
||||
import org.apache.hadoop.fs.Path;
|
||||
import org.apache.hadoop.hbase.HBaseConfiguration;
|
||||
import org.apache.hadoop.hbase.HColumnDescriptor;
|
||||
import org.apache.hadoop.hbase.HConstants;
|
||||
import org.apache.hadoop.hbase.HTableDescriptor;
|
||||
import org.apache.hadoop.hbase.TableName;
|
||||
import org.apache.hadoop.hbase.client.Admin;
|
||||
import org.apache.hadoop.hbase.client.Connection;
|
||||
import org.apache.hadoop.hbase.client.ConnectionFactory;
|
||||
import org.apache.hadoop.hbase.io.compress.Compression.Algorithm;
|
||||
|
||||
public class Example {
|
||||
|
||||
private static final String TABLE_NAME = "MY_TABLE_NAME_TOO";
|
||||
private static final String CF_DEFAULT = "DEFAULT_COLUMN_FAMILY";
|
||||
|
||||
public static void createOrOverwrite(Admin admin, HTableDescriptor table) throws IOException {
|
||||
if (admin.tableExists(table.getTableName())) {
|
||||
admin.disableTable(table.getTableName());
|
||||
admin.deleteTable(table.getTableName());
|
||||
}
|
||||
admin.createTable(table);
|
||||
}
|
||||
|
||||
public static void createSchemaTables(Configuration config) throws IOException {
|
||||
try (Connection connection = ConnectionFactory.createConnection(config);
|
||||
Admin admin = connection.getAdmin()) {
|
||||
|
||||
HTableDescriptor table = new HTableDescriptor(TableName.valueOf(TABLE_NAME));
|
||||
table.addFamily(new HColumnDescriptor(CF_DEFAULT).setCompressionType(Algorithm.SNAPPY));
|
||||
|
||||
System.out.print("Creating table. ");
|
||||
createOrOverwrite(admin, table);
|
||||
System.out.println(" Done.");
|
||||
}
|
||||
}
|
||||
|
||||
public static void modifySchema (Configuration config) throws IOException {
|
||||
try (Connection connection = ConnectionFactory.createConnection(config);
|
||||
Admin admin = connection.getAdmin()) {
|
||||
|
||||
TableName tableName = TableName.valueOf(TABLE_NAME);
|
||||
if (admin.tableExists(tableName)) {
|
||||
System.out.println("Table does not exist.");
|
||||
System.exit(-1);
|
||||
}
|
||||
|
||||
HTableDescriptor table = new HTableDescriptor(tableName);
|
||||
|
||||
// Update existing table
|
||||
HColumnDescriptor newColumn = new HColumnDescriptor("NEWCF");
|
||||
newColumn.setCompactionCompressionType(Algorithm.GZ);
|
||||
newColumn.setMaxVersions(HConstants.ALL_VERSIONS);
|
||||
admin.addColumn(tableName, newColumn);
|
||||
|
||||
// Update existing column family
|
||||
HColumnDescriptor existingColumn = new HColumnDescriptor(CF_DEFAULT);
|
||||
existingColumn.setCompactionCompressionType(Algorithm.GZ);
|
||||
existingColumn.setMaxVersions(HConstants.ALL_VERSIONS);
|
||||
table.modifyFamily(existingColumn);
|
||||
admin.modifyTable(tableName, table);
|
||||
|
||||
// Disable an existing table
|
||||
admin.disableTable(tableName);
|
||||
|
||||
// Delete an existing column family
|
||||
admin.deleteColumn(tableName, CF_DEFAULT.getBytes("UTF-8"));
|
||||
|
||||
// Delete a table (Need to be disabled first)
|
||||
admin.deleteTable(tableName);
|
||||
}
|
||||
}
|
||||
|
||||
public static void main(String... args) throws IOException {
|
||||
Configuration config = HBaseConfiguration.create();
|
||||
|
||||
//Add any necessary configuration files (hbase-site.xml, core-site.xml)
|
||||
config.addResource(new Path(System.getenv("HBASE_CONF_DIR"), "hbase-site.xml"));
|
||||
config.addResource(new Path(System.getenv("HADOOP_CONF_DIR"), "core-site.xml"));
|
||||
createSchemaTables(config);
|
||||
modifySchema(config);
|
||||
}
|
||||
}
|
||||
----
|
||||
====
|
||||
|
|
@ -0,0 +1,37 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[hbase.history]]
|
||||
== HBase History
|
||||
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
* 2006: link:http://research.google.com/archive/bigtable.html[BigTable] paper published by Google.
|
||||
* 2006 (end of year): HBase development starts.
|
||||
* 2008: HBase becomes Hadoop sub-project.
|
||||
* 2010: HBase becomes Apache top-level project.
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,212 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[hbck.in.depth]]
|
||||
== hbck In Depth
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
HBaseFsck (hbck) is a tool for checking for region consistency and table integrity problems and repairing a corrupted HBase.
|
||||
It works in two basic modes -- a read-only inconsistency identifying mode and a multi-phase read-write repair mode.
|
||||
|
||||
=== Running hbck to identify inconsistencies
|
||||
|
||||
To check to see if your HBase cluster has corruptions, run hbck against your HBase cluster:
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck
|
||||
----
|
||||
|
||||
At the end of the commands output it prints OK or tells you the number of INCONSISTENCIES present.
|
||||
You may also want to run run hbck a few times because some inconsistencies can be transient (e.g.
|
||||
cluster is starting up or a region is splitting). Operationally you may want to run hbck regularly and setup alert (e.g.
|
||||
via nagios) if it repeatedly reports inconsistencies . A run of hbck will report a list of inconsistencies along with a brief description of the regions and tables affected.
|
||||
The using the `-details` option will report more details including a representative listing of all the splits present in all the tables.
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck -details
|
||||
----
|
||||
|
||||
If you just want to know if some tables are corrupted, you can limit hbck to identify inconsistencies in only specific tables.
|
||||
For example the following command would only attempt to check table TableFoo and TableBar.
|
||||
The benefit is that hbck will run in less time.
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck TableFoo TableBar
|
||||
----
|
||||
|
||||
=== Inconsistencies
|
||||
|
||||
If after several runs, inconsistencies continue to be reported, you may have encountered a corruption.
|
||||
These should be rare, but in the event they occur newer versions of HBase include the hbck tool enabled with automatic repair options.
|
||||
|
||||
There are two invariants that when violated create inconsistencies in HBase:
|
||||
|
||||
* HBase's region consistency invariant is satisfied if every region is assigned and deployed on exactly one region server, and all places where this state kept is in accordance.
|
||||
* HBase's table integrity invariant is satisfied if for each table, every possible row key resolves to exactly one region.
|
||||
|
||||
Repairs generally work in three phases -- a read-only information gathering phase that identifies inconsistencies, a table integrity repair phase that restores the table integrity invariant, and then finally a region consistency repair phase that restores the region consistency invariant.
|
||||
Starting from version 0.90.0, hbck could detect region consistency problems report on a subset of possible table integrity problems.
|
||||
It also included the ability to automatically fix the most common inconsistency, region assignment and deployment consistency problems.
|
||||
This repair could be done by using the `-fix` command line option.
|
||||
These problems close regions if they are open on the wrong server or on multiple region servers and also assigns regions to region servers if they are not open.
|
||||
|
||||
Starting from HBase versions 0.90.7, 0.92.2 and 0.94.0, several new command line options are introduced to aid repairing a corrupted HBase.
|
||||
This hbck sometimes goes by the nickname ``uberhbck''. Each particular version of uber hbck is compatible with the HBase's of the same major version (0.90.7 uberhbck can repair a 0.90.4). However, versions <=0.90.6 and versions <=0.92.1 may require restarting the master or failing over to a backup master.
|
||||
|
||||
=== Localized repairs
|
||||
|
||||
When repairing a corrupted HBase, it is best to repair the lowest risk inconsistencies first.
|
||||
These are generally region consistency repairs -- localized single region repairs, that only modify in-memory data, ephemeral zookeeper data, or patch holes in the META table.
|
||||
Region consistency requires that the HBase instance has the state of the region's data in HDFS (.regioninfo files), the region's row in the hbase:meta table., and region's deployment/assignments on region servers and the master in accordance.
|
||||
Options for repairing region consistency include:
|
||||
|
||||
* `-fixAssignments` (equivalent to the 0.90 `-fix` option) repairs unassigned, incorrectly assigned or multiply assigned regions.
|
||||
* `-fixMeta` which removes meta rows when corresponding regions are not present in HDFS and adds new meta rows if they regions are present in HDFS while not in META. To fix deployment and assignment problems you can run this command:
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck -fixAssignments
|
||||
----
|
||||
|
||||
To fix deployment and assignment problems as well as repairing incorrect meta rows you can run this command:
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck -fixAssignments -fixMeta
|
||||
----
|
||||
|
||||
There are a few classes of table integrity problems that are low risk repairs.
|
||||
The first two are degenerate (startkey == endkey) regions and backwards regions (startkey > endkey). These are automatically handled by sidelining the data to a temporary directory (/hbck/xxxx). The third low-risk class is hdfs region holes.
|
||||
This can be repaired by using the:
|
||||
|
||||
* `-fixHdfsHoles` option for fabricating new empty regions on the file system.
|
||||
If holes are detected you can use -fixHdfsHoles and should include -fixMeta and -fixAssignments to make the new region consistent.
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck -fixAssignments -fixMeta -fixHdfsHoles
|
||||
----
|
||||
|
||||
Since this is a common operation, we've added a the `-repairHoles` flag that is equivalent to the previous command:
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck -repairHoles
|
||||
----
|
||||
|
||||
If inconsistencies still remain after these steps, you most likely have table integrity problems related to orphaned or overlapping regions.
|
||||
|
||||
=== Region Overlap Repairs
|
||||
|
||||
Table integrity problems can require repairs that deal with overlaps.
|
||||
This is a riskier operation because it requires modifications to the file system, requires some decision making, and may require some manual steps.
|
||||
For these repairs it is best to analyze the output of a `hbck -details` run so that you isolate repairs attempts only upon problems the checks identify.
|
||||
Because this is riskier, there are safeguard that should be used to limit the scope of the repairs.
|
||||
WARNING: This is a relatively new and have only been tested on online but idle HBase instances (no reads/writes). Use at your own risk in an active production environment! The options for repairing table integrity violations include:
|
||||
|
||||
* `-fixHdfsOrphans` option for ``adopting'' a region directory that is missing a region metadata file (the .regioninfo file).
|
||||
* `-fixHdfsOverlaps` ability for fixing overlapping regions
|
||||
|
||||
When repairing overlapping regions, a region's data can be modified on the file system in two ways: 1) by merging regions into a larger region or 2) by sidelining regions by moving data to ``sideline'' directory where data could be restored later.
|
||||
Merging a large number of regions is technically correct but could result in an extremely large region that requires series of costly compactions and splitting operations.
|
||||
In these cases, it is probably better to sideline the regions that overlap with the most other regions (likely the largest ranges) so that merges can happen on a more reasonable scale.
|
||||
Since these sidelined regions are already laid out in HBase's native directory and HFile format, they can be restored by using HBase's bulk load mechanism.
|
||||
The default safeguard thresholds are conservative.
|
||||
These options let you override the default thresholds and to enable the large region sidelining feature.
|
||||
|
||||
* `-maxMerge <n>` maximum number of overlapping regions to merge
|
||||
* `-sidelineBigOverlaps` if more than maxMerge regions are overlapping, sideline attempt to sideline the regions overlapping with the most other regions.
|
||||
* `-maxOverlapsToSideline <n>` if sidelining large overlapping regions, sideline at most n regions.
|
||||
|
||||
Since often times you would just want to get the tables repaired, you can use this option to turn on all repair options:
|
||||
|
||||
* `-repair` includes all the region consistency options and only the hole repairing table integrity options.
|
||||
|
||||
Finally, there are safeguards to limit repairs to only specific tables.
|
||||
For example the following command would only attempt to check and repair table TableFoo and TableBar.
|
||||
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck -repair TableFoo TableBar
|
||||
----
|
||||
|
||||
==== Special cases: Meta is not properly assigned
|
||||
|
||||
There are a few special cases that hbck can handle as well.
|
||||
Sometimes the meta table's only region is inconsistently assigned or deployed.
|
||||
In this case there is a special `-fixMetaOnly` option that can try to fix meta assignments.
|
||||
|
||||
----
|
||||
|
||||
$ ./bin/hbase hbck -fixMetaOnly -fixAssignments
|
||||
----
|
||||
|
||||
==== Special cases: HBase version file is missing
|
||||
|
||||
HBase's data on the file system requires a version file in order to start.
|
||||
If this flie is missing, you can use the `-fixVersionFile` option to fabricating a new HBase version file.
|
||||
This assumes that the version of hbck you are running is the appropriate version for the HBase cluster.
|
||||
|
||||
==== Special case: Root and META are corrupt.
|
||||
|
||||
The most drastic corruption scenario is the case where the ROOT or META is corrupted and HBase will not start.
|
||||
In this case you can use the OfflineMetaRepair tool create new ROOT and META regions and tables.
|
||||
This tool assumes that HBase is offline.
|
||||
It then marches through the existing HBase home directory, loads as much information from region metadata files (.regioninfo files) as possible from the file system.
|
||||
If the region metadata has proper table integrity, it sidelines the original root and meta table directories, and builds new ones with pointers to the region directories and their data.
|
||||
|
||||
----
|
||||
|
||||
$ ./bin/hbase org.apache.hadoop.hbase.util.hbck.OfflineMetaRepair
|
||||
----
|
||||
|
||||
NOTE: This tool is not as clever as uberhbck but can be used to bootstrap repairs that uberhbck can complete.
|
||||
If the tool succeeds you should be able to start hbase and run online repairs if necessary.
|
||||
|
||||
==== Special cases: Offline split parent
|
||||
|
||||
Once a region is split, the offline parent will be cleaned up automatically.
|
||||
Sometimes, daughter regions are split again before their parents are cleaned up.
|
||||
HBase can clean up parents in the right order.
|
||||
However, there could be some lingering offline split parents sometimes.
|
||||
They are in META, in HDFS, and not deployed.
|
||||
But HBase can't clean them up.
|
||||
In this case, you can use the `-fixSplitParents` option to reset them in META to be online and not split.
|
||||
Therefore, hbck can merge them with other regions if fixing overlapping regions option is used.
|
||||
|
||||
This option should not normally be used, and it is not in `-fixAll`.
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1 @@
|
|||
../../site/resources/images
|
||||
|
|
@ -0,0 +1,596 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[mapreduce]]
|
||||
= HBase and MapReduce
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
Apache MapReduce is a software framework used to analyze large amounts of data, and is the framework used most often with link:http://hadoop.apache.org/[Apache Hadoop].
|
||||
MapReduce itself is out of the scope of this document.
|
||||
A good place to get started with MapReduce is http://hadoop.apache.org/docs/r2.6.0/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html.
|
||||
MapReduce version 2 (MR2)is now part of link:http://hadoop.apache.org/docs/r2.3.0/hadoop-yarn/hadoop-yarn-site/[YARN].
|
||||
|
||||
This chapter discusses specific configuration steps you need to take to use MapReduce on data within HBase.
|
||||
In addition, it discusses other interactions and issues between HBase and MapReduce jobs.
|
||||
|
||||
.`mapred` and `mapreduce`
|
||||
[NOTE]
|
||||
====
|
||||
There are two mapreduce packages in HBase as in MapReduce itself: _org.apache.hadoop.hbase.mapred_ and _org.apache.hadoop.hbase.mapreduce_.
|
||||
The former does old-style API and the latter the new style.
|
||||
The latter has more facility though you can usually find an equivalent in the older package.
|
||||
Pick the package that goes with your MapReduce deploy.
|
||||
When in doubt or starting over, pick the _org.apache.hadoop.hbase.mapreduce_.
|
||||
In the notes below, we refer to o.a.h.h.mapreduce but replace with the o.a.h.h.mapred if that is what you are using.
|
||||
====
|
||||
|
||||
[[hbase.mapreduce.classpath]]
|
||||
== HBase, MapReduce, and the CLASSPATH
|
||||
|
||||
By default, MapReduce jobs deployed to a MapReduce cluster do not have access to either the HBase configuration under `$HBASE_CONF_DIR` or the HBase classes.
|
||||
|
||||
To give the MapReduce jobs the access they need, you could add _hbase-site.xml_ to _$HADOOP_HOME/conf_ and add HBase jars to the _$HADOOP_HOME/lib_ directory.
|
||||
You would then need to copy these changes across your cluster. Or you can edit _$HADOOP_HOME/conf/hadoop-env.sh_ and add them to the `HADOOP_CLASSPATH` variable.
|
||||
However, this approach is not recommended because it will pollute your Hadoop install with HBase references.
|
||||
It also requires you to restart the Hadoop cluster before Hadoop can use the HBase data.
|
||||
|
||||
The recommended approach is to let HBase add its dependency jars itself and use `HADOOP_CLASSPATH` or `-libjars`.
|
||||
|
||||
Since HBase 0.90.x, HBase adds its dependency JARs to the job configuration itself.
|
||||
The dependencies only need to be available on the local `CLASSPATH`.
|
||||
The following example runs the bundled HBase link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/RowCounter.html[RowCounter] MapReduce job against a table named `usertable`.
|
||||
If you have not set the environment variables expected in the command (the parts prefixed by a `$` sign and surrounded by curly braces), you can use the actual system paths instead.
|
||||
Be sure to use the correct version of the HBase JAR for your system.
|
||||
The backticks (``` symbols) cause ths shell to execute the sub-commands, setting the output of `hbase classpath` (the command to dump HBase CLASSPATH) to `HADOOP_CLASSPATH`.
|
||||
This example assumes you use a BASH-compatible shell.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/lib/hbase-server-VERSION.jar rowcounter usertable
|
||||
----
|
||||
|
||||
When the command runs, internally, the HBase JAR finds the dependencies it needs for ZooKeeper, Guava, and its other dependencies on the passed `HADOOP_CLASSPATH` and adds the JARs to the MapReduce job configuration.
|
||||
See the source at `TableMapReduceUtil#addDependencyJars(org.apache.hadoop.mapreduce.Job)` for how this is done.
|
||||
|
||||
The command `hbase mapredcp` can also help you dump the CLASSPATH entries required by MapReduce, which are the same jars `TableMapReduceUtil#addDependencyJars` would add.
|
||||
You can add them together with HBase conf directory to `HADOOP_CLASSPATH`.
|
||||
For jobs that do not package their dependencies or call `TableMapReduceUtil#addDependencyJars`, the following command structure is necessary:
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase mapredcp`:${HBASE_HOME}/conf hadoop jar MyApp.jar MyJobMainClass -libjars $(${HBASE_HOME}/bin/hbase mapredcp | tr ':' ',') ...
|
||||
----
|
||||
|
||||
[NOTE]
|
||||
====
|
||||
The example may not work if you are running HBase from its build directory rather than an installed location.
|
||||
You may see an error like the following:
|
||||
|
||||
----
|
||||
java.lang.RuntimeException: java.lang.ClassNotFoundException: org.apache.hadoop.hbase.mapreduce.RowCounter$RowCounterMapper
|
||||
----
|
||||
|
||||
If this occurs, try modifying the command as follows, so that it uses the HBase JARs from the _target/_ directory within the build environment.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ HADOOP_CLASSPATH=${HBASE_BUILD_HOME}/hbase-server/target/hbase-server-VERSION-SNAPSHOT.jar:`${HBASE_BUILD_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_BUILD_HOME}/hbase-server/target/hbase-server-VERSION-SNAPSHOT.jar rowcounter usertable
|
||||
----
|
||||
====
|
||||
|
||||
.Notice to MapReduce users of HBase between 0.96.1 and 0.98.4
|
||||
[CAUTION]
|
||||
====
|
||||
Some MapReduce jobs that use HBase fail to launch.
|
||||
The symptom is an exception similar to the following:
|
||||
|
||||
----
|
||||
Exception in thread "main" java.lang.IllegalAccessError: class
|
||||
com.google.protobuf.ZeroCopyLiteralByteString cannot access its superclass
|
||||
com.google.protobuf.LiteralByteString
|
||||
at java.lang.ClassLoader.defineClass1(Native Method)
|
||||
at java.lang.ClassLoader.defineClass(ClassLoader.java:792)
|
||||
at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
|
||||
at java.net.URLClassLoader.defineClass(URLClassLoader.java:449)
|
||||
at java.net.URLClassLoader.access$100(URLClassLoader.java:71)
|
||||
at java.net.URLClassLoader$1.run(URLClassLoader.java:361)
|
||||
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
|
||||
at java.security.AccessController.doPrivileged(Native Method)
|
||||
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
|
||||
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
|
||||
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
|
||||
at
|
||||
org.apache.hadoop.hbase.protobuf.ProtobufUtil.toScan(ProtobufUtil.java:818)
|
||||
at
|
||||
org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil.convertScanToString(TableMapReduceUtil.java:433)
|
||||
at
|
||||
org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil.initTableMapperJob(TableMapReduceUtil.java:186)
|
||||
at
|
||||
org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil.initTableMapperJob(TableMapReduceUtil.java:147)
|
||||
at
|
||||
org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil.initTableMapperJob(TableMapReduceUtil.java:270)
|
||||
at
|
||||
org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil.initTableMapperJob(TableMapReduceUtil.java:100)
|
||||
...
|
||||
----
|
||||
|
||||
This is caused by an optimization introduced in link:https://issues.apache.org/jira/browse/HBASE-9867[HBASE-9867] that inadvertently introduced a classloader dependency.
|
||||
|
||||
This affects both jobs using the `-libjars` option and "fat jar," those which package their runtime dependencies in a nested `lib` folder.
|
||||
|
||||
In order to satisfy the new classloader requirements, `hbase-protocol.jar` must be included in Hadoop's classpath.
|
||||
See <<hbase.mapreduce.classpath>> for current recommendations for resolving classpath errors.
|
||||
The following is included for historical purposes.
|
||||
|
||||
This can be resolved system-wide by including a reference to the `hbase-protocol.jar` in Hadoop's lib directory, via a symlink or by copying the jar into the new location.
|
||||
|
||||
This can also be achieved on a per-job launch basis by including it in the `HADOOP_CLASSPATH` environment variable at job submission time.
|
||||
When launching jobs that package their dependencies, all three of the following job launching commands satisfy this requirement:
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ HADOOP_CLASSPATH=/path/to/hbase-protocol.jar:/path/to/hbase/conf hadoop jar MyJob.jar MyJobMainClass
|
||||
$ HADOOP_CLASSPATH=$(hbase mapredcp):/path/to/hbase/conf hadoop jar MyJob.jar MyJobMainClass
|
||||
$ HADOOP_CLASSPATH=$(hbase classpath) hadoop jar MyJob.jar MyJobMainClass
|
||||
----
|
||||
|
||||
For jars that do not package their dependencies, the following command structure is necessary:
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ HADOOP_CLASSPATH=$(hbase mapredcp):/etc/hbase/conf hadoop jar MyApp.jar MyJobMainClass -libjars $(hbase mapredcp | tr ':' ',') ...
|
||||
----
|
||||
|
||||
See also link:https://issues.apache.org/jira/browse/HBASE-10304[HBASE-10304] for further discussion of this issue.
|
||||
====
|
||||
|
||||
== MapReduce Scan Caching
|
||||
|
||||
TableMapReduceUtil now restores the option to set scanner caching (the number of rows which are cached before returning the result to the client) on the Scan object that is passed in.
|
||||
This functionality was lost due to a bug in HBase 0.95 (link:https://issues.apache.org/jira/browse/HBASE-11558[HBASE-11558]), which is fixed for HBase 0.98.5 and 0.96.3.
|
||||
The priority order for choosing the scanner caching is as follows:
|
||||
|
||||
. Caching settings which are set on the scan object.
|
||||
. Caching settings which are specified via the configuration option `hbase.client.scanner.caching`, which can either be set manually in _hbase-site.xml_ or via the helper method `TableMapReduceUtil.setScannerCaching()`.
|
||||
. The default value `HConstants.DEFAULT_HBASE_CLIENT_SCANNER_CACHING`, which is set to `100`.
|
||||
|
||||
Optimizing the caching settings is a balance between the time the client waits for a result and the number of sets of results the client needs to receive.
|
||||
If the caching setting is too large, the client could end up waiting for a long time or the request could even time out.
|
||||
If the setting is too small, the scan needs to return results in several pieces.
|
||||
If you think of the scan as a shovel, a bigger cache setting is analogous to a bigger shovel, and a smaller cache setting is equivalent to more shoveling in order to fill the bucket.
|
||||
|
||||
The list of priorities mentioned above allows you to set a reasonable default, and override it for specific operations.
|
||||
|
||||
See the API documentation for link:https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html[Scan] for more details.
|
||||
|
||||
== Bundled HBase MapReduce Jobs
|
||||
|
||||
The HBase JAR also serves as a Driver for some bundled MapReduce jobs.
|
||||
To learn about the bundled MapReduce jobs, run the following command.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-server-VERSION.jar
|
||||
An example program must be given as the first argument.
|
||||
Valid program names are:
|
||||
copytable: Export a table from local cluster to peer cluster
|
||||
completebulkload: Complete a bulk data load.
|
||||
export: Write table data to HDFS.
|
||||
import: Import data written by Export.
|
||||
importtsv: Import data in TSV format.
|
||||
rowcounter: Count rows in HBase table
|
||||
----
|
||||
|
||||
Each of the valid program names are bundled MapReduce jobs.
|
||||
To run one of the jobs, model your command after the following example.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-server-VERSION.jar rowcounter myTable
|
||||
----
|
||||
|
||||
== HBase as a MapReduce Job Data Source and Data Sink
|
||||
|
||||
HBase can be used as a data source, link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableInputFormat.html[TableInputFormat], and data sink, link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableOutputFormat.html[TableOutputFormat] or link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/MultiTableOutputFormat.html[MultiTableOutputFormat], for MapReduce jobs.
|
||||
Writing MapReduce jobs that read or write HBase, it is advisable to subclass link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableMapper.html[TableMapper] and/or link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableReducer.html[TableReducer].
|
||||
See the do-nothing pass-through classes link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/IdentityTableMapper.html[IdentityTableMapper] and link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/IdentityTableReducer.html[IdentityTableReducer] for basic usage.
|
||||
For a more involved example, see link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/RowCounter.html[RowCounter] or review the `org.apache.hadoop.hbase.mapreduce.TestTableMapReduce` unit test.
|
||||
|
||||
If you run MapReduce jobs that use HBase as source or sink, need to specify source and sink table and column names in your configuration.
|
||||
|
||||
When you read from HBase, the `TableInputFormat` requests the list of regions from HBase and makes a map, which is either a `map-per-region` or `mapreduce.job.maps` map, whichever is smaller.
|
||||
If your job only has two maps, raise `mapreduce.job.maps` to a number greater than the number of regions.
|
||||
Maps will run on the adjacent TaskTracker/NodeManager if you are running a TaskTracer/NodeManager and RegionServer per node.
|
||||
When writing to HBase, it may make sense to avoid the Reduce step and write back into HBase from within your map.
|
||||
This approach works when your job does not need the sort and collation that MapReduce does on the map-emitted data.
|
||||
On insert, HBase 'sorts' so there is no point double-sorting (and shuffling data around your MapReduce cluster) unless you need to.
|
||||
If you do not need the Reduce, your map might emit counts of records processed for reporting at the end of the job, or set the number of Reduces to zero and use TableOutputFormat.
|
||||
If running the Reduce step makes sense in your case, you should typically use multiple reducers so that load is spread across the HBase cluster.
|
||||
|
||||
A new HBase partitioner, the link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/HRegionPartitioner.html[HRegionPartitioner], can run as many reducers the number of existing regions.
|
||||
The HRegionPartitioner is suitable when your table is large and your upload will not greatly alter the number of existing regions upon completion.
|
||||
Otherwise use the default partitioner.
|
||||
|
||||
== Writing HFiles Directly During Bulk Import
|
||||
|
||||
If you are importing into a new table, you can bypass the HBase API and write your content directly to the filesystem, formatted into HBase data files (HFiles). Your import will run faster, perhaps an order of magnitude faster.
|
||||
For more on how this mechanism works, see <<arch.bulk.load>>.
|
||||
|
||||
== RowCounter Example
|
||||
|
||||
The included link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/RowCounter.html[RowCounter] MapReduce job uses `TableInputFormat` and does a count of all rows in the specified table.
|
||||
To run it, use the following command:
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ ./bin/hadoop jar hbase-X.X.X.jar
|
||||
----
|
||||
|
||||
This will invoke the HBase MapReduce Driver class.
|
||||
Select `rowcounter` from the choice of jobs offered.
|
||||
This will print rowcounter usage advice to standard output.
|
||||
Specify the tablename, column to count, and output directory.
|
||||
If you have classpath errors, see <<hbase.mapreduce.classpath>>.
|
||||
|
||||
[[splitter]]
|
||||
== Map-Task Splitting
|
||||
|
||||
[[splitter.default]]
|
||||
=== The Default HBase MapReduce Splitter
|
||||
|
||||
When link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableInputFormat.html[TableInputFormat] is used to source an HBase table in a MapReduce job, its splitter will make a map task for each region of the table.
|
||||
Thus, if there are 100 regions in the table, there will be 100 map-tasks for the job - regardless of how many column families are selected in the Scan.
|
||||
|
||||
[[splitter.custom]]
|
||||
=== Custom Splitters
|
||||
|
||||
For those interested in implementing custom splitters, see the method `getSplits` in link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableInputFormatBase.html[TableInputFormatBase].
|
||||
That is where the logic for map-task assignment resides.
|
||||
|
||||
[[mapreduce.example]]
|
||||
== HBase MapReduce Examples
|
||||
|
||||
[[mapreduce.example.read]]
|
||||
=== HBase MapReduce Read Example
|
||||
|
||||
The following is an example of using HBase as a MapReduce source in read-only manner.
|
||||
Specifically, there is a Mapper instance but no Reducer, and nothing is being emitted from the Mapper.
|
||||
There job would be defined as follows...
|
||||
|
||||
[source,java]
|
||||
----
|
||||
Configuration config = HBaseConfiguration.create();
|
||||
Job job = new Job(config, "ExampleRead");
|
||||
job.setJarByClass(MyReadJob.class); // class that contains mapper
|
||||
|
||||
Scan scan = new Scan();
|
||||
scan.setCaching(500); // 1 is the default in Scan, which will be bad for MapReduce jobs
|
||||
scan.setCacheBlocks(false); // don't set to true for MR jobs
|
||||
// set other scan attrs
|
||||
...
|
||||
|
||||
TableMapReduceUtil.initTableMapperJob(
|
||||
tableName, // input HBase table name
|
||||
scan, // Scan instance to control CF and attribute selection
|
||||
MyMapper.class, // mapper
|
||||
null, // mapper output key
|
||||
null, // mapper output value
|
||||
job);
|
||||
job.setOutputFormatClass(NullOutputFormat.class); // because we aren't emitting anything from mapper
|
||||
|
||||
boolean b = job.waitForCompletion(true);
|
||||
if (!b) {
|
||||
throw new IOException("error with job!");
|
||||
}
|
||||
----
|
||||
|
||||
...and the mapper instance would extend link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableMapper.html[TableMapper]...
|
||||
|
||||
[source,java]
|
||||
----
|
||||
public static class MyMapper extends TableMapper<Text, Text> {
|
||||
|
||||
public void map(ImmutableBytesWritable row, Result value, Context context) throws InterruptedException, IOException {
|
||||
// process data for the row from the Result instance.
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
[[mapreduce.example.readwrite]]
|
||||
=== HBase MapReduce Read/Write Example
|
||||
|
||||
The following is an example of using HBase both as a source and as a sink with MapReduce.
|
||||
This example will simply copy data from one table to another.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
Configuration config = HBaseConfiguration.create();
|
||||
Job job = new Job(config,"ExampleReadWrite");
|
||||
job.setJarByClass(MyReadWriteJob.class); // class that contains mapper
|
||||
|
||||
Scan scan = new Scan();
|
||||
scan.setCaching(500); // 1 is the default in Scan, which will be bad for MapReduce jobs
|
||||
scan.setCacheBlocks(false); // don't set to true for MR jobs
|
||||
// set other scan attrs
|
||||
|
||||
TableMapReduceUtil.initTableMapperJob(
|
||||
sourceTable, // input table
|
||||
scan, // Scan instance to control CF and attribute selection
|
||||
MyMapper.class, // mapper class
|
||||
null, // mapper output key
|
||||
null, // mapper output value
|
||||
job);
|
||||
TableMapReduceUtil.initTableReducerJob(
|
||||
targetTable, // output table
|
||||
null, // reducer class
|
||||
job);
|
||||
job.setNumReduceTasks(0);
|
||||
|
||||
boolean b = job.waitForCompletion(true);
|
||||
if (!b) {
|
||||
throw new IOException("error with job!");
|
||||
}
|
||||
----
|
||||
|
||||
An explanation is required of what `TableMapReduceUtil` is doing, especially with the reducer. link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableOutputFormat.html[TableOutputFormat] is being used as the outputFormat class, and several parameters are being set on the config (e.g., `TableOutputFormat.OUTPUT_TABLE`), as well as setting the reducer output key to `ImmutableBytesWritable` and reducer value to `Writable`.
|
||||
These could be set by the programmer on the job and conf, but `TableMapReduceUtil` tries to make things easier.
|
||||
|
||||
The following is the example mapper, which will create a `Put` and matching the input `Result` and emit it.
|
||||
Note: this is what the CopyTable utility does.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
public static class MyMapper extends TableMapper<ImmutableBytesWritable, Put> {
|
||||
|
||||
public void map(ImmutableBytesWritable row, Result value, Context context) throws IOException, InterruptedException {
|
||||
// this example is just copying the data from the source table...
|
||||
context.write(row, resultToPut(row,value));
|
||||
}
|
||||
|
||||
private static Put resultToPut(ImmutableBytesWritable key, Result result) throws IOException {
|
||||
Put put = new Put(key.get());
|
||||
for (KeyValue kv : result.raw()) {
|
||||
put.add(kv);
|
||||
}
|
||||
return put;
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
There isn't actually a reducer step, so `TableOutputFormat` takes care of sending the `Put` to the target table.
|
||||
|
||||
This is just an example, developers could choose not to use `TableOutputFormat` and connect to the target table themselves.
|
||||
|
||||
[[mapreduce.example.readwrite.multi]]
|
||||
=== HBase MapReduce Read/Write Example With Multi-Table Output
|
||||
|
||||
TODO: example for `MultiTableOutputFormat`.
|
||||
|
||||
[[mapreduce.example.summary]]
|
||||
=== HBase MapReduce Summary to HBase Example
|
||||
|
||||
The following example uses HBase as a MapReduce source and sink with a summarization step.
|
||||
This example will count the number of distinct instances of a value in a table and write those summarized counts in another table.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
Configuration config = HBaseConfiguration.create();
|
||||
Job job = new Job(config,"ExampleSummary");
|
||||
job.setJarByClass(MySummaryJob.class); // class that contains mapper and reducer
|
||||
|
||||
Scan scan = new Scan();
|
||||
scan.setCaching(500); // 1 is the default in Scan, which will be bad for MapReduce jobs
|
||||
scan.setCacheBlocks(false); // don't set to true for MR jobs
|
||||
// set other scan attrs
|
||||
|
||||
TableMapReduceUtil.initTableMapperJob(
|
||||
sourceTable, // input table
|
||||
scan, // Scan instance to control CF and attribute selection
|
||||
MyMapper.class, // mapper class
|
||||
Text.class, // mapper output key
|
||||
IntWritable.class, // mapper output value
|
||||
job);
|
||||
TableMapReduceUtil.initTableReducerJob(
|
||||
targetTable, // output table
|
||||
MyTableReducer.class, // reducer class
|
||||
job);
|
||||
job.setNumReduceTasks(1); // at least one, adjust as required
|
||||
|
||||
boolean b = job.waitForCompletion(true);
|
||||
if (!b) {
|
||||
throw new IOException("error with job!");
|
||||
}
|
||||
----
|
||||
|
||||
In this example mapper a column with a String-value is chosen as the value to summarize upon.
|
||||
This value is used as the key to emit from the mapper, and an `IntWritable` represents an instance counter.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
public static class MyMapper extends TableMapper<Text, IntWritable> {
|
||||
public static final byte[] CF = "cf".getBytes();
|
||||
public static final byte[] ATTR1 = "attr1".getBytes();
|
||||
|
||||
private final IntWritable ONE = new IntWritable(1);
|
||||
private Text text = new Text();
|
||||
|
||||
public void map(ImmutableBytesWritable row, Result value, Context context) throws IOException, InterruptedException {
|
||||
String val = new String(value.getValue(CF, ATTR1));
|
||||
text.set(val); // we can only emit Writables...
|
||||
context.write(text, ONE);
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
In the reducer, the "ones" are counted (just like any other MR example that does this), and then emits a `Put`.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
public static class MyTableReducer extends TableReducer<Text, IntWritable, ImmutableBytesWritable> {
|
||||
public static final byte[] CF = "cf".getBytes();
|
||||
public static final byte[] COUNT = "count".getBytes();
|
||||
|
||||
public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
|
||||
int i = 0;
|
||||
for (IntWritable val : values) {
|
||||
i += val.get();
|
||||
}
|
||||
Put put = new Put(Bytes.toBytes(key.toString()));
|
||||
put.add(CF, COUNT, Bytes.toBytes(i));
|
||||
|
||||
context.write(null, put);
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
[[mapreduce.example.summary.file]]
|
||||
=== HBase MapReduce Summary to File Example
|
||||
|
||||
This very similar to the summary example above, with exception that this is using HBase as a MapReduce source but HDFS as the sink.
|
||||
The differences are in the job setup and in the reducer.
|
||||
The mapper remains the same.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
Configuration config = HBaseConfiguration.create();
|
||||
Job job = new Job(config,"ExampleSummaryToFile");
|
||||
job.setJarByClass(MySummaryFileJob.class); // class that contains mapper and reducer
|
||||
|
||||
Scan scan = new Scan();
|
||||
scan.setCaching(500); // 1 is the default in Scan, which will be bad for MapReduce jobs
|
||||
scan.setCacheBlocks(false); // don't set to true for MR jobs
|
||||
// set other scan attrs
|
||||
|
||||
TableMapReduceUtil.initTableMapperJob(
|
||||
sourceTable, // input table
|
||||
scan, // Scan instance to control CF and attribute selection
|
||||
MyMapper.class, // mapper class
|
||||
Text.class, // mapper output key
|
||||
IntWritable.class, // mapper output value
|
||||
job);
|
||||
job.setReducerClass(MyReducer.class); // reducer class
|
||||
job.setNumReduceTasks(1); // at least one, adjust as required
|
||||
FileOutputFormat.setOutputPath(job, new Path("/tmp/mr/mySummaryFile")); // adjust directories as required
|
||||
|
||||
boolean b = job.waitForCompletion(true);
|
||||
if (!b) {
|
||||
throw new IOException("error with job!");
|
||||
}
|
||||
----
|
||||
|
||||
As stated above, the previous Mapper can run unchanged with this example.
|
||||
As for the Reducer, it is a "generic" Reducer instead of extending TableMapper and emitting Puts.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
public static class MyReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
|
||||
|
||||
public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
|
||||
int i = 0;
|
||||
for (IntWritable val : values) {
|
||||
i += val.get();
|
||||
}
|
||||
context.write(key, new IntWritable(i));
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
[[mapreduce.example.summary.noreducer]]
|
||||
=== HBase MapReduce Summary to HBase Without Reducer
|
||||
|
||||
It is also possible to perform summaries without a reducer - if you use HBase as the reducer.
|
||||
|
||||
An HBase target table would need to exist for the job summary.
|
||||
The Table method `incrementColumnValue` would be used to atomically increment values.
|
||||
From a performance perspective, it might make sense to keep a Map of values with their values to be incremented for each map-task, and make one update per key at during the `cleanup` method of the mapper.
|
||||
However, your mileage may vary depending on the number of rows to be processed and unique keys.
|
||||
|
||||
In the end, the summary results are in HBase.
|
||||
|
||||
[[mapreduce.example.summary.rdbms]]
|
||||
=== HBase MapReduce Summary to RDBMS
|
||||
|
||||
Sometimes it is more appropriate to generate summaries to an RDBMS.
|
||||
For these cases, it is possible to generate summaries directly to an RDBMS via a custom reducer.
|
||||
The `setup` method can connect to an RDBMS (the connection information can be passed via custom parameters in the context) and the cleanup method can close the connection.
|
||||
|
||||
It is critical to understand that number of reducers for the job affects the summarization implementation, and you'll have to design this into your reducer.
|
||||
Specifically, whether it is designed to run as a singleton (one reducer) or multiple reducers.
|
||||
Neither is right or wrong, it depends on your use-case.
|
||||
Recognize that the more reducers that are assigned to the job, the more simultaneous connections to the RDBMS will be created - this will scale, but only to a point.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
public static class MyRdbmsReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
|
||||
|
||||
private Connection c = null;
|
||||
|
||||
public void setup(Context context) {
|
||||
// create DB connection...
|
||||
}
|
||||
|
||||
public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
|
||||
// do summarization
|
||||
// in this example the keys are Text, but this is just an example
|
||||
}
|
||||
|
||||
public void cleanup(Context context) {
|
||||
// close db connection
|
||||
}
|
||||
|
||||
}
|
||||
----
|
||||
|
||||
In the end, the summary results are written to your RDBMS table/s.
|
||||
|
||||
[[mapreduce.htable.access]]
|
||||
== Accessing Other HBase Tables in a MapReduce Job
|
||||
|
||||
Although the framework currently allows one HBase table as input to a MapReduce job, other HBase tables can be accessed as lookup tables, etc., in a MapReduce job via creating an Table instance in the setup method of the Mapper.
|
||||
[source,java]
|
||||
----
|
||||
public class MyMapper extends TableMapper<Text, LongWritable> {
|
||||
private Table myOtherTable;
|
||||
|
||||
public void setup(Context context) {
|
||||
// In here create a Connection to the cluster and save it or use the Connection
|
||||
// from the existing table
|
||||
myOtherTable = connection.getTable("myOtherTable");
|
||||
}
|
||||
|
||||
public void map(ImmutableBytesWritable row, Result value, Context context) throws IOException, InterruptedException {
|
||||
// process Result...
|
||||
// use 'myOtherTable' for lookups
|
||||
}
|
||||
----
|
||||
|
||||
[[mapreduce.specex]]
|
||||
== Speculative Execution
|
||||
|
||||
It is generally advisable to turn off speculative execution for MapReduce jobs that use HBase as a source.
|
||||
This can either be done on a per-Job basis through properties, on on the entire cluster.
|
||||
Especially for longer running jobs, speculative execution will create duplicate map-tasks which will double-write your data to HBase; this is probably not what you want.
|
||||
|
||||
See <<spec.ex,spec.ex>> for more information.
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,38 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[orca]]
|
||||
== Apache HBase Orca
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
.Apache HBase Orca
|
||||
image::jumping-orca_rotated_25percent.png[]
|
||||
|
||||
link:https://issues.apache.org/jira/browse/HBASE-4920[An Orca is the Apache HBase mascot.] See NOTICES.txt.
|
||||
Our Orca logo we got here: http://www.vectorfree.com/jumping-orca It is licensed Creative Commons Attribution 3.0.
|
||||
See https://creativecommons.org/licenses/by/3.0/us/ We changed the logo by stripping the colored background, inverting it and then rotating it some.
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,80 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[other.info]]
|
||||
== Other Information About HBase
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
[[other.info.videos]]
|
||||
=== HBase Videos
|
||||
|
||||
.Introduction to HBase
|
||||
* link:http://www.cloudera.com/content/cloudera/en/resources/library/presentation/chicago_data_summit_apache_hbase_an_introduction_todd_lipcon.html[Introduction to HBase] by Todd Lipcon (Chicago Data Summit 2011).
|
||||
* link:http://www.cloudera.com/videos/intorduction-hbase-todd-lipcon[Introduction to HBase] by Todd Lipcon (2010).
|
||||
link:http://www.cloudera.com/videos/hadoop-world-2011-presentation-video-building-realtime-big-data-services-at-facebook-with-hadoop-and-hbase[Building Real Time Services at Facebook with HBase] by Jonathan Gray (Hadoop World 2011).
|
||||
|
||||
link:http://www.cloudera.com/videos/hw10_video_how_stumbleupon_built_and_advertising_platform_using_hbase_and_hadoop[HBase and Hadoop, Mixing Real-Time and Batch Processing at StumbleUpon] by JD Cryans (Hadoop World 2010).
|
||||
|
||||
[[other.info.pres]]
|
||||
=== HBase Presentations (Slides)
|
||||
|
||||
link:http://www.cloudera.com/content/cloudera/en/resources/library/hadoopworld/hadoop-world-2011-presentation-video-advanced-hbase-schema-design.html[Advanced HBase Schema Design] by Lars George (Hadoop World 2011).
|
||||
|
||||
link:http://www.slideshare.net/cloudera/chicago-data-summit-apache-hbase-an-introduction[Introduction to HBase] by Todd Lipcon (Chicago Data Summit 2011).
|
||||
|
||||
link:http://www.slideshare.net/cloudera/hw09-practical-h-base-getting-the-most-from-your-h-base-install[Getting The Most From Your HBase Install] by Ryan Rawson, Jonathan Gray (Hadoop World 2009).
|
||||
|
||||
[[other.info.papers]]
|
||||
=== HBase Papers
|
||||
|
||||
link:http://research.google.com/archive/bigtable.html[BigTable] by Google (2006).
|
||||
|
||||
link:http://www.larsgeorge.com/2010/05/hbase-file-locality-in-hdfs.html[HBase and HDFS Locality] by Lars George (2010).
|
||||
|
||||
link:http://ianvarley.com/UT/MR/Varley_MastersReport_Full_2009-08-07.pdf[No Relation: The Mixed Blessings of Non-Relational Databases] by Ian Varley (2009).
|
||||
|
||||
[[other.info.sites]]
|
||||
=== HBase Sites
|
||||
|
||||
link:http://www.cloudera.com/blog/category/hbase/[Cloudera's HBase Blog] has a lot of links to useful HBase information.
|
||||
|
||||
* link:http://www.cloudera.com/blog/2010/04/cap-confusion-problems-with-partition-tolerance/[CAP Confusion] is a relevant entry for background information on distributed storage systems.
|
||||
|
||||
link:http://wiki.apache.org/hadoop/HBase/HBasePresentations[HBase Wiki] has a page with a number of presentations.
|
||||
|
||||
link:http://refcardz.dzone.com/refcardz/hbase[HBase RefCard] from DZone.
|
||||
|
||||
[[other.info.books]]
|
||||
=== HBase Books
|
||||
|
||||
link:http://shop.oreilly.com/product/0636920014348.do[HBase: The Definitive Guide] by Lars George.
|
||||
|
||||
[[other.info.books.hadoop]]
|
||||
=== Hadoop Books
|
||||
|
||||
link:http://shop.oreilly.com/product/9780596521981.do[Hadoop: The Definitive Guide] by Tom White.
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,890 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
|
||||
[[performance]]
|
||||
= Apache HBase Performance Tuning
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
[[perf.os]]
|
||||
== Operating System
|
||||
|
||||
[[perf.os.ram]]
|
||||
=== Memory
|
||||
|
||||
RAM, RAM, RAM.
|
||||
Don't starve HBase.
|
||||
|
||||
[[perf.os.64]]
|
||||
=== 64-bit
|
||||
|
||||
Use a 64-bit platform (and 64-bit JVM).
|
||||
|
||||
[[perf.os.swap]]
|
||||
=== Swapping
|
||||
|
||||
Watch out for swapping.
|
||||
Set `swappiness` to 0.
|
||||
|
||||
[[perf.network]]
|
||||
== Network
|
||||
|
||||
Perhaps the most important factor in avoiding network issues degrading Hadoop and HBase performance is the switching hardware that is used, decisions made early in the scope of the project can cause major problems when you double or triple the size of your cluster (or more).
|
||||
|
||||
Important items to consider:
|
||||
|
||||
* Switching capacity of the device
|
||||
* Number of systems connected
|
||||
* Uplink capacity
|
||||
|
||||
[[perf.network.1switch]]
|
||||
=== Single Switch
|
||||
|
||||
The single most important factor in this configuration is that the switching capacity of the hardware is capable of handling the traffic which can be generated by all systems connected to the switch.
|
||||
Some lower priced commodity hardware can have a slower switching capacity than could be utilized by a full switch.
|
||||
|
||||
[[perf.network.2switch]]
|
||||
=== Multiple Switches
|
||||
|
||||
Multiple switches are a potential pitfall in the architecture.
|
||||
The most common configuration of lower priced hardware is a simple 1Gbps uplink from one switch to another.
|
||||
This often overlooked pinch point can easily become a bottleneck for cluster communication.
|
||||
Especially with MapReduce jobs that are both reading and writing a lot of data the communication across this uplink could be saturated.
|
||||
|
||||
Mitigation of this issue is fairly simple and can be accomplished in multiple ways:
|
||||
|
||||
* Use appropriate hardware for the scale of the cluster which you're attempting to build.
|
||||
* Use larger single switch configurations i.e.
|
||||
single 48 port as opposed to 2x 24 port
|
||||
* Configure port trunking for uplinks to utilize multiple interfaces to increase cross switch bandwidth.
|
||||
|
||||
[[perf.network.multirack]]
|
||||
=== Multiple Racks
|
||||
|
||||
Multiple rack configurations carry the same potential issues as multiple switches, and can suffer performance degradation from two main areas:
|
||||
|
||||
* Poor switch capacity performance
|
||||
* Insufficient uplink to another rack
|
||||
|
||||
If the the switches in your rack have appropriate switching capacity to handle all the hosts at full speed, the next most likely issue will be caused by homing more of your cluster across racks.
|
||||
The easiest way to avoid issues when spanning multiple racks is to use port trunking to create a bonded uplink to other racks.
|
||||
The downside of this method however, is in the overhead of ports that could potentially be used.
|
||||
An example of this is, creating an 8Gbps port channel from rack A to rack B, using 8 of your 24 ports to communicate between racks gives you a poor ROI, using too few however can mean you're not getting the most out of your cluster.
|
||||
|
||||
Using 10Gbe links between racks will greatly increase performance, and assuming your switches support a 10Gbe uplink or allow for an expansion card will allow you to save your ports for machines as opposed to uplinks.
|
||||
|
||||
[[perf.network.ints]]
|
||||
=== Network Interfaces
|
||||
|
||||
Are all the network interfaces functioning correctly? Are you sure? See the Troubleshooting Case Study in <<casestudies.slownode>>.
|
||||
|
||||
[[perf.network.call_me_maybe]]
|
||||
=== Network Consistency and Partition Tolerance
|
||||
The link:http://en.wikipedia.org/wiki/CAP_theorem[CAP Theorem] states that a distributed system can maintain two out of the following three charateristics:
|
||||
- *C*onsistency -- all nodes see the same data.
|
||||
- *A*vailability -- every request receives a response about whether it succeeded or failed.
|
||||
- *P*artition tolerance -- the system continues to operate even if some of its components become unavailable to the others.
|
||||
|
||||
HBase favors consistency and partition tolerance, where a decision has to be made. Coda Hale explains why partition tolerance is so important, in http://codahale.com/you-cant-sacrifice-partition-tolerance/.
|
||||
|
||||
Robert Yokota used an automated testing framework called link:https://aphyr.com/tags/jepsen[Jepson] to test HBase's partition tolerance in the face of network partitions, using techniques modeled after Aphyr's link:https://aphyr.com/posts/281-call-me-maybe-carly-rae-jepsen-and-the-perils-of-network-partitions[Call Me Maybe] series. The results, available as a link:http://eng.yammer.com/call-me-maybe-hbase/[blog post] and an link:http://eng.yammer.com/call-me-maybe-hbase-addendum/[addendum], show that HBase performs correctly.
|
||||
|
||||
[[jvm]]
|
||||
== Java
|
||||
|
||||
[[gc]]
|
||||
=== The Garbage Collector and Apache HBase
|
||||
|
||||
[[gcpause]]
|
||||
==== Long GC pauses
|
||||
|
||||
In his presentation, link:http://www.slideshare.net/cloudera/hbase-hug-presentation[Avoiding Full GCs with MemStore-Local Allocation Buffers], Todd Lipcon describes two cases of stop-the-world garbage collections common in HBase, especially during loading; CMS failure modes and old generation heap fragmentation brought.
|
||||
|
||||
To address the first, start the CMS earlier than default by adding `-XX:CMSInitiatingOccupancyFraction` and setting it down from defaults.
|
||||
Start at 60 or 70 percent (The lower you bring down the threshold, the more GCing is done, the more CPU used). To address the second fragmentation issue, Todd added an experimental facility,
|
||||
(MSLAB), that must be explicitly enabled in Apache HBase 0.90.x (It's defaulted to be _on_ in Apache 0.92.x HBase). Set `hbase.hregion.memstore.mslab.enabled` to true in your `Configuration`.
|
||||
See the cited slides for background and detail.
|
||||
The latest JVMs do better regards fragmentation so make sure you are running a recent release.
|
||||
Read down in the message, link:http://osdir.com/ml/hotspot-gc-use/2011-11/msg00002.html[Identifying concurrent mode failures caused by fragmentation].
|
||||
Be aware that when enabled, each MemStore instance will occupy at least an MSLAB instance of memory.
|
||||
If you have thousands of regions or lots of regions each with many column families, this allocation of MSLAB may be responsible for a good portion of your heap allocation and in an extreme case cause you to OOME.
|
||||
Disable MSLAB in this case, or lower the amount of memory it uses or float less regions per server.
|
||||
|
||||
If you have a write-heavy workload, check out link:https://issues.apache.org/jira/browse/HBASE-8163[HBASE-8163 MemStoreChunkPool: An improvement for JAVA GC when using MSLAB].
|
||||
It describes configurations to lower the amount of young GC during write-heavy loadings.
|
||||
If you do not have HBASE-8163 installed, and you are trying to improve your young GC times, one trick to consider -- courtesy of our Liang Xie -- is to set the GC config `-XX:PretenureSizeThreshold` in _hbase-env.sh_ to be just smaller than the size of `hbase.hregion.memstore.mslab.chunksize` so MSLAB allocations happen in the tenured space directly rather than first in the young gen.
|
||||
You'd do this because these MSLAB allocations are going to likely make it to the old gen anyways and rather than pay the price of a copies between s0 and s1 in eden space followed by the copy up from young to old gen after the MSLABs have achieved sufficient tenure, save a bit of YGC churn and allocate in the old gen directly.
|
||||
|
||||
For more information about GC logs, see <<trouble.log.gc>>.
|
||||
|
||||
Consider also enabling the off-heap Block Cache.
|
||||
This has been shown to mitigate GC pause times.
|
||||
See <<block.cache>>
|
||||
|
||||
[[perf.configurations]]
|
||||
== HBase Configurations
|
||||
|
||||
See <<recommended_configurations>>.
|
||||
|
||||
[[perf.compactions.and.splits]]
|
||||
=== Managing Compactions
|
||||
|
||||
For larger systems, managing link:[compactions and splits] may be something you want to consider.
|
||||
|
||||
[[perf.handlers]]
|
||||
=== `hbase.regionserver.handler.count`
|
||||
|
||||
See <<hbase.regionserver.handler.count>>.
|
||||
|
||||
[[perf.hfile.block.cache.size]]
|
||||
=== `hfile.block.cache.size`
|
||||
|
||||
See <<hfile.block.cache.size>>.
|
||||
A memory setting for the RegionServer process.
|
||||
|
||||
[[blockcache.prefetch]]
|
||||
=== Prefetch Option for Blockcache
|
||||
|
||||
link:https://issues.apache.org/jira/browse/HBASE-9857[HBASE-9857] adds a new option to prefetch HFile contents when opening the BlockCache, if a Column family or RegionServer property is set.
|
||||
This option is available for HBase 0.98.3 and later.
|
||||
The purpose is to warm the BlockCache as rapidly as possible after the cache is opened, using in-memory table data, and not counting the prefetching as cache misses.
|
||||
This is great for fast reads, but is not a good idea if the data to be preloaded will not fit into the BlockCache.
|
||||
It is useful for tuning the IO impact of prefetching versus the time before all data blocks are in cache.
|
||||
|
||||
To enable prefetching on a given column family, you can use HBase Shell or use the API.
|
||||
|
||||
.Enable Prefetch Using HBase Shell
|
||||
====
|
||||
----
|
||||
hbase> create 'MyTable', { NAME => 'myCF', PREFETCH_BLOCKS_ON_OPEN => 'true' }
|
||||
----
|
||||
====
|
||||
|
||||
.Enable Prefetch Using the API
|
||||
====
|
||||
[source,java]
|
||||
----
|
||||
|
||||
// ...
|
||||
HTableDescriptor tableDesc = new HTableDescriptor("myTable");
|
||||
HColumnDescriptor cfDesc = new HColumnDescriptor("myCF");
|
||||
cfDesc.setPrefetchBlocksOnOpen(true);
|
||||
tableDesc.addFamily(cfDesc);
|
||||
// ...
|
||||
----
|
||||
====
|
||||
|
||||
See the API documentation for link:https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/io/hfile/CacheConfig.html[CacheConfig].
|
||||
|
||||
[[perf.rs.memstore.size]]
|
||||
=== `hbase.regionserver.global.memstore.size`
|
||||
|
||||
See <<hbase.regionserver.global.memstore.size>>.
|
||||
This memory setting is often adjusted for the RegionServer process depending on needs.
|
||||
|
||||
[[perf.rs.memstore.size.lower.limit]]
|
||||
=== `hbase.regionserver.global.memstore.size.lower.limit`
|
||||
|
||||
See <<hbase.regionserver.global.memstore.size.lower.limit>>.
|
||||
This memory setting is often adjusted for the RegionServer process depending on needs.
|
||||
|
||||
[[perf.hstore.blockingstorefiles]]
|
||||
=== `hbase.hstore.blockingStoreFiles`
|
||||
|
||||
See <<hbase.hstore.blockingstorefiles>>.
|
||||
If there is blocking in the RegionServer logs, increasing this can help.
|
||||
|
||||
[[perf.hregion.memstore.block.multiplier]]
|
||||
=== `hbase.hregion.memstore.block.multiplier`
|
||||
|
||||
See <<hbase.hregion.memstore.block.multiplier>>.
|
||||
If there is enough RAM, increasing this can help.
|
||||
|
||||
[[hbase.regionserver.checksum.verify.performance]]
|
||||
=== `hbase.regionserver.checksum.verify`
|
||||
|
||||
Have HBase write the checksum into the datablock and save having to do the checksum seek whenever you read.
|
||||
|
||||
See <<hbase.regionserver.checksum.verify>>, <<hbase.hstore.bytes.per.checksum>> and <<hbase.hstore.checksum.algorithm>>. For more information see the release note on link:https://issues.apache.org/jira/browse/HBASE-5074[HBASE-5074 support checksums in HBase block cache].
|
||||
|
||||
=== Tuning `callQueue` Options
|
||||
|
||||
link:https://issues.apache.org/jira/browse/HBASE-11355[HBASE-11355] introduces several callQueue tuning mechanisms which can increase performance.
|
||||
See the JIRA for some benchmarking information.
|
||||
|
||||
To increase the number of callqueues, set `hbase.ipc.server.num.callqueue` to a value greater than `1`.
|
||||
To split the callqueue into separate read and write queues, set `hbase.ipc.server.callqueue.read.ratio` to a value between `0` and `1`.
|
||||
This factor weights the queues toward writes (if below .5) or reads (if above .5). Another way to say this is that the factor determines what percentage of the split queues are used for reads.
|
||||
The following examples illustrate some of the possibilities.
|
||||
Note that you always have at least one write queue, no matter what setting you use.
|
||||
|
||||
* The default value of `0` does not split the queue.
|
||||
* A value of `.3` uses 30% of the queues for reading and 60% for writing.
|
||||
Given a value of `10` for `hbase.ipc.server.num.callqueue`, 3 queues would be used for reads and 7 for writes.
|
||||
* A value of `.5` uses the same number of read queues and write queues.
|
||||
Given a value of `10` for `hbase.ipc.server.num.callqueue`, 5 queues would be used for reads and 5 for writes.
|
||||
* A value of `.6` uses 60% of the queues for reading and 30% for reading.
|
||||
Given a value of `10` for `hbase.ipc.server.num.callqueue`, 7 queues would be used for reads and 3 for writes.
|
||||
* A value of `1.0` uses one queue to process write requests, and all other queues process read requests.
|
||||
A value higher than `1.0` has the same effect as a value of `1.0`.
|
||||
Given a value of `10` for `hbase.ipc.server.num.callqueue`, 9 queues would be used for reads and 1 for writes.
|
||||
|
||||
You can also split the read queues so that separate queues are used for short reads (from Get operations) and long reads (from Scan operations), by setting the `hbase.ipc.server.callqueue.scan.ratio` option.
|
||||
This option is a factor between 0 and 1, which determine the ratio of read queues used for Gets and Scans.
|
||||
More queues are used for Gets if the value is below `.5` and more are used for scans if the value is above `.5`.
|
||||
No matter what setting you use, at least one read queue is used for Get operations.
|
||||
|
||||
* A value of `0` does not split the read queue.
|
||||
* A value of `.3` uses 60% of the read queues for Gets and 30% for Scans.
|
||||
Given a value of `20` for `hbase.ipc.server.num.callqueue` and a value of `.5` for `hbase.ipc.server.callqueue.read.ratio`, 10 queues would be used for reads, out of those 10, 7 would be used for Gets and 3 for Scans.
|
||||
* A value of `.5` uses half the read queues for Gets and half for Scans.
|
||||
Given a value of `20` for `hbase.ipc.server.num.callqueue` and a value of `.5` for `hbase.ipc.server.callqueue.read.ratio`, 10 queues would be used for reads, out of those 10, 5 would be used for Gets and 5 for Scans.
|
||||
* A value of `.6` uses 30% of the read queues for Gets and 60% for Scans.
|
||||
Given a value of `20` for `hbase.ipc.server.num.callqueue` and a value of `.5` for `hbase.ipc.server.callqueue.read.ratio`, 10 queues would be used for reads, out of those 10, 3 would be used for Gets and 7 for Scans.
|
||||
* A value of `1.0` uses all but one of the read queues for Scans.
|
||||
Given a value of `20` for `hbase.ipc.server.num.callqueue` and a value of`.5` for `hbase.ipc.server.callqueue.read.ratio`, 10 queues would be used for reads, out of those 10, 1 would be used for Gets and 9 for Scans.
|
||||
|
||||
You can use the new option `hbase.ipc.server.callqueue.handler.factor` to programmatically tune the number of queues:
|
||||
|
||||
* A value of `0` uses a single shared queue between all the handlers.
|
||||
* A value of `1` uses a separate queue for each handler.
|
||||
* A value between `0` and `1` tunes the number of queues against the number of handlers.
|
||||
For instance, a value of `.5` shares one queue between each two handlers.
|
||||
+
|
||||
Having more queues, such as in a situation where you have one queue per handler, reduces contention when adding a task to a queue or selecting it from a queue.
|
||||
The trade-off is that if you have some queues with long-running tasks, a handler may end up waiting to execute from that queue rather than processing another queue which has waiting tasks.
|
||||
|
||||
|
||||
For these values to take effect on a given RegionServer, the RegionServer must be restarted.
|
||||
These parameters are intended for testing purposes and should be used carefully.
|
||||
|
||||
[[perf.zookeeper]]
|
||||
== ZooKeeper
|
||||
|
||||
See <<zookeeper>> for information on configuring ZooKeeper, and see the part about having a dedicated disk.
|
||||
|
||||
[[perf.schema]]
|
||||
== Schema Design
|
||||
|
||||
[[perf.number.of.cfs]]
|
||||
=== Number of Column Families
|
||||
|
||||
See <<number.of.cfs>>.
|
||||
|
||||
[[perf.schema.keys]]
|
||||
=== Key and Attribute Lengths
|
||||
|
||||
See <<keysize>>.
|
||||
See also <<perf.compression.however>> for compression caveats.
|
||||
|
||||
[[schema.regionsize]]
|
||||
=== Table RegionSize
|
||||
|
||||
The regionsize can be set on a per-table basis via `setFileSize` on link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HTableDescriptor.html[HTableDescriptor] in the event where certain tables require different regionsizes than the configured default regionsize.
|
||||
|
||||
See <<ops.capacity.regions>> for more information.
|
||||
|
||||
[[schema.bloom]]
|
||||
=== Bloom Filters
|
||||
|
||||
A Bloom filter, named for its creator, Burton Howard Bloom, is a data structure which is designed to predict whether a given element is a member of a set of data.
|
||||
A positive result from a Bloom filter is not always accurate, but a negative result is guaranteed to be accurate.
|
||||
Bloom filters are designed to be "accurate enough" for sets of data which are so large that conventional hashing mechanisms would be impractical.
|
||||
For more information about Bloom filters in general, refer to http://en.wikipedia.org/wiki/Bloom_filter.
|
||||
|
||||
In terms of HBase, Bloom filters provide a lightweight in-memory structure to reduce the number of disk reads for a given Get operation (Bloom filters do not work with Scans) to only the StoreFiles likely to contain the desired Row.
|
||||
The potential performance gain increases with the number of parallel reads.
|
||||
|
||||
The Bloom filters themselves are stored in the metadata of each HFile and never need to be updated.
|
||||
When an HFile is opened because a region is deployed to a RegionServer, the Bloom filter is loaded into memory.
|
||||
|
||||
HBase includes some tuning mechanisms for folding the Bloom filter to reduce the size and keep the false positive rate within a desired range.
|
||||
|
||||
Bloom filters were introduced in link:https://issues.apache.org/jira/browse/HBASE-1200[HBASE-1200].
|
||||
Since HBase 0.96, row-based Bloom filters are enabled by default.
|
||||
(link:https://issues.apache.org/jira/browse/HBASE-8450[HBASE-])
|
||||
|
||||
For more information on Bloom filters in relation to HBase, see <<blooms>> for more information, or the following Quora discussion: link:http://www.quora.com/How-are-bloom-filters-used-in-HBase[How are bloom filters used in HBase?].
|
||||
|
||||
[[bloom.filters.when]]
|
||||
==== When To Use Bloom Filters
|
||||
|
||||
Since HBase 0.96, row-based Bloom filters are enabled by default.
|
||||
You may choose to disable them or to change some tables to use row+column Bloom filters, depending on the characteristics of your data and how it is loaded into HBase.
|
||||
|
||||
To determine whether Bloom filters could have a positive impact, check the value of `blockCacheHitRatio` in the RegionServer metrics.
|
||||
If Bloom filters are enabled, the value of `blockCacheHitRatio` should increase, because the Bloom filter is filtering out blocks that are definitely not needed.
|
||||
|
||||
You can choose to enable Bloom filters for a row or for a row+column combination.
|
||||
If you generally scan entire rows, the row+column combination will not provide any benefit.
|
||||
A row-based Bloom filter can operate on a row+column Get, but not the other way around.
|
||||
However, if you have a large number of column-level Puts, such that a row may be present in every StoreFile, a row-based filter will always return a positive result and provide no benefit.
|
||||
Unless you have one column per row, row+column Bloom filters require more space, in order to store more keys.
|
||||
Bloom filters work best when the size of each data entry is at least a few kilobytes in size.
|
||||
|
||||
Overhead will be reduced when your data is stored in a few larger StoreFiles, to avoid extra disk IO during low-level scans to find a specific row.
|
||||
|
||||
Bloom filters need to be rebuilt upon deletion, so may not be appropriate in environments with a large number of deletions.
|
||||
|
||||
==== Enabling Bloom Filters
|
||||
|
||||
Bloom filters are enabled on a Column Family.
|
||||
You can do this by using the setBloomFilterType method of HColumnDescriptor or using the HBase API.
|
||||
Valid values are `NONE` (the default), `ROW`, or `ROWCOL`.
|
||||
See <<bloom.filters.when>> for more information on `ROW` versus `ROWCOL`.
|
||||
See also the API documentation for link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html[HColumnDescriptor].
|
||||
|
||||
The following example creates a table and enables a ROWCOL Bloom filter on the `colfam1` column family.
|
||||
|
||||
----
|
||||
|
||||
hbase> create 'mytable',{NAME => 'colfam1', BLOOMFILTER => 'ROWCOL'}
|
||||
----
|
||||
|
||||
==== Configuring Server-Wide Behavior of Bloom Filters
|
||||
|
||||
You can configure the following settings in the _hbase-site.xml_.
|
||||
|
||||
[cols="1,1,1", options="header"]
|
||||
|===
|
||||
| Parameter
|
||||
| Default
|
||||
| Description
|
||||
|
||||
| io.hfile.bloom.enabled
|
||||
| yes
|
||||
| Set to no to kill bloom filters server-wide if something goes wrong
|
||||
|
||||
| io.hfile.bloom.error.rate
|
||||
| .01
|
||||
| The average false positive rate for bloom filters. Folding is used to
|
||||
maintain the false positive rate. Expressed as a decimal representation of a
|
||||
percentage.
|
||||
|
||||
| io.hfile.bloom.max.fold
|
||||
| 7
|
||||
| The guaranteed maximum fold rate. Changing this setting should not be
|
||||
necessary and is not recommended.
|
||||
|
||||
| io.storefile.bloom.max.keys
|
||||
| 128000000
|
||||
| For default (single-block) Bloom filters, this specifies the maximum number of keys.
|
||||
|
||||
| io.storefile.delete.family.bloom.enabled
|
||||
| true
|
||||
| Master switch to enable Delete Family Bloom filters and store them in the StoreFile.
|
||||
|
||||
| io.storefile.bloom.block.size
|
||||
| 65536
|
||||
| Target Bloom block size. Bloom filter blocks of approximately this size
|
||||
are interleaved with data blocks.
|
||||
|
||||
| hfile.block.bloom.cacheonwrite
|
||||
| false
|
||||
| Enables cache-on-write for inline blocks of a compound Bloom filter.
|
||||
|===
|
||||
|
||||
[[schema.cf.blocksize]]
|
||||
=== ColumnFamily BlockSize
|
||||
|
||||
The blocksize can be configured for each ColumnFamily in a table, and defaults to 64k.
|
||||
Larger cell values require larger blocksizes.
|
||||
There is an inverse relationship between blocksize and the resulting StoreFile indexes (i.e., if the blocksize is doubled then the resulting indexes should be roughly halved).
|
||||
|
||||
See link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html[HColumnDescriptor] and <<store>>for more information.
|
||||
|
||||
[[cf.in.memory]]
|
||||
=== In-Memory ColumnFamilies
|
||||
|
||||
ColumnFamilies can optionally be defined as in-memory.
|
||||
Data is still persisted to disk, just like any other ColumnFamily.
|
||||
In-memory blocks have the highest priority in the <<block.cache>>, but it is not a guarantee that the entire table will be in memory.
|
||||
|
||||
See link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html[HColumnDescriptor] for more information.
|
||||
|
||||
[[perf.compression]]
|
||||
=== Compression
|
||||
|
||||
Production systems should use compression with their ColumnFamily definitions.
|
||||
See <<compression>> for more information.
|
||||
|
||||
[[perf.compression.however]]
|
||||
==== However...
|
||||
|
||||
Compression deflates data _on disk_.
|
||||
When it's in-memory (e.g., in the MemStore) or on the wire (e.g., transferring between RegionServer and Client) it's inflated.
|
||||
So while using ColumnFamily compression is a best practice, but it's not going to completely eliminate the impact of over-sized Keys, over-sized ColumnFamily names, or over-sized Column names.
|
||||
|
||||
See <<keysize>> on for schema design tips, and <<keyvalue>> for more information on HBase stores data internally.
|
||||
|
||||
[[perf.general]]
|
||||
== HBase General Patterns
|
||||
|
||||
[[perf.general.constants]]
|
||||
=== Constants
|
||||
|
||||
When people get started with HBase they have a tendency to write code that looks like this:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
Get get = new Get(rowkey);
|
||||
Result r = table.get(get);
|
||||
byte[] b = r.getValue(Bytes.toBytes("cf"), Bytes.toBytes("attr")); // returns current version of value
|
||||
----
|
||||
|
||||
But especially when inside loops (and MapReduce jobs), converting the columnFamily and column-names to byte-arrays repeatedly is surprisingly expensive.
|
||||
It's better to use constants for the byte-arrays, like this:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
public static final byte[] CF = "cf".getBytes();
|
||||
public static final byte[] ATTR = "attr".getBytes();
|
||||
...
|
||||
Get get = new Get(rowkey);
|
||||
Result r = table.get(get);
|
||||
byte[] b = r.getValue(CF, ATTR); // returns current version of value
|
||||
----
|
||||
|
||||
[[perf.writing]]
|
||||
== Writing to HBase
|
||||
|
||||
[[perf.batch.loading]]
|
||||
=== Batch Loading
|
||||
|
||||
Use the bulk load tool if you can.
|
||||
See <<arch.bulk.load>>.
|
||||
Otherwise, pay attention to the below.
|
||||
|
||||
[[precreate.regions]]
|
||||
=== Table Creation: Pre-Creating Regions
|
||||
|
||||
Tables in HBase are initially created with one region by default.
|
||||
For bulk imports, this means that all clients will write to the same region until it is large enough to split and become distributed across the cluster.
|
||||
A useful pattern to speed up the bulk import process is to pre-create empty regions.
|
||||
Be somewhat conservative in this, because too-many regions can actually degrade performance.
|
||||
|
||||
There are two different approaches to pre-creating splits.
|
||||
The first approach is to rely on the default `Admin` strategy (which is implemented in `Bytes.split`)...
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
byte[] startKey = ...; // your lowest key
|
||||
byte[] endKey = ...; // your highest key
|
||||
int numberOfRegions = ...; // # of regions to create
|
||||
admin.createTable(table, startKey, endKey, numberOfRegions);
|
||||
----
|
||||
|
||||
And the other approach is to define the splits yourself...
|
||||
|
||||
[source,java]
|
||||
----
|
||||
byte[][] splits = ...; // create your own splits
|
||||
admin.createTable(table, splits);
|
||||
----
|
||||
|
||||
See <<rowkey.regionsplits>> for issues related to understanding your keyspace and pre-creating regions.
|
||||
See <<manual_region_splitting_decisions,manual region splitting decisions>> for discussion on manually pre-splitting regions.
|
||||
|
||||
[[def.log.flush]]
|
||||
=== Table Creation: Deferred Log Flush
|
||||
|
||||
The default behavior for Puts using the Write Ahead Log (WAL) is that `WAL` edits will be written immediately.
|
||||
If deferred log flush is used, WAL edits are kept in memory until the flush period.
|
||||
The benefit is aggregated and asynchronous `WAL`- writes, but the potential downside is that if the RegionServer goes down the yet-to-be-flushed edits are lost.
|
||||
This is safer, however, than not using WAL at all with Puts.
|
||||
|
||||
Deferred log flush can be configured on tables via link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HTableDescriptor.html[HTableDescriptor].
|
||||
The default value of `hbase.regionserver.optionallogflushinterval` is 1000ms.
|
||||
|
||||
[[perf.hbase.client.autoflush]]
|
||||
=== HBase Client: AutoFlush
|
||||
|
||||
When performing a lot of Puts, make sure that setAutoFlush is set to false on your link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html[Table] instance.
|
||||
Otherwise, the Puts will be sent one at a time to the RegionServer.
|
||||
Puts added via `table.add(Put)` and `table.add( <List> Put)` wind up in the same write buffer.
|
||||
If `autoFlush = false`, these messages are not sent until the write-buffer is filled.
|
||||
To explicitly flush the messages, call `flushCommits`.
|
||||
Calling `close` on the `Table` instance will invoke `flushCommits`.
|
||||
|
||||
[[perf.hbase.client.putwal]]
|
||||
=== HBase Client: Turn off WAL on Puts
|
||||
|
||||
A frequent request is to disable the WAL to increase performance of Puts.
|
||||
This is only appropriate for bulk loads, as it puts your data at risk by removing the protection of the WAL in the event of a region server crash.
|
||||
Bulk loads can be re-run in the event of a crash, with little risk of data loss.
|
||||
|
||||
WARNING: If you disable the WAL for anything other than bulk loads, your data is at risk.
|
||||
|
||||
In general, it is best to use WAL for Puts, and where loading throughput is a concern to use bulk loading techniques instead.
|
||||
For normal Puts, you are not likely to see a performance improvement which would outweigh the risk.
|
||||
To disable the WAL, see <<wal.disable>>.
|
||||
|
||||
[[perf.hbase.client.regiongroup]]
|
||||
=== HBase Client: Group Puts by RegionServer
|
||||
|
||||
In addition to using the writeBuffer, grouping `Put`s by RegionServer can reduce the number of client RPC calls per writeBuffer flush.
|
||||
There is a utility `HTableUtil` currently on TRUNK that does this, but you can either copy that or implement your own version for those still on 0.90.x or earlier.
|
||||
|
||||
[[perf.hbase.write.mr.reducer]]
|
||||
=== MapReduce: Skip The Reducer
|
||||
|
||||
When writing a lot of data to an HBase table from a MR job (e.g., with link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableOutputFormat.html[TableOutputFormat]), and specifically where Puts are being emitted from the Mapper, skip the Reducer step.
|
||||
When a Reducer step is used, all of the output (Puts) from the Mapper will get spooled to disk, then sorted/shuffled to other Reducers that will most likely be off-node.
|
||||
It's far more efficient to just write directly to HBase.
|
||||
|
||||
For summary jobs where HBase is used as a source and a sink, then writes will be coming from the Reducer step (e.g., summarize values then write out result). This is a different processing problem than from the the above case.
|
||||
|
||||
[[perf.one.region]]
|
||||
=== Anti-Pattern: One Hot Region
|
||||
|
||||
If all your data is being written to one region at a time, then re-read the section on processing timeseries data.
|
||||
|
||||
Also, if you are pre-splitting regions and all your data is _still_ winding up in a single region even though your keys aren't monotonically increasing, confirm that your keyspace actually works with the split strategy.
|
||||
There are a variety of reasons that regions may appear "well split" but won't work with your data.
|
||||
As the HBase client communicates directly with the RegionServers, this can be obtained via link:hhttp://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#getRegionLocation(byte[])[Table.getRegionLocation].
|
||||
|
||||
See <<precreate.regions>>, as well as <<perf.configurations>>
|
||||
|
||||
[[perf.reading]]
|
||||
== Reading from HBase
|
||||
|
||||
The mailing list can help if you are having performance issues.
|
||||
For example, here is a good general thread on what to look at addressing read-time issues: link:http://search-hadoop.com/m/qOo2yyHtCC1[HBase Random Read latency > 100ms]
|
||||
|
||||
[[perf.hbase.client.caching]]
|
||||
=== Scan Caching
|
||||
|
||||
If HBase is used as an input source for a MapReduce job, for example, make sure that the input link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html[Scan] instance to the MapReduce job has `setCaching` set to something greater than the default (which is 1). Using the default value means that the map-task will make call back to the region-server for every record processed.
|
||||
Setting this value to 500, for example, will transfer 500 rows at a time to the client to be processed.
|
||||
There is a cost/benefit to have the cache value be large because it costs more in memory for both client and RegionServer, so bigger isn't always better.
|
||||
|
||||
[[perf.hbase.client.caching.mr]]
|
||||
==== Scan Caching in MapReduce Jobs
|
||||
|
||||
Scan settings in MapReduce jobs deserve special attention.
|
||||
Timeouts can result (e.g., UnknownScannerException) in Map tasks if it takes longer to process a batch of records before the client goes back to the RegionServer for the next set of data.
|
||||
This problem can occur because there is non-trivial processing occurring per row.
|
||||
If you process rows quickly, set caching higher.
|
||||
If you process rows more slowly (e.g., lots of transformations per row, writes), then set caching lower.
|
||||
|
||||
Timeouts can also happen in a non-MapReduce use case (i.e., single threaded HBase client doing a Scan), but the processing that is often performed in MapReduce jobs tends to exacerbate this issue.
|
||||
|
||||
[[perf.hbase.client.selection]]
|
||||
=== Scan Attribute Selection
|
||||
|
||||
Whenever a Scan is used to process large numbers of rows (and especially when used as a MapReduce source), be aware of which attributes are selected.
|
||||
If `scan.addFamily` is called then _all_ of the attributes in the specified ColumnFamily will be returned to the client.
|
||||
If only a small number of the available attributes are to be processed, then only those attributes should be specified in the input scan because attribute over-selection is a non-trivial performance penalty over large datasets.
|
||||
|
||||
[[perf.hbase.client.seek]]
|
||||
=== Avoid scan seeks
|
||||
|
||||
When columns are selected explicitly with `scan.addColumn`, HBase will schedule seek operations to seek between the selected columns.
|
||||
When rows have few columns and each column has only a few versions this can be inefficient.
|
||||
A seek operation is generally slower if does not seek at least past 5-10 columns/versions or 512-1024 bytes.
|
||||
|
||||
In order to opportunistically look ahead a few columns/versions to see if the next column/version can be found that way before a seek operation is scheduled, a new attribute `Scan.HINT_LOOKAHEAD` can be set the on Scan object.
|
||||
The following code instructs the RegionServer to attempt two iterations of next before a seek is scheduled:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
Scan scan = new Scan();
|
||||
scan.addColumn(...);
|
||||
scan.setAttribute(Scan.HINT_LOOKAHEAD, Bytes.toBytes(2));
|
||||
table.getScanner(scan);
|
||||
----
|
||||
|
||||
[[perf.hbase.mr.input]]
|
||||
=== MapReduce - Input Splits
|
||||
|
||||
For MapReduce jobs that use HBase tables as a source, if there a pattern where the "slow" map tasks seem to have the same Input Split (i.e., the RegionServer serving the data), see the Troubleshooting Case Study in <<casestudies.slownode>>.
|
||||
|
||||
[[perf.hbase.client.scannerclose]]
|
||||
=== Close ResultScanners
|
||||
|
||||
This isn't so much about improving performance but rather _avoiding_ performance problems.
|
||||
If you forget to close link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/ResultScanner.html[ResultScanners] you can cause problems on the RegionServers.
|
||||
Always have ResultScanner processing enclosed in try/catch blocks.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
Scan scan = new Scan();
|
||||
// set attrs...
|
||||
ResultScanner rs = table.getScanner(scan);
|
||||
try {
|
||||
for (Result r = rs.next(); r != null; r = rs.next()) {
|
||||
// process result...
|
||||
} finally {
|
||||
rs.close(); // always close the ResultScanner!
|
||||
}
|
||||
table.close();
|
||||
----
|
||||
|
||||
[[perf.hbase.client.blockcache]]
|
||||
=== Block Cache
|
||||
|
||||
link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html[Scan] instances can be set to use the block cache in the RegionServer via the `setCacheBlocks` method.
|
||||
For input Scans to MapReduce jobs, this should be `false`.
|
||||
For frequently accessed rows, it is advisable to use the block cache.
|
||||
|
||||
Cache more data by moving your Block Cache off-heap.
|
||||
See <<offheap.blockcache>>
|
||||
|
||||
[[perf.hbase.client.rowkeyonly]]
|
||||
=== Optimal Loading of Row Keys
|
||||
|
||||
When performing a table link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html[scan] where only the row keys are needed (no families, qualifiers, values or timestamps), add a FilterList with a `MUST_PASS_ALL` operator to the scanner using `setFilter`.
|
||||
The filter list should include both a link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/FirstKeyOnlyFilter.html[FirstKeyOnlyFilter] and a link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/KeyOnlyFilter.html[KeyOnlyFilter].
|
||||
Using this filter combination will result in a worst case scenario of a RegionServer reading a single value from disk and minimal network traffic to the client for a single row.
|
||||
|
||||
[[perf.hbase.read.dist]]
|
||||
=== Concurrency: Monitor Data Spread
|
||||
|
||||
When performing a high number of concurrent reads, monitor the data spread of the target tables.
|
||||
If the target table(s) have too few regions then the reads could likely be served from too few nodes.
|
||||
|
||||
See <<precreate.regions>>, as well as <<perf.configurations>>
|
||||
|
||||
[[blooms]]
|
||||
=== Bloom Filters
|
||||
|
||||
Enabling Bloom Filters can save your having to go to disk and can help improve read latencies.
|
||||
|
||||
link:http://en.wikipedia.org/wiki/Bloom_filter[Bloom filters] were developed over in link:https://issues.apache.org/jira/browse/HBASE-1200[HBase-1200 Add bloomfilters].
|
||||
For description of the development process -- why static blooms rather than dynamic -- and for an overview of the unique properties that pertain to blooms in HBase, as well as possible future directions, see the _Development Process_ section of the document link:https://issues.apache.org/jira/secure/attachment/12444007/Bloom_Filters_in_HBase.pdf[BloomFilters in HBase] attached to link:https://issues.apache.org/jira/browse/HBASE-1200[HBASE-1200].
|
||||
The bloom filters described here are actually version two of blooms in HBase.
|
||||
In versions up to 0.19.x, HBase had a dynamic bloom option based on work done by the link:http://www.one-lab.org[European Commission One-Lab Project 034819].
|
||||
The core of the HBase bloom work was later pulled up into Hadoop to implement org.apache.hadoop.io.BloomMapFile.
|
||||
Version 1 of HBase blooms never worked that well.
|
||||
Version 2 is a rewrite from scratch though again it starts with the one-lab work.
|
||||
|
||||
See also <<schema.bloom>>.
|
||||
|
||||
[[bloom_footprint]]
|
||||
==== Bloom StoreFile footprint
|
||||
|
||||
Bloom filters add an entry to the `StoreFile` general `FileInfo` data structure and then two extra entries to the `StoreFile` metadata section.
|
||||
|
||||
===== BloomFilter in the `StoreFile``FileInfo` data structure
|
||||
|
||||
`FileInfo` has a `BLOOM_FILTER_TYPE` entry which is set to `NONE`, `ROW` or `ROWCOL.`
|
||||
|
||||
===== BloomFilter entries in `StoreFile` metadata
|
||||
|
||||
`BLOOM_FILTER_META` holds Bloom Size, Hash Function used, etc.
|
||||
It's small in size and is cached on `StoreFile.Reader` load
|
||||
|
||||
`BLOOM_FILTER_DATA` is the actual bloomfilter data.
|
||||
Obtained on-demand.
|
||||
Stored in the LRU cache, if it is enabled (It's enabled by default).
|
||||
|
||||
[[config.bloom]]
|
||||
==== Bloom Filter Configuration
|
||||
|
||||
===== `io.hfile.bloom.enabled` global kill switch
|
||||
|
||||
`io.hfile.bloom.enabled` in `Configuration` serves as the kill switch in case something goes wrong.
|
||||
Default = `true`.
|
||||
|
||||
===== `io.hfile.bloom.error.rate`
|
||||
|
||||
`io.hfile.bloom.error.rate` = average false positive rate.
|
||||
Default = 1%. Decrease rate by ½ (e.g.
|
||||
to .5%) == +1 bit per bloom entry.
|
||||
|
||||
===== `io.hfile.bloom.max.fold`
|
||||
|
||||
`io.hfile.bloom.max.fold` = guaranteed minimum fold rate.
|
||||
Most people should leave this alone.
|
||||
Default = 7, or can collapse to at least 1/128th of original size.
|
||||
See the _Development Process_ section of the document link:https://issues.apache.org/jira/secure/attachment/12444007/Bloom_Filters_in_HBase.pdf[BloomFilters in HBase] for more on what this option means.
|
||||
|
||||
=== Hedged Reads
|
||||
|
||||
Hedged reads are a feature of HDFS, introduced in link:https://issues.apache.org/jira/browse/HDFS-5776[HDFS-5776].
|
||||
Normally, a single thread is spawned for each read request.
|
||||
However, if hedged reads are enabled, the client waits some configurable amount of time, and if the read does not return, the client spawns a second read request, against a different block replica of the same data.
|
||||
Whichever read returns first is used, and the other read request is discarded.
|
||||
Hedged reads can be helpful for times where a rare slow read is caused by a transient error such as a failing disk or flaky network connection.
|
||||
|
||||
Because a HBase RegionServer is a HDFS client, you can enable hedged reads in HBase, by adding the following properties to the RegionServer's hbase-site.xml and tuning the values to suit your environment.
|
||||
|
||||
.Configuration for Hedged Reads
|
||||
* `dfs.client.hedged.read.threadpool.size` - the number of threads dedicated to servicing hedged reads.
|
||||
If this is set to 0 (the default), hedged reads are disabled.
|
||||
* `dfs.client.hedged.read.threshold.millis` - the number of milliseconds to wait before spawning a second read thread.
|
||||
|
||||
.Hedged Reads Configuration Example
|
||||
====
|
||||
[source,xml]
|
||||
----
|
||||
<property>
|
||||
<name>dfs.client.hedged.read.threadpool.size</name>
|
||||
<value>20</value> <!-- 20 threads -->
|
||||
</property>
|
||||
<property>
|
||||
<name>dfs.client.hedged.read.threshold.millis</name>
|
||||
<value>10</value> <!-- 10 milliseconds -->
|
||||
</property>
|
||||
----
|
||||
====
|
||||
|
||||
Use the following metrics to tune the settings for hedged reads on your cluster.
|
||||
See <<hbase_metrics>> for more information.
|
||||
|
||||
.Metrics for Hedged Reads
|
||||
* hedgedReadOps - the number of times hedged read threads have been triggered.
|
||||
This could indicate that read requests are often slow, or that hedged reads are triggered too quickly.
|
||||
* hedgeReadOpsWin - the number of times the hedged read thread was faster than the original thread.
|
||||
This could indicate that a given RegionServer is having trouble servicing requests.
|
||||
|
||||
[[perf.deleting]]
|
||||
== Deleting from HBase
|
||||
|
||||
[[perf.deleting.queue]]
|
||||
=== Using HBase Tables as Queues
|
||||
|
||||
HBase tables are sometimes used as queues.
|
||||
In this case, special care must be taken to regularly perform major compactions on tables used in this manner.
|
||||
As is documented in <<datamodel>>, marking rows as deleted creates additional StoreFiles which then need to be processed on reads.
|
||||
Tombstones only get cleaned up with major compactions.
|
||||
|
||||
See also <<compaction>> and link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Admin.html#majorCompact%28java.lang.String%29[Admin.majorCompact].
|
||||
|
||||
[[perf.deleting.rpc]]
|
||||
=== Delete RPC Behavior
|
||||
|
||||
Be aware that `Table.delete(Delete)` doesn't use the writeBuffer.
|
||||
It will execute an RegionServer RPC with each invocation.
|
||||
For a large number of deletes, consider `Table.delete(List)`.
|
||||
|
||||
See http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#delete%28org.apache.hadoop.hbase.client.Delete%29
|
||||
|
||||
[[perf.hdfs]]
|
||||
== HDFS
|
||||
|
||||
Because HBase runs on <<arch.hdfs>> it is important to understand how it works and how it affects HBase.
|
||||
|
||||
[[perf.hdfs.curr]]
|
||||
=== Current Issues With Low-Latency Reads
|
||||
|
||||
The original use-case for HDFS was batch processing.
|
||||
As such, there low-latency reads were historically not a priority.
|
||||
With the increased adoption of Apache HBase this is changing, and several improvements are already in development.
|
||||
See the link:https://issues.apache.org/jira/browse/HDFS-1599[Umbrella Jira Ticket for HDFS Improvements for HBase].
|
||||
|
||||
[[perf.hdfs.configs.localread]]
|
||||
=== Leveraging local data
|
||||
|
||||
Since Hadoop 1.0.0 (also 0.22.1, 0.23.1, CDH3u3 and HDP 1.0) via link:https://issues.apache.org/jira/browse/HDFS-2246[HDFS-2246], it is possible for the DFSClient to take a "short circuit" and read directly from the disk instead of going through the DataNode when the data is local.
|
||||
What this means for HBase is that the RegionServers can read directly off their machine's disks instead of having to open a socket to talk to the DataNode, the former being generally much faster.
|
||||
See JD's link:http://files.meetup.com/1350427/hug_ebay_jdcryans.pdf[Performance Talk].
|
||||
Also see link:http://search-hadoop.com/m/zV6dKrLCVh1[HBase, mail # dev - read short circuit] thread for more discussion around short circuit reads.
|
||||
|
||||
To enable "short circuit" reads, it will depend on your version of Hadoop.
|
||||
The original shortcircuit read patch was much improved upon in Hadoop 2 in link:https://issues.apache.org/jira/browse/HDFS-347[HDFS-347].
|
||||
See http://blog.cloudera.com/blog/2013/08/how-improved-short-circuit-local-reads-bring-better-performance-and-security-to-hadoop/ for details on the difference between the old and new implementations.
|
||||
See link:http://archive.cloudera.com/cdh4/cdh/4/hadoop/hadoop-project-dist/hadoop-hdfs/ShortCircuitLocalReads.html[Hadoop shortcircuit reads configuration page] for how to enable the latter, better version of shortcircuit.
|
||||
For example, here is a minimal config.
|
||||
enabling short-circuit reads added to _hbase-site.xml_:
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
<property>
|
||||
<name>dfs.client.read.shortcircuit</name>
|
||||
<value>true</value>
|
||||
<description>
|
||||
This configuration parameter turns on short-circuit local reads.
|
||||
</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>dfs.domain.socket.path</name>
|
||||
<value>/home/stack/sockets/short_circuit_read_socket_PORT</value>
|
||||
<description>
|
||||
Optional. This is a path to a UNIX domain socket that will be used for
|
||||
communication between the DataNode and local HDFS clients.
|
||||
If the string "_PORT" is present in this path, it will be replaced by the
|
||||
TCP port of the DataNode.
|
||||
</description>
|
||||
</property>
|
||||
----
|
||||
|
||||
Be careful about permissions for the directory that hosts the shared domain socket; dfsclient will complain if open to other than the hbase user.
|
||||
|
||||
If you are running on an old Hadoop, one that is without link:https://issues.apache.org/jira/browse/HDFS-347[HDFS-347] but that has link:https://issues.apache.org/jira/browse/HDFS-2246[HDFS-2246], you must set two configurations.
|
||||
First, the hdfs-site.xml needs to be amended.
|
||||
Set the property `dfs.block.local-path-access.user` to be the _only_ user that can use the shortcut.
|
||||
This has to be the user that started HBase.
|
||||
Then in hbase-site.xml, set `dfs.client.read.shortcircuit` to be `true`
|
||||
|
||||
Services -- at least the HBase RegionServers -- will need to be restarted in order to pick up the new configurations.
|
||||
|
||||
.dfs.client.read.shortcircuit.buffer.size
|
||||
[NOTE]
|
||||
====
|
||||
The default for this value is too high when running on a highly trafficked HBase.
|
||||
In HBase, if this value has not been set, we set it down from the default of 1M to 128k (Since HBase 0.98.0 and 0.96.1). See link:https://issues.apache.org/jira/browse/HBASE-8143[HBASE-8143 HBase on Hadoop 2 with local short circuit reads (ssr) causes OOM]). The Hadoop DFSClient in HBase will allocate a direct byte buffer of this size for _each_ block it has open; given HBase keeps its HDFS files open all the time, this can add up quickly.
|
||||
====
|
||||
|
||||
[[perf.hdfs.comp]]
|
||||
=== Performance Comparisons of HBase vs. HDFS
|
||||
|
||||
A fairly common question on the dist-list is why HBase isn't as performant as HDFS files in a batch context (e.g., as a MapReduce source or sink). The short answer is that HBase is doing a lot more than HDFS (e.g., reading the KeyValues, returning the most current row or specified timestamps, etc.), and as such HBase is 4-5 times slower than HDFS in this processing context.
|
||||
There is room for improvement and this gap will, over time, be reduced, but HDFS will always be faster in this use-case.
|
||||
|
||||
[[perf.ec2]]
|
||||
== Amazon EC2
|
||||
|
||||
Performance questions are common on Amazon EC2 environments because it is a shared environment.
|
||||
You will not see the same throughput as a dedicated server.
|
||||
In terms of running tests on EC2, run them several times for the same reason (i.e., it's a shared environment and you don't know what else is happening on the server).
|
||||
|
||||
If you are running on EC2 and post performance questions on the dist-list, please state this fact up-front that because EC2 issues are practically a separate class of performance issues.
|
||||
|
||||
[[perf.hbase.mr.cluster]]
|
||||
== Collocating HBase and MapReduce
|
||||
|
||||
It is often recommended to have different clusters for HBase and MapReduce.
|
||||
A better qualification of this is: don't collocate a HBase that serves live requests with a heavy MR workload.
|
||||
OLTP and OLAP-optimized systems have conflicting requirements and one will lose to the other, usually the former.
|
||||
For example, short latency-sensitive disk reads will have to wait in line behind longer reads that are trying to squeeze out as much throughput as possible.
|
||||
MR jobs that write to HBase will also generate flushes and compactions, which will in turn invalidate blocks in the <<block.cache>>.
|
||||
|
||||
If you need to process the data from your live HBase cluster in MR, you can ship the deltas with <<copy.table>> or use replication to get the new data in real time on the OLAP cluster.
|
||||
In the worst case, if you really need to collocate both, set MR to use less Map and Reduce slots than you'd normally configure, possibly just one.
|
||||
|
||||
When HBase is used for OLAP operations, it's preferable to set it up in a hardened way like configuring the ZooKeeper session timeout higher and giving more memory to the MemStores (the argument being that the Block Cache won't be used much since the workloads are usually long scans).
|
||||
|
||||
[[perf.casestudy]]
|
||||
== Case Studies
|
||||
|
||||
For Performance and Troubleshooting Case Studies, see <<casestudies>>.
|
||||
|
||||
ifdef::backend-docbook[]
|
||||
[index]
|
||||
== Index
|
||||
// Generated automatically by the DocBook toolchain.
|
||||
endif::backend-docbook[]
|
||||
|
|
@ -0,0 +1,64 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[preface]
|
||||
= Preface
|
||||
:doctype: article
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
This is the official reference guide for the link:http://hbase.apache.org/[HBase] version it ships with.
|
||||
|
||||
Herein you will find either the definitive documentation on an HBase topic as of its standing when the referenced HBase version shipped, or it will point to the location in link:http://hbase.apache.org/apidocs/index.html[Javadoc], link:https://issues.apache.org/jira/browse/HBASE[JIRA] or link:http://wiki.apache.org/hadoop/Hbase[wiki] where the pertinent information can be found.
|
||||
|
||||
.About This Guide
|
||||
This reference guide is a work in progress. The source for this guide can be found in the _src/main/asciidoc directory of the HBase source. This reference guide is marked up using link:http://asciidoc.org/[AsciiDoc] from which the finished guide is generated as part of the 'site' build target. Run
|
||||
[source,bourne]
|
||||
----
|
||||
mvn site
|
||||
----
|
||||
to generate this documentation.
|
||||
Amendments and improvements to the documentation are welcomed.
|
||||
Click link:https://issues.apache.org/jira/secure/CreateIssueDetails!init.jspa?pid=12310753&issuetype=1&components=12312132&summary=SHORT+DESCRIPTION[this link] to file a new documentation bug against Apache HBase with some values pre-selected.
|
||||
|
||||
.Contributing to the Documentation
|
||||
For an overview of AsciiDoc and suggestions to get started contributing to the documentation, see the <<appendix_contributing_to_documentation,relevant section later in this documentation>>.
|
||||
|
||||
.Heads-up if this is your first foray into the world of distributed computing...
|
||||
If this is your first foray into the wonderful world of Distributed Computing, then you are in for some interesting times.
|
||||
First off, distributed systems are hard; making a distributed system hum requires a disparate skillset that spans systems (hardware and software) and networking.
|
||||
|
||||
Your cluster's operation can hiccup because of any of a myriad set of reasons from bugs in HBase itself through misconfigurations -- misconfiguration of HBase but also operating system misconfigurations -- through to hardware problems whether it be a bug in your network card drivers or an underprovisioned RAM bus (to mention two recent examples of hardware issues that manifested as "HBase is slow"). You will also need to do a recalibration if up to this your computing has been bound to a single box.
|
||||
Here is one good starting point: link:http://en.wikipedia.org/wiki/Fallacies_of_Distributed_Computing[Fallacies of Distributed Computing].
|
||||
|
||||
That said, you are welcome. +
|
||||
It's a fun place to be. +
|
||||
Yours, the HBase Community.
|
||||
|
||||
.Reporting Bugs
|
||||
|
||||
Please use link:https://issues.apache.org/jira/browse/hbase[JIRA] to report non-security-related bugs.
|
||||
|
||||
To protect existing HBase installations from new vulnerabilities, please *do not* use JIRA to report security-related bugs. Instead, send your report to the mailing list private@apache.org, which allows anyone to send messages, but restricts who can read them. Someone on that list will contact you to follow up on your report.
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,222 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[hbase.rpc]]
|
||||
== 0.95 RPC Specification
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
In 0.95, all client/server communication is done with link:https://developers.google.com/protocol-buffers/[protobuf'ed] Messages rather than with link:http://hadoop.apache.org/docs/current/api/org/apache/hadoop/io/Writable.html[Hadoop
|
||||
Writables].
|
||||
Our RPC wire format therefore changes.
|
||||
This document describes the client/server request/response protocol and our new RPC wire-format.
|
||||
|
||||
|
||||
|
||||
For what RPC is like in 0.94 and previous, see Benoît/Tsuna's link:https://github.com/OpenTSDB/asynchbase/blob/master/src/HBaseRpc.java#L164[Unofficial
|
||||
Hadoop / HBase RPC protocol documentation].
|
||||
For more background on how we arrived at this spec., see link:https://docs.google.com/document/d/1WCKwgaLDqBw2vpux0jPsAu2WPTRISob7HGCO8YhfDTA/edit#[HBase
|
||||
RPC: WIP]
|
||||
|
||||
|
||||
|
||||
=== Goals
|
||||
|
||||
|
||||
|
||||
. A wire-format we can evolve
|
||||
. A format that does not require our rewriting server core or radically changing its current architecture (for later).
|
||||
|
||||
=== TODO
|
||||
|
||||
|
||||
|
||||
. List of problems with currently specified format and where we would like to go in a version2, etc.
|
||||
For example, what would we have to change if anything to move server async or to support streaming/chunking?
|
||||
. Diagram on how it works
|
||||
. A grammar that succinctly describes the wire-format.
|
||||
Currently we have these words and the content of the rpc protobuf idl but a grammar for the back and forth would help with groking rpc.
|
||||
Also, a little state machine on client/server interactions would help with understanding (and ensuring correct implementation).
|
||||
|
||||
=== RPC
|
||||
|
||||
The client will send setup information on connection establish.
|
||||
Thereafter, the client invokes methods against the remote server sending a protobuf Message and receiving a protobuf Message in response.
|
||||
Communication is synchronous.
|
||||
All back and forth is preceded by an int that has the total length of the request/response.
|
||||
Optionally, Cells(KeyValues) can be passed outside of protobufs in follow-behind Cell blocks (because link:https://docs.google.com/document/d/1WEtrq-JTIUhlnlnvA0oYRLp0F8MKpEBeBSCFcQiacdw/edit#[we
|
||||
can't protobuf megabytes of KeyValues] or Cells). These CellBlocks are encoded and optionally compressed.
|
||||
|
||||
|
||||
|
||||
For more detail on the protobufs involved, see the link:http://svn.apache.org/viewvc/hbase/trunk/hbase-protocol/src/main/protobuf/RPC.proto?view=markup[RPC.proto] file in trunk.
|
||||
|
||||
==== Connection Setup
|
||||
|
||||
Client initiates connection.
|
||||
|
||||
===== Client
|
||||
On connection setup, client sends a preamble followed by a connection header.
|
||||
|
||||
.<preamble>
|
||||
[source]
|
||||
----
|
||||
<MAGIC 4 byte integer> <1 byte RPC Format Version> <1 byte auth type>
|
||||
----
|
||||
|
||||
We need the auth method spec.
|
||||
here so the connection header is encoded if auth enabled.
|
||||
|
||||
E.g.: HBas0x000x50 -- 4 bytes of MAGIC -- `HBas' -- plus one-byte of version, 0 in this case, and one byte, 0x50 (SIMPLE). of an auth type.
|
||||
|
||||
.<Protobuf ConnectionHeader Message>
|
||||
Has user info, and ``protocol'', as well as the encoders and compression the client will use sending CellBlocks.
|
||||
CellBlock encoders and compressors are for the life of the connection.
|
||||
CellBlock encoders implement org.apache.hadoop.hbase.codec.Codec.
|
||||
CellBlocks may then also be compressed.
|
||||
Compressors implement org.apache.hadoop.io.compress.CompressionCodec.
|
||||
This protobuf is written using writeDelimited so is prefaced by a pb varint with its serialized length
|
||||
|
||||
===== Server
|
||||
|
||||
After client sends preamble and connection header, server does NOT respond if successful connection setup.
|
||||
No response means server is READY to accept requests and to give out response.
|
||||
If the version or authentication in the preamble is not agreeable or the server has trouble parsing the preamble, it will throw a org.apache.hadoop.hbase.ipc.FatalConnectionException explaining the error and will then disconnect.
|
||||
If the client in the connection header -- i.e.
|
||||
the protobuf'd Message that comes after the connection preamble -- asks for for a Service the server does not support or a codec the server does not have, again we throw a FatalConnectionException with explanation.
|
||||
|
||||
==== Request
|
||||
|
||||
After a Connection has been set up, client makes requests.
|
||||
Server responds.
|
||||
|
||||
A request is made up of a protobuf RequestHeader followed by a protobuf Message parameter.
|
||||
The header includes the method name and optionally, metadata on the optional CellBlock that may be following.
|
||||
The parameter type suits the method being invoked: i.e.
|
||||
if we are doing a getRegionInfo request, the protobuf Message param will be an instance of GetRegionInfoRequest.
|
||||
The response will be a GetRegionInfoResponse.
|
||||
The CellBlock is optionally used ferrying the bulk of the RPC data: i.e Cells/KeyValues.
|
||||
|
||||
===== Request Parts
|
||||
|
||||
.<Total Length>
|
||||
The request is prefaced by an int that holds the total length of what follows.
|
||||
|
||||
.<Protobuf RequestHeader Message>
|
||||
Will have call.id, trace.id, and method name, etc.
|
||||
including optional Metadata on the Cell block IFF one is following.
|
||||
Data is protobuf'd inline in this pb Message or optionally comes in the following CellBlock
|
||||
|
||||
.<Protobuf Param Message>
|
||||
If the method being invoked is getRegionInfo, if you study the Service descriptor for the client to regionserver protocol, you will find that the request sends a GetRegionInfoRequest protobuf Message param in this position.
|
||||
|
||||
.<CellBlock>
|
||||
An encoded and optionally compressed Cell block.
|
||||
|
||||
==== Response
|
||||
|
||||
Same as Request, it is a protobuf ResponseHeader followed by a protobuf Message response where the Message response type suits the method invoked.
|
||||
Bulk of the data may come in a following CellBlock.
|
||||
|
||||
===== Response Parts
|
||||
|
||||
.<Total Length>
|
||||
The response is prefaced by an int that holds the total length of what follows.
|
||||
|
||||
.<Protobuf ResponseHeader Message>
|
||||
Will have call.id, etc.
|
||||
Will include exception if failed processing.
|
||||
Optionally includes metadata on optional, IFF there is a CellBlock following.
|
||||
|
||||
.<Protobuf Response Message>
|
||||
|
||||
Return or may be nothing if exception.
|
||||
If the method being invoked is getRegionInfo, if you study the Service descriptor for the client to regionserver protocol, you will find that the response sends a GetRegionInfoResponse protobuf Message param in this position.
|
||||
|
||||
.<CellBlock>
|
||||
|
||||
An encoded and optionally compressed Cell block.
|
||||
|
||||
==== Exceptions
|
||||
|
||||
There are two distinct types.
|
||||
There is the request failed which is encapsulated inside the response header for the response.
|
||||
The connection stays open to receive new requests.
|
||||
The second type, the FatalConnectionException, kills the connection.
|
||||
|
||||
Exceptions can carry extra information.
|
||||
See the ExceptionResponse protobuf type.
|
||||
It has a flag to indicate do-no-retry as well as other miscellaneous payload to help improve client responsiveness.
|
||||
|
||||
==== CellBlocks
|
||||
|
||||
These are not versioned.
|
||||
Server can do the codec or it cannot.
|
||||
If new version of a codec with say, tighter encoding, then give it a new class name.
|
||||
Codecs will live on the server for all time so old clients can connect.
|
||||
|
||||
=== Notes
|
||||
|
||||
.Constraints
|
||||
In some part, current wire-format -- i.e.
|
||||
all requests and responses preceeded by a length -- has been dictated by current server non-async architecture.
|
||||
|
||||
.One fat pb request or header+param
|
||||
We went with pb header followed by pb param making a request and a pb header followed by pb response for now.
|
||||
Doing header+param rather than a single protobuf Message with both header and param content:
|
||||
|
||||
. Is closer to what we currently have
|
||||
. Having a single fat pb requires extra copying putting the already pb'd param into the body of the fat request pb (and same making result)
|
||||
. We can decide whether to accept the request or not before we read the param; for example, the request might be low priority.
|
||||
As is, we read header+param in one go as server is currently implemented so this is a TODO.
|
||||
|
||||
The advantages are minor.
|
||||
If later, fat request has clear advantage, can roll out a v2 later.
|
||||
|
||||
[[rpc.configs]]
|
||||
==== RPC Configurations
|
||||
|
||||
.CellBlock Codecs
|
||||
To enable a codec other than the default `KeyValueCodec`, set `hbase.client.rpc.codec` to the name of the Codec class to use.
|
||||
Codec must implement hbase's `Codec` Interface.
|
||||
After connection setup, all passed cellblocks will be sent with this codec.
|
||||
The server will return cellblocks using this same codec as long as the codec is on the servers' CLASSPATH (else you will get `UnsupportedCellCodecException`).
|
||||
|
||||
To change the default codec, set `hbase.client.default.rpc.codec`.
|
||||
|
||||
To disable cellblocks completely and to go pure protobuf, set the default to the empty String and do not specify a codec in your Configuration.
|
||||
So, set `hbase.client.default.rpc.codec` to the empty string and do not set `hbase.client.rpc.codec`.
|
||||
This will cause the client to connect to the server with no codec specified.
|
||||
If a server sees no codec, it will return all responses in pure protobuf.
|
||||
Running pure protobuf all the time will be slower than running with cellblocks.
|
||||
|
||||
.Compression
|
||||
Uses hadoops compression codecs.
|
||||
To enable compressing of passed CellBlocks, set `hbase.client.rpc.compressor` to the name of the Compressor to use.
|
||||
Compressor must implement Hadoops' CompressionCodec Interface.
|
||||
After connection setup, all passed cellblocks will be sent compressed.
|
||||
The server will return cellblocks compressed using this same compressor as long as the compressor is on its CLASSPATH (else you will get `UnsupportedCompressionCodecException`).
|
||||
|
||||
:numbered:
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,390 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[shell]]
|
||||
= The Apache HBase Shell
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
|
||||
The Apache HBase Shell is link:http://jruby.org[(J)Ruby]'s IRB with some HBase particular commands added.
|
||||
Anything you can do in IRB, you should be able to do in the HBase Shell.
|
||||
|
||||
To run the HBase shell, do as follows:
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ ./bin/hbase shell
|
||||
----
|
||||
|
||||
Type `help` and then `<RETURN>` to see a listing of shell commands and options.
|
||||
Browse at least the paragraphs at the end of the help output for the gist of how variables and command arguments are entered into the HBase shell; in particular note how table names, rows, and columns, etc., must be quoted.
|
||||
|
||||
See <<shell_exercises,shell exercises>> for example basic shell operation.
|
||||
|
||||
Here is a nicely formatted listing of link:http://learnhbase.wordpress.com/2013/03/02/hbase-shell-commands/[all shell
|
||||
commands] by Rajeshbabu Chintaguntla.
|
||||
|
||||
[[scripting]]
|
||||
== Scripting with Ruby
|
||||
|
||||
For examples scripting Apache HBase, look in the HBase _bin_ directory.
|
||||
Look at the files that end in _*.rb_.
|
||||
To run one of these files, do as follows:
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ ./bin/hbase org.jruby.Main PATH_TO_SCRIPT
|
||||
----
|
||||
|
||||
== Running the Shell in Non-Interactive Mode
|
||||
|
||||
A new non-interactive mode has been added to the HBase Shell (link:https://issues.apache.org/jira/browse/HBASE-11658[HBASE-11658)].
|
||||
Non-interactive mode captures the exit status (success or failure) of HBase Shell commands and passes that status back to the command interpreter.
|
||||
If you use the normal interactive mode, the HBase Shell will only ever return its own exit status, which will nearly always be `0` for success.
|
||||
|
||||
To invoke non-interactive mode, pass the `-n` or `--non-interactive` option to HBase Shell.
|
||||
|
||||
[[hbase.shell.noninteractive]]
|
||||
== HBase Shell in OS Scripts
|
||||
|
||||
You can use the HBase shell from within operating system script interpreters like the Bash shell which is the default command interpreter for most Linux and UNIX distributions.
|
||||
The following guidelines use Bash syntax, but could be adjusted to work with C-style shells such as csh or tcsh, and could probably be modified to work with the Microsoft Windows script interpreter as well. Submissions are welcome.
|
||||
|
||||
NOTE: Spawning HBase Shell commands in this way is slow, so keep that in mind when you are deciding when combining HBase operations with the operating system command line is appropriate.
|
||||
|
||||
.Passing Commands to the HBase Shell
|
||||
====
|
||||
You can pass commands to the HBase Shell in non-interactive mode (see <<hbasee.shell.noninteractive,hbasee.shell.noninteractive>>) using the `echo` command and the `|` (pipe) operator.
|
||||
Be sure to escape characters in the HBase commands which would otherwise be interpreted by the shell.
|
||||
Some debug-level output has been truncated from the example below.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ echo "describe 'test1'" | ./hbase shell -n
|
||||
|
||||
Version 0.98.3-hadoop2, rd5e65a9144e315bb0a964e7730871af32f5018d5, Sat May 31 19:56:09 PDT 2014
|
||||
|
||||
describe 'test1'
|
||||
|
||||
DESCRIPTION ENABLED
|
||||
'test1', {NAME => 'cf', DATA_BLOCK_ENCODING => 'NON true
|
||||
E', BLOOMFILTER => 'ROW', REPLICATION_SCOPE => '0',
|
||||
VERSIONS => '1', COMPRESSION => 'NONE', MIN_VERSIO
|
||||
NS => '0', TTL => 'FOREVER', KEEP_DELETED_CELLS =>
|
||||
'false', BLOCKSIZE => '65536', IN_MEMORY => 'false'
|
||||
, BLOCKCACHE => 'true'}
|
||||
1 row(s) in 3.2410 seconds
|
||||
----
|
||||
|
||||
To suppress all output, echo it to _/dev/null:_
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ echo "describe 'test'" | ./hbase shell -n > /dev/null 2>&1
|
||||
----
|
||||
====
|
||||
|
||||
.Checking the Result of a Scripted Command
|
||||
====
|
||||
Since scripts are not designed to be run interactively, you need a way to check whether your command failed or succeeded.
|
||||
The HBase shell uses the standard convention of returning a value of `0` for successful commands, and some non-zero value for failed commands.
|
||||
Bash stores a command's return value in a special environment variable called `$?`.
|
||||
Because that variable is overwritten each time the shell runs any command, you should store the result in a different, script-defined variable.
|
||||
|
||||
This is a naive script that shows one way to store the return value and make a decision based upon it.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
#!/bin/bash
|
||||
|
||||
echo "describe 'test'" | ./hbase shell -n > /dev/null 2>&1
|
||||
status=$?
|
||||
echo "The status was " $status
|
||||
if ($status == 0); then
|
||||
echo "The command succeeded"
|
||||
else
|
||||
echo "The command may have failed."
|
||||
fi
|
||||
return $status
|
||||
----
|
||||
====
|
||||
|
||||
=== Checking for Success or Failure In Scripts
|
||||
|
||||
Getting an exit code of `0` means that the command you scripted definitely succeeded.
|
||||
However, getting a non-zero exit code does not necessarily mean the command failed.
|
||||
The command could have succeeded, but the client lost connectivity, or some other event obscured its success.
|
||||
This is because RPC commands are stateless.
|
||||
The only way to be sure of the status of an operation is to check.
|
||||
For instance, if your script creates a table, but returns a non-zero exit value, you should check whether the table was actually created before trying again to create it.
|
||||
|
||||
== Read HBase Shell Commands from a Command File
|
||||
|
||||
You can enter HBase Shell commands into a text file, one command per line, and pass that file to the HBase Shell.
|
||||
|
||||
.Example Command File
|
||||
====
|
||||
----
|
||||
create 'test', 'cf'
|
||||
list 'test'
|
||||
put 'test', 'row1', 'cf:a', 'value1'
|
||||
put 'test', 'row2', 'cf:b', 'value2'
|
||||
put 'test', 'row3', 'cf:c', 'value3'
|
||||
put 'test', 'row4', 'cf:d', 'value4'
|
||||
scan 'test'
|
||||
get 'test', 'row1'
|
||||
disable 'test'
|
||||
enable 'test'
|
||||
----
|
||||
====
|
||||
|
||||
.Directing HBase Shell to Execute the Commands
|
||||
====
|
||||
Pass the path to the command file as the only argument to the `hbase shell` command.
|
||||
Each command is executed and its output is shown.
|
||||
If you do not include the `exit` command in your script, you are returned to the HBase shell prompt.
|
||||
There is no way to programmatically check each individual command for success or failure.
|
||||
Also, though you see the output for each command, the commands themselves are not echoed to the screen so it can be difficult to line up the command with its output.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ ./hbase shell ./sample_commands.txt
|
||||
0 row(s) in 3.4170 seconds
|
||||
|
||||
TABLE
|
||||
test
|
||||
1 row(s) in 0.0590 seconds
|
||||
|
||||
0 row(s) in 0.1540 seconds
|
||||
|
||||
0 row(s) in 0.0080 seconds
|
||||
|
||||
0 row(s) in 0.0060 seconds
|
||||
|
||||
0 row(s) in 0.0060 seconds
|
||||
|
||||
ROW COLUMN+CELL
|
||||
row1 column=cf:a, timestamp=1407130286968, value=value1
|
||||
row2 column=cf:b, timestamp=1407130286997, value=value2
|
||||
row3 column=cf:c, timestamp=1407130287007, value=value3
|
||||
row4 column=cf:d, timestamp=1407130287015, value=value4
|
||||
4 row(s) in 0.0420 seconds
|
||||
|
||||
COLUMN CELL
|
||||
cf:a timestamp=1407130286968, value=value1
|
||||
1 row(s) in 0.0110 seconds
|
||||
|
||||
0 row(s) in 1.5630 seconds
|
||||
|
||||
0 row(s) in 0.4360 seconds
|
||||
----
|
||||
====
|
||||
|
||||
== Passing VM Options to the Shell
|
||||
|
||||
You can pass VM options to the HBase Shell using the `HBASE_SHELL_OPTS` environment variable.
|
||||
You can set this in your environment, for instance by editing _~/.bashrc_, or set it as part of the command to launch HBase Shell.
|
||||
The following example sets several garbage-collection-related variables, just for the lifetime of the VM running the HBase Shell.
|
||||
The command should be run all on a single line, but is broken by the `\` character, for readability.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ HBASE_SHELL_OPTS="-verbose:gc -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCDateStamps \
|
||||
-XX:+PrintGCDetails -Xloggc:$HBASE_HOME/logs/gc-hbase.log" ./bin/hbase shell
|
||||
----
|
||||
|
||||
== Shell Tricks
|
||||
|
||||
=== Table variables
|
||||
|
||||
HBase 0.95 adds shell commands that provides jruby-style object-oriented references for tables.
|
||||
Previously all of the shell commands that act upon a table have a procedural style that always took the name of the table as an argument.
|
||||
HBase 0.95 introduces the ability to assign a table to a jruby variable.
|
||||
The table reference can be used to perform data read write operations such as puts, scans, and gets well as admin functionality such as disabling, dropping, describing tables.
|
||||
|
||||
For example, previously you would always specify a table name:
|
||||
|
||||
----
|
||||
hbase(main):000:0> create ‘t’, ‘f’
|
||||
0 row(s) in 1.0970 seconds
|
||||
hbase(main):001:0> put 't', 'rold', 'f', 'v'
|
||||
0 row(s) in 0.0080 seconds
|
||||
|
||||
hbase(main):002:0> scan 't'
|
||||
ROW COLUMN+CELL
|
||||
rold column=f:, timestamp=1378473207660, value=v
|
||||
1 row(s) in 0.0130 seconds
|
||||
|
||||
hbase(main):003:0> describe 't'
|
||||
DESCRIPTION ENABLED
|
||||
't', {NAME => 'f', DATA_BLOCK_ENCODING => 'NONE', BLOOMFILTER => 'ROW', REPLICATION_ true
|
||||
SCOPE => '0', VERSIONS => '1', COMPRESSION => 'NONE', MIN_VERSIONS => '0', TTL => '2
|
||||
147483647', KEEP_DELETED_CELLS => 'false', BLOCKSIZE => '65536', IN_MEMORY => 'false
|
||||
', BLOCKCACHE => 'true'}
|
||||
1 row(s) in 1.4430 seconds
|
||||
|
||||
hbase(main):004:0> disable 't'
|
||||
0 row(s) in 14.8700 seconds
|
||||
|
||||
hbase(main):005:0> drop 't'
|
||||
0 row(s) in 23.1670 seconds
|
||||
|
||||
hbase(main):006:0>
|
||||
----
|
||||
|
||||
Now you can assign the table to a variable and use the results in jruby shell code.
|
||||
|
||||
----
|
||||
hbase(main):007 > t = create 't', 'f'
|
||||
0 row(s) in 1.0970 seconds
|
||||
|
||||
=> Hbase::Table - t
|
||||
hbase(main):008 > t.put 'r', 'f', 'v'
|
||||
0 row(s) in 0.0640 seconds
|
||||
hbase(main):009 > t.scan
|
||||
ROW COLUMN+CELL
|
||||
r column=f:, timestamp=1331865816290, value=v
|
||||
1 row(s) in 0.0110 seconds
|
||||
hbase(main):010:0> t.describe
|
||||
DESCRIPTION ENABLED
|
||||
't', {NAME => 'f', DATA_BLOCK_ENCODING => 'NONE', BLOOMFILTER => 'ROW', REPLICATION_ true
|
||||
SCOPE => '0', VERSIONS => '1', COMPRESSION => 'NONE', MIN_VERSIONS => '0', TTL => '2
|
||||
147483647', KEEP_DELETED_CELLS => 'false', BLOCKSIZE => '65536', IN_MEMORY => 'false
|
||||
', BLOCKCACHE => 'true'}
|
||||
1 row(s) in 0.0210 seconds
|
||||
hbase(main):038:0> t.disable
|
||||
0 row(s) in 6.2350 seconds
|
||||
hbase(main):039:0> t.drop
|
||||
0 row(s) in 0.2340 seconds
|
||||
----
|
||||
|
||||
If the table has already been created, you can assign a Table to a variable by using the get_table method:
|
||||
|
||||
----
|
||||
hbase(main):011 > create 't','f'
|
||||
0 row(s) in 1.2500 seconds
|
||||
|
||||
=> Hbase::Table - t
|
||||
hbase(main):012:0> tab = get_table 't'
|
||||
0 row(s) in 0.0010 seconds
|
||||
|
||||
=> Hbase::Table - t
|
||||
hbase(main):013:0> tab.put ‘r1’ ,’f’, ‘v’
|
||||
0 row(s) in 0.0100 seconds
|
||||
hbase(main):014:0> tab.scan
|
||||
ROW COLUMN+CELL
|
||||
r1 column=f:, timestamp=1378473876949, value=v
|
||||
1 row(s) in 0.0240 seconds
|
||||
hbase(main):015:0>
|
||||
----
|
||||
|
||||
The list functionality has also been extended so that it returns a list of table names as strings.
|
||||
You can then use jruby to script table operations based on these names.
|
||||
The list_snapshots command also acts similarly.
|
||||
|
||||
----
|
||||
hbase(main):016 > tables = list(‘t.*’)
|
||||
TABLE
|
||||
t
|
||||
1 row(s) in 0.1040 seconds
|
||||
|
||||
=> #<#<Class:0x7677ce29>:0x21d377a4>
|
||||
hbase(main):017:0> tables.map { |t| disable t ; drop t}
|
||||
0 row(s) in 2.2510 seconds
|
||||
|
||||
=> [nil]
|
||||
hbase(main):018:0>
|
||||
----
|
||||
|
||||
=== _irbrc_
|
||||
|
||||
Create an _.irbrc_ file for yourself in your home directory.
|
||||
Add customizations.
|
||||
A useful one is command history so commands are save across Shell invocations:
|
||||
[source,bash]
|
||||
----
|
||||
$ more .irbrc
|
||||
require 'irb/ext/save-history'
|
||||
IRB.conf[:SAVE_HISTORY] = 100
|
||||
IRB.conf[:HISTORY_FILE] = "#{ENV['HOME']}/.irb-save-history"
|
||||
----
|
||||
|
||||
See the `ruby` documentation of _.irbrc_ to learn about other possible configurations.
|
||||
|
||||
=== LOG data to timestamp
|
||||
|
||||
To convert the date '08/08/16 20:56:29' from an hbase log into a timestamp, do:
|
||||
|
||||
----
|
||||
hbase(main):021:0> import java.text.SimpleDateFormat
|
||||
hbase(main):022:0> import java.text.ParsePosition
|
||||
hbase(main):023:0> SimpleDateFormat.new("yy/MM/dd HH:mm:ss").parse("08/08/16 20:56:29", ParsePosition.new(0)).getTime() => 1218920189000
|
||||
----
|
||||
|
||||
To go the other direction:
|
||||
|
||||
----
|
||||
hbase(main):021:0> import java.util.Date
|
||||
hbase(main):022:0> Date.new(1218920189000).toString() => "Sat Aug 16 20:56:29 UTC 2008"
|
||||
----
|
||||
|
||||
To output in a format that is exactly like that of the HBase log format will take a little messing with link:http://download.oracle.com/javase/6/docs/api/java/text/SimpleDateFormat.html[SimpleDateFormat].
|
||||
|
||||
=== Debug
|
||||
|
||||
==== Shell debug switch
|
||||
|
||||
You can set a debug switch in the shell to see more output -- e.g.
|
||||
more of the stack trace on exception -- when you run a command:
|
||||
|
||||
[source]
|
||||
----
|
||||
hbase> debug <RETURN>
|
||||
----
|
||||
|
||||
==== DEBUG log level
|
||||
|
||||
To enable DEBUG level logging in the shell, launch it with the `-d` option.
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ ./bin/hbase shell -d
|
||||
----
|
||||
|
||||
=== Commands
|
||||
|
||||
==== count
|
||||
|
||||
Count command returns the number of rows in a table.
|
||||
It's quite fast when configured with the right CACHE
|
||||
|
||||
[source]
|
||||
----
|
||||
hbase> count '<tablename>', CACHE => 1000
|
||||
----
|
||||
|
||||
The above count fetches 1000 rows at a time.
|
||||
Set CACHE lower if your rows are big.
|
||||
Default is to fetch one row at a time.
|
||||
|
|
@ -0,0 +1,42 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
[[sql]]
|
||||
== SQL over HBase
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
The following projects offer some support for SQL over HBase.
|
||||
|
||||
[[phoenix]]
|
||||
=== Apache Phoenix
|
||||
|
||||
link:http://phoenix.apache.org[Apache Phoenix]
|
||||
|
||||
=== Trafodion
|
||||
|
||||
link:https://wiki.trafodion.org/[Trafodion: Transactional SQL-on-HBase]
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,279 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[thrift]]
|
||||
= Thrift API and Filter Language
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
|
||||
Apache link:http://thrift.apache.org/[Thrift] is a cross-platform, cross-language development framework.
|
||||
HBase includes a Thrift API and filter language.
|
||||
The Thrift API relies on client and server processes.
|
||||
Documentation about the HBase Thrift API is located at http://wiki.apache.org/hadoop/Hbase/ThriftApi.
|
||||
|
||||
You can configure Thrift for secure authentication at the server and client side, by following the procedures in <<security.client.thrift>> and <<security.gateway.thrift>>.
|
||||
|
||||
The rest of this chapter discusses the filter language provided by the Thrift API.
|
||||
|
||||
[[thrift.filter_language]]
|
||||
== Filter Language
|
||||
|
||||
Thrift Filter Language was introduced in HBase 0.92.
|
||||
It allows you to perform server-side filtering when accessing HBase over Thrift or in the HBase shell.
|
||||
You can find out more about shell integration by using the `scan help` command in the shell.
|
||||
|
||||
You specify a filter as a string, which is parsed on the server to construct the filter.
|
||||
|
||||
[[general_syntax]]
|
||||
=== General Filter String Syntax
|
||||
|
||||
A simple filter expression is expressed as a string:
|
||||
|
||||
----
|
||||
“FilterName (argument, argument,... , argument)”
|
||||
----
|
||||
|
||||
Keep the following syntax guidelines in mind.
|
||||
|
||||
* Specify the name of the filter followed by the comma-separated argument list in parentheses.
|
||||
* If the argument represents a string, it should be enclosed in single quotes (`'`).
|
||||
* Arguments which represent a boolean, an integer, or a comparison operator (such as <, >, or !=), should not be enclosed in quotes
|
||||
* The filter name must be a single word.
|
||||
All ASCII characters are allowed except for whitespace, single quotes and parentheses.
|
||||
* The filter's arguments can contain any ASCII character.
|
||||
If single quotes are present in the argument, they must be escaped by an additional preceding single quote.
|
||||
|
||||
=== Compound Filters and Operators
|
||||
|
||||
.Binary Operators
|
||||
`AND`::
|
||||
If the `AND` operator is used, the key-value must satisfy both filters.
|
||||
|
||||
`OR`::
|
||||
If the `OR` operator is used, the key-value must satisfy at least one of the filters.
|
||||
|
||||
.Unary Operators
|
||||
`SKIP`::
|
||||
For a particular row, if any of the key-values fail the filter condition, the entire row is skipped.
|
||||
|
||||
`WHILE`::
|
||||
For a particular row, key-values will be emitted until a key-value is reached that fails the filter condition.
|
||||
|
||||
.Compound Operators
|
||||
====
|
||||
You can combine multiple operators to create a hierarchy of filters, such as the following example:
|
||||
[source]
|
||||
----
|
||||
(Filter1 AND Filter2) OR (Filter3 AND Filter4)
|
||||
----
|
||||
====
|
||||
|
||||
=== Order of Evaluation
|
||||
|
||||
. Parentheses have the highest precedence.
|
||||
. The unary operators `SKIP` and `WHILE` are next, and have the same precedence.
|
||||
. The binary operators follow. `AND` has highest precedence, followed by `OR`.
|
||||
|
||||
.Precedence Example
|
||||
====
|
||||
[source]
|
||||
----
|
||||
Filter1 AND Filter2 OR Filter
|
||||
is evaluated as
|
||||
(Filter1 AND Filter2) OR Filter3
|
||||
----
|
||||
|
||||
[source]
|
||||
----
|
||||
Filter1 AND SKIP Filter2 OR Filter3
|
||||
is evaluated as
|
||||
(Filter1 AND (SKIP Filter2)) OR Filter3
|
||||
----
|
||||
====
|
||||
|
||||
You can use parentheses to explicitly control the order of evaluation.
|
||||
|
||||
=== Compare Operator
|
||||
|
||||
The following compare operators are provided:
|
||||
|
||||
. LESS (<)
|
||||
. LESS_OR_EQUAL (<=)
|
||||
. EQUAL (=)
|
||||
. NOT_EQUAL (!=)
|
||||
. GREATER_OR_EQUAL (>=)
|
||||
. GREATER (>)
|
||||
. NO_OP (no operation)
|
||||
|
||||
The client should use the symbols (<, <=, =, !=, >, >=) to express compare operators.
|
||||
|
||||
=== Comparator
|
||||
|
||||
A comparator can be any of the following:
|
||||
|
||||
. _BinaryComparator_ - This lexicographically compares against the specified byte array using Bytes.compareTo(byte[], byte[])
|
||||
. _BinaryPrefixComparator_ - This lexicographically compares against a specified byte array.
|
||||
It only compares up to the length of this byte array.
|
||||
. _RegexStringComparator_ - This compares against the specified byte array using the given regular expression.
|
||||
Only EQUAL and NOT_EQUAL comparisons are valid with this comparator
|
||||
. _SubStringComparator_ - This tests if the given substring appears in a specified byte array.
|
||||
The comparison is case insensitive.
|
||||
Only EQUAL and NOT_EQUAL comparisons are valid with this comparator
|
||||
|
||||
The general syntax of a comparator is: `ComparatorType:ComparatorValue`
|
||||
|
||||
The ComparatorType for the various comparators is as follows:
|
||||
|
||||
. _BinaryComparator_ - binary
|
||||
. _BinaryPrefixComparator_ - binaryprefix
|
||||
. _RegexStringComparator_ - regexstring
|
||||
. _SubStringComparator_ - substring
|
||||
|
||||
The ComparatorValue can be any value.
|
||||
|
||||
.Example ComparatorValues
|
||||
. `binary:abc` will match everything that is lexicographically greater than "abc"
|
||||
. `binaryprefix:abc` will match everything whose first 3 characters are lexicographically equal to "abc"
|
||||
. `regexstring:ab*yz` will match everything that doesn't begin with "ab" and ends with "yz"
|
||||
. `substring:abc123` will match everything that begins with the substring "abc123"
|
||||
|
||||
[[examplephpclientprogram]]
|
||||
=== Example PHP Client Program that uses the Filter Language
|
||||
|
||||
[source,php]
|
||||
----
|
||||
<?
|
||||
$_SERVER['PHP_ROOT'] = realpath(dirname(__FILE__).'/..');
|
||||
require_once $_SERVER['PHP_ROOT'].'/flib/__flib.php';
|
||||
flib_init(FLIB_CONTEXT_SCRIPT);
|
||||
require_module('storage/hbase');
|
||||
$hbase = new HBase('<server_name_running_thrift_server>', <port on which thrift server is running>);
|
||||
$hbase->open();
|
||||
$client = $hbase->getClient();
|
||||
$result = $client->scannerOpenWithFilterString('table_name', "(PrefixFilter ('row2') AND (QualifierFilter (>=, 'binary:xyz'))) AND (TimestampsFilter ( 123, 456))");
|
||||
$to_print = $client->scannerGetList($result,1);
|
||||
while ($to_print) {
|
||||
print_r($to_print);
|
||||
$to_print = $client->scannerGetList($result,1);
|
||||
}
|
||||
$client->scannerClose($result);
|
||||
?>
|
||||
----
|
||||
|
||||
=== Example Filter Strings
|
||||
|
||||
* `"PrefixFilter ('Row') AND PageFilter (1) AND FirstKeyOnlyFilter ()"` will return all key-value pairs that match the following conditions:
|
||||
+
|
||||
. The row containing the key-value should have prefix _Row_
|
||||
. The key-value must be located in the first row of the table
|
||||
. The key-value pair must be the first key-value in the row
|
||||
+
|
||||
* `"(RowFilter (=, 'binary:Row 1') AND TimeStampsFilter (74689, 89734)) OR ColumnRangeFilter ('abc', true, 'xyz', false))"` will return all key-value pairs that match both the following conditions:
|
||||
** The key-value is in a row having row key _Row 1_
|
||||
** The key-value must have a timestamp of either 74689 or 89734.
|
||||
** Or it must match the following condition:
|
||||
*** The key-value pair must be in a column that is lexicographically >= abc and < xyz
|
||||
+
|
||||
* `"SKIP ValueFilter (0)"` will skip the entire row if any of the values in the row is not 0
|
||||
|
||||
[[individualfiltersyntax]]
|
||||
=== Individual Filter Syntax
|
||||
|
||||
KeyOnlyFilter::
|
||||
This filter doesn't take any arguments.
|
||||
It returns only the key component of each key-value.
|
||||
|
||||
FirstKeyOnlyFilter::
|
||||
This filter doesn't take any arguments.
|
||||
It returns only the first key-value from each row.
|
||||
|
||||
PrefixFilter::
|
||||
This filter takes one argument – a prefix of a row key.
|
||||
It returns only those key-values present in a row that starts with the specified row prefix
|
||||
|
||||
ColumnPrefixFilter::
|
||||
This filter takes one argument – a column prefix.
|
||||
It returns only those key-values present in a column that starts with the specified column prefix.
|
||||
The column prefix must be of the form: `“qualifier”`.
|
||||
|
||||
MultipleColumnPrefixFilter::
|
||||
This filter takes a list of column prefixes.
|
||||
It returns key-values that are present in a column that starts with any of the specified column prefixes.
|
||||
Each of the column prefixes must be of the form: `“qualifier”`.
|
||||
|
||||
ColumnCountGetFilter::
|
||||
This filter takes one argument – a limit.
|
||||
It returns the first limit number of columns in the table.
|
||||
|
||||
PageFilter::
|
||||
This filter takes one argument – a page size.
|
||||
It returns page size number of rows from the table.
|
||||
|
||||
ColumnPaginationFilter::
|
||||
This filter takes two arguments – a limit and offset.
|
||||
It returns limit number of columns after offset number of columns.
|
||||
It does this for all the rows.
|
||||
|
||||
InclusiveStopFilter::
|
||||
This filter takes one argument – a row key on which to stop scanning.
|
||||
It returns all key-values present in rows up to and including the specified row.
|
||||
|
||||
TimeStampsFilter::
|
||||
This filter takes a list of timestamps.
|
||||
It returns those key-values whose timestamps matches any of the specified timestamps.
|
||||
|
||||
RowFilter::
|
||||
This filter takes a compare operator and a comparator.
|
||||
It compares each row key with the comparator using the compare operator and if the comparison returns true, it returns all the key-values in that row.
|
||||
|
||||
Family Filter::
|
||||
This filter takes a compare operator and a comparator.
|
||||
It compares each qualifier name with the comparator using the compare operator and if the comparison returns true, it returns all the key-values in that column.
|
||||
|
||||
QualifierFilter::
|
||||
This filter takes a compare operator and a comparator.
|
||||
It compares each qualifier name with the comparator using the compare operator and if the comparison returns true, it returns all the key-values in that column.
|
||||
|
||||
ValueFilter::
|
||||
This filter takes a compare operator and a comparator.
|
||||
It compares each value with the comparator using the compare operator and if the comparison returns true, it returns that key-value.
|
||||
|
||||
DependentColumnFilter::
|
||||
This filter takes two arguments – a family and a qualifier.
|
||||
It tries to locate this column in each row and returns all key-values in that row that have the same timestamp.
|
||||
If the row doesn't contain the specified column – none of the key-values in that row will be returned.
|
||||
|
||||
SingleColumnValueFilter::
|
||||
This filter takes a column family, a qualifier, a compare operator and a comparator.
|
||||
If the specified column is not found – all the columns of that row will be emitted.
|
||||
If the column is found and the comparison with the comparator returns true, all the columns of the row will be emitted.
|
||||
If the condition fails, the row will not be emitted.
|
||||
|
||||
SingleColumnValueExcludeFilter::
|
||||
This filter takes the same arguments and behaves same as SingleColumnValueFilter – however, if the column is found and the condition passes, all the columns of the row will be emitted except for the tested column value.
|
||||
|
||||
ColumnRangeFilter::
|
||||
This filter is used for selecting only those keys with columns that are between minColumn and maxColumn.
|
||||
It also takes two boolean variables to indicate whether to include the minColumn and maxColumn or not.
|
||||
|
|
@ -0,0 +1,194 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
|
||||
[appendix]
|
||||
[[tracing]]
|
||||
== Enabling Dapper-like Tracing in HBase
|
||||
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
link:https://issues.apache.org/jira/browse/HBASE-6449[HBASE-6449] added support for tracing requests through HBase, using the open source tracing library, link:http://github.com/cloudera/htrace[HTrace].
|
||||
Setting up tracing is quite simple, however it currently requires some very minor changes to your client code (it would not be very difficult to remove this requirement).
|
||||
|
||||
[[tracing.spanreceivers]]
|
||||
=== SpanReceivers
|
||||
|
||||
The tracing system works by collecting information in structs called 'Spans'. It is up to you to choose how you want to receive this information by implementing the `SpanReceiver` interface, which defines one method:
|
||||
|
||||
[source]
|
||||
----
|
||||
|
||||
public void receiveSpan(Span span);
|
||||
----
|
||||
|
||||
This method serves as a callback whenever a span is completed.
|
||||
HTrace allows you to use as many SpanReceivers as you want so you can easily send trace information to multiple destinations.
|
||||
|
||||
Configure what SpanReceivers you'd like to us by putting a comma separated list of the fully-qualified class name of classes implementing `SpanReceiver` in _hbase-site.xml_ property: `hbase.trace.spanreceiver.classes`.
|
||||
|
||||
HTrace includes a `LocalFileSpanReceiver` that writes all span information to local files in a JSON-based format.
|
||||
The `LocalFileSpanReceiver` looks in _hbase-site.xml_ for a `hbase.local-file-span-receiver.path` property with a value describing the name of the file to which nodes should write their span information.
|
||||
|
||||
[source]
|
||||
----
|
||||
|
||||
<property>
|
||||
<name>hbase.trace.spanreceiver.classes</name>
|
||||
<value>org.htrace.impl.LocalFileSpanReceiver</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.local-file-span-receiver.path</name>
|
||||
<value>/var/log/hbase/htrace.out</value>
|
||||
</property>
|
||||
----
|
||||
|
||||
HTrace also provides `ZipkinSpanReceiver` which converts spans to link:http://github.com/twitter/zipkin[Zipkin] span format and send them to Zipkin server.
|
||||
In order to use this span receiver, you need to install the jar of htrace-zipkin to your HBase's classpath on all of the nodes in your cluster.
|
||||
|
||||
_htrace-zipkin_ is published to the maven central repository.
|
||||
You could get the latest version from there or just build it locally and then copy it out to all nodes, change your config to use zipkin receiver, distribute the new configuration and then (rolling) restart.
|
||||
|
||||
Here is the example of manual setup procedure.
|
||||
|
||||
----
|
||||
|
||||
$ git clone https://github.com/cloudera/htrace
|
||||
$ cd htrace/htrace-zipkin
|
||||
$ mvn compile assembly:single
|
||||
$ cp target/htrace-zipkin-*-jar-with-dependencies.jar $HBASE_HOME/lib/
|
||||
# copy jar to all nodes...
|
||||
----
|
||||
|
||||
The `ZipkinSpanReceiver` looks in _hbase-site.xml_ for a `hbase.zipkin.collector-hostname` and `hbase.zipkin.collector-port` property with a value describing the Zipkin collector server to which span information are sent.
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<property>
|
||||
<name>hbase.trace.spanreceiver.classes</name>
|
||||
<value>org.htrace.impl.ZipkinSpanReceiver</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zipkin.collector-hostname</name>
|
||||
<value>localhost</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zipkin.collector-port</name>
|
||||
<value>9410</value>
|
||||
</property>
|
||||
----
|
||||
|
||||
If you do not want to use the included span receivers, you are encouraged to write your own receiver (take a look at `LocalFileSpanReceiver` for an example). If you think others would benefit from your receiver, file a JIRA or send a pull request to link:http://github.com/cloudera/htrace[HTrace].
|
||||
|
||||
[[tracing.client.modifications]]
|
||||
== Client Modifications
|
||||
|
||||
In order to turn on tracing in your client code, you must initialize the module sending spans to receiver once per client process.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
private SpanReceiverHost spanReceiverHost;
|
||||
|
||||
...
|
||||
|
||||
Configuration conf = HBaseConfiguration.create();
|
||||
SpanReceiverHost spanReceiverHost = SpanReceiverHost.getInstance(conf);
|
||||
----
|
||||
|
||||
Then you simply start tracing span before requests you think are interesting, and close it when the request is done.
|
||||
For example, if you wanted to trace all of your get operations, you change this:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
Configuration config = HBaseConfiguration.create();
|
||||
Connection connection = ConnectionFactory.createConnection(config);
|
||||
Table table = connection.getTable(TableName.valueOf("t1"));
|
||||
Get get = new Get(Bytes.toBytes("r1"));
|
||||
Result res = table.get(get);
|
||||
----
|
||||
|
||||
into:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
TraceScope ts = Trace.startSpan("Gets", Sampler.ALWAYS);
|
||||
try {
|
||||
Table table = connection.getTable(TableName.valueOf("t1"));
|
||||
Get get = new Get(Bytes.toBytes("r1"));
|
||||
Result res = table.get(get);
|
||||
} finally {
|
||||
ts.close();
|
||||
}
|
||||
----
|
||||
|
||||
If you wanted to trace half of your 'get' operations, you would pass in:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
new ProbabilitySampler(0.5)
|
||||
----
|
||||
|
||||
in lieu of `Sampler.ALWAYS` to `Trace.startSpan()`.
|
||||
See the HTrace _README_ for more information on Samplers.
|
||||
|
||||
[[tracing.client.shell]]
|
||||
== Tracing from HBase Shell
|
||||
|
||||
You can use +trace+ command for tracing requests from HBase Shell. +trace 'start'+ command turns on tracing and +trace
|
||||
'stop'+ command turns off tracing.
|
||||
|
||||
[source]
|
||||
----
|
||||
|
||||
hbase(main):001:0> trace 'start'
|
||||
hbase(main):002:0> put 'test', 'row1', 'f:', 'val1' # traced commands
|
||||
hbase(main):003:0> trace 'stop'
|
||||
----
|
||||
|
||||
+trace 'start'+ and +trace 'stop'+ always returns boolean value representing if or not there is ongoing tracing.
|
||||
As a result, +trace
|
||||
'stop'+ returns false on suceess. +trace 'status'+ just returns if or not tracing is turned on.
|
||||
|
||||
[source]
|
||||
----
|
||||
|
||||
hbase(main):001:0> trace 'start'
|
||||
=> true
|
||||
|
||||
hbase(main):002:0> trace 'status'
|
||||
=> true
|
||||
|
||||
hbase(main):003:0> trace 'stop'
|
||||
=> false
|
||||
|
||||
hbase(main):004:0> trace 'status'
|
||||
=> false
|
||||
----
|
||||
|
||||
:numbered:
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,351 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[unit.tests]]
|
||||
= Unit Testing HBase Applications
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
This chapter discusses unit testing your HBase application using JUnit, Mockito, MRUnit, and HBaseTestingUtility.
|
||||
Much of the information comes from link:http://blog.cloudera.com/blog/2013/09/how-to-test-hbase-applications-using-popular-tools/[a community blog post about testing HBase applications].
|
||||
For information on unit tests for HBase itself, see <<hbase.tests,hbase.tests>>.
|
||||
|
||||
== JUnit
|
||||
|
||||
HBase uses link:http://junit.org[JUnit] 4 for unit tests
|
||||
|
||||
This example will add unit tests to the following example class:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public class MyHBaseDAO {
|
||||
|
||||
public static void insertRecord(Table.getTable(table), HBaseTestObj obj)
|
||||
throws Exception {
|
||||
Put put = createPut(obj);
|
||||
table.put(put);
|
||||
}
|
||||
|
||||
private static Put createPut(HBaseTestObj obj) {
|
||||
Put put = new Put(Bytes.toBytes(obj.getRowKey()));
|
||||
put.add(Bytes.toBytes("CF"), Bytes.toBytes("CQ-1"),
|
||||
Bytes.toBytes(obj.getData1()));
|
||||
put.add(Bytes.toBytes("CF"), Bytes.toBytes("CQ-2"),
|
||||
Bytes.toBytes(obj.getData2()));
|
||||
return put;
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
The first step is to add JUnit dependencies to your Maven POM file:
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<dependency>
|
||||
<groupId>junit</groupId>
|
||||
<artifactId>junit</artifactId>
|
||||
<version>4.11</version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
----
|
||||
|
||||
Next, add some unit tests to your code.
|
||||
Tests are annotated with `@Test`.
|
||||
Here, the unit tests are in bold.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public class TestMyHbaseDAOData {
|
||||
@Test
|
||||
public void testCreatePut() throws Exception {
|
||||
HBaseTestObj obj = new HBaseTestObj();
|
||||
obj.setRowKey("ROWKEY-1");
|
||||
obj.setData1("DATA-1");
|
||||
obj.setData2("DATA-2");
|
||||
Put put = MyHBaseDAO.createPut(obj);
|
||||
assertEquals(obj.getRowKey(), Bytes.toString(put.getRow()));
|
||||
assertEquals(obj.getData1(), Bytes.toString(put.get(Bytes.toBytes("CF"), Bytes.toBytes("CQ-1")).get(0).getValue()));
|
||||
assertEquals(obj.getData2(), Bytes.toString(put.get(Bytes.toBytes("CF"), Bytes.toBytes("CQ-2")).get(0).getValue()));
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
These tests ensure that your `createPut` method creates, populates, and returns a `Put` object with expected values.
|
||||
Of course, JUnit can do much more than this.
|
||||
For an introduction to JUnit, see link:https://github.com/junit-team/junit/wiki/Getting-started.
|
||||
|
||||
== Mockito
|
||||
|
||||
Mockito is a mocking framework.
|
||||
It goes further than JUnit by allowing you to test the interactions between objects without having to replicate the entire environment.
|
||||
You can read more about Mockito at its project site, link:https://code.google.com/p/mockito/.
|
||||
|
||||
You can use Mockito to do unit testing on smaller units.
|
||||
For instance, you can mock a `org.apache.hadoop.hbase.Server` instance or a `org.apache.hadoop.hbase.master.MasterServices` interface reference rather than a full-blown `org.apache.hadoop.hbase.master.HMaster`.
|
||||
|
||||
This example builds upon the example code in <<unit.tests,unit.tests>>, to test the `insertRecord` method.
|
||||
|
||||
First, add a dependency for Mockito to your Maven POM file.
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<dependency>
|
||||
<groupId>org.mockito</groupId>
|
||||
<artifactId>mockito-all</artifactId>
|
||||
<version>1.9.5</version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
----
|
||||
|
||||
Next, add a `@RunWith` annotation to your test class, to direct it to use Mockito.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
@RunWith(MockitoJUnitRunner.class)
|
||||
public class TestMyHBaseDAO{
|
||||
@Mock
|
||||
Configuration config = HBaseConfiguration.create();
|
||||
@Mock
|
||||
Connection connection = ConnectionFactory.createConnection(config);
|
||||
@Mock
|
||||
private Table table;
|
||||
@Captor
|
||||
private ArgumentCaptor putCaptor;
|
||||
|
||||
@Test
|
||||
public void testInsertRecord() throws Exception {
|
||||
//return mock table when getTable is called
|
||||
when(connection.getTable(TableName.valueOf("tablename")).thenReturn(table);
|
||||
//create test object and make a call to the DAO that needs testing
|
||||
HBaseTestObj obj = new HBaseTestObj();
|
||||
obj.setRowKey("ROWKEY-1");
|
||||
obj.setData1("DATA-1");
|
||||
obj.setData2("DATA-2");
|
||||
MyHBaseDAO.insertRecord(table, obj);
|
||||
verify(table).put(putCaptor.capture());
|
||||
Put put = putCaptor.getValue();
|
||||
|
||||
assertEquals(Bytes.toString(put.getRow()), obj.getRowKey());
|
||||
assert(put.has(Bytes.toBytes("CF"), Bytes.toBytes("CQ-1")));
|
||||
assert(put.has(Bytes.toBytes("CF"), Bytes.toBytes("CQ-2")));
|
||||
assertEquals(Bytes.toString(put.get(Bytes.toBytes("CF"),Bytes.toBytes("CQ-1")).get(0).getValue()), "DATA-1");
|
||||
assertEquals(Bytes.toString(put.get(Bytes.toBytes("CF"),Bytes.toBytes("CQ-2")).get(0).getValue()), "DATA-2");
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
This code populates `HBaseTestObj` with ``ROWKEY-1'', ``DATA-1'', ``DATA-2'' as values.
|
||||
It then inserts the record into the mocked table.
|
||||
The Put that the DAO would have inserted is captured, and values are tested to verify that they are what you expected them to be.
|
||||
|
||||
The key here is to manage Connection and Table instance creation outside the DAO.
|
||||
This allows you to mock them cleanly and test Puts as shown above.
|
||||
Similarly, you can now expand into other operations such as Get, Scan, or Delete.
|
||||
|
||||
== MRUnit
|
||||
|
||||
link:http://mrunit.apache.org/[Apache MRUnit] is a library that allows you to unit-test MapReduce jobs.
|
||||
You can use it to test HBase jobs in the same way as other MapReduce jobs.
|
||||
|
||||
Given a MapReduce job that writes to an HBase table called `MyTest`, which has one column family called `CF`, the reducer of such a job could look like the following:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public class MyReducer extends TableReducer<Text, Text, ImmutableBytesWritable> {
|
||||
public static final byte[] CF = "CF".getBytes();
|
||||
public static final byte[] QUALIFIER = "CQ-1".getBytes();
|
||||
public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
|
||||
//bunch of processing to extract data to be inserted, in our case, lets say we are simply
|
||||
//appending all the records we receive from the mapper for this particular
|
||||
//key and insert one record into HBase
|
||||
StringBuffer data = new StringBuffer();
|
||||
Put put = new Put(Bytes.toBytes(key.toString()));
|
||||
for (Text val : values) {
|
||||
data = data.append(val);
|
||||
}
|
||||
put.add(CF, QUALIFIER, Bytes.toBytes(data.toString()));
|
||||
//write to HBase
|
||||
context.write(new ImmutableBytesWritable(Bytes.toBytes(key.toString())), put);
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
To test this code, the first step is to add a dependency to MRUnit to your Maven POM file.
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<dependency>
|
||||
<groupId>org.apache.mrunit</groupId>
|
||||
<artifactId>mrunit</artifactId>
|
||||
<version>1.0.0 </version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
----
|
||||
|
||||
Next, use the ReducerDriver provided by MRUnit, in your Reducer job.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public class MyReducerTest {
|
||||
ReduceDriver<Text, Text, ImmutableBytesWritable, Writable> reduceDriver;
|
||||
byte[] CF = "CF".getBytes();
|
||||
byte[] QUALIFIER = "CQ-1".getBytes();
|
||||
|
||||
@Before
|
||||
public void setUp() {
|
||||
MyReducer reducer = new MyReducer();
|
||||
reduceDriver = ReduceDriver.newReduceDriver(reducer);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testHBaseInsert() throws IOException {
|
||||
String strKey = "RowKey-1", strValue = "DATA", strValue1 = "DATA1",
|
||||
strValue2 = "DATA2";
|
||||
List<Text> list = new ArrayList<Text>();
|
||||
list.add(new Text(strValue));
|
||||
list.add(new Text(strValue1));
|
||||
list.add(new Text(strValue2));
|
||||
//since in our case all that the reducer is doing is appending the records that the mapper
|
||||
//sends it, we should get the following back
|
||||
String expectedOutput = strValue + strValue1 + strValue2;
|
||||
//Setup Input, mimic what mapper would have passed
|
||||
//to the reducer and run test
|
||||
reduceDriver.withInput(new Text(strKey), list);
|
||||
//run the reducer and get its output
|
||||
List<Pair<ImmutableBytesWritable, Writable>> result = reduceDriver.run();
|
||||
|
||||
//extract key from result and verify
|
||||
assertEquals(Bytes.toString(result.get(0).getFirst().get()), strKey);
|
||||
|
||||
//extract value for CF/QUALIFIER and verify
|
||||
Put a = (Put)result.get(0).getSecond();
|
||||
String c = Bytes.toString(a.get(CF, QUALIFIER).get(0).getValue());
|
||||
assertEquals(expectedOutput,c );
|
||||
}
|
||||
|
||||
}
|
||||
----
|
||||
|
||||
Your MRUnit test verifies that the output is as expected, the Put that is inserted into HBase has the correct value, and the ColumnFamily and ColumnQualifier have the correct values.
|
||||
|
||||
MRUnit includes a MapperDriver to test mapping jobs, and you can use MRUnit to test other operations, including reading from HBase, processing data, or writing to HDFS,
|
||||
|
||||
== Integration Testing with a HBase Mini-Cluster
|
||||
|
||||
HBase ships with HBaseTestingUtility, which makes it easy to write integration tests using a [firstterm]_mini-cluster_.
|
||||
The first step is to add some dependencies to your Maven POM file.
|
||||
Check the versions to be sure they are appropriate.
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<dependency>
|
||||
<groupId>org.apache.hadoop</groupId>
|
||||
<artifactId>hadoop-common</artifactId>
|
||||
<version>2.0.0</version>
|
||||
<type>test-jar</type>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>org.apache.hbase</groupId>
|
||||
<artifactId>hbase</artifactId>
|
||||
<version>0.98.3</version>
|
||||
<type>test-jar</type>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>org.apache.hadoop</groupId>
|
||||
<artifactId>hadoop-hdfs</artifactId>
|
||||
<version>2.0.0</version>
|
||||
<type>test-jar</type>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>org.apache.hadoop</groupId>
|
||||
<artifactId>hadoop-hdfs</artifactId>
|
||||
<version>2.0.0</version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
----
|
||||
|
||||
This code represents an integration test for the MyDAO insert shown in <<unit.tests,unit.tests>>.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
public class MyHBaseIntegrationTest {
|
||||
private static HBaseTestingUtility utility;
|
||||
byte[] CF = "CF".getBytes();
|
||||
byte[] QUALIFIER = "CQ-1".getBytes();
|
||||
|
||||
@Before
|
||||
public void setup() throws Exception {
|
||||
utility = new HBaseTestingUtility();
|
||||
utility.startMiniCluster();
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testInsert() throws Exception {
|
||||
HTableInterface table = utility.createTable(Bytes.toBytes("MyTest"),
|
||||
Bytes.toBytes("CF"));
|
||||
HBaseTestObj obj = new HBaseTestObj();
|
||||
obj.setRowKey("ROWKEY-1");
|
||||
obj.setData1("DATA-1");
|
||||
obj.setData2("DATA-2");
|
||||
MyHBaseDAO.insertRecord(table, obj);
|
||||
Get get1 = new Get(Bytes.toBytes(obj.getRowKey()));
|
||||
get1.addColumn(CF, CQ1);
|
||||
Result result1 = table.get(get1);
|
||||
assertEquals(Bytes.toString(result1.getRow()), obj.getRowKey());
|
||||
assertEquals(Bytes.toString(result1.value()), obj.getData1());
|
||||
Get get2 = new Get(Bytes.toBytes(obj.getRowKey()));
|
||||
get2.addColumn(CF, CQ2);
|
||||
Result result2 = table.get(get2);
|
||||
assertEquals(Bytes.toString(result2.getRow()), obj.getRowKey());
|
||||
assertEquals(Bytes.toString(result2.value()), obj.getData2());
|
||||
}
|
||||
}
|
||||
----
|
||||
|
||||
This code creates an HBase mini-cluster and starts it.
|
||||
Next, it creates a table called `MyTest` with one column family, `CF`.
|
||||
A record is inserted, a Get is performed from the same table, and the insertion is verified.
|
||||
|
||||
NOTE: Starting the mini-cluster takes about 20-30 seconds, but that should be appropriate for integration testing.
|
||||
|
||||
To use an HBase mini-cluster on Microsoft Windows, you need to use a Cygwin environment.
|
||||
|
||||
See the paper at link:http://blog.sematext.com/2010/08/30/hbase-case-study-using-hbasetestingutility-for-local-testing-development/[HBase Case-Study: Using HBaseTestingUtility for Local Testing and
|
||||
Development] (2010) for more information about HBaseTestingUtility.
|
||||
|
|
@ -0,0 +1,452 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[upgrading]]
|
||||
= Upgrading
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
You cannot skip major versions when upgrading. If you are upgrading from version 0.90.x to 0.94.x, you must first go from 0.90.x to 0.92.x and then go from 0.92.x to 0.94.x.
|
||||
|
||||
NOTE: It may be possible to skip across versions -- for example go from 0.92.2 straight to 0.98.0 just following the 0.96.x upgrade instructions -- but these scenarios are untested.
|
||||
|
||||
Review <<configuration>>, in particular <<hadoop>>.
|
||||
|
||||
[[hbase.versioning]]
|
||||
== HBase version number and compatibility
|
||||
|
||||
HBase has two versioning schemes, pre-1.0 and post-1.0. Both are detailed below.
|
||||
|
||||
[[hbase.versioning.post10]]
|
||||
=== Post 1.0 versions
|
||||
|
||||
Starting with the 1.0.0 release, HBase is working towards link:http://semver.org/[Semantic Versioning] for its release versioning. In summary:
|
||||
|
||||
.Given a version number MAJOR.MINOR.PATCH, increment the:
|
||||
* MAJOR version when you make incompatible API changes,
|
||||
* MINOR version when you add functionality in a backwards-compatible manner, and
|
||||
* PATCH version when you make backwards-compatible bug fixes.
|
||||
* Additional labels for pre-release and build metadata are available as extensions to the MAJOR.MINOR.PATCH format.
|
||||
|
||||
[[hbase.versioning.compat]]
|
||||
.Compatibility Dimensions
|
||||
In addition to the usual API versioning considerations HBase has other compatibility dimensions that we need to consider.
|
||||
|
||||
.Client-Server wire protocol compatibility
|
||||
* Allows updating client and server out of sync.
|
||||
* We could only allow upgrading the server first. I.e. the server would be backward compatible to an old client, that way new APIs are OK.
|
||||
* Example: A user should be able to use an old client to connect to an upgraded cluster.
|
||||
|
||||
.Server-Server protocol compatibility
|
||||
* Servers of different versions can co-exist in the same cluster.
|
||||
* The wire protocol between servers is compatible.
|
||||
* Workers for distributed tasks, such as replication and log splitting, can co-exist in the same cluster.
|
||||
* Dependent protocols (such as using ZK for coordination) will also not be changed.
|
||||
* Example: A user can perform a rolling upgrade.
|
||||
|
||||
.File format compatibility
|
||||
* Support file formats backward and forward compatible
|
||||
* Example: File, ZK encoding, directory layout is upgraded automatically as part of an HBase upgrade. User can rollback to the older version and everything will continue to work.
|
||||
|
||||
.Client API compatibility
|
||||
* Allow changing or removing existing client APIs.
|
||||
* An API needs to deprecated for a major version before we will change/remove it.
|
||||
* APIs available in a patch version will be available in all later patch versions. However, new APIs may be added which will not be available in earlier patch versions.
|
||||
* Example: A user using a newly deprecated api does not need to modify application code with hbase api calls until the next major version.
|
||||
|
||||
.Client Binary compatibility
|
||||
* Client code written to APIs available in a given patch release can run unchanged (no recompilation needed) against the new jars of later patch versions.
|
||||
* Client code written to APIs available in a given patch release might not run against the old jars from an earlier patch version.
|
||||
* Example: Old compiled client code will work unchanged with the new jars.
|
||||
|
||||
.Server-Side Limited API compatibility (taken from Hadoop)
|
||||
* Internal APIs are marked as Stable, Evolving, or Unstable
|
||||
* This implies binary compatibility for coprocessors and plugins (pluggable classes, including replication) as long as these are only using marked interfaces/classes.
|
||||
* Example: Old compiled Coprocessor, Filter, or Plugin code will work unchanged with the new jars.
|
||||
|
||||
.Dependency Compatibility
|
||||
* An upgrade of HBase will not require an incompatible upgrade of a dependent project, including the Java runtime.
|
||||
* Example: An upgrade of Hadoop will not invalidate any of the compatibilities guarantees we made.
|
||||
|
||||
.Operational Compatibility
|
||||
* Metric changes
|
||||
* Behavioral changes of services
|
||||
* Web page APIs
|
||||
|
||||
.Summary
|
||||
* A patch upgrade is a drop-in replacement. Any change that is not Java binary compatible would not be allowed.footnote:[See http://docs.oracle.com/javase/specs/jls/se7/html/jls-13.html.]. Downgrading versions within patch releases may not be compatible.
|
||||
|
||||
* A minor upgrade requires no application/client code modification. Ideally it would be a drop-in replacement but client code, coprocessors, filters, etc might have to be recompiled if new jars are used.
|
||||
|
||||
* A major upgrade allows the HBase community to make breaking changes.
|
||||
|
||||
.Compatibility Matrix footnote:[Note that this indicates what could break, not that it will break. We will/should add specifics in our release notes.]
|
||||
[cols="1,1,1,1"]
|
||||
|===
|
||||
| | Major | Minor | Patch
|
||||
|Client-Server wire Compatibility| N |Y |Y
|
||||
|Server-Server Compatibility |N |Y |Y
|
||||
|File Format Compatibility | N footnote:[comp_matrix_offline_upgrade_note,Running an offline upgrade tool without rollback might be needed. We will typically only support migrating data from major version X to major version X+1.] | Y |Y
|
||||
|Client API Compatibility | N | Y |Y
|
||||
|Client Binary Compatibility | N | N |Y
|
||||
4+|Server-Side Limited API Compatibility
|
||||
>| Stable | N | Y | Y
|
||||
>| Evolving | N |N |Y
|
||||
>| Unstable | N |N |N
|
||||
|Dependency Compatibility | N |Y |Y
|
||||
|Operational Compatibility | N |N |Y
|
||||
|===
|
||||
|
||||
[[hbase.client.api.surface]]
|
||||
==== HBase API Surface
|
||||
|
||||
HBase has a lot of API points, but for the compatibility matrix above, we differentiate between Client API, Limited Private API, and Private API. HBase uses a version of link:https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-common/Compatibility.html[Hadoop's Interface classification]. HBase's Interface classification classes can be found link:https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/classification/package-summary.html[here].
|
||||
|
||||
* InterfaceAudience: captures the intended audience, possible values are Public (for end users and external projects), LimitedPrivate (for other Projects, Coprocessors or other plugin points), and Private (for internal use).
|
||||
* InterfaceStability: describes what types of interface changes are permitted. Possible values are Stable, Evolving, Unstable, and Deprecated.
|
||||
|
||||
[[hbase.client.api]]
|
||||
HBase Client API::
|
||||
HBase Client API consists of all the classes or methods that are marked with InterfaceAudience.Public interface. All main classes in hbase-client and dependent modules have either InterfaceAudience.Public, InterfaceAudience.LimitedPrivate, or InterfaceAudience.Private marker. Not all classes in other modules (hbase-server, etc) have the marker. If a class is not annotated with one of these, it is assumed to be a InterfaceAudience.Private class.
|
||||
|
||||
[[hbase.limitetprivate.api]]
|
||||
HBase LimitedPrivate API::
|
||||
LimitedPrivate annotation comes with a set of target consumers for the interfaces. Those consumers are coprocessors, phoenix, replication endpoint implemnetations or similar. At this point, HBase only guarantees source and binary compatibility for these interfaces between patch versions.
|
||||
|
||||
[[hbase.private.api]]
|
||||
HBase Private API::
|
||||
All classes annotated with InterfaceAudience.Private or all classes that do not have the annotation are for HBase internal use only. The interfaces and method signatures can change at any point in time. If you are relying on a particular interface that is marked Private, you should open a jira to propose changing the interface to be Public or LimitedPrivate, or an interface exposed for this purpose.
|
||||
|
||||
[[hbase.versioning.pre10]]
|
||||
=== Pre 1.0 versions
|
||||
|
||||
Before the semantic versioning scheme pre-1.0, HBase tracked either Hadoop's versions (0.2x) or 0.9x versions. If you are into the arcane, checkout our old wiki page on link:http://wiki.apache.org/hadoop/Hbase/HBaseVersions[HBase Versioning] which tries to connect the HBase version dots. Below sections cover ONLY the releases before 1.0.
|
||||
|
||||
[[hbase.development.series]]
|
||||
.Odd/Even Versioning or "Development" Series Releases
|
||||
Ahead of big releases, we have been putting up preview versions to start the feedback cycle turning-over earlier. These "Development" Series releases, always odd-numbered, come with no guarantees, not even regards being able to upgrade between two sequential releases (we reserve the right to break compatibility across "Development" Series releases). Needless to say, these releases are not for production deploys. They are a preview of what is coming in the hope that interested parties will take the release for a test drive and flag us early if we there are issues we've missed ahead of our rolling a production-worthy release.
|
||||
|
||||
Our first "Development" Series was the 0.89 set that came out ahead of HBase 0.90.0. HBase 0.95 is another "Development" Series that portends HBase 0.96.0. 0.99.x is the last series in "developer preview" mode before 1.0. Afterwards, we will be using semantic versioning naming scheme (see above).
|
||||
|
||||
[[hbase.binary.compatibility]]
|
||||
.Binary Compatibility
|
||||
When we say two HBase versions are compatible, we mean that the versions are wire and binary compatible. Compatible HBase versions means that clients can talk to compatible but differently versioned servers. It means too that you can just swap out the jars of one version and replace them with the jars of another, compatible version and all will just work. Unless otherwise specified, HBase point versions are (mostly) binary compatible. You can safely do rolling upgrades between binary compatible versions; i.e. across point versions: e.g. from 0.94.5 to 0.94.6. See link:[Does compatibility between versions also mean binary compatibility?] discussion on the HBase dev mailing list.
|
||||
|
||||
[[hbase.rolling.upgrade]]
|
||||
=== Rolling Upgrades
|
||||
|
||||
A rolling upgrade is the process by which you update the servers in your cluster a server at a time. You can rolling upgrade across HBase versions if they are binary or wire compatible. See <<hbase.rolling.restart>> for more on what this means. Coarsely, a rolling upgrade is a graceful stop each server, update the software, and then restart. You do this for each server in the cluster. Usually you upgrade the Master first and then the RegionServers. See <<rolling>> for tools that can help use the rolling upgrade process.
|
||||
|
||||
For example, in the below, HBase was symlinked to the actual HBase install. On upgrade, before running a rolling restart over the cluser, we changed the symlink to point at the new HBase software version and then ran
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ HADOOP_HOME=~/hadoop-2.6.0-CRC-SNAPSHOT ~/hbase/bin/rolling-restart.sh --config ~/conf_hbase
|
||||
----
|
||||
|
||||
The rolling-restart script will first gracefully stop and restart the master, and then each of the RegionServers in turn. Because the symlink was changed, on restart the server will come up using the new HBase version. Check logs for errors as the rolling upgrade proceeds.
|
||||
|
||||
[[hbase.rolling.restart]]
|
||||
.Rolling Upgrade Between Versions that are Binary/Wire Compatible
|
||||
Unless otherwise specified, HBase point versions are binary compatible. You can do a <<hbase.rolling.upgrade>> between HBase point versions. For example, you can go to 0.94.6 from 0.94.5 by doing a rolling upgrade across the cluster replacing the 0.94.5 binary with a 0.94.6 binary.
|
||||
|
||||
In the minor version-particular sections below, we call out where the versions are wire/protocol compatible and in this case, it is also possible to do a <<hbase.rolling.upgrade>>. For example, in <<upgrade1.0.rolling.upgrade>>, we state that it is possible to do a rolling upgrade between hbase-0.98.x and hbase-1.0.0.
|
||||
|
||||
== Upgrade Paths
|
||||
|
||||
[[upgrade1.0]]
|
||||
=== Upgrading from 0.98.x to 1.0.x
|
||||
|
||||
In this section we first note the significant changes that come in with 1.0.0 HBase and then we go over the upgrade process. Be sure to read the significant changes section with care so you avoid surprises.
|
||||
|
||||
==== Changes of Note!
|
||||
|
||||
In here we list important changes that are in 1.0.0 since 0.98.x., changes you should be aware that will go into effect once you upgrade.
|
||||
|
||||
[[zookeeper.3.4]]
|
||||
.ZooKeeper 3.4 is required in HBase 1.0.0
|
||||
See <<zookeeper.requirements>>.
|
||||
|
||||
[[default.ports.changed]]
|
||||
.HBase Default Ports Changed
|
||||
The ports used by HBase changed. They used to be in the 600XX range. In HBase 1.0.0 they have been moved up out of the ephemeral port range and are 160XX instead (Master web UI was 60010 and is now 16010; the RegionServer web UI was 60030 and is now 16030, etc.). If you want to keep the old port locations, copy the port setting configs from _hbase-default.xml_ into _hbase-site.xml_, change them back to the old values from the HBase 0.98.x era, and ensure you've distributed your configurations before you restart.
|
||||
|
||||
[[upgrade1.0.hbase.bucketcache.percentage.in.combinedcache]]
|
||||
.hbase.bucketcache.percentage.in.combinedcache configuration has been REMOVED
|
||||
You may have made use of this configuration if you are using BucketCache. If NOT using BucketCache, this change does not effect you. Its removal means that your L1 LruBlockCache is now sized using `hfile.block.cache.size` -- i.e. the way you would size the on-heap L1 LruBlockCache if you were NOT doing BucketCache -- and the BucketCache size is not whatever the setting for `hbase.bucketcache.size` is. You may need to adjust configs to get the LruBlockCache and BucketCache sizes set to what they were in 0.98.x and previous. If you did not set this config., its default value was 0.9. If you do nothing, your BucketCache will increase in size by 10%. Your L1 LruBlockCache will become `hfile.block.cache.size` times your java heap size (`hfile.block.cache.size` is a float between 0.0 and 1.0). To read more, see link:https://issues.apache.org/jira/browse/HBASE-11520[HBASE-11520 Simplify offheap cache config by removing the confusing "hbase.bucketcache.percentage.in.combinedcache"].
|
||||
|
||||
[[hbase-12068]]
|
||||
.If you have your own customer filters.
|
||||
See the release notes on the issue link:https://issues.apache.org/jira/browse/HBASE-12068[HBASE-12068 [Branch-1\] Avoid need to always do KeyValueUtil#ensureKeyValue for Filter transformCell]; be sure to follow the recommendations therein.
|
||||
|
||||
[[dlr]]
|
||||
.Distributed Log Replay
|
||||
<<distributed.log.replay>> is off by default in HBase 1.0.0. Enabling it can make a big difference improving HBase MTTR. Enable this feature if you are doing a clean stop/start when you are upgrading. You cannot rolling upgrade to this feature (caveat if you are running on a version of HBase in excess of HBase 0.98.4 -- see link:https://issues.apache.org/jira/browse/HBASE-12577[HBASE-12577 Disable distributed log replay by default] for more).
|
||||
|
||||
[[upgrade1.0.rolling.upgrade]]
|
||||
==== Rolling upgrade from 0.98.x to HBase 1.0.0
|
||||
.From 0.96.x to 1.0.0
|
||||
NOTE: You cannot do a <<hbase.rolling.upgrade,rolling upgrade>> from 0.96.x to 1.0.0 without first doing a rolling upgrade to 0.98.x. See comment in link:https://issues.apache.org/jira/browse/HBASE-11164?focusedCommentId=14182330&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-14182330[HBASE-11164 Document and test rolling updates from 0.98 -> 1.0] for the why. Also because HBase 1.0.0 enables HFile v3 by default, link:https://issues.apache.org/jira/browse/HBASE-9801[HBASE-9801 Change the default HFile version to V3], and support for HFile v3 only arrives in 0.98, this is another reason you cannot rolling upgrade from HBase 0.96.x; if the rolling upgrade stalls, the 0.96.x servers cannot open files written by the servers running the newer HBase 1.0.0 with HFile's of version 3.
|
||||
|
||||
There are no known issues running a <<hbase.rolling.upgrade,rolling upgrade>> from HBase 0.98.x to HBase 1.0.0.
|
||||
|
||||
[[upgrade1.0.from.0.94]]
|
||||
==== Upgrading to 1.0 from 0.94
|
||||
You cannot rolling upgrade from 0.94.x to 1.x.x. You must stop your cluster, install the 1.x.x software, run the migration described at <<executing.the.0.96.upgrade>> (substituting 1.x.x. wherever we make mention of 0.96.x in the section below), and then restart. Be sure to upgrade your ZooKeeper if it is a version less than the required 3.4.x.
|
||||
|
||||
[[upgrade0.98]]
|
||||
=== Upgrading from 0.96.x to 0.98.x
|
||||
A rolling upgrade from 0.96.x to 0.98.x works. The two versions are not binary compatible.
|
||||
|
||||
Additional steps are required to take advantage of some of the new features of 0.98.x, including cell visibility labels, cell ACLs, and transparent server side encryption. See <<security>> for more information. Significant performance improvements include a change to the write ahead log threading model that provides higher transaction throughput under high load, reverse scanners, MapReduce over snapshot files, and striped compaction.
|
||||
|
||||
Clients and servers can run with 0.98.x and 0.96.x versions. However, applications may need to be recompiled due to changes in the Java API.
|
||||
|
||||
=== Upgrading from 0.94.x to 0.98.x
|
||||
A rolling upgrade from 0.94.x directly to 0.98.x does not work. The upgrade path follows the same procedures as <<upgrade0.96>>. Additional steps are required to use some of the new features of 0.98.x. See <<upgrade0.98>> for an abbreviated list of these features.
|
||||
|
||||
[[upgrade0.96]]
|
||||
=== Upgrading from 0.94.x to 0.96.x
|
||||
|
||||
==== The "Singularity"
|
||||
|
||||
.HBase 0.96.x was EOL'd, September 1st, 2014
|
||||
NOTE: Do not deploy 0.96.x Deploy at least 0.98.x. See link:https://issues.apache.org/jira/browse/HBASE-11642[EOL 0.96].
|
||||
|
||||
You will have to stop your old 0.94.x cluster completely to upgrade. If you are replicating between clusters, both clusters will have to go down to upgrade. Make sure it is a clean shutdown. The less WAL files around, the faster the upgrade will run (the upgrade will split any log files it finds in the filesystem as part of the upgrade process). All clients must be upgraded to 0.96 too.
|
||||
|
||||
The API has changed. You will need to recompile your code against 0.96 and you may need to adjust applications to go against new APIs (TODO: List of changes).
|
||||
|
||||
[[executing.the.0.96.upgrade]]
|
||||
==== Executing the 0.96 Upgrade
|
||||
|
||||
.HDFS and ZooKeeper must be up!
|
||||
NOTE: HDFS and ZooKeeper should be up and running during the upgrade process.
|
||||
|
||||
HBase 0.96.0 comes with an upgrade script. Run
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ bin/hbase upgrade
|
||||
----
|
||||
to see its usage. The script has two main modes: `-check`, and `-execute`.
|
||||
|
||||
.check
|
||||
The check step is run against a running 0.94 cluster. Run it from a downloaded 0.96.x binary. The check step is looking for the presence of HFile v1 files. These are unsupported in HBase 0.96.0. To have them rewritten as HFile v2 you must run a compaction.
|
||||
|
||||
The check step prints stats at the end of its run (grep for `“Result:”` in the log) printing absolute path of the tables it scanned, any HFile v1 files found, the regions containing said files (these regions will need a major compaction), and any corrupted files if found. A corrupt file is unreadable, and so is undefined (neither HFile v1 nor HFile v2).
|
||||
|
||||
To run the check step, run
|
||||
|
||||
[source,bash]
|
||||
----
|
||||
$ bin/hbase upgrade -check
|
||||
----
|
||||
|
||||
Here is sample output:
|
||||
----
|
||||
Tables Processed:
|
||||
hdfs://localhost:41020/myHBase/.META.
|
||||
hdfs://localhost:41020/myHBase/usertable
|
||||
hdfs://localhost:41020/myHBase/TestTable
|
||||
hdfs://localhost:41020/myHBase/t
|
||||
|
||||
Count of HFileV1: 2
|
||||
HFileV1:
|
||||
hdfs://localhost:41020/myHBase/usertable /fa02dac1f38d03577bd0f7e666f12812/family/249450144068442524
|
||||
hdfs://localhost:41020/myHBase/usertable /ecdd3eaee2d2fcf8184ac025555bb2af/family/249450144068442512
|
||||
|
||||
Count of corrupted files: 1
|
||||
Corrupted Files:
|
||||
hdfs://localhost:41020/myHBase/usertable/fa02dac1f38d03577bd0f7e666f12812/family/1
|
||||
Count of Regions with HFileV1: 2
|
||||
Regions to Major Compact:
|
||||
hdfs://localhost:41020/myHBase/usertable/fa02dac1f38d03577bd0f7e666f12812
|
||||
hdfs://localhost:41020/myHBase/usertable/ecdd3eaee2d2fcf8184ac025555bb2af
|
||||
|
||||
There are some HFileV1, or corrupt files (files with incorrect major version)
|
||||
----
|
||||
|
||||
In the above sample output, there are two HFile v1 files in two regions, and one corrupt file. Corrupt files should probably be removed. The regions that have HFile v1s need to be major compacted. To major compact, start up the hbase shell and review how to compact an individual region. After the major compaction is done, rerun the check step and the HFile v1 files should be gone, replaced by HFile v2 instances.
|
||||
|
||||
By default, the check step scans the HBase root directory (defined as `hbase.rootdir` in the configuration). To scan a specific directory only, pass the `-dir` option.
|
||||
[source,bash]
|
||||
----
|
||||
$ bin/hbase upgrade -check -dir /myHBase/testTable
|
||||
----
|
||||
The above command would detect HFile v1 files in the _/myHBase/testTable_ directory.
|
||||
|
||||
Once the check step reports all the HFile v1 files have been rewritten, it is safe to proceed with the upgrade.
|
||||
|
||||
.execute
|
||||
After the _check_ step shows the cluster is free of HFile v1, it is safe to proceed with the upgrade. Next is the _execute_ step. You must *SHUTDOWN YOUR 0.94.x CLUSTER* before you can run the execute step. The execute step will not run if it detects running HBase masters or RegionServers.
|
||||
|
||||
[NOTE]
|
||||
====
|
||||
HDFS and ZooKeeper should be up and running during the upgrade process. If zookeeper is managed by HBase, then you can start zookeeper so it is available to the upgrade by running
|
||||
[source,bash]
|
||||
----
|
||||
$ ./hbase/bin/hbase-daemon.sh start zookeeper
|
||||
----
|
||||
====
|
||||
|
||||
The execute upgrade step is made of three substeps.
|
||||
|
||||
* Namespaces: HBase 0.96.0 has support for namespaces. The upgrade needs to reorder directories in the filesystem for namespaces to work.
|
||||
|
||||
* ZNodes: All znodes are purged so that new ones can be written in their place using a new protobuf'ed format and a few are migrated in place: e.g. replication and table state znodes
|
||||
|
||||
* WAL Log Splitting: If the 0.94.x cluster shutdown was not clean, we'll split WAL logs as part of migration before we startup on 0.96.0. This WAL splitting runs slower than the native distributed WAL splitting because it is all inside the single upgrade process (so try and get a clean shutdown of the 0.94.0 cluster if you can).
|
||||
|
||||
To run the _execute_ step, make sure that first you have copied HBase 0.96.0 binaries everywhere under servers and under clients. Make sure the 0.94.0 cluster is down. Then do as follows:
|
||||
[source,bash]
|
||||
----
|
||||
$ bin/hbase upgrade -execute
|
||||
----
|
||||
Here is some sample output.
|
||||
|
||||
----
|
||||
Starting Namespace upgrade
|
||||
Created version file at hdfs://localhost:41020/myHBase with version=7
|
||||
Migrating table testTable to hdfs://localhost:41020/myHBase/.data/default/testTable
|
||||
.....
|
||||
Created version file at hdfs://localhost:41020/myHBase with version=8
|
||||
Successfully completed NameSpace upgrade.
|
||||
Starting Znode upgrade
|
||||
.....
|
||||
Successfully completed Znode upgrade
|
||||
|
||||
Starting Log splitting
|
||||
...
|
||||
Successfully completed Log splitting
|
||||
----
|
||||
|
||||
If the output from the execute step looks good, stop the zookeeper instance you started to do the upgrade:
|
||||
[source,bash]
|
||||
----
|
||||
$ ./hbase/bin/hbase-daemon.sh stop zookeeper
|
||||
----
|
||||
Now start up hbase-0.96.0.
|
||||
|
||||
[[s096.migration.troubleshooting]]
|
||||
=== Troubleshooting
|
||||
|
||||
[[s096.migration.troubleshooting.old.client]]
|
||||
.Old Client connecting to 0.96 cluster
|
||||
It will fail with an exception like the below. Upgrade.
|
||||
----
|
||||
17:22:15 Exception in thread "main" java.lang.IllegalArgumentException: Not a host:port pair: PBUF
|
||||
17:22:15 *
|
||||
17:22:15 api-compat-8.ent.cloudera.com <20><> <20><><EFBFBD>(
|
||||
17:22:15 at org.apache.hadoop.hbase.util.Addressing.parseHostname(Addressing.java:60)
|
||||
17:22:15 at org.apache.hadoop.hbase.ServerName.&init>(ServerName.java:101)
|
||||
17:22:15 at org.apache.hadoop.hbase.ServerName.parseVersionedServerName(ServerName.java:283)
|
||||
17:22:15 at org.apache.hadoop.hbase.MasterAddressTracker.bytesToServerName(MasterAddressTracker.java:77)
|
||||
17:22:15 at org.apache.hadoop.hbase.MasterAddressTracker.getMasterAddress(MasterAddressTracker.java:61)
|
||||
17:22:15 at org.apache.hadoop.hbase.client.HConnectionManager$HConnectionImplementation.getMaster(HConnectionManager.java:703)
|
||||
17:22:15 at org.apache.hadoop.hbase.client.HBaseAdmin.&init>(HBaseAdmin.java:126)
|
||||
17:22:15 at Client_4_3_0.setup(Client_4_3_0.java:716)
|
||||
17:22:15 at Client_4_3_0.main(Client_4_3_0.java:63)
|
||||
----
|
||||
|
||||
==== Upgrading `META` to use Protocol Buffers (Protobuf)
|
||||
|
||||
When you upgrade from versions prior to 0.96, `META` needs to be converted to use protocol buffers. This is controlled by the configuration option `hbase.MetaMigrationConvertingToPB`, which is set to `true` by default. Therefore, by default, no action is required on your part.
|
||||
|
||||
The migration is a one-time event. However, every time your cluster starts, `META` is scanned to ensure that it does not need to be converted. If you have a very large number of regions, this scan can take a long time. Starting in 0.98.5, you can set `hbase.MetaMigrationConvertingToPB` to `false` in _hbase-site.xml_, to disable this start-up scan. This should be considered an expert-level setting.
|
||||
|
||||
[[upgrade0.94]]
|
||||
=== Upgrading from 0.92.x to 0.94.x
|
||||
We used to think that 0.92 and 0.94 were interface compatible and that you can do a rolling upgrade between these versions but then we figured that link:https://issues.apache.org/jira/browse/HBASE-5357[HBASE-5357 Use builder pattern in HColumnDescriptor] changed method signatures so rather than return `void` they instead return `HColumnDescriptor`. This will throw`java.lang.NoSuchMethodError: org.apache.hadoop.hbase.HColumnDescriptor.setMaxVersions(I)V` so 0.92 and 0.94 are NOT compatible. You cannot do a rolling upgrade between them.
|
||||
|
||||
[[upgrade0.92]]
|
||||
=== Upgrading from 0.90.x to 0.92.x
|
||||
==== Upgrade Guide
|
||||
You will find that 0.92.0 runs a little differently to 0.90.x releases. Here are a few things to watch out for upgrading from 0.90.x to 0.92.0.
|
||||
|
||||
.tl:dr
|
||||
[NOTE]
|
||||
====
|
||||
These are the important things to know before upgrading.
|
||||
. Once you upgrade, you can’t go back.
|
||||
|
||||
. MSLAB is on by default. Watch that heap usage if you have a lot of regions.
|
||||
|
||||
. Distributed Log Splitting is on by default. It should make RegionServer failover faster.
|
||||
|
||||
. There’s a separate tarball for security.
|
||||
|
||||
. If `-XX:MaxDirectMemorySize` is set in your _hbase-env.sh_, it’s going to enable the experimental off-heap cache (You may not want this).
|
||||
====
|
||||
|
||||
.You can’t go back!
|
||||
To move to 0.92.0, all you need to do is shutdown your cluster, replace your HBase 0.90.x with HBase 0.92.0 binaries (be sure you clear out all 0.90.x instances) and restart (You cannot do a rolling restart from 0.90.x to 0.92.x -- you must restart). On startup, the `.META.` table content is rewritten removing the table schema from the `info:regioninfo` column. Also, any flushes done post first startup will write out data in the new 0.92.0 file format, <<hfilev2>>. This means you cannot go back to 0.90.x once you’ve started HBase 0.92.0 over your HBase data directory.
|
||||
|
||||
.MSLAB is ON by default
|
||||
In 0.92.0, the `<<hbase.hregion.memstore.mslab.enabled,hbase.hregion.memstore.mslab.enabled>>` flag is set to `true` (See <<gcpause>>). In 0.90.x it was false. When it is enabled, memstores will step allocate memory in MSLAB 2MB chunks even if the memstore has zero or just a few small elements. This is fine usually but if you had lots of regions per RegionServer in a 0.90.x cluster (and MSLAB was off), you may find yourself OOME'ing on upgrade because the `thousands of regions * number of column families * 2MB MSLAB` (at a minimum) puts your heap over the top. Set `hbase.hregion.memstore.mslab.enabled` to `false` or set the MSLAB size down from 2MB by setting `hbase.hregion.memstore.mslab.chunksize` to something less.
|
||||
|
||||
[[dls]]
|
||||
.Distributed Log Splitting is on by default
|
||||
Previous, WAL logs on crash were split by the Master alone. In 0.92.0, log splitting is done by the cluster (See link:https://issues.apache.org/jira/browse/hbase-1364[HBASE-1364 [performance\] Distributed splitting of regionserver commit logs] or see the blog post link:http://blog.cloudera.com/blog/2012/07/hbase-log-splitting/[Apache HBase Log Splitting]). This should cut down significantly on the amount of time it takes splitting logs and getting regions back online again.
|
||||
|
||||
.Memory accounting is different now
|
||||
In 0.92.0, <<hfilev2>> indices and bloom filters take up residence in the same LRU used caching blocks that come from the filesystem. In 0.90.x, the HFile v1 indices lived outside of the LRU so they took up space even if the index was on a ‘cold’ file, one that wasn’t being actively used. With the indices now in the LRU, you may find you have less space for block caching. Adjust your block cache accordingly. See the <<block.cache>> for more detail. The block size default size has been changed in 0.92.0 from 0.2 (20 percent of heap) to 0.25.
|
||||
|
||||
.On the Hadoop version to use
|
||||
Run 0.92.0 on Hadoop 1.0.x (or CDH3u3). The performance benefits are worth making the move. Otherwise, our Hadoop prescription is as it has been; you need an Hadoop that supports a working sync. See <<hadoop>>.
|
||||
|
||||
If running on Hadoop 1.0.x (or CDH3u3), enable local read. See link:http://files.meetup.com/1350427/hug_ebay_jdcryans.pdf[Practical Caching] presentation for ruminations on the performance benefits ‘going local’ (and for how to enable local reads).
|
||||
|
||||
.HBase 0.92.0 ships with ZooKeeper 3.4.2
|
||||
If you can, upgrade your ZooKeeper. If you can’t, 3.4.2 clients should work against 3.3.X ensembles (HBase makes use of 3.4.2 API).
|
||||
|
||||
.Online alter is off by default
|
||||
In 0.92.0, we’ve added an experimental online schema alter facility (See <<hbase.online.schema.update.enable,hbase.online.schema.update.enable>>). It's off by default. Enable it at your own risk. Online alter and splitting tables do not play well together so be sure your cluster quiescent using this feature (for now).
|
||||
|
||||
.WebUI
|
||||
The web UI has had a few additions made in 0.92.0. It now shows a list of the regions currently transitioning, recent compactions/flushes, and a process list of running processes (usually empty if all is well and requests are being handled promptly). Other additions including requests by region, a debugging servlet dump, etc.
|
||||
|
||||
.Security tarball
|
||||
We now ship with two tarballs; secure and insecure HBase. Documentation on how to setup a secure HBase is on the way.
|
||||
|
||||
.Changes in HBase replication
|
||||
0.92.0 adds two new features: multi-slave and multi-master replication. The way to enable this is the same as adding a new peer, so in order to have multi-master you would just run add_peer for each cluster that acts as a master to the other slave clusters. Collisions are handled at the timestamp level which may or may not be what you want, this needs to be evaluated on a per use case basis. Replication is still experimental in 0.92 and is disabled by default, run it at your own risk.
|
||||
|
||||
.RegionServer now aborts if OOME
|
||||
If an OOME, we now have the JVM kill -9 the RegionServer process so it goes down fast. Previous, a RegionServer might stick around after incurring an OOME limping along in some wounded state. To disable this facility, and recommend you leave it in place, you’d need to edit the bin/hbase file. Look for the addition of the -XX:OnOutOfMemoryError="kill -9 %p" arguments (See link:https://issues.apache.org/jira/browse/HBASE-4769[HBASE-4769 - ‘Abort RegionServer Immediately on OOME’]).
|
||||
|
||||
.HFile v2 and the “Bigger, Fewer” Tendency
|
||||
0.92.0 stores data in a new format, <<hfilev2>>. As HBase runs, it will move all your data from HFile v1 to HFile v2 format. This auto-migration will run in the background as flushes and compactions run. HFile v2 allows HBase run with larger regions/files. In fact, we encourage that all HBasers going forward tend toward Facebook axiom #1, run with larger, fewer regions. If you have lots of regions now -- more than 100s per host -- you should look into setting your region size up after you move to 0.92.0 (In 0.92.0, default size is now 1G, up from 256M), and then running online merge tool (See link:https://issues.apache.org/jira/browse/HBASE-1621[HBASE-1621 merge tool should work on online cluster, but disabled table]).
|
||||
|
||||
[[upgrade0.90]]
|
||||
=== Upgrading to HBase 0.90.x from 0.20.x or 0.89.x
|
||||
This version of 0.90.x HBase can be started on data written by HBase 0.20.x or HBase 0.89.x. There is no need of a migration step. HBase 0.89.x and 0.90.x does write out the name of region directories differently -- it names them with a md5 hash of the region name rather than a jenkins hash -- so this means that once started, there is no going back to HBase 0.20.x.
|
||||
|
||||
Be sure to remove the _hbase-default.xml_ from your _conf_ directory on upgrade. A 0.20.x version of this file will have sub-optimal configurations for 0.90.x HBase. The _hbase-default.xml_ file is now bundled into the HBase jar and read from there. If you would like to review the content of this file, see it in the src tree at _src/main/resources/hbase-default.xml_ or see <<hbase_default_configurations>>.
|
||||
|
||||
Finally, if upgrading from 0.20.x, check your .META. schema in the shell. In the past we would recommend that users run with a 16kb MEMSTORE_FLUSHSIZE. Run
|
||||
----
|
||||
hbase> scan '-ROOT-'
|
||||
----
|
||||
in the shell. This will output the current `.META.` schema. Check `MEMSTORE_FLUSHSIZE` size. Is it 16kb (16384)? If so, you will need to change this (The 'normal'/default value is 64MB (67108864)). Run the script `bin/set_meta_memstore_size.rb`. This will make the necessary edit to your `.META.` schema. Failure to run this change will make for a slow cluster. See link:https://issues.apache.org/jira/browse/HBASE-3499[HBASE-3499 Users upgrading to 0.90.0 need to have their .META. table updated with the right MEMSTORE_SIZE].
|
||||
|
|
@ -0,0 +1,42 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[appendix]
|
||||
== YCSB
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
link:https://github.com/brianfrankcooper/YCSB/[YCSB: The
|
||||
Yahoo! Cloud Serving Benchmark] and HBase
|
||||
|
||||
TODO: Describe how YCSB is poor for putting up a decent cluster load.
|
||||
|
||||
TODO: Describe setup of YCSB for HBase.
|
||||
In particular, presplit your tables before you start a run.
|
||||
See link:https://issues.apache.org/jira/browse/HBASE-4163[HBASE-4163 Create Split Strategy for YCSB Benchmark] for why and a little shell command for how to do it.
|
||||
|
||||
Ted Dunning redid YCSB so it's mavenized and added facility for verifying workloads.
|
||||
See link:https://github.com/tdunning/YCSB[Ted Dunning's YCSB].
|
||||
|
||||
:numbered:
|
||||
|
|
@ -0,0 +1,451 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
[[zookeeper]]
|
||||
= ZooKeeper(((ZooKeeper)))
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
A distributed Apache HBase installation depends on a running ZooKeeper cluster.
|
||||
All participating nodes and clients need to be able to access the running ZooKeeper ensemble.
|
||||
Apache HBase by default manages a ZooKeeper "cluster" for you.
|
||||
It will start and stop the ZooKeeper ensemble as part of the HBase start/stop process.
|
||||
You can also manage the ZooKeeper ensemble independent of HBase and just point HBase at the cluster it should use.
|
||||
To toggle HBase management of ZooKeeper, use the `HBASE_MANAGES_ZK` variable in _conf/hbase-env.sh_.
|
||||
This variable, which defaults to `true`, tells HBase whether to start/stop the ZooKeeper ensemble servers as part of HBase start/stop.
|
||||
|
||||
When HBase manages the ZooKeeper ensemble, you can specify ZooKeeper configuration using its native _zoo.cfg_ file, or, the easier option is to just specify ZooKeeper options directly in _conf/hbase-site.xml_.
|
||||
A ZooKeeper configuration option can be set as a property in the HBase _hbase-site.xml_ XML configuration file by prefacing the ZooKeeper option name with `hbase.zookeeper.property`.
|
||||
For example, the `clientPort` setting in ZooKeeper can be changed by setting the `hbase.zookeeper.property.clientPort` property.
|
||||
For all default values used by HBase, including ZooKeeper configuration, see <<hbase_default_configurations,hbase default configurations>>.
|
||||
Look for the `hbase.zookeeper.property` prefix.
|
||||
For the full list of ZooKeeper configurations, see ZooKeeper's _zoo.cfg_.
|
||||
HBase does not ship with a _zoo.cfg_ so you will need to browse the _conf_ directory in an appropriate ZooKeeper download.
|
||||
|
||||
You must at least list the ensemble servers in _hbase-site.xml_ using the `hbase.zookeeper.quorum` property.
|
||||
This property defaults to a single ensemble member at `localhost` which is not suitable for a fully distributed HBase.
|
||||
(It binds to the local machine only and remote clients will not be able to connect).
|
||||
|
||||
.How many ZooKeepers should I run?
|
||||
[NOTE]
|
||||
====
|
||||
You can run a ZooKeeper ensemble that comprises 1 node only but in production it is recommended that you run a ZooKeeper ensemble of 3, 5 or 7 machines; the more members an ensemble has, the more tolerant the ensemble is of host failures.
|
||||
Also, run an odd number of machines.
|
||||
In ZooKeeper, an even number of peers is supported, but it is normally not used because an even sized ensemble requires, proportionally, more peers to form a quorum than an odd sized ensemble requires.
|
||||
For example, an ensemble with 4 peers requires 3 to form a quorum, while an ensemble with 5 also requires 3 to form a quorum.
|
||||
Thus, an ensemble of 5 allows 2 peers to fail, and thus is more fault tolerant than the ensemble of 4, which allows only 1 down peer.
|
||||
|
||||
Give each ZooKeeper server around 1GB of RAM, and if possible, its own dedicated disk (A dedicated disk is the best thing you can do to ensure a performant ZooKeeper ensemble). For very heavily loaded clusters, run ZooKeeper servers on separate machines from RegionServers (DataNodes and TaskTrackers).
|
||||
====
|
||||
|
||||
For example, to have HBase manage a ZooKeeper quorum on nodes _rs{1,2,3,4,5}.example.com_, bound to port 2222 (the default is 2181) ensure `HBASE_MANAGE_ZK` is commented out or set to `true` in _conf/hbase-env.sh_ and then edit _conf/hbase-site.xml_ and set `hbase.zookeeper.property.clientPort` and `hbase.zookeeper.quorum`.
|
||||
You should also set `hbase.zookeeper.property.dataDir` to other than the default as the default has ZooKeeper persist data under _/tmp_ which is often cleared on system restart.
|
||||
In the example below we have ZooKeeper persist to _/user/local/zookeeper_.
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
<configuration>
|
||||
...
|
||||
<property>
|
||||
<name>hbase.zookeeper.property.clientPort</name>
|
||||
<value>2222</value>
|
||||
<description>Property from ZooKeeper's config zoo.cfg.
|
||||
The port at which the clients will connect.
|
||||
</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zookeeper.quorum</name>
|
||||
<value>rs1.example.com,rs2.example.com,rs3.example.com,rs4.example.com,rs5.example.com</value>
|
||||
<description>Comma separated list of servers in the ZooKeeper Quorum.
|
||||
For example, "host1.mydomain.com,host2.mydomain.com,host3.mydomain.com".
|
||||
By default this is set to localhost for local and pseudo-distributed modes
|
||||
of operation. For a fully-distributed setup, this should be set to a full
|
||||
list of ZooKeeper quorum servers. If HBASE_MANAGES_ZK is set in hbase-env.sh
|
||||
this is the list of servers which we will start/stop ZooKeeper on.
|
||||
</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zookeeper.property.dataDir</name>
|
||||
<value>/usr/local/zookeeper</value>
|
||||
<description>Property from ZooKeeper's config zoo.cfg.
|
||||
The directory where the snapshot is stored.
|
||||
</description>
|
||||
</property>
|
||||
...
|
||||
</configuration>
|
||||
----
|
||||
|
||||
.What verion of ZooKeeper should I use?
|
||||
[CAUTION]
|
||||
====
|
||||
The newer version, the better.
|
||||
For example, some folks have been bitten by link:https://issues.apache.org/jira/browse/ZOOKEEPER-1277[ZOOKEEPER-1277].
|
||||
If running zookeeper 3.5+, you can ask hbase to make use of the new multi operation by enabling <<hbase.zookeeper.usemulti,hbase.zookeeper.useMulti>>" in your _hbase-site.xml_.
|
||||
====
|
||||
|
||||
.ZooKeeper Maintenance
|
||||
[CAUTION]
|
||||
====
|
||||
Be sure to set up the data dir cleaner described under link:http://zookeeper.apache.org/doc/r3.1.2/zookeeperAdmin.html#sc_maintenance[Zookeeper
|
||||
Maintenance] else you could have 'interesting' problems a couple of months in; i.e.
|
||||
zookeeper could start dropping sessions if it has to run through a directory of hundreds of thousands of logs which is wont to do around leader reelection time -- a process rare but run on occasion whether because a machine is dropped or happens to hiccup.
|
||||
====
|
||||
|
||||
== Using existing ZooKeeper ensemble
|
||||
|
||||
To point HBase at an existing ZooKeeper cluster, one that is not managed by HBase, set `HBASE_MANAGES_ZK` in _conf/hbase-env.sh_ to false
|
||||
|
||||
----
|
||||
|
||||
...
|
||||
# Tell HBase whether it should manage its own instance of Zookeeper or not.
|
||||
export HBASE_MANAGES_ZK=false
|
||||
----
|
||||
|
||||
Next set ensemble locations and client port, if non-standard, in _hbase-site.xml_, or add a suitably configured _zoo.cfg_ to HBase's _CLASSPATH_.
|
||||
HBase will prefer the configuration found in _zoo.cfg_ over any settings in _hbase-site.xml_.
|
||||
|
||||
When HBase manages ZooKeeper, it will start/stop the ZooKeeper servers as a part of the regular start/stop scripts.
|
||||
If you would like to run ZooKeeper yourself, independent of HBase start/stop, you would do the following
|
||||
|
||||
----
|
||||
|
||||
${HBASE_HOME}/bin/hbase-daemons.sh {start,stop} zookeeper
|
||||
----
|
||||
|
||||
Note that you can use HBase in this manner to spin up a ZooKeeper cluster, unrelated to HBase.
|
||||
Just make sure to set `HBASE_MANAGES_ZK` to `false` if you want it to stay up across HBase restarts so that when HBase shuts down, it doesn't take ZooKeeper down with it.
|
||||
|
||||
For more information about running a distinct ZooKeeper cluster, see the ZooKeeper link:http://hadoop.apache.org/zookeeper/docs/current/zookeeperStarted.html[Getting
|
||||
Started Guide].
|
||||
Additionally, see the link:http://wiki.apache.org/hadoop/ZooKeeper/FAQ#A7[ZooKeeper Wiki] or the link:http://zookeeper.apache.org/doc/r3.3.3/zookeeperAdmin.html#sc_zkMulitServerSetup[ZooKeeper
|
||||
documentation] for more information on ZooKeeper sizing.
|
||||
|
||||
[[zk.sasl.auth]]
|
||||
== SASL Authentication with ZooKeeper
|
||||
|
||||
Newer releases of Apache HBase (>= 0.92) will support connecting to a ZooKeeper Quorum that supports SASL authentication (which is available in Zookeeper versions 3.4.0 or later).
|
||||
|
||||
This describes how to set up HBase to mutually authenticate with a ZooKeeper Quorum.
|
||||
ZooKeeper/HBase mutual authentication (link:https://issues.apache.org/jira/browse/HBASE-2418[HBASE-2418]) is required as part of a complete secure HBase configuration (link:https://issues.apache.org/jira/browse/HBASE-3025[HBASE-3025]). For simplicity of explication, this section ignores additional configuration required (Secure HDFS and Coprocessor configuration). It's recommended to begin with an HBase-managed Zookeeper configuration (as opposed to a standalone Zookeeper quorum) for ease of learning.
|
||||
|
||||
=== Operating System Prerequisites
|
||||
|
||||
You need to have a working Kerberos KDC setup.
|
||||
For each `$HOST` that will run a ZooKeeper server, you should have a principle `zookeeper/$HOST`.
|
||||
For each such host, add a service key (using the `kadmin` or `kadmin.local` tool's `ktadd` command) for `zookeeper/$HOST` and copy this file to `$HOST`, and make it readable only to the user that will run zookeeper on `$HOST`.
|
||||
Note the location of this file, which we will use below as _$PATH_TO_ZOOKEEPER_KEYTAB_.
|
||||
|
||||
Similarly, for each `$HOST` that will run an HBase server (master or regionserver), you should have a principle: `hbase/$HOST`.
|
||||
For each host, add a keytab file called _hbase.keytab_ containing a service key for `hbase/$HOST`, copy this file to `$HOST`, and make it readable only to the user that will run an HBase service on `$HOST`.
|
||||
Note the location of this file, which we will use below as _$PATH_TO_HBASE_KEYTAB_.
|
||||
|
||||
Each user who will be an HBase client should also be given a Kerberos principal.
|
||||
This principal should usually have a password assigned to it (as opposed to, as with the HBase servers, a keytab file) which only this user knows.
|
||||
The client's principal's `maxrenewlife` should be set so that it can be renewed enough so that the user can complete their HBase client processes.
|
||||
For example, if a user runs a long-running HBase client process that takes at most 3 days, we might create this user's principal within `kadmin` with: `addprinc -maxrenewlife 3days`.
|
||||
The Zookeeper client and server libraries manage their own ticket refreshment by running threads that wake up periodically to do the refreshment.
|
||||
|
||||
On each host that will run an HBase client (e.g. `hbase shell`), add the following file to the HBase home directory's _conf_ directory:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
Client {
|
||||
com.sun.security.auth.module.Krb5LoginModule required
|
||||
useKeyTab=false
|
||||
useTicketCache=true;
|
||||
};
|
||||
----
|
||||
|
||||
We'll refer to this JAAS configuration file as _$CLIENT_CONF_ below.
|
||||
|
||||
=== HBase-managed Zookeeper Configuration
|
||||
|
||||
On each node that will run a zookeeper, a master, or a regionserver, create a link:http://docs.oracle.com/javase/1.4.2/docs/guide/security/jgss/tutorials/LoginConfigFile.html[JAAS] configuration file in the conf directory of the node's _HBASE_HOME_ directory that looks like the following:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
Server {
|
||||
com.sun.security.auth.module.Krb5LoginModule required
|
||||
useKeyTab=true
|
||||
keyTab="$PATH_TO_ZOOKEEPER_KEYTAB"
|
||||
storeKey=true
|
||||
useTicketCache=false
|
||||
principal="zookeeper/$HOST";
|
||||
};
|
||||
Client {
|
||||
com.sun.security.auth.module.Krb5LoginModule required
|
||||
useKeyTab=true
|
||||
useTicketCache=false
|
||||
keyTab="$PATH_TO_HBASE_KEYTAB"
|
||||
principal="hbase/$HOST";
|
||||
};
|
||||
----
|
||||
|
||||
where the _$PATH_TO_HBASE_KEYTAB_ and _$PATH_TO_ZOOKEEPER_KEYTAB_ files are what you created above, and `$HOST` is the hostname for that node.
|
||||
|
||||
The `Server` section will be used by the Zookeeper quorum server, while the `Client` section will be used by the HBase master and regionservers.
|
||||
The path to this file should be substituted for the text _$HBASE_SERVER_CONF_ in the _hbase-env.sh_ listing below.
|
||||
|
||||
The path to this file should be substituted for the text _$CLIENT_CONF_ in the _hbase-env.sh_ listing below.
|
||||
|
||||
Modify your _hbase-env.sh_ to include the following:
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
export HBASE_OPTS="-Djava.security.auth.login.config=$CLIENT_CONF"
|
||||
export HBASE_MANAGES_ZK=true
|
||||
export HBASE_ZOOKEEPER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
|
||||
export HBASE_MASTER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
|
||||
export HBASE_REGIONSERVER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
|
||||
----
|
||||
|
||||
where _$HBASE_SERVER_CONF_ and _$CLIENT_CONF_ are the full paths to the JAAS configuration files created above.
|
||||
|
||||
Modify your _hbase-site.xml_ on each node that will run zookeeper, master or regionserver to contain:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
<configuration>
|
||||
<property>
|
||||
<name>hbase.zookeeper.quorum</name>
|
||||
<value>$ZK_NODES</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.cluster.distributed</name>
|
||||
<value>true</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zookeeper.property.authProvider.1</name>
|
||||
<value>org.apache.zookeeper.server.auth.SASLAuthenticationProvider</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zookeeper.property.kerberos.removeHostFromPrincipal</name>
|
||||
<value>true</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.zookeeper.property.kerberos.removeRealmFromPrincipal</name>
|
||||
<value>true</value>
|
||||
</property>
|
||||
</configuration>
|
||||
----
|
||||
|
||||
where `$ZK_NODES` is the comma-separated list of hostnames of the Zookeeper Quorum hosts.
|
||||
|
||||
Start your hbase cluster by running one or more of the following set of commands on the appropriate hosts:
|
||||
|
||||
----
|
||||
|
||||
bin/hbase zookeeper start
|
||||
bin/hbase master start
|
||||
bin/hbase regionserver start
|
||||
----
|
||||
|
||||
=== External Zookeeper Configuration
|
||||
|
||||
Add a JAAS configuration file that looks like:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
Client {
|
||||
com.sun.security.auth.module.Krb5LoginModule required
|
||||
useKeyTab=true
|
||||
useTicketCache=false
|
||||
keyTab="$PATH_TO_HBASE_KEYTAB"
|
||||
principal="hbase/$HOST";
|
||||
};
|
||||
----
|
||||
|
||||
where the _$PATH_TO_HBASE_KEYTAB_ is the keytab created above for HBase services to run on this host, and `$HOST` is the hostname for that node.
|
||||
Put this in the HBase home's configuration directory.
|
||||
We'll refer to this file's full pathname as _$HBASE_SERVER_CONF_ below.
|
||||
|
||||
Modify your hbase-env.sh to include the following:
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
export HBASE_OPTS="-Djava.security.auth.login.config=$CLIENT_CONF"
|
||||
export HBASE_MANAGES_ZK=false
|
||||
export HBASE_MASTER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
|
||||
export HBASE_REGIONSERVER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
|
||||
----
|
||||
|
||||
Modify your _hbase-site.xml_ on each node that will run a master or regionserver to contain:
|
||||
|
||||
[source,xml]
|
||||
----
|
||||
|
||||
<configuration>
|
||||
<property>
|
||||
<name>hbase.zookeeper.quorum</name>
|
||||
<value>$ZK_NODES</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>hbase.cluster.distributed</name>
|
||||
<value>true</value>
|
||||
</property>
|
||||
</configuration>
|
||||
----
|
||||
|
||||
where `$ZK_NODES` is the comma-separated list of hostnames of the Zookeeper Quorum hosts.
|
||||
|
||||
Add a _zoo.cfg_ for each Zookeeper Quorum host containing:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
authProvider.1=org.apache.zookeeper.server.auth.SASLAuthenticationProvider
|
||||
kerberos.removeHostFromPrincipal=true
|
||||
kerberos.removeRealmFromPrincipal=true
|
||||
----
|
||||
|
||||
Also on each of these hosts, create a JAAS configuration file containing:
|
||||
|
||||
[source,java]
|
||||
----
|
||||
|
||||
Server {
|
||||
com.sun.security.auth.module.Krb5LoginModule required
|
||||
useKeyTab=true
|
||||
keyTab="$PATH_TO_ZOOKEEPER_KEYTAB"
|
||||
storeKey=true
|
||||
useTicketCache=false
|
||||
principal="zookeeper/$HOST";
|
||||
};
|
||||
----
|
||||
|
||||
where `$HOST` is the hostname of each Quorum host.
|
||||
We will refer to the full pathname of this file as _$ZK_SERVER_CONF_ below.
|
||||
|
||||
Start your Zookeepers on each Zookeeper Quorum host with:
|
||||
|
||||
[source,bourne]
|
||||
----
|
||||
|
||||
SERVER_JVMFLAGS="-Djava.security.auth.login.config=$ZK_SERVER_CONF" bin/zkServer start
|
||||
----
|
||||
|
||||
Start your HBase cluster by running one or more of the following set of commands on the appropriate nodes:
|
||||
|
||||
----
|
||||
|
||||
bin/hbase master start
|
||||
bin/hbase regionserver start
|
||||
----
|
||||
|
||||
=== Zookeeper Server Authentication Log Output
|
||||
|
||||
If the configuration above is successful, you should see something similar to the following in your Zookeeper server logs:
|
||||
|
||||
----
|
||||
|
||||
11/12/05 22:43:39 INFO zookeeper.Login: successfully logged in.
|
||||
11/12/05 22:43:39 INFO server.NIOServerCnxnFactory: binding to port 0.0.0.0/0.0.0.0:2181
|
||||
11/12/05 22:43:39 INFO zookeeper.Login: TGT refresh thread started.
|
||||
11/12/05 22:43:39 INFO zookeeper.Login: TGT valid starting at: Mon Dec 05 22:43:39 UTC 2011
|
||||
11/12/05 22:43:39 INFO zookeeper.Login: TGT expires: Tue Dec 06 22:43:39 UTC 2011
|
||||
11/12/05 22:43:39 INFO zookeeper.Login: TGT refresh sleeping until: Tue Dec 06 18:36:42 UTC 2011
|
||||
..
|
||||
11/12/05 22:43:59 INFO auth.SaslServerCallbackHandler:
|
||||
Successfully authenticated client: authenticationID=hbase/ip-10-166-175-249.us-west-1.compute.internal@HADOOP.LOCALDOMAIN;
|
||||
authorizationID=hbase/ip-10-166-175-249.us-west-1.compute.internal@HADOOP.LOCALDOMAIN.
|
||||
11/12/05 22:43:59 INFO auth.SaslServerCallbackHandler: Setting authorizedID: hbase
|
||||
11/12/05 22:43:59 INFO server.ZooKeeperServer: adding SASL authorization for authorizationID: hbase
|
||||
----
|
||||
|
||||
=== Zookeeper Client Authentication Log Output
|
||||
|
||||
On the Zookeeper client side (HBase master or regionserver), you should see something similar to the following:
|
||||
|
||||
----
|
||||
|
||||
11/12/05 22:43:59 INFO zookeeper.ZooKeeper: Initiating client connection, connectString=ip-10-166-175-249.us-west-1.compute.internal:2181 sessionTimeout=180000 watcher=master:60000
|
||||
11/12/05 22:43:59 INFO zookeeper.ClientCnxn: Opening socket connection to server /10.166.175.249:2181
|
||||
11/12/05 22:43:59 INFO zookeeper.RecoverableZooKeeper: The identifier of this process is 14851@ip-10-166-175-249
|
||||
11/12/05 22:43:59 INFO zookeeper.Login: successfully logged in.
|
||||
11/12/05 22:43:59 INFO client.ZooKeeperSaslClient: Client will use GSSAPI as SASL mechanism.
|
||||
11/12/05 22:43:59 INFO zookeeper.Login: TGT refresh thread started.
|
||||
11/12/05 22:43:59 INFO zookeeper.ClientCnxn: Socket connection established to ip-10-166-175-249.us-west-1.compute.internal/10.166.175.249:2181, initiating session
|
||||
11/12/05 22:43:59 INFO zookeeper.Login: TGT valid starting at: Mon Dec 05 22:43:59 UTC 2011
|
||||
11/12/05 22:43:59 INFO zookeeper.Login: TGT expires: Tue Dec 06 22:43:59 UTC 2011
|
||||
11/12/05 22:43:59 INFO zookeeper.Login: TGT refresh sleeping until: Tue Dec 06 18:30:37 UTC 2011
|
||||
11/12/05 22:43:59 INFO zookeeper.ClientCnxn: Session establishment complete on server ip-10-166-175-249.us-west-1.compute.internal/10.166.175.249:2181, sessionid = 0x134106594320000, negotiated timeout = 180000
|
||||
----
|
||||
|
||||
=== Configuration from Scratch
|
||||
|
||||
This has been tested on the current standard Amazon Linux AMI.
|
||||
First setup KDC and principals as described above.
|
||||
Next checkout code and run a sanity check.
|
||||
|
||||
----
|
||||
|
||||
git clone git://git.apache.org/hbase.git
|
||||
cd hbase
|
||||
mvn clean test -Dtest=TestZooKeeperACL
|
||||
----
|
||||
|
||||
Then configure HBase as described above.
|
||||
Manually edit target/cached_classpath.txt (see below):
|
||||
|
||||
----
|
||||
|
||||
bin/hbase zookeeper &
|
||||
bin/hbase master &
|
||||
bin/hbase regionserver &
|
||||
----
|
||||
|
||||
=== Future improvements
|
||||
|
||||
==== Fix target/cached_classpath.txt
|
||||
|
||||
You must override the standard hadoop-core jar file from the `target/cached_classpath.txt` file with the version containing the HADOOP-7070 fix.
|
||||
You can use the following script to do this:
|
||||
|
||||
----
|
||||
|
||||
echo `find ~/.m2 -name "*hadoop-core*7070*SNAPSHOT.jar"` ':' `cat target/cached_classpath.txt` | sed 's/ //g' > target/tmp.txt
|
||||
mv target/tmp.txt target/cached_classpath.txt
|
||||
----
|
||||
|
||||
==== Set JAAS configuration programmatically
|
||||
|
||||
This would avoid the need for a separate Hadoop jar that fixes link:https://issues.apache.org/jira/browse/HADOOP-7070[HADOOP-7070].
|
||||
|
||||
==== Elimination of `kerberos.removeHostFromPrincipal` and`kerberos.removeRealmFromPrincipal`
|
||||
|
||||
|
||||
|
||||
ifdef::backend-docbook[]
|
||||
[index]
|
||||
= Index
|
||||
// Generated automatically by the DocBook toolchain.
|
||||
endif::backend-docbook[]
|
||||
|
|
@ -0,0 +1,399 @@
|
|||
/* Asciidoctor default stylesheet | MIT License | http://asciidoctor.org */
|
||||
/* Remove the comments around the @import statement below when using this as a custom stylesheet */
|
||||
/*@import "https://fonts.googleapis.com/css?family=Open+Sans:300,300italic,400,400italic,600,600italic%7CNoto+Serif:400,400italic,700,700italic%7CDroid+Sans+Mono:400";*/
|
||||
article,aside,details,figcaption,figure,footer,header,hgroup,main,nav,section,summary{display:block}
|
||||
audio,canvas,video{display:inline-block}
|
||||
audio:not([controls]){display:none;height:0}
|
||||
[hidden],template{display:none}
|
||||
script{display:none!important}
|
||||
html{font-family:sans-serif;-ms-text-size-adjust:100%;-webkit-text-size-adjust:100%}
|
||||
body{margin:0}
|
||||
a{background:transparent}
|
||||
a:focus{outline:thin dotted}
|
||||
a:active,a:hover{outline:0}
|
||||
h1{font-size:2em;margin:.67em 0}
|
||||
abbr[title]{border-bottom:1px dotted}
|
||||
b,strong{font-weight:bold}
|
||||
dfn{font-style:italic}
|
||||
hr{-moz-box-sizing:content-box;box-sizing:content-box;height:0}
|
||||
mark{background:#ff0;color:#000}
|
||||
code,kbd,pre,samp{font-family:monospace;font-size:1em}
|
||||
pre{white-space:pre-wrap}
|
||||
q{quotes:"\201C" "\201D" "\2018" "\2019"}
|
||||
small{font-size:80%}
|
||||
sub,sup{font-size:75%;line-height:0;position:relative;vertical-align:baseline}
|
||||
sup{top:-.5em}
|
||||
sub{bottom:-.25em}
|
||||
img{border:0}
|
||||
svg:not(:root){overflow:hidden}
|
||||
figure{margin:0}
|
||||
fieldset{border:1px solid silver;margin:0 2px;padding:.35em .625em .75em}
|
||||
legend{border:0;padding:0}
|
||||
button,input,select,textarea{font-family:inherit;font-size:100%;margin:0}
|
||||
button,input{line-height:normal}
|
||||
button,select{text-transform:none}
|
||||
button,html input[type="button"],input[type="reset"],input[type="submit"]{-webkit-appearance:button;cursor:pointer}
|
||||
button[disabled],html input[disabled]{cursor:default}
|
||||
input[type="checkbox"],input[type="radio"]{box-sizing:border-box;padding:0}
|
||||
input[type="search"]{-webkit-appearance:textfield;-moz-box-sizing:content-box;-webkit-box-sizing:content-box;box-sizing:content-box}
|
||||
input[type="search"]::-webkit-search-cancel-button,input[type="search"]::-webkit-search-decoration{-webkit-appearance:none}
|
||||
button::-moz-focus-inner,input::-moz-focus-inner{border:0;padding:0}
|
||||
textarea{overflow:auto;vertical-align:top}
|
||||
table{border-collapse:collapse;border-spacing:0}
|
||||
*,*:before,*:after{-moz-box-sizing:border-box;-webkit-box-sizing:border-box;box-sizing:border-box}
|
||||
html,body{font-size:100%}
|
||||
body{background:#fff;color:rgba(0,0,0,.8);padding:0;margin:0;font-family:"Noto Serif","DejaVu Serif",serif;font-weight:400;font-style:normal;line-height:1;position:relative;cursor:auto}
|
||||
a:hover{cursor:pointer}
|
||||
img,object,embed{max-width:100%;height:auto}
|
||||
object,embed{height:100%}
|
||||
img{-ms-interpolation-mode:bicubic}
|
||||
#map_canvas img,#map_canvas embed,#map_canvas object,.map_canvas img,.map_canvas embed,.map_canvas object{max-width:none!important}
|
||||
.left{float:left!important}
|
||||
.right{float:right!important}
|
||||
.text-left{text-align:left!important}
|
||||
.text-right{text-align:right!important}
|
||||
.text-center{text-align:center!important}
|
||||
.text-justify{text-align:justify!important}
|
||||
.hide{display:none}
|
||||
.antialiased,body{-webkit-font-smoothing:antialiased}
|
||||
img{display:inline-block;vertical-align:middle}
|
||||
textarea{height:auto;min-height:50px}
|
||||
select{width:100%}
|
||||
p.lead,.paragraph.lead>p,#preamble>.sectionbody>.paragraph:first-of-type p{font-size:1.21875em;line-height:1.6}
|
||||
.subheader,.admonitionblock td.content>.title,.audioblock>.title,.exampleblock>.title,.imageblock>.title,.listingblock>.title,.literalblock>.title,.stemblock>.title,.openblock>.title,.paragraph>.title,.quoteblock>.title,table.tableblock>.title,.verseblock>.title,.videoblock>.title,.dlist>.title,.olist>.title,.ulist>.title,.qlist>.title,.hdlist>.title{line-height:1.45;color:#7a2518;font-weight:400;margin-top:0;margin-bottom:.25em}
|
||||
div,dl,dt,dd,ul,ol,li,h1,h2,h3,#toctitle,.sidebarblock>.content>.title,h4,h5,h6,pre,form,p,blockquote,th,td{margin:0;padding:0;direction:ltr}
|
||||
a{color:#2156a5;text-decoration:underline;line-height:inherit}
|
||||
a:hover,a:focus{color:#1d4b8f}
|
||||
a img{border:none}
|
||||
p{font-family:inherit;font-weight:400;font-size:1em;line-height:1.6;margin-bottom:1.25em;text-rendering:optimizeLegibility}
|
||||
p aside{font-size:.875em;line-height:1.35;font-style:italic}
|
||||
h1,h2,h3,#toctitle,.sidebarblock>.content>.title,h4,h5,h6{font-family:"Open Sans","DejaVu Sans",sans-serif;font-weight:300;font-style:normal;color:#ba3925;text-rendering:optimizeLegibility;margin-top:1em;margin-bottom:.5em;line-height:1.0125em}
|
||||
h1 small,h2 small,h3 small,#toctitle small,.sidebarblock>.content>.title small,h4 small,h5 small,h6 small{font-size:60%;color:#e99b8f;line-height:0}
|
||||
h1{font-size:2.125em}
|
||||
h2{font-size:1.6875em}
|
||||
h3,#toctitle,.sidebarblock>.content>.title{font-size:1.375em}
|
||||
h4,h5{font-size:1.125em}
|
||||
h6{font-size:1em}
|
||||
hr{border:solid #ddddd8;border-width:1px 0 0;clear:both;margin:1.25em 0 1.1875em;height:0}
|
||||
em,i{font-style:italic;line-height:inherit}
|
||||
strong,b{font-weight:bold;line-height:inherit}
|
||||
small{font-size:60%;line-height:inherit}
|
||||
code{font-family:"Droid Sans Mono","DejaVu Sans Mono",monospace;font-weight:400;color:rgba(0,0,0,.9)}
|
||||
ul,ol,dl{font-size:1em;line-height:1.6;margin-bottom:1.25em;list-style-position:outside;font-family:inherit}
|
||||
ul,ol,ul.no-bullet,ol.no-bullet{margin-left:1.5em}
|
||||
ul li ul,ul li ol{margin-left:1.25em;margin-bottom:0;font-size:1em}
|
||||
ul.square li ul,ul.circle li ul,ul.disc li ul{list-style:inherit}
|
||||
ul.square{list-style-type:square}
|
||||
ul.circle{list-style-type:circle}
|
||||
ul.disc{list-style-type:disc}
|
||||
ul.no-bullet{list-style:none}
|
||||
ol li ul,ol li ol{margin-left:1.25em;margin-bottom:0}
|
||||
dl dt{margin-bottom:.3125em;font-weight:bold}
|
||||
dl dd{margin-bottom:1.25em}
|
||||
abbr,acronym{text-transform:uppercase;font-size:90%;color:rgba(0,0,0,.8);border-bottom:1px dotted #ddd;cursor:help}
|
||||
abbr{text-transform:none}
|
||||
blockquote{margin:0 0 1.25em;padding:.5625em 1.25em 0 1.1875em;border-left:1px solid #ddd}
|
||||
blockquote cite{display:block;font-size:.9375em;color:rgba(0,0,0,.6)}
|
||||
blockquote cite:before{content:"\2014 \0020"}
|
||||
blockquote cite a,blockquote cite a:visited{color:rgba(0,0,0,.6)}
|
||||
blockquote,blockquote p{line-height:1.6;color:rgba(0,0,0,.85)}
|
||||
@media only screen and (min-width:768px){h1,h2,h3,#toctitle,.sidebarblock>.content>.title,h4,h5,h6{line-height:1.2}
|
||||
h1{font-size:2.75em}
|
||||
h2{font-size:2.3125em}
|
||||
h3,#toctitle,.sidebarblock>.content>.title{font-size:1.6875em}
|
||||
h4{font-size:1.4375em}}table{background:#fff;margin-bottom:1.25em;border:solid 1px #dedede}
|
||||
table thead,table tfoot{background:#f7f8f7;font-weight:bold}
|
||||
table thead tr th,table thead tr td,table tfoot tr th,table tfoot tr td{padding:.5em .625em .625em;font-size:inherit;color:rgba(0,0,0,.8);text-align:left}
|
||||
table tr th,table tr td{padding:.5625em .625em;font-size:inherit;color:rgba(0,0,0,.8)}
|
||||
table tr.even,table tr.alt,table tr:nth-of-type(even){background:#f8f8f7}
|
||||
table thead tr th,table tfoot tr th,table tbody tr td,table tr td,table tfoot tr td{display:table-cell;line-height:1.6}
|
||||
h1,h2,h3,#toctitle,.sidebarblock>.content>.title,h4,h5,h6{line-height:1.2;word-spacing:-.05em}
|
||||
h1 strong,h2 strong,h3 strong,#toctitle strong,.sidebarblock>.content>.title strong,h4 strong,h5 strong,h6 strong{font-weight:400}
|
||||
.clearfix:before,.clearfix:after,.float-group:before,.float-group:after{content:" ";display:table}
|
||||
.clearfix:after,.float-group:after{clear:both}
|
||||
*:not(pre)>code{font-size:.9375em;font-style:normal!important;letter-spacing:0;padding:.1em .5ex;word-spacing:-.15em;background-color:#f7f7f8;-webkit-border-radius:4px;border-radius:4px;line-height:1.45;text-rendering:optimizeSpeed}
|
||||
pre,pre>code{line-height:1.45;color:rgba(0,0,0,.9);font-family:"Droid Sans Mono","DejaVu Sans Mono",monospace;font-weight:400;text-rendering:optimizeSpeed}
|
||||
.keyseq{color:rgba(51,51,51,.8)}
|
||||
kbd{display:inline-block;color:rgba(0,0,0,.8);font-size:.75em;line-height:1.4;background-color:#f7f7f7;border:1px solid #ccc;-webkit-border-radius:3px;border-radius:3px;-webkit-box-shadow:0 1px 0 rgba(0,0,0,.2),0 0 0 .1em white inset;box-shadow:0 1px 0 rgba(0,0,0,.2),0 0 0 .1em #fff inset;margin:-.15em .15em 0 .15em;padding:.2em .6em .2em .5em;vertical-align:middle;white-space:nowrap}
|
||||
.keyseq kbd:first-child{margin-left:0}
|
||||
.keyseq kbd:last-child{margin-right:0}
|
||||
.menuseq,.menu{color:rgba(0,0,0,.8)}
|
||||
b.button:before,b.button:after{position:relative;top:-1px;font-weight:400}
|
||||
b.button:before{content:"[";padding:0 3px 0 2px}
|
||||
b.button:after{content:"]";padding:0 2px 0 3px}
|
||||
p a>code:hover{color:rgba(0,0,0,.9)}
|
||||
#header,#content,#footnotes,#footer{width:100%;margin-left:auto;margin-right:auto;margin-top:0;margin-bottom:0;max-width:62.5em;*zoom:1;position:relative;padding-left:.9375em;padding-right:.9375em}
|
||||
#header:before,#header:after,#content:before,#content:after,#footnotes:before,#footnotes:after,#footer:before,#footer:after{content:" ";display:table}
|
||||
#header:after,#content:after,#footnotes:after,#footer:after{clear:both}
|
||||
#content{margin-top:1.25em}
|
||||
#content:before{content:none}
|
||||
#header>h1:first-child{color:rgba(0,0,0,.85);margin-top:2.25rem;margin-bottom:0}
|
||||
#header>h1:first-child+#toc{margin-top:8px;border-top:1px solid #ddddd8}
|
||||
#header>h1:only-child,body.toc2 #header>h1:nth-last-child(2){border-bottom:1px solid #ddddd8;padding-bottom:8px}
|
||||
#header .details{border-bottom:1px solid #ddddd8;line-height:1.45;padding-top:.25em;padding-bottom:.25em;padding-left:.25em;color:rgba(0,0,0,.6);display:-ms-flexbox;display:-webkit-flex;display:flex;-ms-flex-flow:row wrap;-webkit-flex-flow:row wrap;flex-flow:row wrap}
|
||||
#header .details span:first-child{margin-left:-.125em}
|
||||
#header .details span.email a{color:rgba(0,0,0,.85)}
|
||||
#header .details br{display:none}
|
||||
#header .details br+span:before{content:"\00a0\2013\00a0"}
|
||||
#header .details br+span.author:before{content:"\00a0\22c5\00a0";color:rgba(0,0,0,.85)}
|
||||
#header .details br+span#revremark:before{content:"\00a0|\00a0"}
|
||||
#header #revnumber{text-transform:capitalize}
|
||||
#header #revnumber:after{content:"\00a0"}
|
||||
#content>h1:first-child:not([class]){color:rgba(0,0,0,.85);border-bottom:1px solid #ddddd8;padding-bottom:8px;margin-top:0;padding-top:1rem;margin-bottom:1.25rem}
|
||||
#toc{border-bottom:1px solid #efefed;padding-bottom:.5em}
|
||||
#toc>ul{margin-left:.125em}
|
||||
#toc ul.sectlevel0>li>a{font-style:italic}
|
||||
#toc ul.sectlevel0 ul.sectlevel1{margin:.5em 0}
|
||||
#toc ul{font-family:"Open Sans","DejaVu Sans",sans-serif;list-style-type:none}
|
||||
#toc a{text-decoration:none}
|
||||
#toc a:active{text-decoration:underline}
|
||||
#toctitle{color:#7a2518;font-size:1.2em}
|
||||
@media only screen and (min-width:768px){#toctitle{font-size:1.375em}
|
||||
body.toc2{padding-left:15em;padding-right:0}
|
||||
#toc.toc2{margin-top:0!important;background-color:#f8f8f7;position:fixed;width:15em;left:0;top:0;border-right:1px solid #efefed;border-top-width:0!important;border-bottom-width:0!important;z-index:1000;padding:1.25em 1em;height:100%;overflow:auto}
|
||||
#toc.toc2 #toctitle{margin-top:0;font-size:1.2em}
|
||||
#toc.toc2>ul{font-size:.9em;margin-bottom:0}
|
||||
#toc.toc2 ul ul{margin-left:0;padding-left:1em}
|
||||
#toc.toc2 ul.sectlevel0 ul.sectlevel1{padding-left:0;margin-top:.5em;margin-bottom:.5em}
|
||||
body.toc2.toc-right{padding-left:0;padding-right:15em}
|
||||
body.toc2.toc-right #toc.toc2{border-right-width:0;border-left:1px solid #efefed;left:auto;right:0}}@media only screen and (min-width:1280px){body.toc2{padding-left:20em;padding-right:0}
|
||||
#toc.toc2{width:20em}
|
||||
#toc.toc2 #toctitle{font-size:1.375em}
|
||||
#toc.toc2>ul{font-size:.95em}
|
||||
#toc.toc2 ul ul{padding-left:1.25em}
|
||||
body.toc2.toc-right{padding-left:0;padding-right:20em}}#content #toc{border-style:solid;border-width:1px;border-color:#e0e0dc;margin-bottom:1.25em;padding:1.25em;background:#f8f8f7;-webkit-border-radius:4px;border-radius:4px}
|
||||
#content #toc>:first-child{margin-top:0}
|
||||
#content #toc>:last-child{margin-bottom:0}
|
||||
#footer{max-width:100%;background-color:rgba(0,0,0,.8);padding:1.25em}
|
||||
#footer-text{color:rgba(255,255,255,.8);line-height:1.44}
|
||||
.sect1{padding-bottom:.625em}
|
||||
@media only screen and (min-width:768px){.sect1{padding-bottom:1.25em}}.sect1+.sect1{border-top:1px solid #efefed}
|
||||
#content h1>a.anchor,h2>a.anchor,h3>a.anchor,#toctitle>a.anchor,.sidebarblock>.content>.title>a.anchor,h4>a.anchor,h5>a.anchor,h6>a.anchor{position:absolute;z-index:1001;width:1.5ex;margin-left:-1.5ex;display:block;text-decoration:none!important;visibility:hidden;text-align:center;font-weight:400}
|
||||
#content h1>a.anchor:before,h2>a.anchor:before,h3>a.anchor:before,#toctitle>a.anchor:before,.sidebarblock>.content>.title>a.anchor:before,h4>a.anchor:before,h5>a.anchor:before,h6>a.anchor:before{content:"\00A7";font-size:.85em;display:block;padding-top:.1em}
|
||||
#content h1:hover>a.anchor,#content h1>a.anchor:hover,h2:hover>a.anchor,h2>a.anchor:hover,h3:hover>a.anchor,#toctitle:hover>a.anchor,.sidebarblock>.content>.title:hover>a.anchor,h3>a.anchor:hover,#toctitle>a.anchor:hover,.sidebarblock>.content>.title>a.anchor:hover,h4:hover>a.anchor,h4>a.anchor:hover,h5:hover>a.anchor,h5>a.anchor:hover,h6:hover>a.anchor,h6>a.anchor:hover{visibility:visible}
|
||||
#content h1>a.link,h2>a.link,h3>a.link,#toctitle>a.link,.sidebarblock>.content>.title>a.link,h4>a.link,h5>a.link,h6>a.link{color:#ba3925;text-decoration:none}
|
||||
#content h1>a.link:hover,h2>a.link:hover,h3>a.link:hover,#toctitle>a.link:hover,.sidebarblock>.content>.title>a.link:hover,h4>a.link:hover,h5>a.link:hover,h6>a.link:hover{color:#a53221}
|
||||
.audioblock,.imageblock,.literalblock,.listingblock,.stemblock,.videoblock{margin-bottom:1.25em}
|
||||
.admonitionblock td.content>.title,.audioblock>.title,.exampleblock>.title,.imageblock>.title,.listingblock>.title,.literalblock>.title,.stemblock>.title,.openblock>.title,.paragraph>.title,.quoteblock>.title,table.tableblock>.title,.verseblock>.title,.videoblock>.title,.dlist>.title,.olist>.title,.ulist>.title,.qlist>.title,.hdlist>.title{text-rendering:optimizeLegibility;text-align:left;font-family:"Noto Serif","DejaVu Serif",serif;font-size:1rem;font-style:italic}
|
||||
table.tableblock>caption.title{white-space:nowrap;overflow:visible;max-width:0}
|
||||
.paragraph.lead>p,#preamble>.sectionbody>.paragraph:first-of-type p{color:rgba(0,0,0,.85)}
|
||||
table.tableblock #preamble>.sectionbody>.paragraph:first-of-type p{font-size:inherit}
|
||||
.admonitionblock>table{border-collapse:separate;border:0;background:none;width:100%}
|
||||
.admonitionblock>table td.icon{text-align:center;width:80px}
|
||||
.admonitionblock>table td.icon img{max-width:none}
|
||||
.admonitionblock>table td.icon .title{font-weight:bold;font-family:"Open Sans","DejaVu Sans",sans-serif;text-transform:uppercase}
|
||||
.admonitionblock>table td.content{padding-left:1.125em;padding-right:1.25em;border-left:1px solid #ddddd8;color:rgba(0,0,0,.6)}
|
||||
.admonitionblock>table td.content>:last-child>:last-child{margin-bottom:0}
|
||||
.exampleblock>.content{border-style:solid;border-width:1px;border-color:#e6e6e6;margin-bottom:1.25em;padding:1.25em;background:#fff;-webkit-border-radius:4px;border-radius:4px}
|
||||
.exampleblock>.content>:first-child{margin-top:0}
|
||||
.exampleblock>.content>:last-child{margin-bottom:0}
|
||||
.sidebarblock{border-style:solid;border-width:1px;border-color:#e0e0dc;margin-bottom:1.25em;padding:1.25em;background:#f8f8f7;-webkit-border-radius:4px;border-radius:4px}
|
||||
.sidebarblock>:first-child{margin-top:0}
|
||||
.sidebarblock>:last-child{margin-bottom:0}
|
||||
.sidebarblock>.content>.title{color:#7a2518;margin-top:0;text-align:center}
|
||||
.exampleblock>.content>:last-child>:last-child,.exampleblock>.content .olist>ol>li:last-child>:last-child,.exampleblock>.content .ulist>ul>li:last-child>:last-child,.exampleblock>.content .qlist>ol>li:last-child>:last-child,.sidebarblock>.content>:last-child>:last-child,.sidebarblock>.content .olist>ol>li:last-child>:last-child,.sidebarblock>.content .ulist>ul>li:last-child>:last-child,.sidebarblock>.content .qlist>ol>li:last-child>:last-child{margin-bottom:0}
|
||||
.literalblock pre,.listingblock pre:not(.highlight),.listingblock pre[class="highlight"],.listingblock pre[class^="highlight "],.listingblock pre.CodeRay,.listingblock pre.prettyprint{background:#f7f7f8}
|
||||
.sidebarblock .literalblock pre,.sidebarblock .listingblock pre:not(.highlight),.sidebarblock .listingblock pre[class="highlight"],.sidebarblock .listingblock pre[class^="highlight "],.sidebarblock .listingblock pre.CodeRay,.sidebarblock .listingblock pre.prettyprint{background:#f2f1f1}
|
||||
.literalblock pre,.literalblock pre[class],.listingblock pre,.listingblock pre[class]{-webkit-border-radius:4px;border-radius:4px;word-wrap:break-word;padding:1em;font-size:.8125em}
|
||||
.literalblock pre.nowrap,.literalblock pre[class].nowrap,.listingblock pre.nowrap,.listingblock pre[class].nowrap{overflow-x:auto;white-space:pre;word-wrap:normal}
|
||||
@media only screen and (min-width:768px){.literalblock pre,.literalblock pre[class],.listingblock pre,.listingblock pre[class]{font-size:.90625em}}@media only screen and (min-width:1280px){.literalblock pre,.literalblock pre[class],.listingblock pre,.listingblock pre[class]{font-size:1em}}.literalblock.output pre{color:#f7f7f8;background-color:rgba(0,0,0,.9)}
|
||||
.listingblock pre.highlightjs{padding:0}
|
||||
.listingblock pre.highlightjs>code{padding:1em;-webkit-border-radius:4px;border-radius:4px}
|
||||
.listingblock pre.prettyprint{border-width:0}
|
||||
.listingblock>.content{position:relative}
|
||||
.listingblock code[data-lang]:before{display:none;content:attr(data-lang);position:absolute;font-size:.75em;top:.425rem;right:.5rem;line-height:1;text-transform:uppercase;color:#999}
|
||||
.listingblock:hover code[data-lang]:before{display:block}
|
||||
.listingblock.terminal pre .command:before{content:attr(data-prompt);padding-right:.5em;color:#999}
|
||||
.listingblock.terminal pre .command:not([data-prompt]):before{content:"$"}
|
||||
table.pyhltable{border-collapse:separate;border:0;margin-bottom:0;background:none}
|
||||
table.pyhltable td{vertical-align:top;padding-top:0;padding-bottom:0}
|
||||
table.pyhltable td.code{padding-left:.75em;padding-right:0}
|
||||
pre.pygments .lineno,table.pyhltable td:not(.code){color:#999;padding-left:0;padding-right:.5em;border-right:1px solid #ddddd8}
|
||||
pre.pygments .lineno{display:inline-block;margin-right:.25em}
|
||||
table.pyhltable .linenodiv{background:none!important;padding-right:0!important}
|
||||
.quoteblock{margin:0 1em 1.25em 1.5em;display:table}
|
||||
.quoteblock>.title{margin-left:-1.5em;margin-bottom:.75em}
|
||||
.quoteblock blockquote,.quoteblock blockquote p{color:rgba(0,0,0,.85);font-size:1.15rem;line-height:1.75;word-spacing:.1em;letter-spacing:0;font-style:italic;text-align:justify}
|
||||
.quoteblock blockquote{margin:0;padding:0;border:0}
|
||||
.quoteblock blockquote:before{content:"\201c";float:left;font-size:2.75em;font-weight:bold;line-height:.6em;margin-left:-.6em;color:#7a2518;text-shadow:0 1px 2px rgba(0,0,0,.1)}
|
||||
.quoteblock blockquote>.paragraph:last-child p{margin-bottom:0}
|
||||
.quoteblock .attribution{margin-top:.5em;margin-right:.5ex;text-align:right}
|
||||
.quoteblock .quoteblock{margin-left:0;margin-right:0;padding:.5em 0;border-left:3px solid rgba(0,0,0,.6)}
|
||||
.quoteblock .quoteblock blockquote{padding:0 0 0 .75em}
|
||||
.quoteblock .quoteblock blockquote:before{display:none}
|
||||
.verseblock{margin:0 1em 1.25em 1em}
|
||||
.verseblock pre{font-family:"Open Sans","DejaVu Sans",sans;font-size:1.15rem;color:rgba(0,0,0,.85);font-weight:300;text-rendering:optimizeLegibility}
|
||||
.verseblock pre strong{font-weight:400}
|
||||
.verseblock .attribution{margin-top:1.25rem;margin-left:.5ex}
|
||||
.quoteblock .attribution,.verseblock .attribution{font-size:.9375em;line-height:1.45;font-style:italic}
|
||||
.quoteblock .attribution br,.verseblock .attribution br{display:none}
|
||||
.quoteblock .attribution cite,.verseblock .attribution cite{display:block;letter-spacing:-.05em;color:rgba(0,0,0,.6)}
|
||||
.quoteblock.abstract{margin:0 0 1.25em 0;display:block}
|
||||
.quoteblock.abstract blockquote,.quoteblock.abstract blockquote p{text-align:left;word-spacing:0}
|
||||
.quoteblock.abstract blockquote:before,.quoteblock.abstract blockquote p:first-of-type:before{display:none}
|
||||
table.tableblock{max-width:100%;border-collapse:separate}
|
||||
table.tableblock td>.paragraph:last-child p>p:last-child,table.tableblock th>p:last-child,table.tableblock td>p:last-child{margin-bottom:0}
|
||||
table.spread{width:100%}
|
||||
table.tableblock,th.tableblock,td.tableblock{border:0 solid #dedede}
|
||||
table.grid-all th.tableblock,table.grid-all td.tableblock{border-width:0 1px 1px 0}
|
||||
table.grid-all tfoot>tr>th.tableblock,table.grid-all tfoot>tr>td.tableblock{border-width:1px 1px 0 0}
|
||||
table.grid-cols th.tableblock,table.grid-cols td.tableblock{border-width:0 1px 0 0}
|
||||
table.grid-all *>tr>.tableblock:last-child,table.grid-cols *>tr>.tableblock:last-child{border-right-width:0}
|
||||
table.grid-rows th.tableblock,table.grid-rows td.tableblock{border-width:0 0 1px 0}
|
||||
table.grid-all tbody>tr:last-child>th.tableblock,table.grid-all tbody>tr:last-child>td.tableblock,table.grid-all thead:last-child>tr>th.tableblock,table.grid-rows tbody>tr:last-child>th.tableblock,table.grid-rows tbody>tr:last-child>td.tableblock,table.grid-rows thead:last-child>tr>th.tableblock{border-bottom-width:0}
|
||||
table.grid-rows tfoot>tr>th.tableblock,table.grid-rows tfoot>tr>td.tableblock{border-width:1px 0 0 0}
|
||||
table.frame-all{border-width:1px}
|
||||
table.frame-sides{border-width:0 1px}
|
||||
table.frame-topbot{border-width:1px 0}
|
||||
th.halign-left,td.halign-left{text-align:left}
|
||||
th.halign-right,td.halign-right{text-align:right}
|
||||
th.halign-center,td.halign-center{text-align:center}
|
||||
th.valign-top,td.valign-top{vertical-align:top}
|
||||
th.valign-bottom,td.valign-bottom{vertical-align:bottom}
|
||||
th.valign-middle,td.valign-middle{vertical-align:middle}
|
||||
table thead th,table tfoot th{font-weight:bold}
|
||||
tbody tr th{display:table-cell;line-height:1.6;background:#f7f8f7}
|
||||
tbody tr th,tbody tr th p,tfoot tr th,tfoot tr th p{color:rgba(0,0,0,.8);font-weight:bold}
|
||||
p.tableblock>code:only-child{background:none;padding:0}
|
||||
p.tableblock{font-size:1em}
|
||||
td>div.verse{white-space:pre}
|
||||
ol{margin-left:1.75em}
|
||||
ul li ol{margin-left:1.5em}
|
||||
dl dd{margin-left:1.125em}
|
||||
dl dd:last-child,dl dd:last-child>:last-child{margin-bottom:0}
|
||||
ol>li p,ul>li p,ul dd,ol dd,.olist .olist,.ulist .ulist,.ulist .olist,.olist .ulist{margin-bottom:.625em}
|
||||
ul.unstyled,ol.unnumbered,ul.checklist,ul.none{list-style-type:none}
|
||||
ul.unstyled,ol.unnumbered,ul.checklist{margin-left:.625em}
|
||||
ul.checklist li>p:first-child>.fa-square-o:first-child,ul.checklist li>p:first-child>.fa-check-square-o:first-child{width:1em;font-size:.85em}
|
||||
ul.checklist li>p:first-child>input[type="checkbox"]:first-child{width:1em;position:relative;top:1px}
|
||||
ul.inline{margin:0 auto .625em auto;margin-left:-1.375em;margin-right:0;padding:0;list-style:none;overflow:hidden}
|
||||
ul.inline>li{list-style:none;float:left;margin-left:1.375em;display:block}
|
||||
ul.inline>li>*{display:block}
|
||||
.unstyled dl dt{font-weight:400;font-style:normal}
|
||||
ol.arabic{list-style-type:decimal}
|
||||
ol.decimal{list-style-type:decimal-leading-zero}
|
||||
ol.loweralpha{list-style-type:lower-alpha}
|
||||
ol.upperalpha{list-style-type:upper-alpha}
|
||||
ol.lowerroman{list-style-type:lower-roman}
|
||||
ol.upperroman{list-style-type:upper-roman}
|
||||
ol.lowergreek{list-style-type:lower-greek}
|
||||
.hdlist>table,.colist>table{border:0;background:none}
|
||||
.hdlist>table>tbody>tr,.colist>table>tbody>tr{background:none}
|
||||
td.hdlist1{padding-right:.75em;font-weight:bold}
|
||||
td.hdlist1,td.hdlist2{vertical-align:top}
|
||||
.literalblock+.colist,.listingblock+.colist{margin-top:-.5em}
|
||||
.colist>table tr>td:first-of-type{padding:0 .75em;line-height:1}
|
||||
.colist>table tr>td:last-of-type{padding:.25em 0}
|
||||
.thumb,.th{line-height:0;display:inline-block;border:solid 4px #fff;-webkit-box-shadow:0 0 0 1px #ddd;box-shadow:0 0 0 1px #ddd}
|
||||
.imageblock.left,.imageblock[style*="float: left"]{margin:.25em .625em 1.25em 0}
|
||||
.imageblock.right,.imageblock[style*="float: right"]{margin:.25em 0 1.25em .625em}
|
||||
.imageblock>.title{margin-bottom:0}
|
||||
.imageblock.thumb,.imageblock.th{border-width:6px}
|
||||
.imageblock.thumb>.title,.imageblock.th>.title{padding:0 .125em}
|
||||
.image.left,.image.right{margin-top:.25em;margin-bottom:.25em;display:inline-block;line-height:0}
|
||||
.image.left{margin-right:.625em}
|
||||
.image.right{margin-left:.625em}
|
||||
a.image{text-decoration:none}
|
||||
span.footnote,span.footnoteref{vertical-align:super;font-size:.875em}
|
||||
span.footnote a,span.footnoteref a{text-decoration:none}
|
||||
span.footnote a:active,span.footnoteref a:active{text-decoration:underline}
|
||||
#footnotes{padding-top:.75em;padding-bottom:.75em;margin-bottom:.625em}
|
||||
#footnotes hr{width:20%;min-width:6.25em;margin:-.25em 0 .75em 0;border-width:1px 0 0 0}
|
||||
#footnotes .footnote{padding:0 .375em;line-height:1.3;font-size:.875em;margin-left:1.2em;text-indent:-1.2em;margin-bottom:.2em}
|
||||
#footnotes .footnote a:first-of-type{font-weight:bold;text-decoration:none}
|
||||
#footnotes .footnote:last-of-type{margin-bottom:0}
|
||||
#content #footnotes{margin-top:-.625em;margin-bottom:0;padding:.75em 0}
|
||||
.gist .file-data>table{border:0;background:#fff;width:100%;margin-bottom:0}
|
||||
.gist .file-data>table td.line-data{width:99%}
|
||||
div.unbreakable{page-break-inside:avoid}
|
||||
.big{font-size:larger}
|
||||
.small{font-size:smaller}
|
||||
.underline{text-decoration:underline}
|
||||
.overline{text-decoration:overline}
|
||||
.line-through{text-decoration:line-through}
|
||||
.aqua{color:#00bfbf}
|
||||
.aqua-background{background-color:#00fafa}
|
||||
.black{color:#000}
|
||||
.black-background{background-color:#000}
|
||||
.blue{color:#0000bf}
|
||||
.blue-background{background-color:#0000fa}
|
||||
.fuchsia{color:#bf00bf}
|
||||
.fuchsia-background{background-color:#fa00fa}
|
||||
.gray{color:#606060}
|
||||
.gray-background{background-color:#7d7d7d}
|
||||
.green{color:#006000}
|
||||
.green-background{background-color:#007d00}
|
||||
.lime{color:#00bf00}
|
||||
.lime-background{background-color:#00fa00}
|
||||
.maroon{color:#600000}
|
||||
.maroon-background{background-color:#7d0000}
|
||||
.navy{color:#000060}
|
||||
.navy-background{background-color:#00007d}
|
||||
.olive{color:#606000}
|
||||
.olive-background{background-color:#7d7d00}
|
||||
.purple{color:#600060}
|
||||
.purple-background{background-color:#7d007d}
|
||||
.red{color:#bf0000}
|
||||
.red-background{background-color:#fa0000}
|
||||
.silver{color:#909090}
|
||||
.silver-background{background-color:#bcbcbc}
|
||||
.teal{color:#006060}
|
||||
.teal-background{background-color:#007d7d}
|
||||
.white{color:#bfbfbf}
|
||||
.white-background{background-color:#fafafa}
|
||||
.yellow{color:#bfbf00}
|
||||
.yellow-background{background-color:#fafa00}
|
||||
span.icon>.fa{cursor:default}
|
||||
.admonitionblock td.icon [class^="fa icon-"]{font-size:2.5em;text-shadow:1px 1px 2px rgba(0,0,0,.5);cursor:default}
|
||||
.admonitionblock td.icon .icon-note:before{content:"\f05a";color:#19407c}
|
||||
.admonitionblock td.icon .icon-tip:before{content:"\f0eb";text-shadow:1px 1px 2px rgba(155,155,0,.8);color:#111}
|
||||
.admonitionblock td.icon .icon-warning:before{content:"\f071";color:#bf6900}
|
||||
.admonitionblock td.icon .icon-caution:before{content:"\f06d";color:#bf3400}
|
||||
.admonitionblock td.icon .icon-important:before{content:"\f06a";color:#bf0000}
|
||||
.conum[data-value]{display:inline-block;color:#fff!important;background-color:rgba(0,0,0,.8);-webkit-border-radius:100px;border-radius:100px;text-align:center;font-size:.75em;width:1.67em;height:1.67em;line-height:1.67em;font-family:"Open Sans","DejaVu Sans",sans-serif;font-style:normal;font-weight:bold}
|
||||
.conum[data-value] *{color:#fff!important}
|
||||
.conum[data-value]+b{display:none}
|
||||
.conum[data-value]:after{content:attr(data-value)}
|
||||
pre .conum[data-value]{position:relative;top:-.125em}
|
||||
b.conum *{color:inherit!important}
|
||||
.conum:not([data-value]):empty{display:none}
|
||||
h1,h2{letter-spacing:-.01em}
|
||||
dt,th.tableblock,td.content{text-rendering:optimizeLegibility}
|
||||
p,td.content{letter-spacing:-.01em}
|
||||
p strong,td.content strong{letter-spacing:-.005em}
|
||||
p,blockquote,dt,td.content{font-size:1.0625rem}
|
||||
p{margin-bottom:1.25rem}
|
||||
.sidebarblock p,.sidebarblock dt,.sidebarblock td.content,p.tableblock{font-size:1em}
|
||||
.exampleblock>.content{background-color:#fffef7;border-color:#e0e0dc;-webkit-box-shadow:0 1px 4px #e0e0dc;box-shadow:0 1px 4px #e0e0dc}
|
||||
.print-only{display:none!important}
|
||||
@media print{@page{margin:1.25cm .75cm}
|
||||
*{-webkit-box-shadow:none!important;box-shadow:none!important;text-shadow:none!important}
|
||||
a{color:inherit!important;text-decoration:underline!important}
|
||||
a.bare,a[href^="#"],a[href^="mailto:"]{text-decoration:none!important}
|
||||
a[href^="http:"]:not(.bare):after,a[href^="https:"]:not(.bare):after{content:"(" attr(href) ")";display:inline-block;font-size:.875em;padding-left:.25em}
|
||||
abbr[title]:after{content:" (" attr(title) ")"}
|
||||
pre,blockquote,tr,img{page-break-inside:avoid}
|
||||
thead{display:table-header-group}
|
||||
img{max-width:100%!important}
|
||||
p,blockquote,dt,td.content{font-size:1em;orphans:3;widows:3}
|
||||
h2,h3,#toctitle,.sidebarblock>.content>.title{page-break-after:avoid}
|
||||
#toc,.sidebarblock,.exampleblock>.content{background:none!important}
|
||||
#toc{border-bottom:1px solid #ddddd8!important;padding-bottom:0!important}
|
||||
.sect1{padding-bottom:0!important}
|
||||
.sect1+.sect1{border:0!important}
|
||||
#header>h1:first-child{margin-top:1.25rem}
|
||||
body.book #header{text-align:center}
|
||||
body.book #header>h1:first-child{border:0!important;margin:2.5em 0 1em 0}
|
||||
body.book #header .details{border:0!important;display:block;padding:0!important}
|
||||
body.book #header .details span:first-child{margin-left:0!important}
|
||||
body.book #header .details br{display:block}
|
||||
body.book #header .details br+span:before{content:none!important}
|
||||
body.book #toc{border:0!important;text-align:left!important;padding:0!important;margin:0!important}
|
||||
body.book #toc,body.book #preamble,body.book h1.sect0,body.book .sect1>h2{page-break-before:always}
|
||||
.listingblock code[data-lang]:before{display:block}
|
||||
#footer{background:none!important;padding:0 .9375em}
|
||||
#footer-text{color:rgba(0,0,0,.6)!important;font-size:.9em}
|
||||
.hide-on-print{display:none!important}
|
||||
.print-only{display:block!important}
|
||||
.hide-for-print{display:none!important}
|
||||
.show-for-print{display:inherit!important}}
|
||||
|
|
@ -0,0 +1,94 @@
|
|||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
|
||||
= Apache HBase (TM) Reference Guide
|
||||
:Author: Apache HBase Team
|
||||
:Email: <hbase-dev@lists.apache.org>
|
||||
:doctype: book
|
||||
:Version: {docVersion}
|
||||
:revnumber: {docVersion}
|
||||
// Logo for PDF -- doesn't render in HTML
|
||||
:title-logo: hbase_logo_with_orca.png
|
||||
:numbered:
|
||||
:toc: left
|
||||
:toclevels: 1
|
||||
:toc-title: Contents
|
||||
:sectanchors:
|
||||
:icons: font
|
||||
:iconsdir: icons
|
||||
:linkcss:
|
||||
:experimental:
|
||||
:source-language: java
|
||||
:leveloffset: 0
|
||||
|
||||
// Logo for HTML -- doesn't render in PDF
|
||||
++++
|
||||
<div>
|
||||
<a href="http://hbase.apache.org"><img src="images/hbase_logo_with_orca.png" alt="Apache HBase Logo" /></a>
|
||||
</div>
|
||||
++++
|
||||
|
||||
// The directory is called _chapters because asciidoctor skips direct
|
||||
// processing of files found in directories starting with an _. This
|
||||
// prevents each chapter being built as its own book.
|
||||
|
||||
include::_chapters/preface.adoc[]
|
||||
|
||||
include::_chapters/getting_started.adoc[]
|
||||
include::_chapters/configuration.adoc[]
|
||||
include::_chapters/upgrading.adoc[]
|
||||
include::_chapters/shell.adoc[]
|
||||
include::_chapters/datamodel.adoc[]
|
||||
include::_chapters/schema_design.adoc[]
|
||||
include::_chapters/mapreduce.adoc[]
|
||||
include::_chapters/security.adoc[]
|
||||
include::_chapters/architecture.adoc[]
|
||||
include::_chapters/hbase_apis.adoc[]
|
||||
include::_chapters/external_apis.adoc[]
|
||||
include::_chapters/thrift_filter_language.adoc[]
|
||||
include::_chapters/cp.adoc[]
|
||||
include::_chapters/performance.adoc[]
|
||||
include::_chapters/troubleshooting.adoc[]
|
||||
include::_chapters/case_studies.adoc[]
|
||||
include::_chapters/ops_mgt.adoc[]
|
||||
include::_chapters/developer.adoc[]
|
||||
include::_chapters/unit_testing.adoc[]
|
||||
include::_chapters/zookeeper.adoc[]
|
||||
include::_chapters/community.adoc[]
|
||||
|
||||
= Appendix
|
||||
|
||||
include::_chapters/appendix_contributing_to_documentation.adoc[]
|
||||
include::_chapters/faq.adoc[]
|
||||
include::_chapters/hbck_in_depth.adoc[]
|
||||
include::_chapters/appendix_acl_matrix.adoc[]
|
||||
include::_chapters/compression.adoc[]
|
||||
include::_chapters/sql.adoc[]
|
||||
include::_chapters/ycsb.adoc[]
|
||||
include::_chapters/appendix_hfile_format.adoc[]
|
||||
include::_chapters/other_info.adoc[]
|
||||
include::_chapters/hbase_history.adoc[]
|
||||
include::_chapters/asf.adoc[]
|
||||
include::_chapters/orca.adoc[]
|
||||
include::_chapters/tracing.adoc[]
|
||||
include::_chapters/rpc.adoc[]
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,400 @@
|
|||
/* Asciidoctor default stylesheet | MIT License | http://asciidoctor.org */
|
||||
/* Remove the comments around the @import statement below when using this as a custom stylesheet */
|
||||
/*@import "https://fonts.googleapis.com/css?family=Open+Sans:300,300italic,400,400italic,600,600italic%7CNoto+Serif:400,400italic,700,700italic%7CDroid+Sans+Mono:400";*/
|
||||
article,aside,details,figcaption,figure,footer,header,hgroup,main,nav,section,summary{display:block}
|
||||
audio,canvas,video{display:inline-block}
|
||||
audio:not([controls]){display:none;height:0}
|
||||
[hidden],template{display:none}
|
||||
script{display:none!important}
|
||||
html{font-family:sans-serif;-ms-text-size-adjust:100%;-webkit-text-size-adjust:100%}
|
||||
body{margin:0}
|
||||
a{background:transparent}
|
||||
a:focus{outline:thin dotted}
|
||||
a:active,a:hover{outline:0}
|
||||
h1{font-size:2em;margin:.67em 0}
|
||||
abbr[title]{border-bottom:1px dotted}
|
||||
b,strong{font-weight:bold}
|
||||
dfn{font-style:italic}
|
||||
hr{-moz-box-sizing:content-box;box-sizing:content-box;height:0}
|
||||
mark{background:#ff0;color:#000}
|
||||
code,kbd,pre,samp{font-family:monospace;font-size:1em}
|
||||
pre{white-space:pre-wrap}
|
||||
q{quotes:"\201C" "\201D" "\2018" "\2019"}
|
||||
small{font-size:80%}
|
||||
sub,sup{font-size:75%;line-height:0;position:relative;vertical-align:baseline}
|
||||
sup{top:-.5em}
|
||||
sub{bottom:-.25em}
|
||||
img{border:0}
|
||||
svg:not(:root){overflow:hidden}
|
||||
figure{margin:0}
|
||||
fieldset{border:1px solid silver;margin:0 2px;padding:.35em .625em .75em}
|
||||
legend{border:0;padding:0}
|
||||
button,input,select,textarea{font-family:inherit;font-size:100%;margin:0}
|
||||
button,input{line-height:normal}
|
||||
button,select{text-transform:none}
|
||||
button,html input[type="button"],input[type="reset"],input[type="submit"]{-webkit-appearance:button;cursor:pointer}
|
||||
button[disabled],html input[disabled]{cursor:default}
|
||||
input[type="checkbox"],input[type="radio"]{box-sizing:border-box;padding:0}
|
||||
input[type="search"]{-webkit-appearance:textfield;-moz-box-sizing:content-box;-webkit-box-sizing:content-box;box-sizing:content-box}
|
||||
input[type="search"]::-webkit-search-cancel-button,input[type="search"]::-webkit-search-decoration{-webkit-appearance:none}
|
||||
button::-moz-focus-inner,input::-moz-focus-inner{border:0;padding:0}
|
||||
textarea{overflow:auto;vertical-align:top}
|
||||
table{border-collapse:collapse;border-spacing:0}
|
||||
*,*:before,*:after{-moz-box-sizing:border-box;-webkit-box-sizing:border-box;box-sizing:border-box}
|
||||
html,body{font-size:100%}
|
||||
body{background:#fff;color:rgba(0,0,0,.8);padding:0;margin:0;font-family:"Noto Serif","DejaVu Serif",serif;font-weight:400;font-style:normal;line-height:1;position:relative;cursor:auto}
|
||||
a:hover{cursor:pointer}
|
||||
img,object,embed{max-width:100%;height:auto}
|
||||
object,embed{height:100%}
|
||||
img{-ms-interpolation-mode:bicubic}
|
||||
#map_canvas img,#map_canvas embed,#map_canvas object,.map_canvas img,.map_canvas embed,.map_canvas object{max-width:none!important}
|
||||
.left{float:left!important}
|
||||
.right{float:right!important}
|
||||
.text-left{text-align:left!important}
|
||||
.text-right{text-align:right!important}
|
||||
.text-center{text-align:center!important}
|
||||
.text-justify{text-align:justify!important}
|
||||
.hide{display:none}
|
||||
.antialiased,body{-webkit-font-smoothing:antialiased}
|
||||
img{display:inline-block;vertical-align:middle}
|
||||
textarea{height:auto;min-height:50px}
|
||||
select{width:100%}
|
||||
p.lead,.paragraph.lead>p,#preamble>.sectionbody>.paragraph:first-of-type p{font-size:1.21875em;line-height:1.6}
|
||||
.subheader,.admonitionblock td.content>.title,.audioblock>.title,.exampleblock>.title,.imageblock>.title,.listingblock>.title,.literalblock>.title,.stemblock>.title,.openblock>.title,.paragraph>.title,.quoteblock>.title,table.tableblock>.title,.verseblock>.title,.videoblock>.title,.dlist>.title,.olist>.title,.ulist>.title,.qlist>.title,.hdlist>.title{line-height:1.45;color:#7a2518;font-weight:400;margin-top:0;margin-bottom:.25em}
|
||||
div,dl,dt,dd,ul,ol,li,h1,h2,h3,#toctitle,.sidebarblock>.content>.title,h4,h5,h6,pre,form,p,blockquote,th,td{margin:0;padding:0;direction:ltr}
|
||||
a{color:#2156a5;text-decoration:underline;line-height:inherit}
|
||||
a:hover,a:focus{color:#1d4b8f}
|
||||
a img{border:none}
|
||||
p{font-family:inherit;font-weight:400;font-size:1em;line-height:1.6;margin-bottom:1.25em;text-rendering:optimizeLegibility}
|
||||
p aside{font-size:.875em;line-height:1.35;font-style:italic}
|
||||
h1,h2,h3,#toctitle,.sidebarblock>.content>.title,h4,h5,h6{font-family:"Open Sans","DejaVu Sans",sans-serif;font-weight:300;font-style:normal;color:#990000;text-rendering:optimizeLegibility;margin-top:1em;margin-bottom:.5em;line-height:1.0125em}
|
||||
h1 small,h2 small,h3 small,#toctitle small,.sidebarblock>.content>.title small,h4 small,h5 small,h6 small{font-size:60%;color:#e99b8f;line-height:0}
|
||||
h1{font-size:2.125em}
|
||||
h2{font-size:1.6875em}
|
||||
h3,#toctitle,.sidebarblock>.content>.title{font-size:1.375em}
|
||||
h4,h5{font-size:1.125em}
|
||||
h6{font-size:1em}
|
||||
hr{border:solid #ddddd8;border-width:1px 0 0;clear:both;margin:1.25em 0 1.1875em;height:0}
|
||||
em,i{font-style:italic;line-height:inherit}
|
||||
strong,b{font-weight:bold;line-height:inherit}
|
||||
small{font-size:60%;line-height:inherit}
|
||||
code{font-family:"Droid Sans Mono","DejaVu Sans Mono",monospace;font-weight:400;color:rgba(0,0,0,.9)}
|
||||
ul,ol,dl{font-size:1em;line-height:1.6;margin-bottom:1.25em;list-style-position:outside;font-family:inherit}
|
||||
ul,ol,ul.no-bullet,ol.no-bullet{margin-left:1.5em}
|
||||
ul li ul,ul li ol{margin-left:1.25em;margin-bottom:0;font-size:1em}
|
||||
ul.square li ul,ul.circle li ul,ul.disc li ul{list-style:inherit}
|
||||
ul.square{list-style-type:square}
|
||||
ul.circle{list-style-type:circle}
|
||||
ul.disc{list-style-type:disc}
|
||||
ul.no-bullet{list-style:none}
|
||||
ol li ul,ol li ol{margin-left:1.25em;margin-bottom:0}
|
||||
dl dt{margin-bottom:.3125em;font-weight:bold}
|
||||
dl dd{margin-bottom:1.25em}
|
||||
abbr,acronym{text-transform:uppercase;font-size:90%;color:rgba(0,0,0,.8);border-bottom:1px dotted #ddd;cursor:help}
|
||||
abbr{text-transform:none}
|
||||
blockquote{margin:0 0 1.25em;padding:.5625em 1.25em 0 1.1875em;border-left:1px solid #ddd}
|
||||
blockquote cite{display:block;font-size:.9375em;color:rgba(0,0,0,.6)}
|
||||
blockquote cite:before{content:"\2014 \0020"}
|
||||
blockquote cite a,blockquote cite a:visited{color:rgba(0,0,0,.6)}
|
||||
blockquote,blockquote p{line-height:1.6;color:rgba(0,0,0,.85)}
|
||||
@media only screen and (min-width:768px){h1,h2,h3,#toctitle,.sidebarblock>.content>.title,h4,h5,h6{line-height:1.2}
|
||||
h1{font-size:2.75em}
|
||||
h2{font-size:2.3125em}
|
||||
h3,#toctitle,.sidebarblock>.content>.title{font-size:1.6875em}
|
||||
h4{font-size:1.4375em}}table{background:#fff;margin-bottom:1.25em;border:solid 1px #dedede}
|
||||
table thead,table tfoot{background:#f7f8f7;font-weight:bold}
|
||||
table thead tr th,table thead tr td,table tfoot tr th,table tfoot tr td{padding:.5em .625em .625em;font-size:inherit;color:rgba(0,0,0,.8);text-align:left}
|
||||
table tr th,table tr td{padding:.5625em .625em;font-size:inherit;color:rgba(0,0,0,.8)}
|
||||
table tr.even,table tr.alt,table tr:nth-of-type(even){background:#f8f8f7}
|
||||
table thead tr th,table tfoot tr th,table tbody tr td,table tr td,table tfoot tr td{display:table-cell;line-height:1.6}
|
||||
h1,h2,h3,#toctitle,.sidebarblock>.content>.title,h4,h5,h6{line-height:1.2;word-spacing:-.05em}
|
||||
h1 strong,h2 strong,h3 strong,#toctitle strong,.sidebarblock>.content>.title strong,h4 strong,h5 strong,h6 strong{font-weight:400}
|
||||
.clearfix:before,.clearfix:after,.float-group:before,.float-group:after{content:" ";display:table}
|
||||
.clearfix:after,.float-group:after{clear:both}
|
||||
*:not(pre)>code{font-size:.9375em;font-style:normal!important;letter-spacing:0;padding:.1em .5ex;word-spacing:-.15em;background-color:#f7f7f8;-webkit-border-radius:4px;border-radius:4px;line-height:1.45;text-rendering:optimizeSpeed}
|
||||
pre,pre>code{line-height:1.45;color:rgba(0,0,0,.9);font-family:"Droid Sans Mono","DejaVu Sans Mono",monospace;font-weight:400;text-rendering:optimizeSpeed}
|
||||
.keyseq{color:rgba(51,51,51,.8)}
|
||||
kbd{display:inline-block;color:rgba(0,0,0,.8);font-size:.75em;line-height:1.4;background-color:#f7f7f7;border:1px solid #ccc;-webkit-border-radius:3px;border-radius:3px;-webkit-box-shadow:0 1px 0 rgba(0,0,0,.2),0 0 0 .1em white inset;box-shadow:0 1px 0 rgba(0,0,0,.2),0 0 0 .1em #fff inset;margin:-.15em .15em 0 .15em;padding:.2em .6em .2em .5em;vertical-align:middle;white-space:nowrap}
|
||||
.keyseq kbd:first-child{margin-left:0}
|
||||
.keyseq kbd:last-child{margin-right:0}
|
||||
.menuseq,.menu{color:rgba(0,0,0,.8)}
|
||||
b.button:before,b.button:after{position:relative;top:-1px;font-weight:400}
|
||||
b.button:before{content:"[";padding:0 3px 0 2px}
|
||||
b.button:after{content:"]";padding:0 2px 0 3px}
|
||||
p a>code:hover{color:rgba(0,0,0,.9)}
|
||||
#header,#content,#footnotes,#footer{width:100%;margin-left:auto;margin-right:auto;margin-top:0;margin-bottom:0;max-width:62.5em;*zoom:1;position:relative;padding-left:.9375em;padding-right:.9375em}
|
||||
#header:before,#header:after,#content:before,#content:after,#footnotes:before,#footnotes:after,#footer:before,#footer:after{content:" ";display:table}
|
||||
#header:after,#content:after,#footnotes:after,#footer:after{clear:both}
|
||||
#content{margin-top:1.25em}
|
||||
#content:before{content:none}
|
||||
#header>h1:first-child{color:rgba(0,0,0,.85);margin-top:2.25rem;margin-bottom:0}
|
||||
#header>h1:first-child+#toc{margin-top:8px;border-top:1px solid #ddddd8}
|
||||
#header>h1:only-child,body.toc2 #header>h1:nth-last-child(2){border-bottom:1px solid #ddddd8;padding-bottom:8px}
|
||||
#header .details{border-bottom:1px solid #ddddd8;line-height:1.45;padding-top:.25em;padding-bottom:.25em;padding-left:.25em;color:rgba(0,0,0,.6);display:-ms-flexbox;display:-webkit-flex;display:flex;-ms-flex-flow:row wrap;-webkit-flex-flow:row wrap;flex-flow:row wrap}
|
||||
#header .details span:first-child{margin-left:-.125em}
|
||||
#header .details span.email a{color:rgba(0,0,0,.85)}
|
||||
#header .details br{display:none}
|
||||
#header .details br+span:before{content:"\00a0\2013\00a0"}
|
||||
#header .details br+span.author:before{content:"\00a0\22c5\00a0";color:rgba(0,0,0,.85)}
|
||||
#header .details br+span#revremark:before{content:"\00a0|\00a0"}
|
||||
#header #revnumber{text-transform:capitalize}
|
||||
#header #revnumber:after{content:"\00a0"}
|
||||
#content>h1:first-child:not([class]){color:rgba(0,0,0,.85);border-bottom:1px solid #ddddd8;padding-bottom:8px;margin-top:0;padding-top:1rem;margin-bottom:1.25rem}
|
||||
#toc{border-bottom:1px solid #efefed;padding-bottom:.5em}
|
||||
#toc>ul{margin-left:.125em}
|
||||
#toc ul.sectlevel0>li>a{font-style:italic}
|
||||
#toc ul.sectlevel0 ul.sectlevel1{margin:.5em 0}
|
||||
#toc ul{font-family:"Open Sans","DejaVu Sans",sans-serif;list-style-type:none}
|
||||
#toc a{text-decoration:none}
|
||||
#toc a:active{text-decoration:underline}
|
||||
#toctitle{color:#7a2518;font-size:1.2em}
|
||||
@media only screen and (min-width:768px){#toctitle{font-size:1.375em}
|
||||
body.toc2{padding-left:15em;padding-right:0}
|
||||
#toc.toc2{margin-top:0!important;background-color:#f8f8f7;position:fixed;width:15em;left:0;top:0;border-right:1px solid #efefed;border-top-width:0!important;border-bottom-width:0!important;z-index:1000;padding:1.25em 1em;height:100%;overflow:auto}
|
||||
#toc.toc2 #toctitle{margin-top:0;font-size:1.2em}
|
||||
#toc.toc2>ul{font-size:.9em;margin-bottom:0}
|
||||
#toc.toc2 ul ul{margin-left:0;padding-left:1em}
|
||||
#toc.toc2 ul.sectlevel0 ul.sectlevel1{padding-left:0;margin-top:.5em;margin-bottom:.5em}
|
||||
body.toc2.toc-right{padding-left:0;padding-right:15em}
|
||||
body.toc2.toc-right #toc.toc2{border-right-width:0;border-left:1px solid #efefed;left:auto;right:0}}@media only screen and (min-width:1280px){body.toc2{padding-left:20em;padding-right:0}
|
||||
#toc.toc2{width:20em}
|
||||
#toc.toc2 #toctitle{font-size:1.375em}
|
||||
#toc.toc2>ul{font-size:.95em}
|
||||
#toc.toc2 ul ul{padding-left:1.25em}
|
||||
body.toc2.toc-right{padding-left:0;padding-right:20em}}#content #toc{border-style:solid;border-width:1px;border-color:#e0e0dc;margin-bottom:1.25em;padding:1.25em;background:#f8f8f7;-webkit-border-radius:4px;border-radius:4px}
|
||||
#content #toc>:first-child{margin-top:0}
|
||||
#content #toc>:last-child{margin-bottom:0}
|
||||
#footer{max-width:100%;background-color:rgba(0,0,0,.8);padding:1.25em}
|
||||
#footer-text,#footer_nav{color:rgba(255,255,255,.8);line-height:1.44}
|
||||
#footer a{color: #990000}
|
||||
.sect1{padding-bottom:.625em}
|
||||
@media only screen and (min-width:768px){.sect1{padding-bottom:1.25em}}.sect1+.sect1{border-top:1px solid #efefed}
|
||||
#content h1>a.anchor,h2>a.anchor,h3>a.anchor,#toctitle>a.anchor,.sidebarblock>.content>.title>a.anchor,h4>a.anchor,h5>a.anchor,h6>a.anchor{position:absolute;z-index:1001;width:1.5ex;margin-left:-1.5ex;display:block;text-decoration:none!important;visibility:hidden;text-align:center;font-weight:400}
|
||||
#content h1>a.anchor:before,h2>a.anchor:before,h3>a.anchor:before,#toctitle>a.anchor:before,.sidebarblock>.content>.title>a.anchor:before,h4>a.anchor:before,h5>a.anchor:before,h6>a.anchor:before{content:"\00A7";font-size:.85em;display:block;padding-top:.1em}
|
||||
#content h1:hover>a.anchor,#content h1>a.anchor:hover,h2:hover>a.anchor,h2>a.anchor:hover,h3:hover>a.anchor,#toctitle:hover>a.anchor,.sidebarblock>.content>.title:hover>a.anchor,h3>a.anchor:hover,#toctitle>a.anchor:hover,.sidebarblock>.content>.title>a.anchor:hover,h4:hover>a.anchor,h4>a.anchor:hover,h5:hover>a.anchor,h5>a.anchor:hover,h6:hover>a.anchor,h6>a.anchor:hover{visibility:visible}
|
||||
#content h1>a.link,h2>a.link,h3>a.link,#toctitle>a.link,.sidebarblock>.content>.title>a.link,h4>a.link,h5>a.link,h6>a.link{color:#990000;text-decoration:none}
|
||||
#content h1>a.link:hover,h2>a.link:hover,h3>a.link:hover,#toctitle>a.link:hover,.sidebarblock>.content>.title>a.link:hover,h4>a.link:hover,h5>a.link:hover,h6>a.link:hover{color:#a53221}
|
||||
.audioblock,.imageblock,.literalblock,.listingblock,.stemblock,.videoblock{margin-bottom:1.25em}
|
||||
.admonitionblock td.content>.title,.audioblock>.title,.exampleblock>.title,.imageblock>.title,.listingblock>.title,.literalblock>.title,.stemblock>.title,.openblock>.title,.paragraph>.title,.quoteblock>.title,table.tableblock>.title,.verseblock>.title,.videoblock>.title,.dlist>.title,.olist>.title,.ulist>.title,.qlist>.title,.hdlist>.title{text-rendering:optimizeLegibility;text-align:left;font-family:"Noto Serif","DejaVu Serif",serif;font-size:1rem;font-style:italic}
|
||||
table.tableblock>caption.title{white-space:nowrap;overflow:visible;max-width:0}
|
||||
.paragraph.lead>p,#preamble>.sectionbody>.paragraph:first-of-type p{color:rgba(0,0,0,.85)}
|
||||
table.tableblock #preamble>.sectionbody>.paragraph:first-of-type p{font-size:inherit}
|
||||
.admonitionblock>table{border-collapse:separate;border:0;background:none;width:100%}
|
||||
.admonitionblock>table td.icon{text-align:center;width:80px}
|
||||
.admonitionblock>table td.icon img{max-width:none}
|
||||
.admonitionblock>table td.icon .title{font-weight:bold;font-family:"Open Sans","DejaVu Sans",sans-serif;text-transform:uppercase}
|
||||
.admonitionblock>table td.content{padding-left:1.125em;padding-right:1.25em;border-left:1px solid #ddddd8;color:rgba(0,0,0,.6)}
|
||||
.admonitionblock>table td.content>:last-child>:last-child{margin-bottom:0}
|
||||
.exampleblock>.content{border-style:solid;border-width:1px;border-color:#e6e6e6;margin-bottom:1.25em;padding:1.25em;background:#fff;-webkit-border-radius:4px;border-radius:4px}
|
||||
.exampleblock>.content>:first-child{margin-top:0}
|
||||
.exampleblock>.content>:last-child{margin-bottom:0}
|
||||
.sidebarblock{border-style:solid;border-width:1px;border-color:#e0e0dc;margin-bottom:1.25em;padding:1.25em;background:#f8f8f7;-webkit-border-radius:4px;border-radius:4px}
|
||||
.sidebarblock>:first-child{margin-top:0}
|
||||
.sidebarblock>:last-child{margin-bottom:0}
|
||||
.sidebarblock>.content>.title{color:#7a2518;margin-top:0;text-align:center}
|
||||
.exampleblock>.content>:last-child>:last-child,.exampleblock>.content .olist>ol>li:last-child>:last-child,.exampleblock>.content .ulist>ul>li:last-child>:last-child,.exampleblock>.content .qlist>ol>li:last-child>:last-child,.sidebarblock>.content>:last-child>:last-child,.sidebarblock>.content .olist>ol>li:last-child>:last-child,.sidebarblock>.content .ulist>ul>li:last-child>:last-child,.sidebarblock>.content .qlist>ol>li:last-child>:last-child{margin-bottom:0}
|
||||
.literalblock pre,.listingblock pre:not(.highlight),.listingblock pre[class="highlight"],.listingblock pre[class^="highlight "],.listingblock pre.CodeRay,.listingblock pre.prettyprint{background:#f7f7f8}
|
||||
.sidebarblock .literalblock pre,.sidebarblock .listingblock pre:not(.highlight),.sidebarblock .listingblock pre[class="highlight"],.sidebarblock .listingblock pre[class^="highlight "],.sidebarblock .listingblock pre.CodeRay,.sidebarblock .listingblock pre.prettyprint{background:#f2f1f1}
|
||||
.literalblock pre,.literalblock pre[class],.listingblock pre,.listingblock pre[class]{-webkit-border-radius:4px;border-radius:4px;word-wrap:break-word;padding:1em;font-size:.8125em}
|
||||
.literalblock pre.nowrap,.literalblock pre[class].nowrap,.listingblock pre.nowrap,.listingblock pre[class].nowrap{overflow-x:auto;white-space:pre;word-wrap:normal}
|
||||
@media only screen and (min-width:768px){.literalblock pre,.literalblock pre[class],.listingblock pre,.listingblock pre[class]{font-size:.90625em}}@media only screen and (min-width:1280px){.literalblock pre,.literalblock pre[class],.listingblock pre,.listingblock pre[class]{font-size:1em}}.literalblock.output pre{color:#f7f7f8;background-color:rgba(0,0,0,.9)}
|
||||
.listingblock pre.highlightjs{padding:0}
|
||||
.listingblock pre.highlightjs>code{padding:1em;-webkit-border-radius:4px;border-radius:4px}
|
||||
.listingblock pre.prettyprint{border-width:0}
|
||||
.listingblock>.content{position:relative}
|
||||
.listingblock code[data-lang]:before{display:none;content:attr(data-lang);position:absolute;font-size:.75em;top:.425rem;right:.5rem;line-height:1;text-transform:uppercase;color:#999}
|
||||
.listingblock:hover code[data-lang]:before{display:block}
|
||||
.listingblock.terminal pre .command:before{content:attr(data-prompt);padding-right:.5em;color:#999}
|
||||
.listingblock.terminal pre .command:not([data-prompt]):before{content:"$"}
|
||||
table.pyhltable{border-collapse:separate;border:0;margin-bottom:0;background:none}
|
||||
table.pyhltable td{vertical-align:top;padding-top:0;padding-bottom:0}
|
||||
table.pyhltable td.code{padding-left:.75em;padding-right:0}
|
||||
pre.pygments .lineno,table.pyhltable td:not(.code){color:#999;padding-left:0;padding-right:.5em;border-right:1px solid #ddddd8}
|
||||
pre.pygments .lineno{display:inline-block;margin-right:.25em}
|
||||
table.pyhltable .linenodiv{background:none!important;padding-right:0!important}
|
||||
.quoteblock{margin:0 1em 1.25em 1.5em;display:table}
|
||||
.quoteblock>.title{margin-left:-1.5em;margin-bottom:.75em}
|
||||
.quoteblock blockquote,.quoteblock blockquote p{color:rgba(0,0,0,.85);font-size:1.15rem;line-height:1.75;word-spacing:.1em;letter-spacing:0;font-style:italic;text-align:justify}
|
||||
.quoteblock blockquote{margin:0;padding:0;border:0}
|
||||
.quoteblock blockquote:before{content:"\201c";float:left;font-size:2.75em;font-weight:bold;line-height:.6em;margin-left:-.6em;color:#7a2518;text-shadow:0 1px 2px rgba(0,0,0,.1)}
|
||||
.quoteblock blockquote>.paragraph:last-child p{margin-bottom:0}
|
||||
.quoteblock .attribution{margin-top:.5em;margin-right:.5ex;text-align:right}
|
||||
.quoteblock .quoteblock{margin-left:0;margin-right:0;padding:.5em 0;border-left:3px solid rgba(0,0,0,.6)}
|
||||
.quoteblock .quoteblock blockquote{padding:0 0 0 .75em}
|
||||
.quoteblock .quoteblock blockquote:before{display:none}
|
||||
.verseblock{margin:0 1em 1.25em 1em}
|
||||
.verseblock pre{font-family:"Open Sans","DejaVu Sans",sans;font-size:1.15rem;color:rgba(0,0,0,.85);font-weight:300;text-rendering:optimizeLegibility}
|
||||
.verseblock pre strong{font-weight:400}
|
||||
.verseblock .attribution{margin-top:1.25rem;margin-left:.5ex}
|
||||
.quoteblock .attribution,.verseblock .attribution{font-size:.9375em;line-height:1.45;font-style:italic}
|
||||
.quoteblock .attribution br,.verseblock .attribution br{display:none}
|
||||
.quoteblock .attribution cite,.verseblock .attribution cite{display:block;letter-spacing:-.05em;color:rgba(0,0,0,.6)}
|
||||
.quoteblock.abstract{margin:0 0 1.25em 0;display:block}
|
||||
.quoteblock.abstract blockquote,.quoteblock.abstract blockquote p{text-align:left;word-spacing:0}
|
||||
.quoteblock.abstract blockquote:before,.quoteblock.abstract blockquote p:first-of-type:before{display:none}
|
||||
table.tableblock{max-width:100%;border-collapse:separate}
|
||||
table.tableblock td>.paragraph:last-child p>p:last-child,table.tableblock th>p:last-child,table.tableblock td>p:last-child{margin-bottom:0}
|
||||
table.spread{width:100%}
|
||||
table.tableblock,th.tableblock,td.tableblock{border:0 solid #dedede}
|
||||
table.grid-all th.tableblock,table.grid-all td.tableblock{border-width:0 1px 1px 0}
|
||||
table.grid-all tfoot>tr>th.tableblock,table.grid-all tfoot>tr>td.tableblock{border-width:1px 1px 0 0}
|
||||
table.grid-cols th.tableblock,table.grid-cols td.tableblock{border-width:0 1px 0 0}
|
||||
table.grid-all *>tr>.tableblock:last-child,table.grid-cols *>tr>.tableblock:last-child{border-right-width:0}
|
||||
table.grid-rows th.tableblock,table.grid-rows td.tableblock{border-width:0 0 1px 0}
|
||||
table.grid-all tbody>tr:last-child>th.tableblock,table.grid-all tbody>tr:last-child>td.tableblock,table.grid-all thead:last-child>tr>th.tableblock,table.grid-rows tbody>tr:last-child>th.tableblock,table.grid-rows tbody>tr:last-child>td.tableblock,table.grid-rows thead:last-child>tr>th.tableblock{border-bottom-width:0}
|
||||
table.grid-rows tfoot>tr>th.tableblock,table.grid-rows tfoot>tr>td.tableblock{border-width:1px 0 0 0}
|
||||
table.frame-all{border-width:1px}
|
||||
table.frame-sides{border-width:0 1px}
|
||||
table.frame-topbot{border-width:1px 0}
|
||||
th.halign-left,td.halign-left{text-align:left}
|
||||
th.halign-right,td.halign-right{text-align:right}
|
||||
th.halign-center,td.halign-center{text-align:center}
|
||||
th.valign-top,td.valign-top{vertical-align:top}
|
||||
th.valign-bottom,td.valign-bottom{vertical-align:bottom}
|
||||
th.valign-middle,td.valign-middle{vertical-align:middle}
|
||||
table thead th,table tfoot th{font-weight:bold}
|
||||
tbody tr th{display:table-cell;line-height:1.6;background:#f7f8f7}
|
||||
tbody tr th,tbody tr th p,tfoot tr th,tfoot tr th p{color:rgba(0,0,0,.8);font-weight:bold}
|
||||
p.tableblock>code:only-child{background:none;padding:0}
|
||||
p.tableblock{font-size:1em}
|
||||
td>div.verse{white-space:pre}
|
||||
ol{margin-left:1.75em}
|
||||
ul li ol{margin-left:1.5em}
|
||||
dl dd{margin-left:1.125em}
|
||||
dl dd:last-child,dl dd:last-child>:last-child{margin-bottom:0}
|
||||
ol>li p,ul>li p,ul dd,ol dd,.olist .olist,.ulist .ulist,.ulist .olist,.olist .ulist{margin-bottom:.625em}
|
||||
ul.unstyled,ol.unnumbered,ul.checklist,ul.none{list-style-type:none}
|
||||
ul.unstyled,ol.unnumbered,ul.checklist{margin-left:.625em}
|
||||
ul.checklist li>p:first-child>.fa-square-o:first-child,ul.checklist li>p:first-child>.fa-check-square-o:first-child{width:1em;font-size:.85em}
|
||||
ul.checklist li>p:first-child>input[type="checkbox"]:first-child{width:1em;position:relative;top:1px}
|
||||
ul.inline{margin:0 auto .625em auto;margin-left:-1.375em;margin-right:0;padding:0;list-style:none;overflow:hidden}
|
||||
ul.inline>li{list-style:none;float:left;margin-left:1.375em;display:block}
|
||||
ul.inline>li>*{display:block}
|
||||
.unstyled dl dt{font-weight:400;font-style:normal}
|
||||
ol.arabic{list-style-type:decimal}
|
||||
ol.decimal{list-style-type:decimal-leading-zero}
|
||||
ol.loweralpha{list-style-type:lower-alpha}
|
||||
ol.upperalpha{list-style-type:upper-alpha}
|
||||
ol.lowerroman{list-style-type:lower-roman}
|
||||
ol.upperroman{list-style-type:upper-roman}
|
||||
ol.lowergreek{list-style-type:lower-greek}
|
||||
.hdlist>table,.colist>table{border:0;background:none}
|
||||
.hdlist>table>tbody>tr,.colist>table>tbody>tr{background:none}
|
||||
td.hdlist1{padding-right:.75em;font-weight:bold}
|
||||
td.hdlist1,td.hdlist2{vertical-align:top}
|
||||
.literalblock+.colist,.listingblock+.colist{margin-top:-.5em}
|
||||
.colist>table tr>td:first-of-type{padding:0 .75em;line-height:1}
|
||||
.colist>table tr>td:last-of-type{padding:.25em 0}
|
||||
.thumb,.th{line-height:0;display:inline-block;border:solid 4px #fff;-webkit-box-shadow:0 0 0 1px #ddd;box-shadow:0 0 0 1px #ddd}
|
||||
.imageblock.left,.imageblock[style*="float: left"]{margin:.25em .625em 1.25em 0}
|
||||
.imageblock.right,.imageblock[style*="float: right"]{margin:.25em 0 1.25em .625em}
|
||||
.imageblock>.title{margin-bottom:0}
|
||||
.imageblock.thumb,.imageblock.th{border-width:6px}
|
||||
.imageblock.thumb>.title,.imageblock.th>.title{padding:0 .125em}
|
||||
.image.left,.image.right{margin-top:.25em;margin-bottom:.25em;display:inline-block;line-height:0}
|
||||
.image.left{margin-right:.625em}
|
||||
.image.right{margin-left:.625em}
|
||||
a.image{text-decoration:none}
|
||||
span.footnote,span.footnoteref{vertical-align:super;font-size:.875em}
|
||||
span.footnote a,span.footnoteref a{text-decoration:none}
|
||||
span.footnote a:active,span.footnoteref a:active{text-decoration:underline}
|
||||
#footnotes{padding-top:.75em;padding-bottom:.75em;margin-bottom:.625em}
|
||||
#footnotes hr{width:20%;min-width:6.25em;margin:-.25em 0 .75em 0;border-width:1px 0 0 0}
|
||||
#footnotes .footnote{padding:0 .375em;line-height:1.3;font-size:.875em;margin-left:1.2em;text-indent:-1.2em;margin-bottom:.2em}
|
||||
#footnotes .footnote a:first-of-type{font-weight:bold;text-decoration:none}
|
||||
#footnotes .footnote:last-of-type{margin-bottom:0}
|
||||
#content #footnotes{margin-top:-.625em;margin-bottom:0;padding:.75em 0}
|
||||
.gist .file-data>table{border:0;background:#fff;width:100%;margin-bottom:0}
|
||||
.gist .file-data>table td.line-data{width:99%}
|
||||
div.unbreakable{page-break-inside:avoid}
|
||||
.big{font-size:larger}
|
||||
.small{font-size:smaller}
|
||||
.underline{text-decoration:underline}
|
||||
.overline{text-decoration:overline}
|
||||
.line-through{text-decoration:line-through}
|
||||
.aqua{color:#00bfbf}
|
||||
.aqua-background{background-color:#00fafa}
|
||||
.black{color:#000}
|
||||
.black-background{background-color:#000}
|
||||
.blue{color:#0000bf}
|
||||
.blue-background{background-color:#0000fa}
|
||||
.fuchsia{color:#bf00bf}
|
||||
.fuchsia-background{background-color:#fa00fa}
|
||||
.gray{color:#606060}
|
||||
.gray-background{background-color:#7d7d7d}
|
||||
.green{color:#006000}
|
||||
.green-background{background-color:#007d00}
|
||||
.lime{color:#00bf00}
|
||||
.lime-background{background-color:#00fa00}
|
||||
.maroon{color:#600000}
|
||||
.maroon-background{background-color:#7d0000}
|
||||
.navy{color:#000060}
|
||||
.navy-background{background-color:#00007d}
|
||||
.olive{color:#606000}
|
||||
.olive-background{background-color:#7d7d00}
|
||||
.purple{color:#600060}
|
||||
.purple-background{background-color:#7d007d}
|
||||
.red{color:#bf0000}
|
||||
.red-background{background-color:#fa0000}
|
||||
.silver{color:#909090}
|
||||
.silver-background{background-color:#bcbcbc}
|
||||
.teal{color:#006060}
|
||||
.teal-background{background-color:#007d7d}
|
||||
.white{color:#bfbfbf}
|
||||
.white-background{background-color:#fafafa}
|
||||
.yellow{color:#bfbf00}
|
||||
.yellow-background{background-color:#fafa00}
|
||||
span.icon>.fa{cursor:default}
|
||||
.admonitionblock td.icon [class^="fa icon-"]{font-size:2.5em;text-shadow:1px 1px 2px rgba(0,0,0,.5);cursor:default}
|
||||
.admonitionblock td.icon .icon-note:before{content:"\f05a";color:#19407c}
|
||||
.admonitionblock td.icon .icon-tip:before{content:"\f0eb";text-shadow:1px 1px 2px rgba(155,155,0,.8);color:#111}
|
||||
.admonitionblock td.icon .icon-warning:before{content:"\f071";color:#bf6900}
|
||||
.admonitionblock td.icon .icon-caution:before{content:"\f06d";color:#bf3400}
|
||||
.admonitionblock td.icon .icon-important:before{content:"\f06a";color:#bf0000}
|
||||
.conum[data-value]{display:inline-block;color:#fff!important;background-color:rgba(0,0,0,.8);-webkit-border-radius:100px;border-radius:100px;text-align:center;font-size:.75em;width:1.67em;height:1.67em;line-height:1.67em;font-family:"Open Sans","DejaVu Sans",sans-serif;font-style:normal;font-weight:bold}
|
||||
.conum[data-value] *{color:#fff!important}
|
||||
.conum[data-value]+b{display:none}
|
||||
.conum[data-value]:after{content:attr(data-value)}
|
||||
pre .conum[data-value]{position:relative;top:-.125em}
|
||||
b.conum *{color:inherit!important}
|
||||
.conum:not([data-value]):empty{display:none}
|
||||
h1,h2{letter-spacing:-.01em}
|
||||
dt,th.tableblock,td.content{text-rendering:optimizeLegibility}
|
||||
p,td.content{letter-spacing:-.01em}
|
||||
p strong,td.content strong{letter-spacing:-.005em}
|
||||
p,blockquote,dt,td.content{font-size:1.0625rem}
|
||||
p{margin-bottom:1.25rem}
|
||||
.sidebarblock p,.sidebarblock dt,.sidebarblock td.content,p.tableblock{font-size:1em}
|
||||
.exampleblock>.content{background-color:#fffef7;border-color:#e0e0dc;-webkit-box-shadow:0 1px 4px #e0e0dc;box-shadow:0 1px 4px #e0e0dc}
|
||||
.print-only{display:none!important}
|
||||
@media print{@page{margin:1.25cm .75cm}
|
||||
*{-webkit-box-shadow:none!important;box-shadow:none!important;text-shadow:none!important}
|
||||
a{color:inherit!important;text-decoration:underline!important}
|
||||
a.bare,a[href^="#"],a[href^="mailto:"]{text-decoration:none!important}
|
||||
a[href^="http:"]:not(.bare):after,a[href^="https:"]:not(.bare):after{content:"(" attr(href) ")";display:inline-block;font-size:.875em;padding-left:.25em}
|
||||
abbr[title]:after{content:" (" attr(title) ")"}
|
||||
pre,blockquote,tr,img{page-break-inside:avoid}
|
||||
thead{display:table-header-group}
|
||||
img{max-width:100%!important}
|
||||
p,blockquote,dt,td.content{font-size:1em;orphans:3;widows:3}
|
||||
h2,h3,#toctitle,.sidebarblock>.content>.title{page-break-after:avoid}
|
||||
#toc,.sidebarblock,.exampleblock>.content{background:none!important}
|
||||
#toc{border-bottom:1px solid #ddddd8!important;padding-bottom:0!important}
|
||||
.sect1{padding-bottom:0!important}
|
||||
.sect1+.sect1{border:0!important}
|
||||
#header>h1:first-child{margin-top:1.25rem}
|
||||
body.book #header{text-align:center}
|
||||
body.book #header>h1:first-child{border:0!important;margin:2.5em 0 1em 0}
|
||||
body.book #header .details{border:0!important;display:block;padding:0!important}
|
||||
body.book #header .details span:first-child{margin-left:0!important}
|
||||
body.book #header .details br{display:block}
|
||||
body.book #header .details br+span:before{content:none!important}
|
||||
body.book #toc{border:0!important;text-align:left!important;padding:0!important;margin:0!important}
|
||||
body.book #toc,body.book #preamble,body.book h1.sect0,body.book .sect1>h2{page-break-before:always}
|
||||
.listingblock code[data-lang]:before{display:block}
|
||||
#footer{background:none!important;padding:0 .9375em}
|
||||
#footer-text{color:rgba(0,0,0,.6)!important;font-size:.9em}
|
||||
.hide-on-print{display:none!important}
|
||||
.print-only{display:block!important}
|
||||
.hide-for-print{display:none!important}
|
||||
.show-for-print{display:inherit!important}}
|
||||
|
|
@ -0,0 +1 @@
|
|||
../site/resources/images
|
||||
|
|
@ -0,0 +1,114 @@
|
|||
////
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
= Apache HBase (TM) ACID Properties
|
||||
|
||||
== About this Document
|
||||
|
||||
Apache HBase (TM) is not an ACID compliant database. However, it does guarantee certain specific properties.
|
||||
|
||||
This specification enumerates the ACID properties of HBase.
|
||||
|
||||
== Definitions
|
||||
|
||||
For the sake of common vocabulary, we define the following terms:
|
||||
Atomicity::
|
||||
An operation is atomic if it either completes entirely or not at all.
|
||||
|
||||
Consistency::
|
||||
All actions cause the table to transition from one valid state directly to another (eg a row will not disappear during an update, etc).
|
||||
|
||||
Isolation::
|
||||
an operation is isolated if it appears to complete independently of any other concurrent transaction.
|
||||
|
||||
Durability::
|
||||
Any update that reports "successful" to the client will not be lost.
|
||||
|
||||
Visibility::
|
||||
An update is considered visible if any subsequent read will see the update as having been committed.
|
||||
|
||||
|
||||
The terms _must_ and _may_ are used as specified by link:[RFC 2119].
|
||||
|
||||
In short, the word "must" implies that, if some case exists where the statement is not true, it is a bug. The word _may_ implies that, even if the guarantee is provided in a current release, users should not rely on it.
|
||||
|
||||
== APIs to Consider
|
||||
- Read APIs
|
||||
* get
|
||||
* scan
|
||||
- Write APIs
|
||||
* put
|
||||
* batch put
|
||||
* delete
|
||||
- Combination (read-modify-write) APIs
|
||||
* incrementColumnValue
|
||||
* checkAndPut
|
||||
|
||||
== Guarantees Provided
|
||||
|
||||
.Atomicity
|
||||
. All mutations are atomic within a row. Any put will either wholely succeed or wholely fail.footnoteref[Puts will either wholely succeed or wholely fail, provided that they are actually sent to the RegionServer. If the writebuffer is used, Puts will not be sent until the writebuffer is filled or it is explicitly flushed.]
|
||||
.. An operation that returns a _success_ code has completely succeeded.
|
||||
.. An operation that returns a _failure_ code has completely failed.
|
||||
.. An operation that times out may have succeeded and may have failed. However, it will not have partially succeeded or failed.
|
||||
. This is true even if the mutation crosses multiple column families within a row.
|
||||
. APIs that mutate several rows will _not_ be atomic across the multiple rows. For example, a multiput that operates on rows 'a','b', and 'c' may return having mutated some but not all of the rows. In such cases, these APIs will return a list of success codes, each of which may be succeeded, failed, or timed out as described above.
|
||||
. The checkAndPut API happens atomically like the typical _compareAndSet (CAS)_ operation found in many hardware architectures.
|
||||
. The order of mutations is seen to happen in a well-defined order for each row, with no interleaving. For example, if one writer issues the mutation `a=1,b=1,c=1` and another writer issues the mutation `a=2,b=2,c=`, the row must either be `a=1,b=1,c=1` or `a=2,b=2,c=2` and must *not* be something like `a=1,b=2,c=1`. +
|
||||
NOTE:This is not true _across rows_ for multirow batch mutations.
|
||||
|
||||
== Consistency and Isolation
|
||||
. All rows returned via any access API will consist of a complete row that existed at some point in the table's history.
|
||||
. This is true across column families - i.e a get of a full row that occurs concurrent with some mutations 1,2,3,4,5 will return a complete row that existed at some point in time between mutation i and i+1 for some i between 1 and 5.
|
||||
. The state of a row will only move forward through the history of edits to it.
|
||||
|
||||
== Consistency of Scans
|
||||
A scan is *not* a consistent view of a table. Scans do *not* exhibit _snapshot isolation_.
|
||||
|
||||
Rather, scans have the following properties:
|
||||
. Any row returned by the scan will be a consistent view (i.e. that version of the complete row existed at some point in time)footnoteref[consistency,A consistent view is not guaranteed intra-row scanning -- i.e. fetching a portion of a row in one RPC then going back to fetch another portion of the row in a subsequent RPC. Intra-row scanning happens when you set a limit on how many values to return per Scan#next (See link:http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html#setBatch(int)"[Scan#setBatch(int)]).]
|
||||
. A scan will always reflect a view of the data _at least as new as_ the beginning of the scan. This satisfies the visibility guarantees enumerated below.
|
||||
.. For example, if client A writes data X and then communicates via a side channel to client B, any scans started by client B will contain data at least as new as X.
|
||||
.. A scan _must_ reflect all mutations committed prior to the construction of the scanner, and _may_ reflect some mutations committed subsequent to the construction of the scanner.
|
||||
.. Scans must include _all_ data written prior to the scan (except in the case where data is subsequently mutated, in which case it _may_ reflect the mutation)
|
||||
|
||||
Those familiar with relational databases will recognize this isolation level as "read committed".
|
||||
|
||||
NOTE: The guarantees listed above regarding scanner consistency are referring to "transaction commit time", not the "timestamp" field of each cell. That is to say, a scanner started at time _t_ may see edits with a timestamp value greater than _t_, if those edits were committed with a "forward dated" timestamp before the scanner was constructed.
|
||||
|
||||
== Visibility
|
||||
|
||||
. When a client receives a "success" response for any mutation, that mutation is immediately visible to both that client and any client with whom it later communicates through side channels.footnoteref[consistency]
|
||||
. A row must never exhibit so-called "time-travel" properties. That is to say, if a series of mutations moves a row sequentially through a series of states, any sequence of concurrent reads will return a subsequence of those states. +
|
||||
For example, if a row's cells are mutated using the `incrementColumnValue` API, a client must never see the value of any cell decrease. +
|
||||
This is true regardless of which read API is used to read back the mutation.
|
||||
. Any version of a cell that has been returned to a read operation is guaranteed to be durably stored.
|
||||
|
||||
== Durability
|
||||
. All visible data is also durable data. That is to say, a read will never return data that has not been made durable on disk.footnoteref[durability,In the context of Apache HBase, _durably on disk_; implies an `hflush()` call on the transaction log. This does not actually imply an `fsync()` to magnetic media, but rather just that the data has been written to the OS cache on all replicas of the log. In the case of a full datacenter power loss, it is possible that the edits are not truly durable.]
|
||||
. Any operation that returns a "success" code (eg does not throw an exception) will be made durable.footnoteref[durability]
|
||||
. Any operation that returns a "failure" code will not be made durable (subject to the Atomicity guarantees above).
|
||||
. All reasonable failure scenarios will not affect any of the guarantees of this document.
|
||||
|
||||
== Tunability
|
||||
|
||||
All of the above guarantees must be possible within Apache HBase. For users who would like to trade off some guarantees for performance, HBase may offer several tuning options. For example:
|
||||
|
||||
* Visibility may be tuned on a per-read basis to allow stale reads or time travel.
|
||||
* Durability may be tuned to only flush data to disk on a periodic basis.
|
||||
|
||||
== More Information
|
||||
|
||||
For more information, see the link:book.html#client[client architecture] and link:book.html#datamodel[data model] sections in the Apache HBase Reference Guide.
|
||||
|
|
@ -0,0 +1,19 @@
|
|||
////
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
= Bulk Loads in Apache HBase (TM)
|
||||
|
||||
This page has been retired. The contents have been moved to the link:book.html#arch.bulk.load[Bulk Loading] section in the Reference Guide.
|
||||
|
||||
|
|
@ -0,0 +1,193 @@
|
|||
////
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
|
||||
== Installing Apache HBase (TM) on Windows using Cygwin
|
||||
|
||||
== Introduction
|
||||
|
||||
link:http://hbase.apache.org[Apache HBase (TM)] is a distributed, column-oriented store, modeled after Google's link:http://research.google.com/archive/bigtable.html[BigTable]. Apache HBase is built on top of link:http://hadoop.apache.org[Hadoop] for its link:http://hadoop.apache.org/mapreduce[MapReduce] link:http://hadoop.apache.org/hdfs[distributed file system] implementations. All these projects are open-source and part of the link:http://www.apache.org[Apache Software Foundation].
|
||||
|
||||
== Purpose
|
||||
|
||||
This document explains the *intricacies* of running Apache HBase on Windows using Cygwin* as an all-in-one single-node installation for testing and development. The HBase link:http://hbase.apache.org/apidocs/overview-summary.html#overview_description[Overview] and link:book.html#getting_started[QuickStart] guides on the other hand go a long way in explaning how to setup link:http://hadoop.apache.org/hbase[HBase] in more complex deployment scenarios.
|
||||
|
||||
== Installation
|
||||
|
||||
For running Apache HBase on Windows, 3 technologies are required:
|
||||
* Java
|
||||
* Cygwin
|
||||
* SSH
|
||||
|
||||
The following paragraphs detail the installation of each of the aforementioned technologies.
|
||||
|
||||
=== Java
|
||||
|
||||
HBase depends on the link:http://java.sun.com/javase/6/[Java Platform, Standard Edition, 6 Release]. So the target system has to be provided with at least the Java Runtime Environment (JRE); however if the system will also be used for development, the Jave Development Kit (JDK) is preferred. You can download the latest versions for both from link:http://java.sun.com/javase/downloads/index.jsp[Sun's download page]. Installation is a simple GUI wizard that guides you through the process.
|
||||
|
||||
=== Cygwin
|
||||
|
||||
Cygwin is probably the oddest technology in this solution stack. It provides a dynamic link library that emulates most of a *nix environment on Windows. On top of that a whole bunch of the most common *nix tools are supplied. Combined, the DLL with the tools form a very *nix-alike environment on Windows.
|
||||
|
||||
For installation, Cygwin provides the link:http://cygwin.com/setup.exe[`setup.exe` utility] that tracks the versions of all installed components on the target system and provides the mechanism for installing or updating everything from the mirror sites of Cygwin.
|
||||
|
||||
To support installation, the `setup.exe` utility uses 2 directories on the target system. The *Root* directory for Cygwin (defaults to _C:\cygwin)_ which will become _/_ within the eventual Cygwin installation; and the *Local Package* directory (e.g. _C:\cygsetup_ that is the cache where `setup.exe`stores the packages before they are installed. The cache must not be the same folder as the Cygwin root.
|
||||
|
||||
Perform following steps to install Cygwin, which are elaboratly detailed in the link:http://cygwin.com/cygwin-ug-net/setup-net.html[2nd chapter] of the link:http://cygwin.com/cygwin-ug-net/cygwin-ug-net.html[Cygwin User's Guide].
|
||||
|
||||
. Make sure you have `Administrator` privileges on the target system.
|
||||
. Choose and create you Root and *Local Package* directories. A good suggestion is to use `C:\cygwin\root` and `C:\cygwin\setup` folders.
|
||||
. Download the `setup.exe` utility and save it to the *Local Package* directory. Run the `setup.exe` utility.
|
||||
.. Choose the `Install from Internet` option.
|
||||
.. Choose your *Root* and *Local Package* folders.
|
||||
.. Select an appropriate mirror.
|
||||
.. Don't select any additional packages yet, as we only want to install Cygwin for now.
|
||||
.. Wait for download and install.
|
||||
.. Finish the installation.
|
||||
. Optionally, you can now also add a shortcut to your Start menu pointing to the `setup.exe` utility in the *Local Package *folder.
|
||||
. Add `CYGWIN_HOME` system-wide environment variable that points to your *Root* directory.
|
||||
. Add `%CYGWIN_HOME%\bin` to the end of your `PATH` environment variable.
|
||||
. Reboot the sytem after making changes to the environment variables otherwise the OS will not be able to find the Cygwin utilities.
|
||||
. Test your installation by running your freshly created shortcuts or the `Cygwin.bat` command in the *Root* folder. You should end up in a terminal window that is running a link:http://www.gnu.org/software/bash/manual/bashref.html[Bash shell]. Test the shell by issuing following commands:
|
||||
.. `cd /` should take you to thr *Root* directory in Cygwin.
|
||||
.. The `LS` commands that should list all files and folders in the current directory.
|
||||
.. Use the `exit` command to end the terminal.
|
||||
. When needed, to *uninstall* Cygwin you can simply delete the *Root* and *Local Package* directory, and the *shortcuts* that were created during installation.
|
||||
|
||||
=== SSH
|
||||
|
||||
HBase (and Hadoop) rely on link:http://nl.wikipedia.org/wiki/Secure_Shell[*SSH*] for interprocess/-node *communication* and launching* remote commands*. SSH will be provisioned on the target system via Cygwin, which supports running Cygwin programs as *Windows services*!
|
||||
|
||||
. Rerun the `*setup.exe*`* utility*.
|
||||
. Leave all parameters as is, skipping through the wizard using the `Next` button until the `Select Packages` panel is shown.
|
||||
. Maximize the window and click the `View` button to toggle to the list view, which is ordered alfabetically on `Package`, making it easier to find the packages we'll need.
|
||||
. Select the following packages by clicking the status word (normally `Skip`) so it's marked for installation. Use the `Next `button to download and install the packages.
|
||||
.. `OpenSSH`
|
||||
.. `tcp_wrappers`
|
||||
.. `diffutils`
|
||||
.. `zlib`
|
||||
. Wait for the install to complete and finish the installation.
|
||||
|
||||
=== HBase
|
||||
|
||||
Download the *latest release* of Apache HBase from link:http://www.apache.org/dyn/closer.cgi/hbase/. As the Apache HBase distributable is just a zipped archive, installation is as simple as unpacking the archive so it ends up in its final *installation* directory. Notice that HBase has to be installed in Cygwin and a good directory suggestion is to use `/usr/local/` (or [`*Root* directory]\usr\local` in Windows slang). You should end up with a `/usr/local/hbase-_versi` installation in Cygwin.
|
||||
|
||||
This finishes installation. We go on with the configuration.
|
||||
|
||||
== Configuration
|
||||
|
||||
There are 3 parts left to configure: *Java, SSH and HBase* itself. Following paragraphs explain eacht topic in detail.
|
||||
|
||||
=== Java
|
||||
|
||||
One important thing to remember in shell scripting in general (i.e. *nix and Windows) is that managing, manipulating and assembling path names that contains spaces can be very hard, due to the need to escape and quote those characters and strings. So we try to stay away from spaces in path names. *nix environments can help us out here very easily by using *symbolic links*.
|
||||
|
||||
. Create a link in `/usr/local` to the Java home directory by using the following command and substituting the name of your chosen Java environment: +
|
||||
----
|
||||
LN -s /cygdrive/c/Program\ Files/Java/*_jre name_*/usr/local/*_jre name_*
|
||||
----
|
||||
. Test your java installation by changing directories to your Java folder `CD /usr/local/_jre name_` and issueing the command `./bin/java -version`. This should output your version of the chosen JRE.
|
||||
|
||||
=== SSH
|
||||
|
||||
Configuring *SSH *is quite elaborate, but primarily a question of launching it by default as a* Windows service*.
|
||||
|
||||
. On Windows Vista and above make sure you run the Cygwin shell with *elevated privileges*, by right-clicking on the shortcut an using `Run as Administrator`.
|
||||
. First of all, we have to make sure the *rights on some crucial files* are correct. Use the commands underneath. You can verify all rights by using the `LS -L` command on the different files. Also, notice the auto-completion feature in the shell using `TAB` is extremely handy in these situations.
|
||||
.. `chmod +r /etc/passwd` to make the passwords file readable for all
|
||||
.. `chmod u+w /etc/passwd` to make the passwords file writable for the owner
|
||||
.. `chmod +r /etc/group` to make the groups file readable for all
|
||||
.. `chmod u+w /etc/group` to make the groups file writable for the owner
|
||||
.. `chmod 755 /var` to make the var folder writable to owner and readable and executable to all
|
||||
. Edit the */etc/hosts.allow* file using your favorite editor (why not VI in the shell!) and make sure the following two lines are in there before the `PARANOID` line: +
|
||||
----
|
||||
ALL : localhost 127.0.0.1/32 : allow
|
||||
ALL : [::1]/128 : allow
|
||||
----
|
||||
. Next we have to *configure SSH* by using the script `ssh-host-config`.
|
||||
.. If this script asks to overwrite an existing `/etc/ssh_config`, answer `yes`.
|
||||
.. If this script asks to overwrite an existing `/etc/sshd_config`, answer `yes`.
|
||||
.. If this script asks to use privilege separation, answer `yes`.
|
||||
.. If this script asks to install `sshd` as a service, answer `yes`. Make sure you started your shell as Adminstrator!
|
||||
.. If this script asks for the CYGWIN value, just `enter` as the default is `ntsec`.
|
||||
.. If this script asks to create the `sshd` account, answer `yes`.
|
||||
.. If this script asks to use a different user name as service account, answer `no` as the default will suffice.
|
||||
.. If this script asks to create the `cyg_server` account, answer `yes`. Enter a password for the account.
|
||||
. *Start the SSH service* using `net start sshd` or `cygrunsrv --start sshd`. Notice that `cygrunsrv` is the utility that make the process run as a Windows service. Confirm that you see a message stating that `the CYGWIN sshd service was started succesfully.`
|
||||
. Harmonize Windows and Cygwin* user account* by using the commands: +
|
||||
----
|
||||
mkpasswd -cl > /etc/passwd
|
||||
mkgroup --local > /etc/group
|
||||
----
|
||||
. Test *the installation of SSH:
|
||||
.. Open a new Cygwin terminal.
|
||||
.. Use the command `whoami` to verify your userID.
|
||||
.. Issue an `ssh localhost` to connect to the system itself.
|
||||
.. Answer `yes` when presented with the server's fingerprint.
|
||||
.. Issue your password when prompted.
|
||||
.. Test a few commands in the remote session
|
||||
.. The `exit` command should take you back to your first shell in Cygwin.
|
||||
. `Exit` should terminate the Cygwin shell.
|
||||
|
||||
=== HBase
|
||||
|
||||
If all previous configurations are working properly, we just need some tinkering at the *HBase config* files to properly resolve on Windows/Cygwin. All files and paths referenced here start from the HBase `[*installation* directory]` as working directory.
|
||||
|
||||
. HBase uses the `./conf/*hbase-env.sh*` to configure its dependencies on the runtime environment. Copy and uncomment following lines just underneath their original, change them to fit your environemnt. They should read something like: +
|
||||
----
|
||||
export JAVA_HOME=/usr/local/_jre name_
|
||||
export HBASE_IDENT_STRING=$HOSTNAME
|
||||
----
|
||||
. HBase uses the _./conf/`*hbase-default.xml*`_ file for configuration. Some properties do not resolve to existing directories because the JVM runs on Windows. This is the major issue to keep in mind when working with Cygwin: within the shell all paths are *nix-alike, hence relative to the root `/`. However, every parameter that is to be consumed within the windows processes themself, need to be Windows settings, hence `C:\`-alike. Change following propeties in the configuration file, adjusting paths where necessary to conform with your own installation:
|
||||
.. `hbase.rootdir` must read e.g. `file:///C:/cygwin/root/tmp/hbase/data`
|
||||
.. `hbase.tmp.dir` must read `C:/cygwin/root/tmp/hbase/tmp`
|
||||
.. `hbase.zookeeper.quorum` must read `127.0.0.1` because for some reason `localhost` doesn't seem to resolve properly on Cygwin.
|
||||
. Make sure the configured `hbase.rootdir` and `hbase.tmp.dir` *directories exist* and have the proper* rights* set up e.g. by issuing a `chmod 777` on them.
|
||||
|
||||
== Testing
|
||||
|
||||
This should conclude the installation and configuration of Apache HBase on Windows using Cygwin. So it's time *to test it*.
|
||||
|
||||
. Start a Cygwin* terminal*, if you haven't already.
|
||||
. Change directory to HBase *installation* using `CD /usr/local/hbase-_version_`, preferably using auto-completion.
|
||||
. *Start HBase* using the command `./bin/start-hbase.sh`
|
||||
.. When prompted to accept the SSH fingerprint, answer `yes`.
|
||||
.. When prompted, provide your password. Maybe multiple times.
|
||||
.. When the command completes, the HBase server should have started.
|
||||
.. However, to be absolutely certain, check the logs in the `./logs` directory for any exceptions.
|
||||
. Next we *start the HBase shell* using the command `./bin/hbase shell`
|
||||
. We run some simple *test commands*
|
||||
.. Create a simple table using command `create 'test', 'data'`
|
||||
.. Verify the table exists using the command `list`
|
||||
.. Insert data into the table using e.g. +
|
||||
----
|
||||
put 'test', 'row1', 'data:1', 'value1'
|
||||
put 'test', 'row2', 'data:2', 'value2'
|
||||
put 'test', 'row3', 'data:3', 'value3'
|
||||
----
|
||||
.. List all rows in the table using the command `scan 'test'` that should list all the rows previously inserted. Notice how 3 new columns where added without changing the schema!
|
||||
.. Finally we get rid of the table by issuing `disable 'test'` followed by `drop 'test'` and verified by `list` which should give an empty listing.
|
||||
. *Leave the shell* by `exit`
|
||||
. To *stop the HBase server* issue the `./bin/stop-hbase.sh` command. And wait for it to complete!!! Killing the process might corrupt your data on disk.
|
||||
. In case of *problems*,
|
||||
.. Verify the HBase logs in the `./logs` directory.
|
||||
.. Try to fix the problem
|
||||
.. Get help on the forums or IRC (`#hbase@freenode.net`). People are very active and keen to help out!
|
||||
.. Stop and retest the server.
|
||||
|
||||
== Conclusion
|
||||
|
||||
Now your *HBase *server is running, *start coding* and build that next killer app on this particular, but scalable datastore!
|
||||
|
||||
|
|
@ -0,0 +1,40 @@
|
|||
////
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
|
||||
= Export Control
|
||||
|
||||
This distribution uses or includes cryptographic software. The country in
|
||||
which you currently reside may have restrictions on the import, possession,
|
||||
use, and/or re-export to another country, of encryption software. BEFORE
|
||||
using any encryption software, please check your country's laws, regulations
|
||||
and policies concerning the import, possession, or use, and re-export of
|
||||
encryption software, to see if this is permitted. See the
|
||||
link:http://www.wassenaar.org/[Wassenaar Arrangement] for more
|
||||
information.
|
||||
|
||||
The U.S. Government Department of Commerce, Bureau of Industry and Security
|
||||
(BIS), has classified this software as Export Commodity Control Number (ECCN)
|
||||
5D002.C.1, which includes information security software using or performing
|
||||
cryptographic functions with asymmetric algorithms. The form and manner of this
|
||||
Apache Software Foundation distribution makes it eligible for export under the
|
||||
License Exception ENC Technology Software Unrestricted (TSU) exception (see the
|
||||
BIS Export Administration Regulations, Section 740.13) for both object code and
|
||||
source code.
|
||||
|
||||
Apache HBase uses the built-in java cryptography libraries. See Oracle's
|
||||
information regarding
|
||||
link:http://www.oracle.com/us/products/export/export-regulations-345813.html[Java cryptographic export regulations]
|
||||
for more details.
|
||||
|
|
@ -0,0 +1,71 @@
|
|||
////
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
= Apache HBase™ Home
|
||||
|
||||
.Welcome to Apache HBase(TM)
|
||||
link:http://www.apache.org/[Apache HBase(TM)] is the link:http://hadoop.apache.org[Hadoop] database, a distributed, scalable, big data store.
|
||||
|
||||
.When Would I Use Apache HBase?
|
||||
Use Apache HBase when you need random, realtime read/write access to your Big Data. +
|
||||
This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware.
|
||||
|
||||
Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's link:http://research.google.com/archive/bigtable.html[Bigtable: A Distributed Storage System for Structured Data] by Chang et al.
|
||||
|
||||
Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache HBase provides Bigtable-like capabilities on top of Hadoop and HDFS.
|
||||
|
||||
.Features
|
||||
- Linear and modular scalability.
|
||||
- Strictly consistent reads and writes.
|
||||
- Automatic and configurable sharding of tables
|
||||
- Automatic failover support between RegionServers.
|
||||
- Convenient base classes for backing Hadoop MapReduce jobs with Apache HBase tables.
|
||||
- Easy to use Java API for client access.
|
||||
- Block cache and Bloom Filters for real-time queries.
|
||||
- Query predicate push down via server side Filters
|
||||
- Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options
|
||||
- Extensible jruby-based (JIRB) shell
|
||||
- Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX
|
||||
|
||||
.Where Can I Get More Information?
|
||||
See the link:book.html#arch.overview[Architecture Overview], the link:book.html#faq[FAQ] and the other documentation links at the top!
|
||||
|
||||
.Export Control
|
||||
The HBase distribution includes cryptographic software. See the link:export_control.html[export control notice].
|
||||
|
||||
== News
|
||||
Feb 17, 2015:: link:http://www.meetup.com/hbaseusergroup/events/219260093/[HBase meetup around Strata+Hadoop World] in San Jose
|
||||
|
||||
January 15th, 2015:: link:http://www.meetup.com/hbaseusergroup/events/218744798/[HBase meetup @ AppDynamics] in San Francisco
|
||||
|
||||
November 20th, 2014:: link:http://www.meetup.com/hbaseusergroup/events/205219992/[HBase meetup @ WANdisco] in San Ramon
|
||||
|
||||
October 27th, 2014:: link:http://www.meetup.com/hbaseusergroup/events/207386102/[HBase Meetup @ Apple] in Cupertino
|
||||
|
||||
October 15th, 2014:: link:http://www.meetup.com/HBase-NYC/events/207655552[HBase Meetup @ Google] on the night before Strata/HW in NYC
|
||||
|
||||
September 25th, 2014:: link:http://www.meetup.com/hbaseusergroup/events/203173692/[HBase Meetup @ Continuuity] in Palo Alto
|
||||
|
||||
August 28th, 2014:: link:http://www.meetup.com/hbaseusergroup/events/197773762/[HBase Meetup @ Sift Science] in San Francisco
|
||||
|
||||
July 17th, 2014:: link:http://www.meetup.com/hbaseusergroup/events/190994082/[HBase Meetup @ HP] in Sunnyvale
|
||||
|
||||
June 5th, 2014:: link:http://www.meetup.com/Hadoop-Summit-Community-San-Jose/events/179081342/[HBase BOF at Hadoop Summit], San Jose Convention Center
|
||||
|
||||
May 5th, 2014:: link:http://www.hbasecon.com[HBaseCon2014] at the Hilton San Francisco on Union Square
|
||||
|
||||
March 12th, 2014:: link:http://www.meetup.com/hbaseusergroup/events/160757912/[HBase Meetup @ Ancestry.com] in San Francisco
|
||||
|
||||
View link:old_news.html[Old News]
|
||||
|
|
@ -0,0 +1,97 @@
|
|||
////
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
= Apache HBase (TM) Metrics
|
||||
|
||||
== Introduction
|
||||
Apache HBase (TM) emits Hadoop link:http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/metrics/package-summary.html[metrics].
|
||||
|
||||
== Setup
|
||||
|
||||
First read up on Hadoop link:http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/metrics/package-summary.html[metrics].
|
||||
|
||||
If you are using ganglia, the link:http://wiki.apache.org/hadoop/GangliaMetrics[GangliaMetrics] wiki page is useful read.
|
||||
|
||||
To have HBase emit metrics, edit `$HBASE_HOME/conf/hadoop-metrics.properties` and enable metric 'contexts' per plugin. As of this writing, hadoop supports *file* and *ganglia* plugins. Yes, the hbase metrics files is named hadoop-metrics rather than _hbase-metrics_ because currently at least the hadoop metrics system has the properties filename hardcoded. Per metrics _context_, comment out the NullContext and enable one or more plugins instead.
|
||||
|
||||
If you enable the _hbase_ context, on regionservers you'll see total requests since last
|
||||
metric emission, count of regions and storefiles as well as a count of memstore size.
|
||||
On the master, you'll see a count of the cluster's requests.
|
||||
|
||||
Enabling the _rpc_ context is good if you are interested in seeing
|
||||
metrics on each hbase rpc method invocation (counts and time taken).
|
||||
|
||||
The _jvm_ context is useful for long-term stats on running hbase jvms -- memory used, thread counts, etc. As of this writing, if more than one jvm is running emitting metrics, at least in ganglia, the stats are aggregated rather than reported per instance.
|
||||
|
||||
== Using with JMX
|
||||
|
||||
In addition to the standard output contexts supported by the Hadoop
|
||||
metrics package, you can also export HBase metrics via Java Management
|
||||
Extensions (JMX). This will allow viewing HBase stats in JConsole or
|
||||
any other JMX client.
|
||||
|
||||
=== Enable HBase stats collection
|
||||
|
||||
To enable JMX support in HBase, first edit `$HBASE_HOME/conf/hadoop-metrics.properties` to support metrics refreshing. (If you've running 0.94.1 and above, or have already configured `hadoop-metrics.properties` for another output context, you can skip this step).
|
||||
[source,bash]
|
||||
----
|
||||
# Configuration of the "hbase" context for null
|
||||
hbase.class=org.apache.hadoop.metrics.spi.NullContextWithUpdateThread
|
||||
hbase.period=60
|
||||
|
||||
# Configuration of the "jvm" context for null
|
||||
jvm.class=org.apache.hadoop.metrics.spi.NullContextWithUpdateThread
|
||||
jvm.period=60
|
||||
|
||||
# Configuration of the "rpc" context for null
|
||||
rpc.class=org.apache.hadoop.metrics.spi.NullContextWithUpdateThread
|
||||
rpc.period=60
|
||||
----
|
||||
|
||||
=== Setup JMX Remote Access
|
||||
|
||||
For remote access, you will need to configure JMX remote passwords and access profiles. Create the files:
|
||||
`$HBASE_HOME/conf/jmxremote.passwd` (set permissions
|
||||
to 600):: +
|
||||
----
|
||||
monitorRole monitorpass
|
||||
controlRole controlpass
|
||||
----
|
||||
|
||||
`$HBASE_HOME/conf/jmxremote.access`:: +
|
||||
----
|
||||
monitorRole readonly
|
||||
controlRole readwrite
|
||||
----
|
||||
|
||||
=== Configure JMX in HBase startup
|
||||
|
||||
Finally, edit the `$HBASE_HOME/conf/hbase-env.sh` script to add JMX support:
|
||||
[source,bash]
|
||||
----
|
||||
HBASE_JMX_OPTS="-Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.ssl=false"
|
||||
HBASE_JMX_OPTS="$HBASE_JMX_OPTS -Dcom.sun.management.jmxremote.password.file=$HBASE_HOME/conf/jmxremote.passwd"
|
||||
HBASE_JMX_OPTS="$HBASE_JMX_OPTS -Dcom.sun.management.jmxremote.access.file=$HBASE_HOME/conf/jmxremote.access"
|
||||
|
||||
export HBASE_MASTER_OPTS="$HBASE_JMX_OPTS -Dcom.sun.management.jmxremote.port=10101"
|
||||
export HBASE_REGIONSERVER_OPTS="$HBASE_JMX_OPTS -Dcom.sun.management.jmxremote.port=10102"
|
||||
----
|
||||
|
||||
After restarting the processes you want to monitor, you should now be able to run JConsole (included with the JDK since JDK 5.0) to view the statistics via JMX. HBase MBeans are exported under the *`hadoop`* domain in JMX.
|
||||
|
||||
|
||||
== Understanding HBase Metrics
|
||||
|
||||
For more information on understanding HBase metrics, see the link:book.html#hbase_metrics[metrics section] in the Apache HBase Reference Guide.
|
||||
|
||||
|
|
@ -0,0 +1,117 @@
|
|||
////
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
= Old Apache HBase (TM) News
|
||||
|
||||
February 10th, 2014:: link:http://www.meetup.com/hbaseusergroup/events/163139322/[HBase Meetup @ Continuuity] in Palo Alto
|
||||
|
||||
January 30th, 2014:: link:http://www.meetup.com/hbaseusergroup/events/158491762/[HBase Meetup @ Apple] in Cupertino
|
||||
|
||||
January 30th, 2014:: link:http://www.meetup.com/Los-Angeles-HBase-User-group/events/160560282/[Los Angeles HBase User Group] in El Segundo
|
||||
|
||||
October 24th, 2013:: link:http://www.meetup.com/hbaseusergroup/events/140759692/[HBase User] and link:http://www.meetup.com/hackathon/events/144366512/[Developer] Meetup at HortonWorksin Palo Alto
|
||||
|
||||
September 26, 2013:: link:http://www.meetup.com/hbaseusergroup/events/135862292/[HBase Meetup at Arista Networks] in San Francisco
|
||||
|
||||
August 20th, 2013:: link:http://www.meetup.com/hbaseusergroup/events/120534362/[HBase Meetup at Flurry] in San Francisco
|
||||
|
||||
July 16th, 2013:: link:http://www.meetup.com/hbaseusergroup/events/119929152/[HBase Meetup at Twitter] in San Francisco
|
||||
|
||||
June 25th, 2013:: link:http://www.meetup.com/hbaseusergroup/events/119154442/[Hadoop Summit Meetup].at San Jose Convention Center
|
||||
|
||||
June 14th, 2013:: link:http://kijicon.eventbrite.com/[KijiCon: Building Big Data Apps] in San Francisco.
|
||||
|
||||
June 13th, 2013:: link:http://www.hbasecon.com/[HBaseCon2013] in San Francisco. Submit an Abstract!
|
||||
|
||||
June 12th, 2013:: link:http://www.meetup.com/hackathon/events/123403802/[HBaseConHackAthon] at the Cloudera office in San Francisco.
|
||||
|
||||
April 11th, 2013:: link:http://www.meetup.com/hbaseusergroup/events/103587852/[HBase Meetup at AdRoll] in San Francisco
|
||||
|
||||
February 28th, 2013:: link:http://www.meetup.com/hbaseusergroup/events/96584102/[HBase Meetup at Intel Mission Campus]
|
||||
|
||||
February 19th, 2013:: link:http://www.meetup.com/hackathon/events/103633042/[Developers PowWow] at HortonWorks' new digs
|
||||
|
||||
January 23rd, 2013:: link:http://www.meetup.com/hbaseusergroup/events/91381312/[HBase Meetup at WibiData World HQ!]
|
||||
|
||||
December 4th, 2012:: link:http://www.meetup.com/hackathon/events/90536432/[0.96 Bug Squashing and Testing Hackathon] at Cloudera, SF.
|
||||
|
||||
October 29th, 2012:: link:http://www.meetup.com/hbaseusergroup/events/82791572/[HBase User Group Meetup] at Wize Commerce in San Mateo.
|
||||
|
||||
October 25th, 2012:: link:http://www.meetup.com/HBase-NYC/events/81728932/[Strata/Hadoop World HBase Meetup.] in NYC
|
||||
|
||||
September 11th, 2012:: link:http://www.meetup.com/hbaseusergroup/events/80621872/[Contributor's Pow-Wow at HortonWorks HQ.]
|
||||
|
||||
August 8th, 2012:: link:http://www.apache.org/dyn/closer.cgi/hbase/[Apache HBase 0.94.1 is available for download]
|
||||
|
||||
June 15th, 2012:: link:http://www.meetup.com/hbaseusergroup/events/59829652/[Birds-of-a-feather] in San Jose, day after:: link:http://hadoopsummit.org[Hadoop Summit]
|
||||
|
||||
May 23rd, 2012:: link:http://www.meetup.com/hackathon/events/58953522/[HackConAthon] in Palo Alto
|
||||
|
||||
May 22nd, 2012:: link:http://www.hbasecon.com[HBaseCon2012] in San Francisco
|
||||
|
||||
March 27th, 2012:: link:http://www.meetup.com/hbaseusergroup/events/56021562/[Meetup @ StumbleUpon] in San Francisco
|
||||
|
||||
January 19th, 2012:: link:http://www.meetup.com/hbaseusergroup/events/46702842/[Meetup @ EBay]
|
||||
|
||||
January 23rd, 2012:: Apache HBase 0.92.0 released. link:http://www.apache.org/dyn/closer.cgi/hbase/[Download it!]
|
||||
|
||||
December 23rd, 2011:: Apache HBase 0.90.5 released. link:http://www.apache.org/dyn/closer.cgi/hbase/[Download it!]
|
||||
|
||||
November 29th, 2011:: link:http://www.meetup.com/hackathon/events/41025972/[Developer Pow-Wow in SF] at Salesforce HQ
|
||||
|
||||
November 7th, 2011:: link:http://www.meetup.com/hbaseusergroup/events/35682812/[HBase Meetup in NYC (6PM)] at the AppNexus office
|
||||
|
||||
August 22nd, 2011:: link:http://www.meetup.com/hbaseusergroup/events/28518471/[HBase Hackathon (11AM) and Meetup (6PM)] at FB in PA
|
||||
|
||||
June 30th, 2011:: link:http://www.meetup.com/hbaseusergroup/events/20572251/[HBase Contributor Day], the day after the:: link:http://developer.yahoo.com/events/hadoopsummit2011/[Hadoop Summit] hosted by Y!
|
||||
|
||||
June 8th, 2011:: link:http://berlinbuzzwords.de/wiki/hbase-workshop-and-hackathon[HBase Hackathon] in Berlin to coincide with:: link:http://berlinbuzzwords.de/[Berlin Buzzwords]
|
||||
|
||||
May 19th, 2011: Apache HBase 0.90.3 released. link:http://www.apache.org/dyn/closer.cgi/hbase/[Download it!]
|
||||
|
||||
April 12th, 2011: Apache HBase 0.90.2 released. link:http://www.apache.org/dyn/closer.cgi/hbase/[Download it!]
|
||||
|
||||
March 21st, 2011:: link:http://www.meetup.com/hackathon/events/16770852/[HBase 0.92 Hackathon at StumbleUpon, SF]
|
||||
February 22nd, 2011:: link:http://www.meetup.com/hbaseusergroup/events/16492913/[HUG12: February HBase User Group at StumbleUpon SF]
|
||||
December 13th, 2010:: link:http://www.meetup.com/hackathon/calendar/15597555/[HBase Hackathon: Coprocessor Edition]
|
||||
November 19th, 2010:: link:http://huguk.org/[Hadoop HUG in London] is all about Apache HBase
|
||||
November 15-19th, 2010:: link:http://www.devoxx.com/display/Devoxx2K10/Home[Devoxx] features HBase Training and multiple HBase presentations
|
||||
|
||||
October 12th, 2010:: HBase-related presentations by core contributors and users at:: link:http://www.cloudera.com/company/press-center/hadoop-world-nyc/[Hadoop World 2010]
|
||||
|
||||
October 11th, 2010:: link:http://www.meetup.com/hbaseusergroup/calendar/14606174/[HUG-NYC: HBase User Group NYC Edition] (Night before Hadoop World)
|
||||
June 30th, 2010:: link:http://www.meetup.com/hbaseusergroup/calendar/13562846/[Apache HBase Contributor Workshop] (Day after Hadoop Summit)
|
||||
May 10th, 2010:: Apache HBase graduates from Hadoop sub-project to Apache Top Level Project
|
||||
|
||||
April 19, 2010:: Signup for link:http://www.meetup.com/hbaseusergroup/calendar/12689490/[HBase User Group Meeting, HUG10] hosted by Trend Micro
|
||||
|
||||
March 10th, 2010:: link:http://www.meetup.com/hbaseusergroup/calendar/12689351/[HBase User Group Meeting, HUG9] hosted by Mozilla
|
||||
|
||||
January 27th, 2010:: Sign up for the link:http://www.meetup.com/hbaseusergroup/calendar/12241393/[HBase User Group Meeting, HUG8], at StumbleUpon in SF
|
||||
|
||||
September 8th, 2010:: Apache HBase 0.20.0 is faster, stronger, slimmer, and sweeter tasting than any previous Apache HBase release. Get it off the link:http://www.apache.org/dyn/closer.cgi/hbase/[Releases] page.
|
||||
|
||||
November 2-6th, 2009:: link:http://dev.us.apachecon.com/c/acus2009/[ApacheCon] in Oakland. The Apache Foundation will be celebrating its 10th anniversary in beautiful Oakland by the Bay. Lots of good talks and meetups including an HBase presentation by a couple of the lads.
|
||||
|
||||
October 2nd, 2009:: HBase at Hadoop World in NYC. A few of us will be talking on Practical HBase out east at link:http://www.cloudera.com/hadoop-world-nyc[Hadoop World: NYC].
|
||||
|
||||
August 7th-9th, 2009:: HUG7 and HBase Hackathon at StumbleUpon in SF: Sign up for the:: link:http://www.meetup.com/hbaseusergroup/calendar/10950511/[HBase User Group Meeting, HUG7] or for the link:http://www.meetup.com/hackathon/calendar/10951718/[Hackathon] or for both (all are welcome!).
|
||||
|
||||
June, 2009:: HBase at HadoopSummit2009 and at NOSQL: See the link:http://wiki.apache.org/hadoop/HBase/HBasePresentations[presentations]
|
||||
|
||||
March 3rd, 2009 :: HUG6 -- link:http://www.meetup.com/hbaseusergroup/calendar/9764004/[HBase User Group 6]
|
||||
|
||||
January 30th, 2009:: LA Hbackathon: link:http://www.meetup.com/hbasela/calendar/9450876/[HBase January Hackathon Los Angeles] at link:http://streamy.com[Streamy] in Manhattan Beach
|
||||
|
||||
|
|
@ -0,0 +1,19 @@
|
|||
////
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
|
||||
= Running Apache HBase (TM) in pseudo-distributed mode
|
||||
This page has been retired. The contents have been moved to the link:book.html#distributed[Distributed Operation: Pseudo- and Fully-distributed modes] section in the Reference Guide.
|
||||
|
||||
|
|
@ -0,0 +1,18 @@
|
|||
////
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
= Apache HBase (TM) Replication
|
||||
|
||||
This information has been moved to link:book.html#cluster_replication"[the Cluster Replication] section of the link:book.html[Apache HBase Reference Guide].
|
||||
|
|
@ -0,0 +1,22 @@
|
|||
////
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
= Other Apache HBase (TM) Resources
|
||||
|
||||
== Books
|
||||
HBase: The Definitive Guide:: link:http://shop.oreilly.com/product/0636920014348.do[HBase: The Definitive Guide, _Random Access to Your Planet-Size Data_] by Lars George. Publisher: O'Reilly Media, Released: August 2011, Pages: 556.
|
||||
|
||||
HBase In Action:: link:http://www.manning.com/dimidukkhurana[HBase In Action] By Nick Dimiduk and Amandeep Khurana. Publisher: Manning, MEAP Began: January 2012, Softbound print: Fall 2012, Pages: 350.
|
||||
|
||||
HBase Administration Cookbook:: link:http://www.packtpub.com/hbase-administration-for-optimum-database-performance-cookbook/book[HBase Administration Cookbook] by Yifeng Jiang. Publisher: PACKT Publishing, Release: Expected August 2012, Pages: 335.
|
||||
|
||||
|
|
@ -0,0 +1,30 @@
|
|||
////
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
////
|
||||
|
||||
= Apache HBase(TM) Sponsors
|
||||
|
||||
First off, thanks to link:http://www.apache.org/foundation/thanks.html[all who sponsor] our parent, the Apache Software Foundation.
|
||||
|
||||
The below companies have been gracious enough to provide their commerical tool offerings free of charge to the Apache HBase(TM) project.
|
||||
|
||||
* The crew at link:http://www.ej-technologies.com/[ej-technologies] have been letting us use link:http://www.ej-technologies.com/products/jprofiler/overview.html[JProfiler] for years now.
|
||||
|
||||
* The lads at link:http://headwaysoftware.com/[headway software] have given us a license for link:http://headwaysoftware.com/products/?code=Restructure101[Restructure101] so we can untangle our interdependency mess.
|
||||
|
||||
* link:http://www.yourkit.com[YourKit] allows us to use their link:http://www.yourkit.com/overview/index.jsp[Java Profiler].
|
||||
* Some of us use link:http://www.jetbrains.com/idea[IntelliJ IDEA] thanks to link:http://www.jetbrains.com/[JetBrains].
|
||||
|
||||
== Sponsoring the Apache Software Foundation">
|
||||
To contribute to the Apache Software Foundation, a good idea in our opinion, see the link:http://www.apache.org/foundation/sponsorship.html[ASF Sponsorship] page.
|
||||
|
||||
|
|
@ -0,0 +1,8 @@
|
|||
|
||||
# Redirect replication URL to the right section of the book
|
||||
# Rule added 2015-1-12 -- can be removed in 6 months
|
||||
Redirect permanent /replication.html /book.html#_cluster_replication
|
||||
|
||||
# Redirect old page-per-chapter book sections to new single file.
|
||||
RedirectMatch permanent ^/book/(.*)\.html$ /book.html#$1
|
||||
RedirectMatch permanent ^/book/$ /book.html
|
||||
|
|
@ -0,0 +1 @@
|
|||
# This directory is here so that we can have rewrite rules in our .htaccess to maintain old links. Otherwise we fall under some top-level niceness redirects because we have a file named book.html.
|
||||
|
|
@ -72,8 +72,10 @@ h4 {
|
|||
|
||||
#banner {
|
||||
background: none;
|
||||
padding: 10px;
|
||||
}
|
||||
|
||||
/*
|
||||
#banner img {
|
||||
padding: 10px;
|
||||
margin: auto;
|
||||
|
|
@ -82,6 +84,7 @@ h4 {
|
|||
float: center;
|
||||
height:;
|
||||
}
|
||||
*/
|
||||
|
||||
#breadcrumbs {
|
||||
background-image: url();
|
||||
|
|
|
|||
Binary file not shown.
|
After Width: | Height: | Size: 11 KiB |
Binary file not shown.
Binary file not shown.
Binary file not shown.
|
After Width: | Height: | Size: 330 KiB |
|
|
@ -19,18 +19,34 @@
|
|||
*/
|
||||
-->
|
||||
|
||||
|
||||
<project xmlns="http://maven.apache.org/DECORATION/1.0.0"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/DECORATION/1.0.0 http://maven.apache.org/xsd/decoration-1.0.0.xsd">
|
||||
<skin>
|
||||
<groupId>lt.velykis.maven.skins</groupId>
|
||||
<artifactId>reflow-maven-skin</artifactId>
|
||||
<version>1.1.1</version>
|
||||
</skin>
|
||||
<custom>
|
||||
<reflowSkin>
|
||||
<theme>bootswatch-spacelab</theme>
|
||||
<bottomNav maxSpan="9">
|
||||
<column>Apache HBase Project</column>
|
||||
<column>^Documentation</column>
|
||||
<column>0.94 Documentation|ASF</column>
|
||||
</bottomNav>
|
||||
</reflowSkin>
|
||||
</custom>
|
||||
<bannerLeft>
|
||||
<name>Apache HBase</name>
|
||||
<src>images/hbase_logo.png</src>
|
||||
<href>http://hbase.apache.org/</href>
|
||||
</bannerLeft>
|
||||
<bannerRight />
|
||||
<version position="right" />
|
||||
<publishDate position="right" />
|
||||
<bannerRight>
|
||||
<name>Apache HBase Orca</name>
|
||||
<src>images/hbasecon2015.30percent.png</src>
|
||||
<href>http://hbasecon.com/</href>
|
||||
</bannerRight>
|
||||
<body>
|
||||
<menu name="Apache HBase Project">
|
||||
<item name="Overview" href="index.html"/>
|
||||
|
|
@ -47,35 +63,31 @@
|
|||
<item name="Other resources" href="resources.html" />
|
||||
</menu>
|
||||
<menu name="Documentation">
|
||||
<item name="Getting Started" href="book/quickstart.html" />
|
||||
<item name="User API" href="apidocs/index.html" />
|
||||
<item name="Developer API" href="devapidocs/index.html" />
|
||||
<item name="Reference Guide" href="book.html" target="_blank" />
|
||||
<item name="Reference Guide (PDF)" href="apache_hbase_reference_guide.pdf" target="_blank" />
|
||||
<item name="Getting Started" href="book.html#quickstart" target="_blank" />
|
||||
<item name="User API" href="apidocs/index.html" target="_blank" />
|
||||
<item name="Developer API" href="devapidocs/index.html" target="_blank" />
|
||||
<item name="X-Ref" href="xref/index.html" />
|
||||
<item name="Ref Guide (multi-page)" href="book/book.html" />
|
||||
<item name="Ref Guide (single-page)" href="book.html" />
|
||||
<item name="中文参考指南(单页)" href="http://abloz.com/hbase/book.html" />
|
||||
<item name="FAQ" href="book/faq.html" />
|
||||
<item name="Videos/Presentations" href="book.html#other.info" />
|
||||
<item name="Wiki" href="http://wiki.apache.org/hadoop/Hbase" />
|
||||
<item name="ACID Semantics" href="acid-semantics.html" />
|
||||
<item name="Bulk Loads" href="book.html#arch.bulk.load" />
|
||||
<item name="Metrics" href="metrics.html" />
|
||||
<item name="HBase on Windows" href="cygwin.html" />
|
||||
<item name="Cluster replication" href="replication.html" />
|
||||
<item name="中文参考指南(单页)" href="http://abloz.com/hbase/book.html" target="_blank" />
|
||||
<item name="FAQ" href="book.html#faq" target="_blank" />
|
||||
<item name="Videos/Presentations" href="book.html#other.info" target="_blank" />
|
||||
<item name="Wiki" href="http://wiki.apache.org/hadoop/Hbase" target="_blank" />
|
||||
<item name="ACID Semantics" href="acid-semantics.html" target="_blank" />
|
||||
<item name="Bulk Loads" href="book.html#arch.bulk.load" target="_blank" />
|
||||
<item name="Metrics" href="metrics.html" target="_blank" />
|
||||
<item name="HBase on Windows" href="cygwin.html" target="_blank" />
|
||||
<item name="Cluster replication" href="replication.html" target="_blank" />
|
||||
</menu>
|
||||
<menu name="0.94 Documentation">
|
||||
<item name="API" href="0.94/apidocs/index.html" />
|
||||
<item name="X-Ref" href="0.94/xref/index.html" />
|
||||
<item name="Ref Guide (single-page)" href="0.94/book.html" />
|
||||
<item name="API" href="0.94/apidocs/index.html" target="_blank" />
|
||||
<item name="X-Ref" href="0.94/xref/index.html" target="_blank" />
|
||||
<item name="Ref Guide (single-page)" href="0.94/book.html" target="_blank" />
|
||||
</menu>
|
||||
<menu name="ASF">
|
||||
<item name="Apache Software Foundation" href="http://www.apache.org/foundation/" />
|
||||
<item name="How Apache Works" href="http://www.apache.org/foundation/how-it-works.html" />
|
||||
<item name="Sponsoring Apache" href="http://www.apache.org/foundation/sponsorship.html" />
|
||||
<item name="Apache Software Foundation" href="http://www.apache.org/foundation/" target="_blank" />
|
||||
<item name="How Apache Works" href="http://www.apache.org/foundation/how-it-works.html" target="_blank" />
|
||||
<item name="Sponsoring Apache" href="http://www.apache.org/foundation/sponsorship.html" target="_blank" />
|
||||
</menu>
|
||||
</body>
|
||||
<skin>
|
||||
<groupId>org.apache.maven.skins</groupId>
|
||||
<artifactId>maven-stylus-skin</artifactId>
|
||||
</skin>
|
||||
</project>
|
||||
|
|
|
|||
|
|
@ -17,17 +17,21 @@
|
|||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/XDOC/2.0 http://maven.apache.org/xsd/xdoc-2.0.xsd">
|
||||
<properties>
|
||||
<title>Apache HBase™ Home</title>
|
||||
<title>Apache HBase™ Home</title>
|
||||
<link rel="shortcut icon" href="/images/favicon.ico" />
|
||||
</properties>
|
||||
|
||||
<body>
|
||||
<section name="Welcome to Apache HBase™">
|
||||
<p><a href="http://www.apache.org/">Apache</a> HBase™ is the <a href="http://hadoop.apache.org">Hadoop</a> database, a distributed, scalable, big data store.
|
||||
<section name="Welcome to Apache HBase™">
|
||||
<p><a href="http://www.apache.org/">Apache</a> HBase™ is the <a href="http://hadoop.apache.org">Hadoop</a> database, a distributed, scalable, big data store.
|
||||
</p>
|
||||
<h4>Download Apache HBase™</h4>
|
||||
<p>
|
||||
Click <b><a href="http://www.apache.org/dyn/closer.cgi/hbase/">here</a></b> to download Apache HBase™.
|
||||
</p>
|
||||
<h4>When Would I Use Apache HBase?</h4>
|
||||
<p>
|
||||
Use Apache HBase when you need random, realtime read/write access to your Big Data.
|
||||
Use Apache HBase™ when you need random, realtime read/write access to your Big Data.
|
||||
This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware.
|
||||
Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's <a href="http://research.google.com/archive/bigtable.html">Bigtable: A Distributed Storage System for Structured Data</a> by Chang et al.
|
||||
Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache HBase provides Bigtable-like capabilities on top of Hadoop and HDFS.
|
||||
|
|
@ -68,6 +72,14 @@ Apache HBase is an open-source, distributed, versioned, non-relational database
|
|||
</p>
|
||||
</section>
|
||||
<section name="News">
|
||||
<p>May 7th, 2015 <a href="http://hbasecon.com/">HBaseCon2015</a> in San Francisco</p>
|
||||
<p>February 17th, 2015 <a href="http://www.meetup.com/hbaseusergroup/events/219260093/">HBase meetup around Strata+Hadoop World</a> in San Jose</p>
|
||||
<p>January 15th, 2015 <a href="http://www.meetup.com/hbaseusergroup/events/218744798/">HBase meetup @ AppDynamics</a> in San Francisco</p>
|
||||
<p>November 20th, 2014 <a href="http://www.meetup.com/hbaseusergroup/events/205219992/">HBase meetup @ WANdisco</a> in San Ramon</p>
|
||||
<p>October 27th, 2014 <a href="http://www.meetup.com/hbaseusergroup/events/207386102/">HBase Meetup @ Apple</a> in Cupertino</p>
|
||||
<p>October 15th, 2014 <a href="http://www.meetup.com/HBase-NYC/events/207655552">HBase Meetup @ Google</a> on the night before Strata/HW in NYC</p>
|
||||
<p>September 25th, 2014 <a href="http://www.meetup.com/hbaseusergroup/events/203173692/">HBase Meetup @ Continuuity</a> in Palo Alto</p>
|
||||
<p>August 28th, 2014 <a href="http://www.meetup.com/hbaseusergroup/events/197773762/">HBase Meetup @ Sift Science</a> in San Francisco</p>
|
||||
<p>July 17th, 2014 <a href="http://www.meetup.com/hbaseusergroup/events/190994082/">HBase Meetup @ HP</a> in Sunnyvale</p>
|
||||
<p>June 5th, 2014 <a href="http://www.meetup.com/Hadoop-Summit-Community-San-Jose/events/179081342/">HBase BOF at Hadoop Summit</a>, San Jose Convention Center</p>
|
||||
<p>May 5th, 2014 <a href="http://www.hbasecon.com">HBaseCon2014</a> at the Hilton San Francisco on Union Square</p>
|
||||
|
|
|
|||
|
|
@ -26,520 +26,6 @@
|
|||
</title>
|
||||
</properties>
|
||||
<body>
|
||||
<section name="Overview">
|
||||
<p>
|
||||
The replication feature of Apache HBase (TM) provides a way to copy data between HBase deployments. It
|
||||
can serve as a disaster recovery solution and can contribute to provide
|
||||
higher availability at the HBase layer. It can also serve more practically;
|
||||
for example, as a way to easily copy edits from a web-facing cluster to a "MapReduce"
|
||||
cluster which will process old and new data and ship back the results
|
||||
automatically.
|
||||
</p>
|
||||
<p>
|
||||
The basic architecture pattern used for Apache HBase replication is (HBase cluster) master-push;
|
||||
it is much easier to keep track of what’s currently being replicated since
|
||||
each region server has its own write-ahead-log (aka WAL or HLog), just like
|
||||
other well known solutions like MySQL master/slave replication where
|
||||
there’s only one bin log to keep track of. One master cluster can
|
||||
replicate to any number of slave clusters, and each region server will
|
||||
participate to replicate their own stream of edits. For more information
|
||||
on the different properties of master/slave replication and other types
|
||||
of replication, please consult <a href="http://highscalability.com/blog/2009/8/24/how-google-serves-data-from-multiple-datacenters.html">
|
||||
How Google Serves Data From Multiple Datacenters</a>.
|
||||
</p>
|
||||
<p>
|
||||
The replication is done asynchronously, meaning that the clusters can
|
||||
be geographically distant, the links between them can be offline for
|
||||
some time, and rows inserted on the master cluster won’t be
|
||||
available at the same time on the slave clusters (eventual consistency).
|
||||
</p>
|
||||
<p>
|
||||
The replication format used in this design is conceptually the same as
|
||||
<a href="http://dev.mysql.com/doc/refman/5.1/en/replication-formats.html">
|
||||
MySQL’s statement-based replication </a>. Instead of SQL statements, whole
|
||||
WALEdits (consisting of multiple cell inserts coming from the clients'
|
||||
Put and Delete) are replicated in order to maintain atomicity.
|
||||
</p>
|
||||
<p>
|
||||
The HLogs from each region server are the basis of HBase replication,
|
||||
and must be kept in HDFS as long as they are needed to replicate data
|
||||
to any slave cluster. Each RS reads from the oldest log it needs to
|
||||
replicate and keeps the current position inside ZooKeeper to simplify
|
||||
failure recovery. That position can be different for every slave
|
||||
cluster, same for the queue of HLogs to process.
|
||||
</p>
|
||||
<p>
|
||||
The clusters participating in replication can be of asymmetric sizes
|
||||
and the master cluster will do its “best effort” to balance the stream
|
||||
of replication on the slave clusters by relying on randomization.
|
||||
</p>
|
||||
<p>
|
||||
As of version 0.92, Apache HBase supports master/master and cyclic
|
||||
replication as well as replication to multiple slaves.
|
||||
</p>
|
||||
<img src="images/replication_overview.png"/>
|
||||
</section>
|
||||
<section name="Enabling replication">
|
||||
<p>
|
||||
The guide on enabling and using cluster replication is contained
|
||||
in the API documentation shipped with your Apache HBase distribution.
|
||||
</p>
|
||||
<p>
|
||||
The most up-to-date documentation is
|
||||
<a href="apidocs/org/apache/hadoop/hbase/replication/package-summary.html#requirements">
|
||||
available at this address</a>.
|
||||
</p>
|
||||
</section>
|
||||
<section name="Life of a log edit">
|
||||
<p>
|
||||
The following sections describe the life of a single edit going from a
|
||||
client that communicates with a master cluster all the way to a single
|
||||
slave cluster.
|
||||
</p>
|
||||
<section name="Normal processing">
|
||||
<p>
|
||||
The client uses an API that sends a Put, Delete or ICV to a region
|
||||
server. The key values are transformed into a WALEdit by the region
|
||||
server and is inspected by the replication code that, for each family
|
||||
that is scoped for replication, adds the scope to the edit. The edit
|
||||
is appended to the current WAL and is then applied to its MemStore.
|
||||
</p>
|
||||
<p>
|
||||
In a separate thread, the edit is read from the log (as part of a batch)
|
||||
and only the KVs that are replicable are kept (that is, that they are part
|
||||
of a family scoped GLOBAL in the family's schema, non-catalog so not
|
||||
hbase:meta or -ROOT-, and did not originate in the target slave cluster - in
|
||||
case of cyclic replication).
|
||||
</p>
|
||||
<p>
|
||||
The edit is then tagged with the master's cluster UUID.
|
||||
When the buffer is filled, or the reader hits the end of the file,
|
||||
the buffer is sent to a random region server on the slave cluster.
|
||||
</p>
|
||||
<p>
|
||||
Synchronously, the region server that receives the edits reads them
|
||||
sequentially and separates each of them into buffers, one per table.
|
||||
Once all edits are read, each buffer is flushed using HTable, the normal
|
||||
HBase client.The master's cluster UUID is retained in the edits applied at
|
||||
the slave cluster in order to allow cyclic replication.
|
||||
</p>
|
||||
<p>
|
||||
Back in the master cluster's region server, the offset for the current
|
||||
WAL that's being replicated is registered in ZooKeeper.
|
||||
</p>
|
||||
</section>
|
||||
<section name="Non-responding slave clusters">
|
||||
<p>
|
||||
The edit is inserted in the same way.
|
||||
</p>
|
||||
<p>
|
||||
In the separate thread, the region server reads, filters and buffers
|
||||
the log edits the same way as during normal processing. The slave
|
||||
region server that's contacted doesn't answer to the RPC, so the master
|
||||
region server will sleep and retry up to a configured number of times.
|
||||
If the slave RS still isn't available, the master cluster RS will select a
|
||||
new subset of RS to replicate to and will retry sending the buffer of
|
||||
edits.
|
||||
</p>
|
||||
<p>
|
||||
In the mean time, the WALs will be rolled and stored in a queue in
|
||||
ZooKeeper. Logs that are archived by their region server (archiving is
|
||||
basically moving a log from the region server's logs directory to a
|
||||
central logs archive directory) will update their paths in the in-memory
|
||||
queue of the replicating thread.
|
||||
</p>
|
||||
<p>
|
||||
When the slave cluster is finally available, the buffer will be applied
|
||||
the same way as during normal processing. The master cluster RS will then
|
||||
replicate the backlog of logs.
|
||||
</p>
|
||||
</section>
|
||||
</section>
|
||||
<section name="Internals">
|
||||
<p>
|
||||
This section describes in depth how each of replication's internal
|
||||
features operate.
|
||||
</p>
|
||||
<section name="Replication Zookeeper State">
|
||||
<p>
|
||||
HBase replication maintains all of its state in Zookeeper. By default, this state is
|
||||
contained in the base znode:
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication
|
||||
</pre>
|
||||
<p>
|
||||
There are two major child znodes in the base replication znode:
|
||||
<ul>
|
||||
<li><b>Peers znode:</b> /hbase/replication/peers</li>
|
||||
<li><b>RS znode:</b> /hbase/replication/rs</li>
|
||||
</ul>
|
||||
</p>
|
||||
<section name="The Peers znode">
|
||||
<p>
|
||||
The <b>peers znode</b> contains a list of all peer replication clusters and the
|
||||
current replication state of those clusters. It has one child <i>peer znode</i>
|
||||
for each peer cluster. The <i>peer znode</i> is named with the cluster id provided
|
||||
by the user in the HBase shell. The value of the <i>peer znode</i> contains
|
||||
the peers cluster key provided by the user in the HBase Shell. The cluster key
|
||||
contains a list of zookeeper nodes in the clusters quorum, the client port for the
|
||||
zookeeper quorum, and the base znode for HBase
|
||||
(i.e. “zk1.host.com,zk2.host.com,zk3.host.com:2181:/hbase”).
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/peers
|
||||
/1 [Value: zk1.host.com,zk2.host.com,zk3.host.com:2181:/hbase]
|
||||
/2 [Value: zk5.host.com,zk6.host.com,zk7.host.com:2181:/hbase]
|
||||
</pre>
|
||||
<p>
|
||||
Each of these <i>peer znodes</i> has a child znode that indicates whether or not
|
||||
replication is enabled on that peer cluster. These <i>peer-state znodes</i> do not
|
||||
have child znodes and simply contain a boolean value (i.e. ENABLED or DISABLED).
|
||||
This value is read/maintained by the <i>ReplicationPeer.PeerStateTracker</i> class.
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/peers
|
||||
/1/peer-state [Value: ENABLED]
|
||||
/2/peer-state [Value: DISABLED]
|
||||
</pre>
|
||||
</section>
|
||||
<section name="The RS znode">
|
||||
<p>
|
||||
The <b>rs znode</b> contains a list of all outstanding HLog files in the cluster
|
||||
that need to be replicated. The list is divided into a set of queues organized by
|
||||
region server and the peer cluster the region server is shipping the HLogs to. The
|
||||
<b>rs znode</b> has one child znode for each region server in the cluster. The child
|
||||
znode name is simply the regionserver name (a concatenation of the region server’s
|
||||
hostname, client port and start code). These region servers could either be dead or alive.
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/rs
|
||||
/hostname.example.org,6020,1234
|
||||
/hostname2.example.org,6020,2856
|
||||
</pre>
|
||||
<p>
|
||||
Within each region server znode, the region server maintains a set of HLog replication
|
||||
queues. Each region server has one queue for every peer cluster it replicates to.
|
||||
These queues are represented by child znodes named using the cluster id of the peer
|
||||
cluster they represent (see the peer znode section).
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/rs
|
||||
/hostname.example.org,6020,1234
|
||||
/1
|
||||
/2
|
||||
</pre>
|
||||
<p>
|
||||
Each queue has one child znode for every HLog that still needs to be replicated.
|
||||
The value of these HLog child znodes is the latest position that has been replicated.
|
||||
This position is updated every time a HLog entry is replicated.
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/rs
|
||||
/hostname.example.org,6020,1234
|
||||
/1
|
||||
23522342.23422 [VALUE: 254]
|
||||
12340993.22342 [VALUE: 0]
|
||||
</pre>
|
||||
</section>
|
||||
</section>
|
||||
<section name="Configuration Parameters">
|
||||
<section name="Zookeeper znode paths">
|
||||
<p>
|
||||
All of the base znode names are configurable through parameters:
|
||||
</p>
|
||||
<table border="1">
|
||||
<tr>
|
||||
<td><b>Parameter</b></td>
|
||||
<td><b>Default Value</b></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>zookeeper.znode.parent</td>
|
||||
<td>/hbase</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>zookeeper.znode.replication</td>
|
||||
<td>replication</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>zookeeper.znode.replication.peers</td>
|
||||
<td>peers</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>zookeeper.znode.replication.peers.state</td>
|
||||
<td>peer-state</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>zookeeper.znode.replication.rs</td>
|
||||
<td>rs</td>
|
||||
</tr>
|
||||
</table>
|
||||
<p>
|
||||
The default replication znode structure looks like the following:
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/peers/{peerId}/peer-state
|
||||
/hbase/replication/rs
|
||||
</pre>
|
||||
</section>
|
||||
<section name="Other parameters">
|
||||
<ul>
|
||||
<li><b>hbase.replication</b> (Default: false) - Controls whether replication is enabled
|
||||
or disabled for the cluster.</li>
|
||||
<li><b>replication.sleep.before.failover</b> (Default: 2000) - The amount of time a failover
|
||||
worker waits before attempting to replicate a dead region server’s HLog queues.</li>
|
||||
<li><b>replication.executor.workers</b> (Default: 1) - The number of dead region servers
|
||||
one region server should attempt to failover simultaneously.</li>
|
||||
</ul>
|
||||
</section>
|
||||
</section>
|
||||
<section name="Choosing region servers to replicate to">
|
||||
<p>
|
||||
When a master cluster RS initiates a replication source to a slave cluster,
|
||||
it first connects to the slave's ZooKeeper ensemble using the provided
|
||||
cluster key (that key is composed of the value of hbase.zookeeper.quorum,
|
||||
zookeeper.znode.parent and hbase.zookeeper.property.clientPort). It
|
||||
then scans the "rs" directory to discover all the available sinks
|
||||
(region servers that are accepting incoming streams of edits to replicate)
|
||||
and will randomly choose a subset of them using a configured
|
||||
ratio (which has a default value of 10%). For example, if a slave
|
||||
cluster has 150 machines, 15 will be chosen as potential recipient for
|
||||
edits that this master cluster RS will be sending. Since this is done by all
|
||||
master cluster RSs, the probability that all slave RSs are used is very high,
|
||||
and this method works for clusters of any size. For example, a master cluster
|
||||
of 10 machines replicating to a slave cluster of 5 machines with a ratio
|
||||
of 10% means that the master cluster RSs will choose one machine each
|
||||
at random, thus the chance of overlapping and full usage of the slave
|
||||
cluster is higher.
|
||||
</p>
|
||||
<p>
|
||||
A ZK watcher is placed on the ${zookeeper.znode.parent}/rs node of
|
||||
the slave cluster by each of the master cluster's region servers.
|
||||
This watch is used to monitor changes in the composition of the
|
||||
slave cluster. When nodes are removed from the slave cluster (or
|
||||
if nodes go down and/or come back up), the master cluster's region
|
||||
servers will respond by selecting a new pool of slave region servers
|
||||
to replicate to.
|
||||
</p>
|
||||
</section>
|
||||
<section name="Keeping track of logs">
|
||||
<p>
|
||||
Every master cluster RS has its own znode in the replication znodes hierarchy.
|
||||
It contains one znode per peer cluster (if 5 slave clusters, 5 znodes
|
||||
are created), and each of these contain a queue
|
||||
of HLogs to process. Each of these queues will track the HLogs created
|
||||
by that RS, but they can differ in size. For example, if one slave
|
||||
cluster becomes unavailable for some time then the HLogs should not be deleted,
|
||||
thus they need to stay in the queue (while the others are processed).
|
||||
See the section named "Region server failover" for an example.
|
||||
</p>
|
||||
<p>
|
||||
When a source is instantiated, it contains the current HLog that the
|
||||
region server is writing to. During log rolling, the new file is added
|
||||
to the queue of each slave cluster's znode just before it's made available.
|
||||
This ensures that all the sources are aware that a new log exists
|
||||
before HLog is able to append edits into it, but this operations is
|
||||
now more expensive.
|
||||
The queue items are discarded when the replication thread cannot read
|
||||
more entries from a file (because it reached the end of the last block)
|
||||
and that there are other files in the queue.
|
||||
This means that if a source is up-to-date and replicates from the log
|
||||
that the region server writes to, reading up to the "end" of the
|
||||
current file won't delete the item in the queue.
|
||||
</p>
|
||||
<p>
|
||||
When a log is archived (because it's not used anymore or because there's
|
||||
too many of them per hbase.regionserver.maxlogs typically because insertion
|
||||
rate is faster than region flushing), it will notify the source threads that the path
|
||||
for that log changed. If the a particular source was already done with
|
||||
it, it will just ignore the message. If it's in the queue, the path
|
||||
will be updated in memory. If the log is currently being replicated,
|
||||
the change will be done atomically so that the reader doesn't try to
|
||||
open the file when it's already moved. Also, moving a file is a NameNode
|
||||
operation so, if the reader is currently reading the log, it won't
|
||||
generate any exception.
|
||||
</p>
|
||||
</section>
|
||||
<section name="Reading, filtering and sending edits">
|
||||
<p>
|
||||
By default, a source will try to read from a log file and ship log
|
||||
entries as fast as possible to a sink. This is first limited by the
|
||||
filtering of log entries; only KeyValues that are scoped GLOBAL and
|
||||
that don't belong to catalog tables will be retained. A second limit
|
||||
is imposed on the total size of the list of edits to replicate per slave,
|
||||
which by default is 64MB. This means that a master cluster RS with 3 slaves
|
||||
will use at most 192MB to store data to replicate. This doesn't account
|
||||
the data filtered that wasn't garbage collected.
|
||||
</p>
|
||||
<p>
|
||||
Once the maximum size of edits was buffered or the reader hits the end
|
||||
of the log file, the source thread will stop reading and will choose
|
||||
at random a sink to replicate to (from the list that was generated by
|
||||
keeping only a subset of slave RSs). It will directly issue a RPC to
|
||||
the chosen machine and will wait for the method to return. If it's
|
||||
successful, the source will determine if the current file is emptied
|
||||
or if it should continue to read from it. If the former, it will delete
|
||||
the znode in the queue. If the latter, it will register the new offset
|
||||
in the log's znode. If the RPC threw an exception, the source will retry
|
||||
10 times until trying to find a different sink.
|
||||
</p>
|
||||
</section>
|
||||
<section name="Cleaning logs">
|
||||
<p>
|
||||
If replication isn't enabled, the master's logs cleaning thread will
|
||||
delete old logs using a configured TTL. This doesn't work well with
|
||||
replication since archived logs passed their TTL may still be in a
|
||||
queue. Thus, the default behavior is augmented so that if a log is
|
||||
passed its TTL, the cleaning thread will lookup every queue until it
|
||||
finds the log (while caching the ones it finds). If it's not found,
|
||||
the log will be deleted. The next time it has to look for a log,
|
||||
it will first use its cache.
|
||||
</p>
|
||||
</section>
|
||||
<section name="Region server failover">
|
||||
<p>
|
||||
As long as region servers don't fail, keeping track of the logs in ZK
|
||||
doesn't add any value. Unfortunately, they do fail, so since ZooKeeper
|
||||
is highly available we can count on it and its semantics to help us
|
||||
managing the transfer of the queues.
|
||||
</p>
|
||||
<p>
|
||||
All the master cluster RSs keep a watcher on every other one of them to be
|
||||
notified when one dies (just like the master does). When it happens,
|
||||
they all race to create a znode called "lock" inside the dead RS' znode
|
||||
that contains its queues. The one that creates it successfully will
|
||||
proceed by transferring all the queues to its own znode (one by one
|
||||
since ZK doesn't support the rename operation) and will delete all the
|
||||
old ones when it's done. The recovered queues' znodes will be named
|
||||
with the id of the slave cluster appended with the name of the dead
|
||||
server.
|
||||
</p>
|
||||
<p>
|
||||
Once that is done, the master cluster RS will create one new source thread per
|
||||
copied queue, and each of them will follow the read/filter/ship pattern.
|
||||
The main difference is that those queues will never have new data since
|
||||
they don't belong to their new region server, which means that when
|
||||
the reader hits the end of the last log, the queue's znode will be
|
||||
deleted and the master cluster RS will close that replication source.
|
||||
</p>
|
||||
<p>
|
||||
For example, consider a master cluster with 3 region servers that's
|
||||
replicating to a single slave with id '2'. The following hierarchy
|
||||
represents what the znodes layout could be at some point in time. We
|
||||
can see the RSs' znodes all contain a "peers" znode that contains a
|
||||
single queue. The znode names in the queues represent the actual file
|
||||
names on HDFS in the form "address,port.timestamp".
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/rs/
|
||||
1.1.1.1,60020,123456780/
|
||||
2/
|
||||
1.1.1.1,60020.1234 (Contains a position)
|
||||
1.1.1.1,60020.1265
|
||||
1.1.1.2,60020,123456790/
|
||||
2/
|
||||
1.1.1.2,60020.1214 (Contains a position)
|
||||
1.1.1.2,60020.1248
|
||||
1.1.1.2,60020.1312
|
||||
1.1.1.3,60020, 123456630/
|
||||
2/
|
||||
1.1.1.3,60020.1280 (Contains a position)
|
||||
</pre>
|
||||
<p>
|
||||
Now let's say that 1.1.1.2 loses its ZK session. The survivors will race
|
||||
to create a lock, and for some reasons 1.1.1.3 wins. It will then start
|
||||
transferring all the queues to its local peers znode by appending the
|
||||
name of the dead server. Right before 1.1.1.3 is able to clean up the
|
||||
old znodes, the layout will look like the following:
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/rs/
|
||||
1.1.1.1,60020,123456780/
|
||||
2/
|
||||
1.1.1.1,60020.1234 (Contains a position)
|
||||
1.1.1.1,60020.1265
|
||||
1.1.1.2,60020,123456790/
|
||||
lock
|
||||
2/
|
||||
1.1.1.2,60020.1214 (Contains a position)
|
||||
1.1.1.2,60020.1248
|
||||
1.1.1.2,60020.1312
|
||||
1.1.1.3,60020,123456630/
|
||||
2/
|
||||
1.1.1.3,60020.1280 (Contains a position)
|
||||
|
||||
2-1.1.1.2,60020,123456790/
|
||||
1.1.1.2,60020.1214 (Contains a position)
|
||||
1.1.1.2,60020.1248
|
||||
1.1.1.2,60020.1312
|
||||
</pre>
|
||||
<p>
|
||||
Some time later, but before 1.1.1.3 is able to finish replicating the
|
||||
last HLog from 1.1.1.2, let's say that it dies too (also some new logs
|
||||
were created in the normal queues). The last RS will then try to lock
|
||||
1.1.1.3's znode and will begin transferring all the queues. The new
|
||||
layout will be:
|
||||
</p>
|
||||
<pre>
|
||||
/hbase/replication/rs/
|
||||
1.1.1.1,60020,123456780/
|
||||
2/
|
||||
1.1.1.1,60020.1378 (Contains a position)
|
||||
|
||||
2-1.1.1.3,60020,123456630/
|
||||
1.1.1.3,60020.1325 (Contains a position)
|
||||
1.1.1.3,60020.1401
|
||||
|
||||
2-1.1.1.2,60020,123456790-1.1.1.3,60020,123456630/
|
||||
1.1.1.2,60020.1312 (Contains a position)
|
||||
1.1.1.3,60020,123456630/
|
||||
lock
|
||||
2/
|
||||
1.1.1.3,60020.1325 (Contains a position)
|
||||
1.1.1.3,60020.1401
|
||||
|
||||
2-1.1.1.2,60020,123456790/
|
||||
1.1.1.2,60020.1312 (Contains a position)
|
||||
</pre>
|
||||
</section>
|
||||
</section>
|
||||
<section name="Replication Metrics">
|
||||
Following the some useful metrics which can be used to check the replication progress:
|
||||
<ul>
|
||||
<li><b>source.sizeOfLogQueue:</b> number of HLogs to process (excludes the one which is being
|
||||
processed) at the Replication source</li>
|
||||
<li><b>source.shippedOps:</b> number of mutations shipped</li>
|
||||
<li><b>source.logEditsRead:</b> number of mutations read from HLogs at the replication source</li>
|
||||
<li><b>source.ageOfLastShippedOp:</b> age of last batch that was shipped by the replication source</li>
|
||||
</ul>
|
||||
Please note that the above metrics are at the global level at this regionserver. In 0.95.0 and onwards, these
|
||||
metrics are also exposed per peer level.
|
||||
</section>
|
||||
|
||||
<section name="FAQ">
|
||||
<section name="GLOBAL means replicate? Any provision to replicate only to cluster X and not to cluster Y? or is that for later?">
|
||||
<p>
|
||||
Yes, this is for much later.
|
||||
</p>
|
||||
</section>
|
||||
<section name="You need a bulk edit shipper? Something that allows you transfer 64MB of edits in one go?">
|
||||
<p>
|
||||
You can use the HBase-provided utility called CopyTable from the package
|
||||
org.apache.hadoop.hbase.mapreduce in order to have a discp-like tool to
|
||||
bulk copy data.
|
||||
</p>
|
||||
</section>
|
||||
<section name="Is it a mistake that WALEdit doesn't carry Put and Delete objects, that we have to reinstantiate not only when replicating but when replaying edits also?">
|
||||
<p>
|
||||
Yes, this behavior would help a lot but it's not currently available
|
||||
in HBase (BatchUpdate had that, but it was lost in the new API).
|
||||
</p>
|
||||
</section>
|
||||
<section name="Is there an issue replicating on Hadoop 1.0/1.1 when short-circuit reads are enabled?">
|
||||
<p>
|
||||
Yes. See <a href="https://issues.apache.org/jira/browse/HDFS-2757">HDFS-2757</a>.
|
||||
</p>
|
||||
</section>
|
||||
</section>
|
||||
<p>This information has been moved to <a href="http://hbase.apache.org/book.html#cluster_replication">the Cluster Replication</a> section of the <a href="http://hbase.apache.org/book.html">Apache HBase Reference Guide</a>.</p>
|
||||
</body>
|
||||
</document>
|
||||
|
|
|
|||
|
|
@ -0,0 +1,92 @@
|
|||
<?xml version="1.0"?>
|
||||
<xsl:stylesheet xmlns:xsl="http://www.w3.org/1999/XSL/Transform" version="1.0">
|
||||
|
||||
|
||||
<!--
|
||||
/**
|
||||
* Copyright 2010 The Apache Software Foundation
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
This stylesheet is used making an html version of hbase-default.adoc.
|
||||
-->
|
||||
|
||||
<xsl:output method="text"/>
|
||||
|
||||
<!-- Normalize space -->
|
||||
<xsl:template match="text()">
|
||||
<xsl:if test="normalize-space(.)">
|
||||
<xsl:value-of select="normalize-space(.)"/>
|
||||
</xsl:if>
|
||||
</xsl:template>
|
||||
|
||||
<!-- Grab nodes of the <configuration> element -->
|
||||
<xsl:template match="configuration">
|
||||
|
||||
<!-- Print the license at the top of the file -->
|
||||
////
|
||||
/**
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
////
|
||||
:doctype: book
|
||||
:numbered:
|
||||
:toc: left
|
||||
:icons: font
|
||||
:experimental:
|
||||
|
||||
[[hbase_default_configurations]]
|
||||
=== HBase Default Configuration
|
||||
|
||||
The documentation below is generated using the default hbase configuration file, _hbase-default.xml_, as source.
|
||||
|
||||
<xsl:for-each select="property">
|
||||
<xsl:if test="not(@skipInDoc)">
|
||||
[[<xsl:apply-templates select="name"/>]]
|
||||
`<xsl:apply-templates select="name"/>`::
|
||||
+
|
||||
.Description
|
||||
<xsl:apply-templates select="description"/>
|
||||
+
|
||||
.Default
|
||||
<xsl:choose>
|
||||
<xsl:when test="value != ''">`<xsl:apply-templates select="value"/>`
|
||||
|
||||
</xsl:when>
|
||||
<xsl:otherwise>none</xsl:otherwise>
|
||||
</xsl:choose>
|
||||
</xsl:if>
|
||||
</xsl:for-each>
|
||||
|
||||
</xsl:template>
|
||||
</xsl:stylesheet>
|
||||
|
|
@ -1,66 +0,0 @@
|
|||
<?xml version="1.0"?>
|
||||
<xsl:stylesheet xmlns:xsl="http://www.w3.org/1999/XSL/Transform" version="1.0">
|
||||
<xsl:output method="xml"/>
|
||||
<xsl:template match="configuration">
|
||||
<!--
|
||||
/**
|
||||
* Copyright 2010 The Apache Software Foundation
|
||||
*
|
||||
* Licensed to the Apache Software Foundation (ASF) under one
|
||||
* or more contributor license agreements. See the NOTICE file
|
||||
* distributed with this work for additional information
|
||||
* regarding copyright ownership. The ASF licenses this file
|
||||
* to you under the Apache License, Version 2.0 (the
|
||||
* "License"); you may not use this file except in compliance
|
||||
* with the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
This stylesheet is used making an html version of hbase-default.xml.
|
||||
-->
|
||||
<glossary xml:id="hbase_default_configurations"
|
||||
version="5.0" xmlns="http://docbook.org/ns/docbook"
|
||||
xmlns:xlink="http://www.w3.org/1999/xlink"
|
||||
xmlns:xi="http://www.w3.org/2001/XInclude"
|
||||
xmlns:svg="http://www.w3.org/2000/svg"
|
||||
xmlns:m="http://www.w3.org/1998/Math/MathML"
|
||||
xmlns:html="http://www.w3.org/1999/xhtml"
|
||||
xmlns:db="http://docbook.org/ns/docbook">
|
||||
<title>HBase Default Configuration</title>
|
||||
|
||||
<para>
|
||||
The documentation below is generated using the default hbase configuration file,
|
||||
<filename>hbase-default.xml</filename>, as source.
|
||||
</para>
|
||||
|
||||
<xsl:for-each select="property">
|
||||
<xsl:if test="not(@skipInDoc)">
|
||||
<glossentry>
|
||||
<xsl:attribute name="xml:id">
|
||||
<xsl:value-of select="name" />
|
||||
</xsl:attribute>
|
||||
<glossterm>
|
||||
<varname><xsl:value-of select="name"/></varname>
|
||||
</glossterm>
|
||||
<glossdef>
|
||||
<para><xsl:value-of select="description"/></para>
|
||||
<formalpara>
|
||||
<title>Default</title>
|
||||
<para><varname><xsl:value-of select="value"/></varname></para>
|
||||
</formalpara>
|
||||
</glossdef>
|
||||
</glossentry>
|
||||
</xsl:if>
|
||||
</xsl:for-each>
|
||||
|
||||
</glossary>
|
||||
|
||||
</xsl:template>
|
||||
</xsl:stylesheet>
|
||||
Loading…
Reference in New Issue