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HBASE-12738 Chunk Ref Guide into file-per-chapter

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<?xml version="1.0" encoding="UTF-8"?>
<appendix
xml:id="asf"
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">
<!--/**
* Licensed to the Apache Software Foundation (ASF) under one
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* 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
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* 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.
*/
-->
<title>HBase and the Apache Software Foundation</title>
<para>HBase is a project in the Apache Software Foundation and as such there are responsibilities to the ASF to ensure
a healthy project.</para>
<section xml:id="asf.devprocess"><title>ASF Development Process</title>
<para>See the <link xlink:href="http://www.apache.org/dev/#committers">Apache Development Process page</link>
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.
</para>
</section>
<section xml:id="asf.reporting"><title>ASF Board Reporting</title>
<para>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 xlink:href="http://www.apache.org/foundation/board/reporting">ASF board reporting</link> for more information.
</para>
</section>
</appendix>

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<?xml version="1.0" encoding="UTF-8"?>
<appendix
xml:id="compression"
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"
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xmlns:m="http://www.w3.org/1998/Math/MathML"
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xmlns:db="http://docbook.org/ns/docbook">
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* 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.
*/
-->
<title>Compression and Data Block Encoding In
HBase<indexterm><primary>Compression</primary><secondary>Data Block
Encoding</secondary><seealso>codecs</seealso></indexterm></title>
<note>
<para>Codecs mentioned in this section are for encoding and decoding data blocks or row keys.
For information about replication codecs, see <xref
linkend="cluster.replication.preserving.tags" />.</para>
</note>
<para>Some of the information in this section is pulled from a <link
xlink:href="http://search-hadoop.com/m/lL12B1PFVhp1/v=threaded">discussion</link> on the
HBase Development mailing list.</para>
<para>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.</para>
<para>Compressors and data block encoding can be used together on the same ColumnFamily.</para>
<formalpara>
<title>Changes Take Effect Upon Compaction</title>
<para>If you change compression or encoding for a ColumnFamily, the changes take effect during
compaction.</para>
</formalpara>
<para>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.</para>
<para>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 <xref
linkend="compression.test" /> utility to check that a given codec is correctly
installed.</para>
<para>To configure HBase to use a compressor, see <xref
linkend="compressor.install" />. To enable a compressor for a ColumnFamily, see <xref
linkend="changing.compression" />. To enable data block encoding for a ColumnFamily, see
<xref linkend="data.block.encoding.enable" />.</para>
<itemizedlist>
<title>Block Compressors</title>
<listitem>
<para>none</para>
</listitem>
<listitem>
<para>Snappy</para>
</listitem>
<listitem>
<para>LZO</para>
</listitem>
<listitem>
<para>LZ4</para>
</listitem>
<listitem>
<para>GZ</para>
</listitem>
</itemizedlist>
<itemizedlist xml:id="data.block.encoding.types">
<title>Data Block Encoding Types</title>
<listitem>
<para>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
<literal>RowKey:Family:Qualifier0</literal> and the next key might be
<literal>RowKey:Family:Qualifier1</literal>. 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 <literal>23</literal>, since they have the
first 23 characters in common.</para>
<para>Obviously if the keys tend to have nothing in common, Prefix will not provide much
benefit.</para>
<para>The following image shows a hypothetical ColumnFamily with no data block encoding.</para>
<figure>
<title>ColumnFamily with No Encoding</title>
<mediaobject>
<imageobject>
<imagedata fileref="data_block_no_encoding.png" width="800"/>
</imageobject>
<caption><para>A ColumnFamily with no encoding></para></caption>
</mediaobject>
</figure>
<para>Here is the same data with prefix data encoding.</para>
<figure>
<title>ColumnFamily with Prefix Encoding</title>
<mediaobject>
<imageobject>
<imagedata fileref="data_block_prefix_encoding.png" width="800"/>
</imageobject>
<caption><para>A ColumnFamily with prefix encoding</para></caption>
</mediaobject>
</figure>
</listitem>
<listitem>
<para>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.</para>
<para>Diff encoding is disabled by default because writing and scanning are slower but more
data is cached.</para>
<para>This image shows the same ColumnFamily from the previous images, with Diff encoding.</para>
<figure>
<title>ColumnFamily with Diff Encoding</title>
<mediaobject>
<imageobject>
<imagedata fileref="data_block_diff_encoding.png" width="800"/>
</imageobject>
<caption><para>A ColumnFamily with diff encoding</para></caption>
</mediaobject>
</figure>
</listitem>
<listitem>
<para>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.</para>
</listitem>
<listitem>
<para>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
xlink:href="https://issues.apache.org/jira/browse/HBASE-4676">HBASE-4676</link>. It is
difficult to graphically illustrate a prefix tree, so no image is included. See the
Wikipedia article for <link
xlink:href="http://en.wikipedia.org/wiki/Trie">Trie</link> for more general information
about this data structure.</para>
</listitem>
</itemizedlist>
<section>
<title>Which Compressor or Data Block Encoder To Use</title>
<para>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 xlink:href="http://search-hadoop.com/m/lL12B1PFVhp1">Documenting Guidance on compression and codecs</link>. </para>
<itemizedlist>
<listitem>
<para>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.</para>
</listitem>
<listitem>
<para>If the values are large (and not precompressed, such as images), use a data block
compressor.</para>
</listitem>
<listitem>
<para>Use GZIP for <firstterm>cold data</firstterm>, which is accessed infrequently. GZIP
compression uses more CPU resources than Snappy or LZO, but provides a higher
compression ratio.</para>
</listitem>
<listitem>
<para>Use Snappy or LZO for <firstterm>hot data</firstterm>, which is accessed
frequently. Snappy and LZO use fewer CPU resources than GZIP, but do not provide as high
of a compression ratio.</para>
</listitem>
<listitem>
<para>In most cases, enabling Snappy or LZO by default is a good choice, because they have
a low performance overhead and provide space savings.</para>
</listitem>
<listitem>
<para>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.</para>
</listitem>
</itemizedlist>
</section>
<section xml:id="hadoop.native.lib">
<title>Making use of Hadoop Native Libraries in HBase</title>
<para>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.</para>
<para>If you see the following in your HBase logs, you know that HBase was unable
to locate the Hadoop native libraries:
<programlisting>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</programlisting>
If the libraries loaded successfully, the WARN message does not show.
</para>
<para>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):
<programlisting>$ ./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</programlisting>
Above shows that the native hadoop library is not available in HBase context.
</para>
<para>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 <varname>LD_LIBRARY_PATH</varname> environment
variable.</para>
<para>Where the JVM looks to find native librarys is "system dependent"
(See <classname>java.lang.System#loadLibrary(name)</classname>). On linux, by default,
is going to look in <filename>lib/native/PLATFORM</filename> where <varname>PLATFORM</varname>
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
<varname>os.name</varname> and <varname>os.arch</varname> 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:
<programlisting>....
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
...
</programlisting>
So in this case, the PLATFORM string is <varname>Linux-amd64-64</varname>.
Copying the Hadoop native libraries or symlinking at <filename>lib/native/Linux-amd64-64</filename>
will ensure they are found. Check with the Hadoop <filename>NativeLibraryChecker</filename>.
</para>
<para>Here is example of how to point at the Hadoop libs with <varname>LD_LIBRARY_PATH</varname>
environment variable:
<programlisting>$ 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 &amp; initialized native-bzip2 library system-native
2014-08-26 13:42:49,337 INFO [main] zlib.ZlibFactory: Successfully loaded &amp; 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</programlisting>
Set in <filename>hbase-env.sh</filename> the LD_LIBRARY_PATH environment variable when starting your HBase.
</para>
</section>
<section>
<title>Compressor Configuration, Installation, and Use</title>
<section
xml:id="compressor.install">
<title>Configure HBase For Compressors</title>
<para>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 </para>
<section>
<title>Compressor Support On the Master</title>
<para>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,
<code>hbase.master.check.compression</code>, defaults to <literal>true</literal>. This
prevents the situation described in <link
xlink:href="https://issues.apache.org/jira/browse/HBASE-6370">HBASE-6370</link>, 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. </para>
<para>If <code>hbase.master.check.compression</code> 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.</para>
</section>
<section>
<title>Install GZ Support Via Native Libraries</title>
<para>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 <envar>HBASE_LIBRARY_PATH</envar> for the user running
HBase. If native libraries are not available and Java's GZIP is used, <literal>Got
brand-new compressor</literal> reports will be present in the logs. See <xref
linkend="brand.new.compressor" />).</para>
</section>
<section
xml:id="lzo.compression">
<title>Install LZO Support</title>
<para>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
xlink:href="http://wiki.apache.org/hadoop/UsingLzoCompression">Using LZO
Compression</link> wiki page for information on configuring LZO support for HBase. </para>
<para>If you depend upon LZO compression, consider configuring your RegionServers to fail
to start if LZO is not available. See <xref
linkend="hbase.regionserver.codecs" />.</para>
</section>
<section
xml:id="lz4.compression">
<title>Configure LZ4 Support</title>
<para>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 <xref
linkend="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:
<programlisting language="bourne">$ cd $HBASE_HOME
$ mkdir lib/native
$ ln -s $HADOOP_HOME/lib/native lib/native/Linux-amd64-64</programlisting>
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.:
<screen>
hbase(main):003:0> <userinput>alter 'TestTable', {NAME => 'info', COMPRESSION => 'LZ4'}</userinput>
</screen>
</para>
</section>
<section
xml:id="snappy.compression.installation">
<title>Install Snappy Support</title>
<para>HBase does not ship with Snappy support because of licensing issues. You can install
Snappy binaries (for instance, by using <command>yum install snappy</command> on CentOS)
or build Snappy from source. After installing Snappy, search for the shared library,
which will be called <filename>libsnappy.so.X</filename> where X is a number. If you
built from source, copy the shared library to a known location on your system, such as
<filename>/opt/snappy/lib/</filename>.</para>
<para>In addition to the Snappy library, HBase also needs access to the Hadoop shared
library, which will be called something like <filename>libhadoop.so.X.Y</filename>,
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.</para>
<note>
<para>The Snappy and Hadoop libraries need to be available on each node of your cluster.
See <xref
linkend="compression.test" /> to find out how to test that this is the case.</para>
<para>See <xref
linkend="hbase.regionserver.codecs" /> to configure your RegionServers to fail to
start if a given compressor is not available.</para>
</note>
<para>Each of these library locations need to be added to the environment variable
<envar>HBASE_LIBRARY_PATH</envar> for the operating system user that runs HBase. You
need to restart the RegionServer for the changes to take effect.</para>
</section>
<section
xml:id="compression.test">
<title>CompressionTest</title>
<para>You can use the CompressionTest tool to verify that your compressor is available to
HBase:</para>
<screen language="bourne">
$ hbase org.apache.hadoop.hbase.util.CompressionTest hdfs://<replaceable>host/path/to/hbase</replaceable> snappy
</screen>
</section>
<section
xml:id="hbase.regionserver.codecs">
<title>Enforce Compression Settings On a RegionServer</title>
<para>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
<filename>hbase-site.xml</filename>, and setting its value to a comma-separated list
of codecs that need to be available. For example, if you set this property to
<literal>lzo,gz</literal>, 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.</para>
</section>
</section>
<section
xml:id="changing.compression">
<title>Enable Compression On a ColumnFamily</title>
<para>To enable compression for a ColumnFamily, use an <code>alter</code> 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.</para>
<example>
<title>Enabling Compression on a ColumnFamily of an Existing Table using HBase
Shell</title>
<screen><![CDATA[
hbase> disable 'test'
hbase> alter 'test', {NAME => 'cf', COMPRESSION => 'GZ'}
hbase> enable 'test']]>
</screen>
</example>
<example>
<title>Creating a New Table with Compression On a ColumnFamily</title>
<screen><![CDATA[
hbase> create 'test2', { NAME => 'cf2', COMPRESSION => 'SNAPPY' }
]]></screen>
</example>
<example>
<title>Verifying a ColumnFamily's Compression Settings</title>
<screen><![CDATA[
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
]]></screen>
</example>
</section>
<section>
<title>Testing Compression Performance</title>
<para>HBase includes a tool called LoadTestTool which provides mechanisms to test your
compression performance. You must specify either <literal>-write</literal> or
<literal>-update-read</literal> as your first parameter, and if you do not specify another
parameter, usage advice is printed for each option.</para>
<example>
<title><command>LoadTestTool</command> Usage</title>
<screen language="bourne"><![CDATA[
$ 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
]]></screen>
</example>
<example>
<title>Example Usage of LoadTestTool</title>
<screen language="bourne">
$ 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
</screen>
</example>
</section>
</section>
<section xml:id="data.block.encoding.enable">
<title>Enable Data Block Encoding</title>
<para>Codecs are built into HBase so no extra configuration is needed. Codecs are enabled on a
table by setting the <code>DATA_BLOCK_ENCODING</code> property. Disable the table before
altering its DATA_BLOCK_ENCODING setting. Following is an example using HBase Shell:</para>
<example>
<title>Enable Data Block Encoding On a Table</title>
<screen><![CDATA[
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
]]></screen>
</example>
<example>
<title>Verifying a ColumnFamily's Data Block Encoding</title>
<screen><![CDATA[
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
]]></screen>
</example>
</section>
</appendix>

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<!--presumes the pre-site target has put the hbase-default.xml at this location--> <!--presumes the pre-site target has put the hbase-default.xml at this location-->
<xi:include <xi:include
xmlns:xi="http://www.w3.org/2001/XInclude" xmlns:xi="http://www.w3.org/2001/XInclude"
href="../../../target/docbkx/hbase-default.xml"> href="hbase-default.xml">
<xi:fallback> <!--<xi:fallback>
<section <section
xml:id="hbase_default_configurations"> xml:id="hbase_default_configurations">
<title /> <title />
@ -1007,7 +1007,7 @@ stopping hbase...............</screen>
</section> </section>
</section> </section>
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</xi:include> </xi:include>
</section> </section>

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<?xml version="1.0"?>
<xsl:stylesheet
xmlns:xsl="http://www.w3.org/1999/XSL/Transform"
version="1.0">
<!--
/**
* 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.
*/
-->
<xsl:import href="urn:docbkx:stylesheet/docbook.xsl"/>
<xsl:import href="urn:docbkx:stylesheet/highlight.xsl"/>
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<xsl:param name="body.margin.top">10mm</xsl:param>
<xsl:param name="body.margin.bottom">15mm</xsl:param>
<xsl:param name="region.after.extent">10mm</xsl:param>
<xsl:param name="page.margin.bottom">0mm</xsl:param>
<xsl:param name="page.margin.outer">18mm</xsl:param>
<xsl:param name="page.margin.inner">18mm</xsl:param>
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<xsl:param name="body.font.small">8</xsl:param>
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<xsl:param name="ulink.hyphenate.chars">/&amp;?</xsl:param>
<xsl:param name="ulink.hyphenate">&#x200B;</xsl:param>
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<xsl:attribute name="break-after">page</xsl:attribute>
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<?xml version="1.0" encoding="UTF-8"?>
<chapter
xml:id="datamodel"
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">
<!--/**
* 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.
*/
-->
<title>Data Model</title>
<para>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.</para>
<variablelist>
<title>HBase Data Model Terminology</title>
<varlistentry>
<term>Table</term>
<listitem>
<para>An HBase table consists of multiple rows.</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Row</term>
<listitem>
<para>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.</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Column</term>
<listitem>
<para>A column in HBase consists of a column family and a column qualifier, which are
delimited by a <literal>:</literal> (colon) character.</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Column Family</term>
<listitem>
<para>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.</para>
<para>Column families are specified when you create your table, and influence the way your
data is stored in the underlying filesystem. Therefore, the column families should be
considered carefully during schema design.</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Column Qualifier</term>
<listitem>
<para>A column qualifier is added to a column family to provide the index for a given
piece of data. Given a column family <literal>content</literal>, a column qualifier
might be <literal>content:html</literal>, and another might be
<literal>content:pdf</literal>. Though column families are fixed at table creation,
column qualifiers are mutable and may differ greatly between rows.</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Cell</term>
<listitem>
<para>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.</para>
<para>A cell's value is an uninterpreted array of bytes.</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Timestamp</term>
<listitem>
<para>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.</para>
<caution>
<para>Direct manipulation of timestamps is an advanced feature which is only exposed for
special cases that are deeply integrated with HBase, and is discouraged in general.
Encoding a timestamp at the application level is the preferred pattern.</para>
</caution>
<para>You can specify the maximum number of versions of a value that HBase retains, per column
family. When the maximum number of versions is reached, the oldest versions are
eventually deleted. By default, only the newest version is kept.</para>
</listitem>
</varlistentry>
</variablelist>
<section
xml:id="conceptual.view">
<title>Conceptual View</title>
<para>You can read a very understandable explanation of the HBase data model in the blog post <link
xlink:href="http://jimbojw.com/wiki/index.php?title=Understanding_Hbase_and_BigTable">Understanding
HBase and BigTable</link> by Jim R. Wilson. Another good explanation is available in the
PDF <link
xlink:href="http://0b4af6cdc2f0c5998459-c0245c5c937c5dedcca3f1764ecc9b2f.r43.cf2.rackcdn.com/9353-login1210_khurana.pdf">Introduction
to Basic Schema Design</link> 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.</para>
<para> The following example is a slightly modified form of the one on page 2 of the <link
xlink:href="http://research.google.com/archive/bigtable.html">BigTable</link> paper. There
is a table called <varname>webtable</varname> that contains two rows
(<literal>com.cnn.www</literal>
and <literal>com.example.www</literal>), three column families named
<varname>contents</varname>, <varname>anchor</varname>, and <varname>people</varname>. In
this example, for the first row (<literal>com.cnn.www</literal>),
<varname>anchor</varname> contains two columns (<varname>anchor:cssnsi.com</varname>,
<varname>anchor:my.look.ca</varname>) and <varname>contents</varname> contains one column
(<varname>contents:html</varname>). This example contains 5 versions of the row with the
row key <literal>com.cnn.www</literal>, and one version of the row with the row key
<literal>com.example.www</literal>. The <varname>contents:html</varname> column qualifier contains the entire
HTML of a given website. Qualifiers of the <varname>anchor</varname> 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 <varname>people</varname> column family represents
people associated with the site.
</para>
<note>
<title>Column Names</title>
<para> By convention, a column name is made of its column family prefix and a
<emphasis>qualifier</emphasis>. For example, the column
<emphasis>contents:html</emphasis> is made up of the column family
<varname>contents</varname> and the <varname>html</varname> qualifier. The colon
character (<literal>:</literal>) delimits the column family from the column family
<emphasis>qualifier</emphasis>. </para>
</note>
<table
frame="all">
<title>Table <varname>webtable</varname></title>
<tgroup
cols="5"
align="left"
colsep="1"
rowsep="1">
<colspec
colname="c1" />
<colspec
colname="c2" />
<colspec
colname="c3" />
<colspec
colname="c4" />
<colspec
colname="c5" />
<thead>
<row>
<entry>Row Key</entry>
<entry>Time Stamp</entry>
<entry>ColumnFamily <varname>contents</varname></entry>
<entry>ColumnFamily <varname>anchor</varname></entry>
<entry>ColumnFamily <varname>people</varname></entry>
</row>
</thead>
<tbody>
<row>
<entry>"com.cnn.www"</entry>
<entry>t9</entry>
<entry />
<entry><varname>anchor:cnnsi.com</varname> = "CNN"</entry>
<entry />
</row>
<row>
<entry>"com.cnn.www"</entry>
<entry>t8</entry>
<entry />
<entry><varname>anchor:my.look.ca</varname> = "CNN.com"</entry>
<entry />
</row>
<row>
<entry>"com.cnn.www"</entry>
<entry>t6</entry>
<entry><varname>contents:html</varname> = "&lt;html&gt;..."</entry>
<entry />
<entry />
</row>
<row>
<entry>"com.cnn.www"</entry>
<entry>t5</entry>
<entry><varname>contents:html</varname> = "&lt;html&gt;..."</entry>
<entry />
<entry />
</row>
<row>
<entry>"com.cnn.www"</entry>
<entry>t3</entry>
<entry><varname>contents:html</varname> = "&lt;html&gt;..."</entry>
<entry />
<entry />
</row>
<row>
<entry>"com.example.www"</entry>
<entry>t5</entry>
<entry><varname>contents:html</varname> = "&lt;html&gt;..."</entry>
<entry></entry>
<entry>people:author = "John Doe"</entry>
</row>
</tbody>
</tgroup>
</table>
<para>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.</para>
<programlisting><![CDATA[
{
"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"
}
}
}
]]></programlisting>
</section>
<section
xml:id="physical.view">
<title>Physical View</title>
<para> 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.</para>
<table
frame="all">
<title>ColumnFamily <varname>anchor</varname></title>
<tgroup
cols="3"
align="left"
colsep="1"
rowsep="1">
<colspec
colname="c1" />
<colspec
colname="c2" />
<colspec
colname="c3" />
<thead>
<row>
<entry>Row Key</entry>
<entry>Time Stamp</entry>
<entry>Column Family <varname>anchor</varname></entry>
</row>
</thead>
<tbody>
<row>
<entry>"com.cnn.www"</entry>
<entry>t9</entry>
<entry><varname>anchor:cnnsi.com</varname> = "CNN"</entry>
</row>
<row>
<entry>"com.cnn.www"</entry>
<entry>t8</entry>
<entry><varname>anchor:my.look.ca</varname> = "CNN.com"</entry>
</row>
</tbody>
</tgroup>
</table>
<table
frame="all">
<title>ColumnFamily <varname>contents</varname></title>
<tgroup
cols="3"
align="left"
colsep="1"
rowsep="1">
<colspec
colname="c1" />
<colspec
colname="c2" />
<colspec
colname="c3" />
<thead>
<row>
<entry>Row Key</entry>
<entry>Time Stamp</entry>
<entry>ColumnFamily "contents:"</entry>
</row>
</thead>
<tbody>
<row>
<entry>"com.cnn.www"</entry>
<entry>t6</entry>
<entry><varname>contents:html</varname> = "&lt;html&gt;..."</entry>
</row>
<row>
<entry>"com.cnn.www"</entry>
<entry>t5</entry>
<entry><varname>contents:html</varname> = "&lt;html&gt;..."</entry>
</row>
<row>
<entry>"com.cnn.www"</entry>
<entry>t3</entry>
<entry><varname>contents:html</varname> = "&lt;html&gt;..."</entry>
</row>
</tbody>
</tgroup>
</table>
<para>The empty cells shown in the
conceptual view are not stored at all.
Thus a request for the value of the <varname>contents:html</varname> column at time stamp
<literal>t8</literal> would return no value. Similarly, a request for an
<varname>anchor:my.look.ca</varname> value at time stamp <literal>t9</literal> 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
<varname>com.cnn.www</varname> if no timestamp is specified would be: the value of
<varname>contents:html</varname> from timestamp <literal>t6</literal>, the value of
<varname>anchor:cnnsi.com</varname> from timestamp <literal>t9</literal>, the value of
<varname>anchor:my.look.ca</varname> from timestamp <literal>t8</literal>. </para>
<para>For more information about the internals of how Apache HBase stores data, see <xref
linkend="regions.arch" />. </para>
</section>
<section
xml:id="namespace">
<title>Namespace</title>
<para> 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: <itemizedlist>
<listitem>
<para>Quota Management (HBASE-8410) - Restrict the amount of resources (ie regions,
tables) a namespace can consume.</para>
</listitem>
<listitem>
<para>Namespace Security Administration (HBASE-9206) - provide another level of security
administration for tenants.</para>
</listitem>
<listitem>
<para>Region server groups (HBASE-6721) - A namespace/table can be pinned onto a subset
of regionservers thus guaranteeing a course level of isolation.</para>
</listitem>
</itemizedlist>
</para>
<section
xml:id="namespace_creation">
<title>Namespace management</title>
<para> 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:</para>
<programlisting language="xml"><![CDATA[<table namespace>:<table qualifier>]]></programlisting>
<example>
<title>Examples</title>
<programlisting language="bourne">
#Create a namespace
create_namespace 'my_ns'
</programlisting>
<programlisting language="bourne">
#create my_table in my_ns namespace
create 'my_ns:my_table', 'fam'
</programlisting>
<programlisting language="bourne">
#drop namespace
drop_namespace 'my_ns'
</programlisting>
<programlisting language="bourne">
#alter namespace
alter_namespace 'my_ns', {METHOD => 'set', 'PROPERTY_NAME' => 'PROPERTY_VALUE'}
</programlisting>
</example>
</section>
<section
xml:id="namespace_special">
<title>Predefined namespaces</title>
<para> There are two predefined special namespaces: </para>
<itemizedlist>
<listitem>
<para>hbase - system namespace, used to contain hbase internal tables</para>
</listitem>
<listitem>
<para>default - tables with no explicit specified namespace will automatically fall into
this namespace.</para>
</listitem>
</itemizedlist>
<example>
<title>Examples</title>
<programlisting language="bourne">
#namespace=foo and table qualifier=bar
create 'foo:bar', 'fam'
#namespace=default and table qualifier=bar
create 'bar', 'fam'
</programlisting>
</example>
</section>
</section>
<section
xml:id="table">
<title>Table</title>
<para> Tables are declared up front at schema definition time. </para>
</section>
<section
xml:id="row">
<title>Row</title>
<para>Row keys are uninterrpreted 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.</para>
</section>
<section
xml:id="columnfamily">
<title>Column Family<indexterm><primary>Column Family</primary></indexterm></title>
<para> Columns in Apache HBase are grouped into <emphasis>column families</emphasis>. All
column members of a column family have the same prefix. For example, the columns
<emphasis>courses:history</emphasis> and <emphasis>courses:math</emphasis> are both
members of the <emphasis>courses</emphasis> column family. The colon character
(<literal>:</literal>) delimits the column family from the <indexterm><primary>column
family qualifier</primary><secondary>Column Family Qualifier</secondary></indexterm>.
The column family prefix must be composed of <emphasis>printable</emphasis> characters. The
qualifying tail, the column family <emphasis>qualifier</emphasis>, 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.</para>
<para>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.</para>
</section>
<section
xml:id="cells">
<title>Cells<indexterm><primary>Cells</primary></indexterm></title>
<para>A <emphasis>{row, column, version} </emphasis>tuple exactly specifies a
<literal>cell</literal> in HBase. Cell content is uninterrpreted bytes</para>
</section>
<section
xml:id="data_model_operations">
<title>Data Model Operations</title>
<para>The four primary data model operations are Get, Put, Scan, and Delete. Operations are
applied via <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html">Table</link>
instances.
</para>
<section
xml:id="get">
<title>Get</title>
<para><link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html">Get</link>
returns attributes for a specified row. Gets are executed via <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#get(org.apache.hadoop.hbase.client.Get)">
Table.get</link>. </para>
</section>
<section
xml:id="put">
<title>Put</title>
<para><link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Put.html">Put</link>
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
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#put(org.apache.hadoop.hbase.client.Put)">
Table.put</link> (writeBuffer) or <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#batch(java.util.List, java.lang.Object[])">
Table.batch</link> (non-writeBuffer). </para>
</section>
<section
xml:id="scan">
<title>Scans</title>
<para><link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link>
allow iteration over multiple rows for specified attributes. </para>
<para>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".</para>
<programlisting language="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!
</programlisting>
<para>Note that generally the easiest way to specify a specific stop point for a scan is by
using the <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/InclusiveStopFilter.html">InclusiveStopFilter</link>
class. </para>
</section>
<section
xml:id="delete">
<title>Delete</title>
<para><link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Delete.html">Delete</link>
removes a row from a table. Deletes are executed via <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Table.html#delete(org.apache.hadoop.hbase.client.Delete)">
HTable.delete</link>. </para>
<para>HBase does not modify data in place, and so deletes are handled by creating new
markers called <emphasis>tombstones</emphasis>. These tombstones, along with the dead
values, are cleaned up on major compactions. </para>
<para>See <xref
linkend="version.delete" /> for more information on deleting versions of columns, and
see <xref
linkend="compaction" /> for more information on compactions. </para>
</section>
</section>
<section
xml:id="versions">
<title>Versions<indexterm><primary>Versions</primary></indexterm></title>
<para>A <emphasis>{row, column, version} </emphasis>tuple exactly specifies a
<literal>cell</literal> 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.</para>
<para>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
<code>java.util.Date.getTime()</code> or <code>System.currentTimeMillis()</code>, that is:
<quote>the difference, measured in milliseconds, between the current time and midnight,
January 1, 1970 UTC</quote>.</para>
<para>The HBase version dimension is stored in decreasing order, so that when reading from a
store file, the most recent values are found first.</para>
<para>There is a lot of confusion over the semantics of <literal>cell</literal> versions, in
HBase. In particular:</para>
<itemizedlist>
<listitem>
<para>If multiple writes to a cell have the same version, only the last written is
fetchable.</para>
</listitem>
<listitem>
<para>It is OK to write cells in a non-increasing version order.</para>
</listitem>
</itemizedlist>
<para>Below we describe how the version dimension in HBase currently works. See <link
xlink:href="https://issues.apache.org/jira/browse/HBASE-2406">HBASE-2406</link> for
discussion of HBase versions. <link
xlink:href="http://outerthought.org/blog/417-ot.html">Bending time in HBase</link>
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 limiitation
<emphasis>Overwriting values at existing timestamps</emphasis> mentioned in the
article no longer holds in HBase. This section is basically a synopsis of this article
by Bruno Dumon.</para>
<section xml:id="specify.number.of.versions">
<title>Specifying the Number of Versions to Store</title>
<para>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 <command>alter</command> command, via
<code>HColumnDescriptor.DEFAULT_VERSIONS</code>. Prior to HBase 0.96, the default number
of versions kept was <literal>3</literal>, but in 0.96 and newer has been changed to
<literal>1</literal>.</para>
<example>
<title>Modify the Maximum Number of Versions for a Column</title>
<para>This example uses HBase Shell to keep a maximum of 5 versions of column
<code>f1</code>. You could also use <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html"
>HColumnDescriptor</link>.</para>
<screen><![CDATA[hbase> alter ‘t1′, NAME => ‘f1′, VERSIONS => 5]]></screen>
</example>
<example>
<title>Modify the Minimum Number of Versions for a Column</title>
<para>You can also specify the minimum number of versions to store. By default, this is
set to 0, which means the feature is disabled. The following example sets the minimum
number of versions on field <code>f1</code> to <literal>2</literal>, via HBase Shell.
You could also use <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html"
>HColumnDescriptor</link>.</para>
<screen><![CDATA[hbase> alter ‘t1′, NAME => ‘f1′, MIN_VERSIONS => 2]]></screen>
</example>
<para>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
<option>hbase.column.max.version</option> in <filename>hbase-site.xml</filename>. See
<xref linkend="hbase.column.max.version"/>.</para>
</section>
<section
xml:id="versions.ops">
<title>Versions and HBase Operations</title>
<para>In this section we look at the behavior of the version dimension for each of the core
HBase operations.</para>
<section>
<title>Get/Scan</title>
<para>Gets are implemented on top of Scans. The below discussion of <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html">Get</link>
applies equally to <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scans</link>.</para>
<para>By default, i.e. if you specify no explicit version, when doing a
<literal>get</literal>, 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:</para>
<itemizedlist>
<listitem>
<para>to return more than one version, see <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html#setMaxVersions()">Get.setMaxVersions()</link></para>
</listitem>
<listitem>
<para>to return versions other than the latest, see <link
xlink:href="???">Get.setTimeRange()</link></para>
<para>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.</para>
</listitem>
</itemizedlist>
</section>
<section
xml:id="default_get_example">
<title>Default Get Example</title>
<para>The following Get will only retrieve the current version of the row</para>
<programlisting language="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
</programlisting>
</section>
<section
xml:id="versioned_get_example">
<title>Versioned Get Example</title>
<para>The following Get will return the last 3 versions of the row.</para>
<programlisting language="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&lt;KeyValue&gt; kv = r.getColumn(CF, ATTR); // returns all versions of this column
</programlisting>
</section>
<section>
<title>Put</title>
<para>Doing a put always creates a new version of a <literal>cell</literal>, at a certain
timestamp. By default the system uses the server's <literal>currentTimeMillis</literal>,
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.</para>
<para>To overwrite an existing value, do a put at exactly the same row, column, and
version as that of the cell you would overshadow.</para>
<section
xml:id="implicit_version_example">
<title>Implicit Version Example</title>
<para>The following Put will be implicitly versioned by HBase with the current
time.</para>
<programlisting language="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);
</programlisting>
</section>
<section
xml:id="explicit_version_example">
<title>Explicit Version Example</title>
<para>The following Put has the version timestamp explicitly set.</para>
<programlisting language="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);
</programlisting>
<para>Caution: the version timestamp is 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 a part of the rowkey,
or both. </para>
</section>
</section>
<section
xml:id="version.delete">
<title>Delete</title>
<para>There are three different types of internal delete markers. See Lars Hofhansl's blog
for discussion of his attempt adding another, <link
xlink:href="http://hadoop-hbase.blogspot.com/2012/01/scanning-in-hbase.html">Scanning
in HBase: Prefix Delete Marker</link>. </para>
<itemizedlist>
<listitem>
<para>Delete: for a specific version of a column.</para>
</listitem>
<listitem>
<para>Delete column: for all versions of a column.</para>
</listitem>
<listitem>
<para>Delete family: for all columns of a particular ColumnFamily</para>
</listitem>
</itemizedlist>
<para>When deleting an entire row, HBase will internally create a tombstone for each
ColumnFamily (i.e., not each individual column). </para>
<para>Deletes work by creating <emphasis>tombstone</emphasis> markers. For example, let's
suppose we want to delete a row. For this you can specify a version, or else by default
the <literal>currentTimeMillis</literal> is used. What this means is <quote>delete all
cells where the version is less than or equal to this version</quote>. 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 <emphasis>tombstone</emphasis> 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.</para>
<para>For an informative discussion on how deletes and versioning interact, see the thread <link
xlink:href="http://comments.gmane.org/gmane.comp.java.hadoop.hbase.user/28421">Put w/
timestamp -> Deleteall -> Put w/ timestamp fails</link> up on the user mailing
list.</para>
<para>Also see <xref
linkend="keyvalue" /> for more information on the internal KeyValue format. </para>
<para>Delete markers are purged during the next major compaction of the store, unless the
<option>KEEP_DELETED_CELLS</option> option is set in the column family. To keep the
deletes for a configurable amount of time, you can set the delete TTL via the
<option>hbase.hstore.time.to.purge.deletes</option> property in
<filename>hbase-site.xml</filename>. If
<option>hbase.hstore.time.to.purge.deletes</option> 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 <option>hbase.hstore.time.to.purge.deletes</option>, in
milliseconds. </para>
<note>
<para>This behavior represents a fix for an unexpected change that was introduced in
HBase 0.94, and was fixed in <link
xlink:href="https://issues.apache.org/jira/browse/HBASE-10118">HBASE-10118</link>.
The change has been backported to HBase 0.94 and newer branches.</para>
</note>
</section>
</section>
<section>
<title>Current Limitations</title>
<section>
<title>Deletes mask Puts</title>
<para>Deletes mask puts, even puts that happened after the delete
was entered. See <link xlink:href="https://issues.apache.org/jira/browse/HBASE-2256"
>HBASE-2256</link>. Remember that a delete writes a tombstone, which only
disappears after then next major compaction has run. Suppose you do
a delete of everything &lt;= T. After this you do a new put with a
timestamp &lt;= 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.</para>
</section>
<section
xml:id="major.compactions.change.query.results">
<title>Major compactions change query results</title>
<para><quote>...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...</quote> (See <emphasis>Garbage Collection</emphasis> in <link
xlink:href="http://outerthought.org/blog/417-ot.html">Bending time in
HBase</link>.)</para>
</section>
</section>
</section>
<section xml:id="dm.sort">
<title>Sort Order</title>
<para>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).
</para>
</section>
<section xml:id="dm.column.metadata">
<title>Column Metadata</title>
<para>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 heterogenous set of columns
between rows as well, it is your responsibility to keep track of the column names.
</para>
<para>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 <xref linkend="keyvalue" />.
</para>
</section>
<section xml:id="joins"><title>Joins</title>
<para>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.
</para>
<para>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.
</para>
</section>
<section xml:id="acid"><title>ACID</title>
<para>See <link xlink:href="http://hbase.apache.org/acid-semantics.html">ACID Semantics</link>.
Lars Hofhansl has also written a note on
<link xlink:href="http://hadoop-hbase.blogspot.com/2012/03/acid-in-hbase.html">ACID in HBase</link>.</para>
</section>
</chapter>

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<?xml version="1.0" encoding="UTF-8"?>
<appendix
xml:id="faq"
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">
<!--/**
* 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.
*/
-->
<title >FAQ</title>
<qandaset defaultlabel='qanda'>
<qandadiv><title>General</title>
<qandaentry>
<question><para>When should I use HBase?</para></question>
<answer>
<para>See the <xref linkend="arch.overview" /> in the Architecture chapter.
</para>
</answer>
</qandaentry>
<qandaentry>
<question><para>Are there other HBase FAQs?</para></question>
<answer>
<para>
See the FAQ that is up on the wiki, <link xlink:href="http://wiki.apache.org/hadoop/Hbase/FAQ">HBase Wiki FAQ</link>.
</para>
</answer>
</qandaentry>
<qandaentry xml:id="faq.sql">
<question><para>Does HBase support SQL?</para></question>
<answer>
<para>
Not really. SQL-ish support for HBase via <link xlink:href="http://hive.apache.org/">Hive</link> is in development, however Hive is based on MapReduce which is not generally suitable for low-latency requests.
See the <xref linkend="datamodel" /> section for examples on the HBase client.
</para>
</answer>
</qandaentry>
<qandaentry>
<question><para>How can I find examples of NoSQL/HBase?</para></question>
<answer>
<para>See the link to the BigTable paper in <xref linkend="other.info" /> in the appendix, as
well as the other papers.
</para>
</answer>
</qandaentry>
<qandaentry>
<question><para>What is the history of HBase?</para></question>
<answer>
<para>See <xref linkend="hbase.history"/>.
</para>
</answer>
</qandaentry>
</qandadiv>
<qandadiv>
<title>Upgrading</title>
<qandaentry>
<question>
<para>How do I upgrade Maven-managed projects from HBase 0.94 to HBase 0.96+?</para>
</question>
<answer>
<para>In HBase 0.96, the project moved to a modular structure. Adjust your project's
dependencies to rely upon the <filename>hbase-client</filename> 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 <xref
linkend="upgrade0.96"/> or <xref linkend="upgrade0.98"/> for more
information.</para>
<example>
<title>Maven Dependency for HBase 0.98</title>
<programlisting language="xml"><![CDATA[
<dependency>
<groupId>org.apache.hbase</groupId>
<artifactId>hbase-client</artifactId>
<version>0.98.5-hadoop2</version>
</dependency>
]]></programlisting>
</example>
<example>
<title>Maven Dependency for HBase 0.96</title>
<programlisting language="xml"><![CDATA[
<dependency>
<groupId>org.apache.hbase</groupId>
<artifactId>hbase-client</artifactId>
<version>0.96.2-hadoop2</version>
</dependency>
]]></programlisting>
</example>
<example>
<title>Maven Dependency for HBase 0.94</title>
<programlisting language="xml"><![CDATA[
<dependency>
<groupId>org.apache.hbase</groupId>
<artifactId>hbase</artifactId>
<version>0.94.3</version>
</dependency>
]]></programlisting>
</example>
</answer>
</qandaentry>
</qandadiv>
<qandadiv xml:id="faq.arch"><title>Architecture</title>
<qandaentry xml:id="faq.arch.regions">
<question><para>How does HBase handle Region-RegionServer assignment and locality?</para></question>
<answer>
<para>
See <xref linkend="regions.arch" />.
</para>
</answer>
</qandaentry>
</qandadiv>
<qandadiv xml:id="faq.config"><title>Configuration</title>
<qandaentry xml:id="faq.config.started">
<question><para>How can I get started with my first cluster?</para></question>
<answer>
<para>
See <xref linkend="quickstart" />.
</para>
</answer>
</qandaentry>
<qandaentry xml:id="faq.config.options">
<question><para>Where can I learn about the rest of the configuration options?</para></question>
<answer>
<para>
See <xref linkend="configuration" />.
</para>
</answer>
</qandaentry>
</qandadiv>
<qandadiv xml:id="faq.design"><title>Schema Design / Data Access</title>
<qandaentry xml:id="faq.design.schema">
<question><para>How should I design my schema in HBase?</para></question>
<answer>
<para>
See <xref linkend="datamodel" /> and <xref linkend="schema" />
</para>
</answer>
</qandaentry>
<qandaentry>
<question><para>
How can I store (fill in the blank) in HBase?
</para></question>
<answer>
<para>
See <xref linkend="supported.datatypes" />.
</para>
</answer>
</qandaentry>
<qandaentry xml:id="secondary.indices">
<question><para>
How can I handle secondary indexes in HBase?
</para></question>
<answer>
<para>
See <xref linkend="secondary.indexes" />
</para>
</answer>
</qandaentry>
<qandaentry xml:id="faq.changing.rowkeys">
<question><para>Can I change a table's rowkeys?</para></question>
<answer>
<para> This is a very common question. You can't. See <xref
linkend="changing.rowkeys"/>. </para>
</answer>
</qandaentry>
<qandaentry xml:id="faq.apis">
<question><para>What APIs does HBase support?</para></question>
<answer>
<para>
See <xref linkend="datamodel" />, <xref linkend="client" /> and <xref linkend="nonjava.jvm"/>.
</para>
</answer>
</qandaentry>
</qandadiv>
<qandadiv xml:id="faq.mapreduce"><title>MapReduce</title>
<qandaentry xml:id="faq.mapreduce.use">
<question><para>How can I use MapReduce with HBase?</para></question>
<answer>
<para>
See <xref linkend="mapreduce" />
</para>
</answer>
</qandaentry>
</qandadiv>
<qandadiv><title>Performance and Troubleshooting</title>
<qandaentry>
<question><para>
How can I improve HBase cluster performance?
</para></question>
<answer>
<para>
See <xref linkend="performance" />.
</para>
</answer>
</qandaentry>
<qandaentry>
<question><para>
How can I troubleshoot my HBase cluster?
</para></question>
<answer>
<para>
See <xref linkend="trouble" />.
</para>
</answer>
</qandaentry>
</qandadiv>
<qandadiv xml:id="ec2"><title>Amazon EC2</title>
<qandaentry>
<question><para>
I am running HBase on Amazon EC2 and...
</para></question>
<answer>
<para>
EC2 issues are a special case. See Troubleshooting <xref linkend="trouble.ec2" /> and Performance <xref linkend="perf.ec2" /> sections.
</para>
</answer>
</qandaentry>
</qandadiv>
<qandadiv><title xml:id="faq.operations">Operations</title>
<qandaentry>
<question><para>
How do I manage my HBase cluster?
</para></question>
<answer>
<para>
See <xref linkend="ops_mgt" />
</para>
</answer>
</qandaentry>
<qandaentry>
<question><para>
How do I back up my HBase cluster?
</para></question>
<answer>
<para>
See <xref linkend="ops.backup" />
</para>
</answer>
</qandaentry>
</qandadiv>
<qandadiv><title>HBase in Action</title>
<qandaentry>
<question><para>Where can I find interesting videos and presentations on HBase?</para></question>
<answer>
<para>
See <xref linkend="other.info" />
</para>
</answer>
</qandaentry>
</qandadiv>
</qandaset>
</appendix>

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<?xml version="1.0" encoding="UTF-8"?><glossary xml:id="hbase_default_configurations" version="5.0" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:xi="http://www.w3.org/2001/XInclude" xmlns:svg="http://www.w3.org/2000/svg" xmlns:html="http://www.w3.org/1999/xhtml" xmlns="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><glossentry xml:id="hbase.tmp.dir"><glossterm><varname>hbase.tmp.dir</varname></glossterm><glossdef><para>Temporary directory on the local filesystem.
Change this setting to point to a location more permanent
than '/tmp', the usual resolve for java.io.tmpdir, as the
'/tmp' directory is cleared on machine restart.</para><formalpara><title>Default</title><para><varname>${java.io.tmpdir}/hbase-${user.name}</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rootdir"><glossterm><varname>hbase.rootdir</varname></glossterm><glossdef><para>The directory shared by region servers and into
which HBase persists. The URL should be 'fully-qualified'
to include the filesystem scheme. For example, to specify the
HDFS directory '/hbase' where the HDFS instance's namenode is
running at namenode.example.org on port 9000, set this value to:
hdfs://namenode.example.org:9000/hbase. By default, we write
to whatever ${hbase.tmp.dir} is set too -- usually /tmp --
so change this configuration or else all data will be lost on
machine restart.</para><formalpara><title>Default</title><para><varname>${hbase.tmp.dir}/hbase</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.cluster.distributed"><glossterm><varname>hbase.cluster.distributed</varname></glossterm><glossdef><para>The mode the cluster will be in. Possible values are
false for standalone mode and true for distributed mode. If
false, startup will run all HBase and ZooKeeper daemons together
in the one JVM.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.quorum"><glossterm><varname>hbase.zookeeper.quorum</varname></glossterm><glossdef><para>Comma separated list of servers in the ZooKeeper ensemble
(This config. should have been named hbase.zookeeper.ensemble).
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 ensemble servers. If HBASE_MANAGES_ZK is set in hbase-env.sh
this is the list of servers which hbase will start/stop ZooKeeper on as
part of cluster start/stop. Client-side, we will take this list of
ensemble members and put it together with the hbase.zookeeper.clientPort
config. and pass it into zookeeper constructor as the connectString
parameter.</para><formalpara><title>Default</title><para><varname>localhost</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.local.dir"><glossterm><varname>hbase.local.dir</varname></glossterm><glossdef><para>Directory on the local filesystem to be used
as a local storage.</para><formalpara><title>Default</title><para><varname>${hbase.tmp.dir}/local/</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.info.port"><glossterm><varname>hbase.master.info.port</varname></glossterm><glossdef><para>The port for the HBase Master web UI.
Set to -1 if you do not want a UI instance run.</para><formalpara><title>Default</title><para><varname>16010</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.info.bindAddress"><glossterm><varname>hbase.master.info.bindAddress</varname></glossterm><glossdef><para>The bind address for the HBase Master web UI
</para><formalpara><title>Default</title><para><varname>0.0.0.0</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.logcleaner.plugins"><glossterm><varname>hbase.master.logcleaner.plugins</varname></glossterm><glossdef><para>A comma-separated list of BaseLogCleanerDelegate invoked by
the LogsCleaner service. These WAL cleaners are called in order,
so put the cleaner that prunes the most files in front. To
implement your own BaseLogCleanerDelegate, just put it in HBase's classpath
and add the fully qualified class name here. Always add the above
default log cleaners in the list.</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.master.cleaner.TimeToLiveLogCleaner</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.logcleaner.ttl"><glossterm><varname>hbase.master.logcleaner.ttl</varname></glossterm><glossdef><para>Maximum time a WAL can stay in the .oldlogdir directory,
after which it will be cleaned by a Master thread.</para><formalpara><title>Default</title><para><varname>600000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.hfilecleaner.plugins"><glossterm><varname>hbase.master.hfilecleaner.plugins</varname></glossterm><glossdef><para>A comma-separated list of BaseHFileCleanerDelegate invoked by
the HFileCleaner service. These HFiles cleaners are called in order,
so put the cleaner that prunes the most files in front. To
implement your own BaseHFileCleanerDelegate, just put it in HBase's classpath
and add the fully qualified class name here. Always add the above
default log cleaners in the list as they will be overwritten in
hbase-site.xml.</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.master.cleaner.TimeToLiveHFileCleaner</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.catalog.timeout"><glossterm><varname>hbase.master.catalog.timeout</varname></glossterm><glossdef><para>Timeout value for the Catalog Janitor from the master to
META.</para><formalpara><title>Default</title><para><varname>600000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.infoserver.redirect"><glossterm><varname>hbase.master.infoserver.redirect</varname></glossterm><glossdef><para>Whether or not the Master listens to the Master web
UI port (hbase.master.info.port) and redirects requests to the web
UI server shared by the Master and RegionServer.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.port"><glossterm><varname>hbase.regionserver.port</varname></glossterm><glossdef><para>The port the HBase RegionServer binds to.</para><formalpara><title>Default</title><para><varname>16020</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.info.port"><glossterm><varname>hbase.regionserver.info.port</varname></glossterm><glossdef><para>The port for the HBase RegionServer web UI
Set to -1 if you do not want the RegionServer UI to run.</para><formalpara><title>Default</title><para><varname>16030</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.info.bindAddress"><glossterm><varname>hbase.regionserver.info.bindAddress</varname></glossterm><glossdef><para>The address for the HBase RegionServer web UI</para><formalpara><title>Default</title><para><varname>0.0.0.0</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.info.port.auto"><glossterm><varname>hbase.regionserver.info.port.auto</varname></glossterm><glossdef><para>Whether or not the Master or RegionServer
UI should search for a port to bind to. Enables automatic port
search if hbase.regionserver.info.port is already in use.
Useful for testing, turned off by default.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.handler.count"><glossterm><varname>hbase.regionserver.handler.count</varname></glossterm><glossdef><para>Count of RPC Listener instances spun up on RegionServers.
Same property is used by the Master for count of master handlers.</para><formalpara><title>Default</title><para><varname>30</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.ipc.server.callqueue.handler.factor"><glossterm><varname>hbase.ipc.server.callqueue.handler.factor</varname></glossterm><glossdef><para>Factor to determine the number of call queues.
A value of 0 means a single queue shared between all the handlers.
A value of 1 means that each handler has its own queue.</para><formalpara><title>Default</title><para><varname>0.1</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.ipc.server.callqueue.read.ratio"><glossterm><varname>hbase.ipc.server.callqueue.read.ratio</varname></glossterm><glossdef><para>Split the call queues into read and write queues.
The specified interval (which should be between 0.0 and 1.0)
will be multiplied by the number of call queues.
A value of 0 indicate to not split the call queues, meaning that both read and write
requests will be pushed to the same set of queues.
A value lower than 0.5 means that there will be less read queues than write queues.
A value of 0.5 means there will be the same number of read and write queues.
A value greater than 0.5 means that there will be more read queues than write queues.
A value of 1.0 means that all the queues except one are used to dispatch read requests.
Example: Given the total number of call queues being 10
a read.ratio of 0 means that: the 10 queues will contain both read/write requests.
a read.ratio of 0.3 means that: 3 queues will contain only read requests
and 7 queues will contain only write requests.
a read.ratio of 0.5 means that: 5 queues will contain only read requests
and 5 queues will contain only write requests.
a read.ratio of 0.8 means that: 8 queues will contain only read requests
and 2 queues will contain only write requests.
a read.ratio of 1 means that: 9 queues will contain only read requests
and 1 queues will contain only write requests.
</para><formalpara><title>Default</title><para><varname>0</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.ipc.server.callqueue.scan.ratio"><glossterm><varname>hbase.ipc.server.callqueue.scan.ratio</varname></glossterm><glossdef><para>Given the number of read call queues, calculated from the total number
of call queues multiplied by the callqueue.read.ratio, the scan.ratio property
will split the read call queues into small-read and long-read queues.
A value lower than 0.5 means that there will be less long-read queues than short-read queues.
A value of 0.5 means that there will be the same number of short-read and long-read queues.
A value greater than 0.5 means that there will be more long-read queues than short-read queues
A value of 0 or 1 indicate to use the same set of queues for gets and scans.
Example: Given the total number of read call queues being 8
a scan.ratio of 0 or 1 means that: 8 queues will contain both long and short read requests.
a scan.ratio of 0.3 means that: 2 queues will contain only long-read requests
and 6 queues will contain only short-read requests.
a scan.ratio of 0.5 means that: 4 queues will contain only long-read requests
and 4 queues will contain only short-read requests.
a scan.ratio of 0.8 means that: 6 queues will contain only long-read requests
and 2 queues will contain only short-read requests.
</para><formalpara><title>Default</title><para><varname>0</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.msginterval"><glossterm><varname>hbase.regionserver.msginterval</varname></glossterm><glossdef><para>Interval between messages from the RegionServer to Master
in milliseconds.</para><formalpara><title>Default</title><para><varname>3000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.regionSplitLimit"><glossterm><varname>hbase.regionserver.regionSplitLimit</varname></glossterm><glossdef><para>Limit for the number of regions after which no more region
splitting should take place. This is not a hard limit for the number of
regions but acts as a guideline for the regionserver to stop splitting after
a certain limit. Default is MAX_INT; i.e. do not block splitting.</para><formalpara><title>Default</title><para><varname>2147483647</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.logroll.period"><glossterm><varname>hbase.regionserver.logroll.period</varname></glossterm><glossdef><para>Period at which we will roll the commit log regardless
of how many edits it has.</para><formalpara><title>Default</title><para><varname>3600000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.logroll.errors.tolerated"><glossterm><varname>hbase.regionserver.logroll.errors.tolerated</varname></glossterm><glossdef><para>The number of consecutive WAL close errors we will allow
before triggering a server abort. A setting of 0 will cause the
region server to abort if closing the current WAL writer fails during
log rolling. Even a small value (2 or 3) will allow a region server
to ride over transient HDFS errors.</para><formalpara><title>Default</title><para><varname>2</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.hlog.reader.impl"><glossterm><varname>hbase.regionserver.hlog.reader.impl</varname></glossterm><glossdef><para>The WAL file reader implementation.</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.regionserver.wal.ProtobufLogReader</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.hlog.writer.impl"><glossterm><varname>hbase.regionserver.hlog.writer.impl</varname></glossterm><glossdef><para>The WAL file writer implementation.</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.regionserver.wal.ProtobufLogWriter</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.distributed.log.replay"><glossterm><varname>hbase.master.distributed.log.replay</varname></glossterm><glossdef><para>Enable 'distributed log replay' as default engine splitting
WAL files on server crash. This default is new in hbase 1.0. To fall
back to the old mode 'distributed log splitter', set the value to
'false'. 'Disributed log replay' improves MTTR because it does not
write intermediate files. 'DLR' required that 'hfile.format.version'
be set to version 3 or higher.
</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.global.memstore.size"><glossterm><varname>hbase.regionserver.global.memstore.size</varname></glossterm><glossdef><para>Maximum size of all memstores in a region server before new
updates are blocked and flushes are forced. Defaults to 40% of heap.
Updates are blocked and flushes are forced until size of all memstores
in a region server hits hbase.regionserver.global.memstore.size.lower.limit.</para><formalpara><title>Default</title><para><varname>0.4</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.global.memstore.size.lower.limit"><glossterm><varname>hbase.regionserver.global.memstore.size.lower.limit</varname></glossterm><glossdef><para>Maximum size of all memstores in a region server before flushes are forced.
Defaults to 95% of hbase.regionserver.global.memstore.size.
A 100% value for this value causes the minimum possible flushing to occur when updates are
blocked due to memstore limiting.</para><formalpara><title>Default</title><para><varname>0.95</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.optionalcacheflushinterval"><glossterm><varname>hbase.regionserver.optionalcacheflushinterval</varname></glossterm><glossdef><para>
Maximum amount of time an edit lives in memory before being automatically flushed.
Default 1 hour. Set it to 0 to disable automatic flushing.</para><formalpara><title>Default</title><para><varname>3600000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.catalog.timeout"><glossterm><varname>hbase.regionserver.catalog.timeout</varname></glossterm><glossdef><para>Timeout value for the Catalog Janitor from the regionserver to META.</para><formalpara><title>Default</title><para><varname>600000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.dns.interface"><glossterm><varname>hbase.regionserver.dns.interface</varname></glossterm><glossdef><para>The name of the Network Interface from which a region server
should report its IP address.</para><formalpara><title>Default</title><para><varname>default</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.dns.nameserver"><glossterm><varname>hbase.regionserver.dns.nameserver</varname></glossterm><glossdef><para>The host name or IP address of the name server (DNS)
which a region server should use to determine the host name used by the
master for communication and display purposes.</para><formalpara><title>Default</title><para><varname>default</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.region.split.policy"><glossterm><varname>hbase.regionserver.region.split.policy</varname></glossterm><glossdef><para>
A split policy determines when a region should be split. The various other split policies that
are available currently are ConstantSizeRegionSplitPolicy, DisabledRegionSplitPolicy,
DelimitedKeyPrefixRegionSplitPolicy, KeyPrefixRegionSplitPolicy etc.
</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.regionserver.IncreasingToUpperBoundRegionSplitPolicy</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="zookeeper.session.timeout"><glossterm><varname>zookeeper.session.timeout</varname></glossterm><glossdef><para>ZooKeeper session timeout in milliseconds. It is used in two different ways.
First, this value is used in the ZK client that HBase uses to connect to the ensemble.
It is also used by HBase when it starts a ZK server and it is passed as the 'maxSessionTimeout'. See
http://hadoop.apache.org/zookeeper/docs/current/zookeeperProgrammers.html#ch_zkSessions.
For example, if a HBase region server connects to a ZK ensemble that's also managed by HBase, then the
session timeout will be the one specified by this configuration. But, a region server that connects
to an ensemble managed with a different configuration will be subjected that ensemble's maxSessionTimeout. So,
even though HBase might propose using 90 seconds, the ensemble can have a max timeout lower than this and
it will take precedence. The current default that ZK ships with is 40 seconds, which is lower than HBase's.
</para><formalpara><title>Default</title><para><varname>90000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="zookeeper.znode.parent"><glossterm><varname>zookeeper.znode.parent</varname></glossterm><glossdef><para>Root ZNode for HBase in ZooKeeper. All of HBase's ZooKeeper
files that are configured with a relative path will go under this node.
By default, all of HBase's ZooKeeper file path are configured with a
relative path, so they will all go under this directory unless changed.</para><formalpara><title>Default</title><para><varname>/hbase</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="zookeeper.znode.rootserver"><glossterm><varname>zookeeper.znode.rootserver</varname></glossterm><glossdef><para>Path to ZNode holding root region location. This is written by
the master and read by clients and region servers. If a relative path is
given, the parent folder will be ${zookeeper.znode.parent}. By default,
this means the root location is stored at /hbase/root-region-server.</para><formalpara><title>Default</title><para><varname>root-region-server</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="zookeeper.znode.acl.parent"><glossterm><varname>zookeeper.znode.acl.parent</varname></glossterm><glossdef><para>Root ZNode for access control lists.</para><formalpara><title>Default</title><para><varname>acl</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.dns.interface"><glossterm><varname>hbase.zookeeper.dns.interface</varname></glossterm><glossdef><para>The name of the Network Interface from which a ZooKeeper server
should report its IP address.</para><formalpara><title>Default</title><para><varname>default</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.dns.nameserver"><glossterm><varname>hbase.zookeeper.dns.nameserver</varname></glossterm><glossdef><para>The host name or IP address of the name server (DNS)
which a ZooKeeper server should use to determine the host name used by the
master for communication and display purposes.</para><formalpara><title>Default</title><para><varname>default</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.peerport"><glossterm><varname>hbase.zookeeper.peerport</varname></glossterm><glossdef><para>Port used by ZooKeeper peers to talk to each other.
See http://hadoop.apache.org/zookeeper/docs/r3.1.1/zookeeperStarted.html#sc_RunningReplicatedZooKeeper
for more information.</para><formalpara><title>Default</title><para><varname>2888</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.leaderport"><glossterm><varname>hbase.zookeeper.leaderport</varname></glossterm><glossdef><para>Port used by ZooKeeper for leader election.
See http://hadoop.apache.org/zookeeper/docs/r3.1.1/zookeeperStarted.html#sc_RunningReplicatedZooKeeper
for more information.</para><formalpara><title>Default</title><para><varname>3888</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.useMulti"><glossterm><varname>hbase.zookeeper.useMulti</varname></glossterm><glossdef><para>Instructs HBase to make use of ZooKeeper's multi-update functionality.
This allows certain ZooKeeper operations to complete more quickly and prevents some issues
with rare Replication failure scenarios (see the release note of HBASE-2611 for an example).
IMPORTANT: only set this to true if all ZooKeeper servers in the cluster are on version 3.4+
and will not be downgraded. ZooKeeper versions before 3.4 do not support multi-update and
will not fail gracefully if multi-update is invoked (see ZOOKEEPER-1495).</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.config.read.zookeeper.config"><glossterm><varname>hbase.config.read.zookeeper.config</varname></glossterm><glossdef><para>
Set to true to allow HBaseConfiguration to read the
zoo.cfg file for ZooKeeper properties. Switching this to true
is not recommended, since the functionality of reading ZK
properties from a zoo.cfg file has been deprecated.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.property.initLimit"><glossterm><varname>hbase.zookeeper.property.initLimit</varname></glossterm><glossdef><para>Property from ZooKeeper's config zoo.cfg.
The number of ticks that the initial synchronization phase can take.</para><formalpara><title>Default</title><para><varname>10</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.property.syncLimit"><glossterm><varname>hbase.zookeeper.property.syncLimit</varname></glossterm><glossdef><para>Property from ZooKeeper's config zoo.cfg.
The number of ticks that can pass between sending a request and getting an
acknowledgment.</para><formalpara><title>Default</title><para><varname>5</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.property.dataDir"><glossterm><varname>hbase.zookeeper.property.dataDir</varname></glossterm><glossdef><para>Property from ZooKeeper's config zoo.cfg.
The directory where the snapshot is stored.</para><formalpara><title>Default</title><para><varname>${hbase.tmp.dir}/zookeeper</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.property.clientPort"><glossterm><varname>hbase.zookeeper.property.clientPort</varname></glossterm><glossdef><para>Property from ZooKeeper's config zoo.cfg.
The port at which the clients will connect.</para><formalpara><title>Default</title><para><varname>2181</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.zookeeper.property.maxClientCnxns"><glossterm><varname>hbase.zookeeper.property.maxClientCnxns</varname></glossterm><glossdef><para>Property from ZooKeeper's config zoo.cfg.
Limit on number of concurrent connections (at the socket level) that a
single client, identified by IP address, may make to a single member of
the ZooKeeper ensemble. Set high to avoid zk connection issues running
standalone and pseudo-distributed.</para><formalpara><title>Default</title><para><varname>300</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.write.buffer"><glossterm><varname>hbase.client.write.buffer</varname></glossterm><glossdef><para>Default size of the HTable client write buffer in bytes.
A bigger buffer takes more memory -- on both the client and server
side since server instantiates the passed write buffer to process
it -- but a larger buffer size reduces the number of RPCs made.
For an estimate of server-side memory-used, evaluate
hbase.client.write.buffer * hbase.regionserver.handler.count</para><formalpara><title>Default</title><para><varname>2097152</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.pause"><glossterm><varname>hbase.client.pause</varname></glossterm><glossdef><para>General client pause value. Used mostly as value to wait
before running a retry of a failed get, region lookup, etc.
See hbase.client.retries.number for description of how we backoff from
this initial pause amount and how this pause works w/ retries.</para><formalpara><title>Default</title><para><varname>100</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.retries.number"><glossterm><varname>hbase.client.retries.number</varname></glossterm><glossdef><para>Maximum retries. Used as maximum for all retryable
operations such as the getting of a cell's value, starting a row update,
etc. Retry interval is a rough function based on hbase.client.pause. At
first we retry at this interval but then with backoff, we pretty quickly reach
retrying every ten seconds. See HConstants#RETRY_BACKOFF for how the backup
ramps up. Change this setting and hbase.client.pause to suit your workload.</para><formalpara><title>Default</title><para><varname>35</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.max.total.tasks"><glossterm><varname>hbase.client.max.total.tasks</varname></glossterm><glossdef><para>The maximum number of concurrent tasks a single HTable instance will
send to the cluster.</para><formalpara><title>Default</title><para><varname>100</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.max.perserver.tasks"><glossterm><varname>hbase.client.max.perserver.tasks</varname></glossterm><glossdef><para>The maximum number of concurrent tasks a single HTable instance will
send to a single region server.</para><formalpara><title>Default</title><para><varname>5</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.max.perregion.tasks"><glossterm><varname>hbase.client.max.perregion.tasks</varname></glossterm><glossdef><para>The maximum number of concurrent connections the client will
maintain to a single Region. That is, if there is already
hbase.client.max.perregion.tasks writes in progress for this region, new puts
won't be sent to this region until some writes finishes.</para><formalpara><title>Default</title><para><varname>1</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.scanner.caching"><glossterm><varname>hbase.client.scanner.caching</varname></glossterm><glossdef><para>Number of rows that will be fetched when calling next
on a scanner if it is not served from (local, client) memory. Higher
caching values will enable faster scanners but will eat up more memory
and some calls of next may take longer and longer times when the cache is empty.
Do not set this value such that the time between invocations is greater
than the scanner timeout; i.e. hbase.client.scanner.timeout.period</para><formalpara><title>Default</title><para><varname>100</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.keyvalue.maxsize"><glossterm><varname>hbase.client.keyvalue.maxsize</varname></glossterm><glossdef><para>Specifies the combined maximum allowed size of a KeyValue
instance. This is to set an upper boundary for a single entry saved in a
storage file. Since they cannot be split it helps avoiding that a region
cannot be split any further because the data is too large. It seems wise
to set this to a fraction of the maximum region size. Setting it to zero
or less disables the check.</para><formalpara><title>Default</title><para><varname>10485760</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.scanner.timeout.period"><glossterm><varname>hbase.client.scanner.timeout.period</varname></glossterm><glossdef><para>Client scanner lease period in milliseconds.</para><formalpara><title>Default</title><para><varname>60000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.client.localityCheck.threadPoolSize"><glossterm><varname>hbase.client.localityCheck.threadPoolSize</varname></glossterm><glossdef><para/><formalpara><title>Default</title><para><varname>2</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.bulkload.retries.number"><glossterm><varname>hbase.bulkload.retries.number</varname></glossterm><glossdef><para>Maximum retries. This is maximum number of iterations
to atomic bulk loads are attempted in the face of splitting operations
0 means never give up.</para><formalpara><title>Default</title><para><varname>10</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.balancer.period&#10; "><glossterm><varname>hbase.balancer.period
</varname></glossterm><glossdef><para>Period at which the region balancer runs in the Master.</para><formalpara><title>Default</title><para><varname>300000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regions.slop"><glossterm><varname>hbase.regions.slop</varname></glossterm><glossdef><para>Rebalance if any regionserver has average + (average * slop) regions.</para><formalpara><title>Default</title><para><varname>0.2</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.server.thread.wakefrequency"><glossterm><varname>hbase.server.thread.wakefrequency</varname></glossterm><glossdef><para>Time to sleep in between searches for work (in milliseconds).
Used as sleep interval by service threads such as log roller.</para><formalpara><title>Default</title><para><varname>10000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.server.versionfile.writeattempts"><glossterm><varname>hbase.server.versionfile.writeattempts</varname></glossterm><glossdef><para>
How many time to retry attempting to write a version file
before just aborting. Each attempt is seperated by the
hbase.server.thread.wakefrequency milliseconds.</para><formalpara><title>Default</title><para><varname>3</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hregion.memstore.flush.size"><glossterm><varname>hbase.hregion.memstore.flush.size</varname></glossterm><glossdef><para>
Memstore will be flushed to disk if size of the memstore
exceeds this number of bytes. Value is checked by a thread that runs
every hbase.server.thread.wakefrequency.</para><formalpara><title>Default</title><para><varname>134217728</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hregion.percolumnfamilyflush.size.lower.bound"><glossterm><varname>hbase.hregion.percolumnfamilyflush.size.lower.bound</varname></glossterm><glossdef><para>
If FlushLargeStoresPolicy is used, then every time that we hit the
total memstore limit, we find out all the column families whose memstores
exceed this value, and only flush them, while retaining the others whose
memstores are lower than this limit. If none of the families have their
memstore size more than this, all the memstores will be flushed
(just as usual). This value should be less than half of the total memstore
threshold (hbase.hregion.memstore.flush.size).
</para><formalpara><title>Default</title><para><varname>16777216</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hregion.preclose.flush.size"><glossterm><varname>hbase.hregion.preclose.flush.size</varname></glossterm><glossdef><para>
If the memstores in a region are this size or larger when we go
to close, run a "pre-flush" to clear out memstores before we put up
the region closed flag and take the region offline. On close,
a flush is run under the close flag to empty memory. During
this time the region is offline and we are not taking on any writes.
If the memstore content is large, this flush could take a long time to
complete. The preflush is meant to clean out the bulk of the memstore
before putting up the close flag and taking the region offline so the
flush that runs under the close flag has little to do.</para><formalpara><title>Default</title><para><varname>5242880</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hregion.memstore.block.multiplier"><glossterm><varname>hbase.hregion.memstore.block.multiplier</varname></glossterm><glossdef><para>
Block updates if memstore has hbase.hregion.memstore.block.multiplier
times hbase.hregion.memstore.flush.size bytes. Useful preventing
runaway memstore during spikes in update traffic. Without an
upper-bound, memstore fills such that when it flushes the
resultant flush files take a long time to compact or split, or
worse, we OOME.</para><formalpara><title>Default</title><para><varname>4</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hregion.memstore.mslab.enabled"><glossterm><varname>hbase.hregion.memstore.mslab.enabled</varname></glossterm><glossdef><para>
Enables the MemStore-Local Allocation Buffer,
a feature which works to prevent heap fragmentation under
heavy write loads. This can reduce the frequency of stop-the-world
GC pauses on large heaps.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hregion.max.filesize"><glossterm><varname>hbase.hregion.max.filesize</varname></glossterm><glossdef><para>
Maximum HFile size. If the sum of the sizes of a region's HFiles has grown to exceed this
value, the region is split in two.</para><formalpara><title>Default</title><para><varname>10737418240</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hregion.majorcompaction"><glossterm><varname>hbase.hregion.majorcompaction</varname></glossterm><glossdef><para>Time between major compactions, expressed in milliseconds. Set to 0 to disable
time-based automatic major compactions. User-requested and size-based major compactions will
still run. This value is multiplied by hbase.hregion.majorcompaction.jitter to cause
compaction to start at a somewhat-random time during a given window of time. The default value
is 7 days, expressed in milliseconds. If major compactions are causing disruption in your
environment, you can configure them to run at off-peak times for your deployment, or disable
time-based major compactions by setting this parameter to 0, and run major compactions in a
cron job or by another external mechanism.</para><formalpara><title>Default</title><para><varname>604800000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hregion.majorcompaction.jitter"><glossterm><varname>hbase.hregion.majorcompaction.jitter</varname></glossterm><glossdef><para>A multiplier applied to hbase.hregion.majorcompaction to cause compaction to occur
a given amount of time either side of hbase.hregion.majorcompaction. The smaller the number,
the closer the compactions will happen to the hbase.hregion.majorcompaction
interval.</para><formalpara><title>Default</title><para><varname>0.50</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.compactionThreshold"><glossterm><varname>hbase.hstore.compactionThreshold</varname></glossterm><glossdef><para> If more than this number of StoreFiles exist in any one Store
(one StoreFile is written per flush of MemStore), a compaction is run to rewrite all
StoreFiles into a single StoreFile. Larger values delay compaction, but when compaction does
occur, it takes longer to complete.</para><formalpara><title>Default</title><para><varname>3</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.flusher.count"><glossterm><varname>hbase.hstore.flusher.count</varname></glossterm><glossdef><para> The number of flush threads. With fewer threads, the MemStore flushes will be
queued. With more threads, the flushes will be executed in parallel, increasing the load on
HDFS, and potentially causing more compactions. </para><formalpara><title>Default</title><para><varname>2</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.blockingStoreFiles"><glossterm><varname>hbase.hstore.blockingStoreFiles</varname></glossterm><glossdef><para> If more than this number of StoreFiles exist in any one Store (one StoreFile
is written per flush of MemStore), updates are blocked for this region until a compaction is
completed, or until hbase.hstore.blockingWaitTime has been exceeded.</para><formalpara><title>Default</title><para><varname>10</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.blockingWaitTime"><glossterm><varname>hbase.hstore.blockingWaitTime</varname></glossterm><glossdef><para> The time for which a region will block updates after reaching the StoreFile limit
defined by hbase.hstore.blockingStoreFiles. After this time has elapsed, the region will stop
blocking updates even if a compaction has not been completed.</para><formalpara><title>Default</title><para><varname>90000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.compaction.min"><glossterm><varname>hbase.hstore.compaction.min</varname></glossterm><glossdef><para>The minimum number of StoreFiles which must be eligible for compaction before
compaction can run. The goal of tuning hbase.hstore.compaction.min is to avoid ending up with
too many tiny StoreFiles to compact. Setting this value to 2 would cause a minor compaction
each time you have two StoreFiles in a Store, and this is probably not appropriate. If you
set this value too high, all the other values will need to be adjusted accordingly. For most
cases, the default value is appropriate. In previous versions of HBase, the parameter
hbase.hstore.compaction.min was named hbase.hstore.compactionThreshold.</para><formalpara><title>Default</title><para><varname>3</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.compaction.max"><glossterm><varname>hbase.hstore.compaction.max</varname></glossterm><glossdef><para>The maximum number of StoreFiles which will be selected for a single minor
compaction, regardless of the number of eligible StoreFiles. Effectively, the value of
hbase.hstore.compaction.max controls the length of time it takes a single compaction to
complete. Setting it larger means that more StoreFiles are included in a compaction. For most
cases, the default value is appropriate.</para><formalpara><title>Default</title><para><varname>10</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.compaction.min.size"><glossterm><varname>hbase.hstore.compaction.min.size</varname></glossterm><glossdef><para>A StoreFile smaller than this size will always be eligible for minor compaction.
HFiles this size or larger are evaluated by hbase.hstore.compaction.ratio to determine if
they are eligible. Because this limit represents the "automatic include"limit for all
StoreFiles smaller than this value, this value may need to be reduced in write-heavy
environments where many StoreFiles in the 1-2 MB range are being flushed, because every
StoreFile will be targeted for compaction and the resulting StoreFiles may still be under the
minimum size and require further compaction. If this parameter is lowered, the ratio check is
triggered more quickly. This addressed some issues seen in earlier versions of HBase but
changing this parameter is no longer necessary in most situations. Default: 128 MB expressed
in bytes.</para><formalpara><title>Default</title><para><varname>134217728</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.compaction.max.size"><glossterm><varname>hbase.hstore.compaction.max.size</varname></glossterm><glossdef><para>A StoreFile larger than this size will be excluded from compaction. The effect of
raising hbase.hstore.compaction.max.size is fewer, larger StoreFiles that do not get
compacted often. If you feel that compaction is happening too often without much benefit, you
can try raising this value. Default: the value of LONG.MAX_VALUE, expressed in bytes.</para><formalpara><title>Default</title><para><varname>9223372036854775807</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.compaction.ratio"><glossterm><varname>hbase.hstore.compaction.ratio</varname></glossterm><glossdef><para>For minor compaction, this ratio is used to determine whether a given StoreFile
which is larger than hbase.hstore.compaction.min.size is eligible for compaction. Its
effect is to limit compaction of large StoreFiles. The value of hbase.hstore.compaction.ratio
is expressed as a floating-point decimal. A large ratio, such as 10, will produce a single
giant StoreFile. Conversely, a low value, such as .25, will produce behavior similar to the
BigTable compaction algorithm, producing four StoreFiles. A moderate value of between 1.0 and
1.4 is recommended. When tuning this value, you are balancing write costs with read costs.
Raising the value (to something like 1.4) will have more write costs, because you will
compact larger StoreFiles. However, during reads, HBase will need to seek through fewer
StoreFiles to accomplish the read. Consider this approach if you cannot take advantage of
Bloom filters. Otherwise, you can lower this value to something like 1.0 to reduce the
background cost of writes, and use Bloom filters to control the number of StoreFiles touched
during reads. For most cases, the default value is appropriate.</para><formalpara><title>Default</title><para><varname>1.2F</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.compaction.ratio.offpeak"><glossterm><varname>hbase.hstore.compaction.ratio.offpeak</varname></glossterm><glossdef><para>Allows you to set a different (by default, more aggressive) ratio for determining
whether larger StoreFiles are included in compactions during off-peak hours. Works in the
same way as hbase.hstore.compaction.ratio. Only applies if hbase.offpeak.start.hour and
hbase.offpeak.end.hour are also enabled.</para><formalpara><title>Default</title><para><varname>5.0F</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.time.to.purge.deletes"><glossterm><varname>hbase.hstore.time.to.purge.deletes</varname></glossterm><glossdef><para>The amount of time to delay purging of delete markers with future timestamps. If
unset, or set to 0, all delete markers, including those with future timestamps, are purged
during the next major compaction. Otherwise, a delete marker is kept until the major compaction
which occurs after the marker's timestamp plus the value of this setting, in milliseconds.
</para><formalpara><title>Default</title><para><varname>0</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.offpeak.start.hour"><glossterm><varname>hbase.offpeak.start.hour</varname></glossterm><glossdef><para>The start of off-peak hours, expressed as an integer between 0 and 23, inclusive.
Set to -1 to disable off-peak.</para><formalpara><title>Default</title><para><varname>-1</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.offpeak.end.hour"><glossterm><varname>hbase.offpeak.end.hour</varname></glossterm><glossdef><para>The end of off-peak hours, expressed as an integer between 0 and 23, inclusive. Set
to -1 to disable off-peak.</para><formalpara><title>Default</title><para><varname>-1</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.thread.compaction.throttle"><glossterm><varname>hbase.regionserver.thread.compaction.throttle</varname></glossterm><glossdef><para>There are two different thread pools for compactions, one for large compactions and
the other for small compactions. This helps to keep compaction of lean tables (such as
hbase:meta) fast. If a compaction is larger than this threshold, it
goes into the large compaction pool. In most cases, the default value is appropriate. Default:
2 x hbase.hstore.compaction.max x hbase.hregion.memstore.flush.size (which defaults to 128MB).
The value field assumes that the value of hbase.hregion.memstore.flush.size is unchanged from
the default.</para><formalpara><title>Default</title><para><varname>2684354560</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.compaction.kv.max"><glossterm><varname>hbase.hstore.compaction.kv.max</varname></glossterm><glossdef><para>The maximum number of KeyValues to read and then write in a batch when flushing or
compacting. Set this lower if you have big KeyValues and problems with Out Of Memory
Exceptions Set this higher if you have wide, small rows. </para><formalpara><title>Default</title><para><varname>10</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.storescanner.parallel.seek.enable"><glossterm><varname>hbase.storescanner.parallel.seek.enable</varname></glossterm><glossdef><para>
Enables StoreFileScanner parallel-seeking in StoreScanner,
a feature which can reduce response latency under special conditions.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.storescanner.parallel.seek.threads"><glossterm><varname>hbase.storescanner.parallel.seek.threads</varname></glossterm><glossdef><para>
The default thread pool size if parallel-seeking feature enabled.</para><formalpara><title>Default</title><para><varname>10</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hfile.block.cache.size"><glossterm><varname>hfile.block.cache.size</varname></glossterm><glossdef><para>Percentage of maximum heap (-Xmx setting) to allocate to block cache
used by a StoreFile. Default of 0.4 means allocate 40%.
Set to 0 to disable but it's not recommended; you need at least
enough cache to hold the storefile indices.</para><formalpara><title>Default</title><para><varname>0.4</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hfile.block.index.cacheonwrite"><glossterm><varname>hfile.block.index.cacheonwrite</varname></glossterm><glossdef><para>This allows to put non-root multi-level index blocks into the block
cache at the time the index is being written.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hfile.index.block.max.size"><glossterm><varname>hfile.index.block.max.size</varname></glossterm><glossdef><para>When the size of a leaf-level, intermediate-level, or root-level
index block in a multi-level block index grows to this size, the
block is written out and a new block is started.</para><formalpara><title>Default</title><para><varname>131072</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.bucketcache.ioengine"><glossterm><varname>hbase.bucketcache.ioengine</varname></glossterm><glossdef><para>Where to store the contents of the bucketcache. One of: onheap,
offheap, or file. If a file, set it to file:PATH_TO_FILE. See https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/io/hfile/CacheConfig.html for more information.
</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.bucketcache.combinedcache.enabled"><glossterm><varname>hbase.bucketcache.combinedcache.enabled</varname></glossterm><glossdef><para>Whether or not the bucketcache is used in league with the LRU
on-heap block cache. In this mode, indices and blooms are kept in the LRU
blockcache and the data blocks are kept in the bucketcache.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.bucketcache.size"><glossterm><varname>hbase.bucketcache.size</varname></glossterm><glossdef><para>The size of the buckets for the bucketcache if you only use a single size.
Defaults to the default blocksize, which is 64 * 1024.</para><formalpara><title>Default</title><para><varname>65536</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.bucketcache.sizes"><glossterm><varname>hbase.bucketcache.sizes</varname></glossterm><glossdef><para>A comma-separated list of sizes for buckets for the bucketcache
if you use multiple sizes. Should be a list of block sizes in order from smallest
to largest. The sizes you use will depend on your data access patterns.</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hfile.format.version"><glossterm><varname>hfile.format.version</varname></glossterm><glossdef><para>The HFile format version to use for new files.
Version 3 adds support for tags in hfiles (See http://hbase.apache.org/book.html#hbase.tags).
Distributed Log Replay requires that tags are enabled. Also see the configuration
'hbase.replication.rpc.codec'.
</para><formalpara><title>Default</title><para><varname>3</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hfile.block.bloom.cacheonwrite"><glossterm><varname>hfile.block.bloom.cacheonwrite</varname></glossterm><glossdef><para>Enables cache-on-write for inline blocks of a compound Bloom filter.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="io.storefile.bloom.block.size"><glossterm><varname>io.storefile.bloom.block.size</varname></glossterm><glossdef><para>The size in bytes of a single block ("chunk") of a compound Bloom
filter. This size is approximate, because Bloom blocks can only be
inserted at data block boundaries, and the number of keys per data
block varies.</para><formalpara><title>Default</title><para><varname>131072</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rs.cacheblocksonwrite"><glossterm><varname>hbase.rs.cacheblocksonwrite</varname></glossterm><glossdef><para>Whether an HFile block should be added to the block cache when the
block is finished.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rpc.timeout"><glossterm><varname>hbase.rpc.timeout</varname></glossterm><glossdef><para>This is for the RPC layer to define how long HBase client applications
take for a remote call to time out. It uses pings to check connections
but will eventually throw a TimeoutException.</para><formalpara><title>Default</title><para><varname>60000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rpc.shortoperation.timeout"><glossterm><varname>hbase.rpc.shortoperation.timeout</varname></glossterm><glossdef><para>This is another version of "hbase.rpc.timeout". For those RPC operation
within cluster, we rely on this configuration to set a short timeout limitation
for short operation. For example, short rpc timeout for region server's trying
to report to active master can benefit quicker master failover process.</para><formalpara><title>Default</title><para><varname>10000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.ipc.client.tcpnodelay"><glossterm><varname>hbase.ipc.client.tcpnodelay</varname></glossterm><glossdef><para>Set no delay on rpc socket connections. See
http://docs.oracle.com/javase/1.5.0/docs/api/java/net/Socket.html#getTcpNoDelay()</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.keytab.file"><glossterm><varname>hbase.master.keytab.file</varname></glossterm><glossdef><para>Full path to the kerberos keytab file to use for logging in
the configured HMaster server principal.</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.kerberos.principal"><glossterm><varname>hbase.master.kerberos.principal</varname></glossterm><glossdef><para>Ex. "hbase/_HOST@EXAMPLE.COM". The kerberos principal name
that should be used to run the HMaster process. The principal name should
be in the form: user/hostname@DOMAIN. If "_HOST" is used as the hostname
portion, it will be replaced with the actual hostname of the running
instance.</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.keytab.file"><glossterm><varname>hbase.regionserver.keytab.file</varname></glossterm><glossdef><para>Full path to the kerberos keytab file to use for logging in
the configured HRegionServer server principal.</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.kerberos.principal"><glossterm><varname>hbase.regionserver.kerberos.principal</varname></glossterm><glossdef><para>Ex. "hbase/_HOST@EXAMPLE.COM". The kerberos principal name
that should be used to run the HRegionServer process. The principal name
should be in the form: user/hostname@DOMAIN. If "_HOST" is used as the
hostname portion, it will be replaced with the actual hostname of the
running instance. An entry for this principal must exist in the file
specified in hbase.regionserver.keytab.file</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hadoop.policy.file"><glossterm><varname>hadoop.policy.file</varname></glossterm><glossdef><para>The policy configuration file used by RPC servers to make
authorization decisions on client requests. Only used when HBase
security is enabled.</para><formalpara><title>Default</title><para><varname>hbase-policy.xml</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.superuser"><glossterm><varname>hbase.superuser</varname></glossterm><glossdef><para>List of users or groups (comma-separated), who are allowed
full privileges, regardless of stored ACLs, across the cluster.
Only used when HBase security is enabled.</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.auth.key.update.interval"><glossterm><varname>hbase.auth.key.update.interval</varname></glossterm><glossdef><para>The update interval for master key for authentication tokens
in servers in milliseconds. Only used when HBase security is enabled.</para><formalpara><title>Default</title><para><varname>86400000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.auth.token.max.lifetime"><glossterm><varname>hbase.auth.token.max.lifetime</varname></glossterm><glossdef><para>The maximum lifetime in milliseconds after which an
authentication token expires. Only used when HBase security is enabled.</para><formalpara><title>Default</title><para><varname>604800000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.ipc.client.fallback-to-simple-auth-allowed"><glossterm><varname>hbase.ipc.client.fallback-to-simple-auth-allowed</varname></glossterm><glossdef><para>When a client is configured to attempt a secure connection, but attempts to
connect to an insecure server, that server may instruct the client to
switch to SASL SIMPLE (unsecure) authentication. This setting controls
whether or not the client will accept this instruction from the server.
When false (the default), the client will not allow the fallback to SIMPLE
authentication, and will abort the connection.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.display.keys"><glossterm><varname>hbase.display.keys</varname></glossterm><glossdef><para>When this is set to true the webUI and such will display all start/end keys
as part of the table details, region names, etc. When this is set to false,
the keys are hidden.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.coprocessor.region.classes"><glossterm><varname>hbase.coprocessor.region.classes</varname></glossterm><glossdef><para>A comma-separated list of Coprocessors that are loaded by
default on all tables. For any override coprocessor method, these classes
will be called in order. After implementing your own Coprocessor, just put
it in HBase's classpath and add the fully qualified class name here.
A coprocessor can also be loaded on demand by setting HTableDescriptor.</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rest.port"><glossterm><varname>hbase.rest.port</varname></glossterm><glossdef><para>The port for the HBase REST server.</para><formalpara><title>Default</title><para><varname>8080</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rest.readonly"><glossterm><varname>hbase.rest.readonly</varname></glossterm><glossdef><para>Defines the mode the REST server will be started in. Possible values are:
false: All HTTP methods are permitted - GET/PUT/POST/DELETE.
true: Only the GET method is permitted.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rest.threads.max"><glossterm><varname>hbase.rest.threads.max</varname></glossterm><glossdef><para>The maximum number of threads of the REST server thread pool.
Threads in the pool are reused to process REST requests. This
controls the maximum number of requests processed concurrently.
It may help to control the memory used by the REST server to
avoid OOM issues. If the thread pool is full, incoming requests
will be queued up and wait for some free threads.</para><formalpara><title>Default</title><para><varname>100</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rest.threads.min"><glossterm><varname>hbase.rest.threads.min</varname></glossterm><glossdef><para>The minimum number of threads of the REST server thread pool.
The thread pool always has at least these number of threads so
the REST server is ready to serve incoming requests.</para><formalpara><title>Default</title><para><varname>2</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rest.support.proxyuser"><glossterm><varname>hbase.rest.support.proxyuser</varname></glossterm><glossdef><para>Enables running the REST server to support proxy-user mode.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.defaults.for.version.skip"><glossterm><varname>hbase.defaults.for.version.skip</varname></glossterm><glossdef><para>Set to true to skip the 'hbase.defaults.for.version' check.
Setting this to true can be useful in contexts other than
the other side of a maven generation; i.e. running in an
ide. You'll want to set this boolean to true to avoid
seeing the RuntimException complaint: "hbase-default.xml file
seems to be for and old version of HBase (\${hbase.version}), this
version is X.X.X-SNAPSHOT"</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.coprocessor.master.classes"><glossterm><varname>hbase.coprocessor.master.classes</varname></glossterm><glossdef><para>A comma-separated list of
org.apache.hadoop.hbase.coprocessor.MasterObserver coprocessors that are
loaded by default on the active HMaster process. For any implemented
coprocessor methods, the listed classes will be called in order. After
implementing your own MasterObserver, just put it in HBase's classpath
and add the fully qualified class name here.</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.coprocessor.abortonerror"><glossterm><varname>hbase.coprocessor.abortonerror</varname></glossterm><glossdef><para>Set to true to cause the hosting server (master or regionserver)
to abort if a coprocessor fails to load, fails to initialize, or throws an
unexpected Throwable object. Setting this to false will allow the server to
continue execution but the system wide state of the coprocessor in question
will become inconsistent as it will be properly executing in only a subset
of servers, so this is most useful for debugging only.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.online.schema.update.enable"><glossterm><varname>hbase.online.schema.update.enable</varname></glossterm><glossdef><para>Set true to enable online schema changes.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.table.lock.enable"><glossterm><varname>hbase.table.lock.enable</varname></glossterm><glossdef><para>Set to true to enable locking the table in zookeeper for schema change operations.
Table locking from master prevents concurrent schema modifications to corrupt table
state.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.table.max.rowsize"><glossterm><varname>hbase.table.max.rowsize</varname></glossterm><glossdef><para>
Maximum size of single row in bytes (default is 1 Gb) for Get'ting
or Scan'ning without in-row scan flag set. If row size exceeds this limit
RowTooBigException is thrown to client.
</para><formalpara><title>Default</title><para><varname>1073741824</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.thrift.minWorkerThreads"><glossterm><varname>hbase.thrift.minWorkerThreads</varname></glossterm><glossdef><para>The "core size" of the thread pool. New threads are created on every
connection until this many threads are created.</para><formalpara><title>Default</title><para><varname>16</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.thrift.maxWorkerThreads"><glossterm><varname>hbase.thrift.maxWorkerThreads</varname></glossterm><glossdef><para>The maximum size of the thread pool. When the pending request queue
overflows, new threads are created until their number reaches this number.
After that, the server starts dropping connections.</para><formalpara><title>Default</title><para><varname>1000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.thrift.maxQueuedRequests"><glossterm><varname>hbase.thrift.maxQueuedRequests</varname></glossterm><glossdef><para>The maximum number of pending Thrift connections waiting in the queue. If
there are no idle threads in the pool, the server queues requests. Only
when the queue overflows, new threads are added, up to
hbase.thrift.maxQueuedRequests threads.</para><formalpara><title>Default</title><para><varname>1000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.thrift.htablepool.size.max"><glossterm><varname>hbase.thrift.htablepool.size.max</varname></glossterm><glossdef><para>The upper bound for the table pool used in the Thrift gateways server.
Since this is per table name, we assume a single table and so with 1000 default
worker threads max this is set to a matching number. For other workloads this number
can be adjusted as needed.
</para><formalpara><title>Default</title><para><varname>1000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.thrift.framed"><glossterm><varname>hbase.regionserver.thrift.framed</varname></glossterm><glossdef><para>Use Thrift TFramedTransport on the server side.
This is the recommended transport for thrift servers and requires a similar setting
on the client side. Changing this to false will select the default transport,
vulnerable to DoS when malformed requests are issued due to THRIFT-601.
</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.thrift.framed.max_frame_size_in_mb"><glossterm><varname>hbase.regionserver.thrift.framed.max_frame_size_in_mb</varname></glossterm><glossdef><para>Default frame size when using framed transport</para><formalpara><title>Default</title><para><varname>2</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.thrift.compact"><glossterm><varname>hbase.regionserver.thrift.compact</varname></glossterm><glossdef><para>Use Thrift TCompactProtocol binary serialization protocol.</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.data.umask.enable"><glossterm><varname>hbase.data.umask.enable</varname></glossterm><glossdef><para>Enable, if true, that file permissions should be assigned
to the files written by the regionserver</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.data.umask"><glossterm><varname>hbase.data.umask</varname></glossterm><glossdef><para>File permissions that should be used to write data
files when hbase.data.umask.enable is true</para><formalpara><title>Default</title><para><varname>000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.metrics.showTableName"><glossterm><varname>hbase.metrics.showTableName</varname></glossterm><glossdef><para>Whether to include the prefix "tbl.tablename" in per-column family metrics.
If true, for each metric M, per-cf metrics will be reported for tbl.T.cf.CF.M, if false,
per-cf metrics will be aggregated by column-family across tables, and reported for cf.CF.M.
In both cases, the aggregated metric M across tables and cfs will be reported.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.metrics.exposeOperationTimes"><glossterm><varname>hbase.metrics.exposeOperationTimes</varname></glossterm><glossdef><para>Whether to report metrics about time taken performing an
operation on the region server. Get, Put, Delete, Increment, and Append can all
have their times exposed through Hadoop metrics per CF and per region.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.snapshot.enabled"><glossterm><varname>hbase.snapshot.enabled</varname></glossterm><glossdef><para>Set to true to allow snapshots to be taken / restored / cloned.</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.snapshot.restore.take.failsafe.snapshot"><glossterm><varname>hbase.snapshot.restore.take.failsafe.snapshot</varname></glossterm><glossdef><para>Set to true to take a snapshot before the restore operation.
The snapshot taken will be used in case of failure, to restore the previous state.
At the end of the restore operation this snapshot will be deleted</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.snapshot.restore.failsafe.name"><glossterm><varname>hbase.snapshot.restore.failsafe.name</varname></glossterm><glossdef><para>Name of the failsafe snapshot taken by the restore operation.
You can use the {snapshot.name}, {table.name} and {restore.timestamp} variables
to create a name based on what you are restoring.</para><formalpara><title>Default</title><para><varname>hbase-failsafe-{snapshot.name}-{restore.timestamp}</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.server.compactchecker.interval.multiplier"><glossterm><varname>hbase.server.compactchecker.interval.multiplier</varname></glossterm><glossdef><para>The number that determines how often we scan to see if compaction is necessary.
Normally, compactions are done after some events (such as memstore flush), but if
region didn't receive a lot of writes for some time, or due to different compaction
policies, it may be necessary to check it periodically. The interval between checks is
hbase.server.compactchecker.interval.multiplier multiplied by
hbase.server.thread.wakefrequency.</para><formalpara><title>Default</title><para><varname>1000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.lease.recovery.timeout"><glossterm><varname>hbase.lease.recovery.timeout</varname></glossterm><glossdef><para>How long we wait on dfs lease recovery in total before giving up.</para><formalpara><title>Default</title><para><varname>900000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.lease.recovery.dfs.timeout"><glossterm><varname>hbase.lease.recovery.dfs.timeout</varname></glossterm><glossdef><para>How long between dfs recover lease invocations. Should be larger than the sum of
the time it takes for the namenode to issue a block recovery command as part of
datanode; dfs.heartbeat.interval and the time it takes for the primary
datanode, performing block recovery to timeout on a dead datanode; usually
dfs.client.socket-timeout. See the end of HBASE-8389 for more.</para><formalpara><title>Default</title><para><varname>64000</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.column.max.version"><glossterm><varname>hbase.column.max.version</varname></glossterm><glossdef><para>New column family descriptors will use this value as the default number of versions
to keep.</para><formalpara><title>Default</title><para><varname>1</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.dfs.client.read.shortcircuit.buffer.size"><glossterm><varname>hbase.dfs.client.read.shortcircuit.buffer.size</varname></glossterm><glossdef><para>If the DFSClient configuration
dfs.client.read.shortcircuit.buffer.size is unset, we will
use what is configured here as the short circuit read default
direct byte buffer size. DFSClient native default is 1MB; HBase
keeps its HDFS files open so number of file blocks * 1MB soon
starts to add up and threaten OOME because of a shortage of
direct memory. So, we set it down from the default. Make
it &gt; the default hbase block size set in the HColumnDescriptor
which is usually 64k.
</para><formalpara><title>Default</title><para><varname>131072</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.checksum.verify"><glossterm><varname>hbase.regionserver.checksum.verify</varname></glossterm><glossdef><para>
If set to true (the default), HBase verifies the checksums for hfile
blocks. HBase writes checksums inline with the data when it writes out
hfiles. HDFS (as of this writing) writes checksums to a separate file
than the data file necessitating extra seeks. Setting this flag saves
some on i/o. Checksum verification by HDFS will be internally disabled
on hfile streams when this flag is set. If the hbase-checksum verification
fails, we will switch back to using HDFS checksums (so do not disable HDFS
checksums! And besides this feature applies to hfiles only, not to WALs).
If this parameter is set to false, then hbase will not verify any checksums,
instead it will depend on checksum verification being done in the HDFS client.
</para><formalpara><title>Default</title><para><varname>true</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.bytes.per.checksum"><glossterm><varname>hbase.hstore.bytes.per.checksum</varname></glossterm><glossdef><para>
Number of bytes in a newly created checksum chunk for HBase-level
checksums in hfile blocks.
</para><formalpara><title>Default</title><para><varname>16384</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.hstore.checksum.algorithm"><glossterm><varname>hbase.hstore.checksum.algorithm</varname></glossterm><glossdef><para>
Name of an algorithm that is used to compute checksums. Possible values
are NULL, CRC32, CRC32C.
</para><formalpara><title>Default</title><para><varname>CRC32</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.status.published"><glossterm><varname>hbase.status.published</varname></glossterm><glossdef><para>
This setting activates the publication by the master of the status of the region server.
When a region server dies and its recovery starts, the master will push this information
to the client application, to let them cut the connection immediately instead of waiting
for a timeout.
</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.status.publisher.class"><glossterm><varname>hbase.status.publisher.class</varname></glossterm><glossdef><para>
Implementation of the status publication with a multicast message.
</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.master.ClusterStatusPublisher$MulticastPublisher</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.status.listener.class"><glossterm><varname>hbase.status.listener.class</varname></glossterm><glossdef><para>
Implementation of the status listener with a multicast message.
</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.client.ClusterStatusListener$MulticastListener</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.status.multicast.address.ip"><glossterm><varname>hbase.status.multicast.address.ip</varname></glossterm><glossdef><para>
Multicast address to use for the status publication by multicast.
</para><formalpara><title>Default</title><para><varname>226.1.1.3</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.status.multicast.address.port"><glossterm><varname>hbase.status.multicast.address.port</varname></glossterm><glossdef><para>
Multicast port to use for the status publication by multicast.
</para><formalpara><title>Default</title><para><varname>16100</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.dynamic.jars.dir"><glossterm><varname>hbase.dynamic.jars.dir</varname></glossterm><glossdef><para>
The directory from which the custom filter/co-processor jars can be loaded
dynamically by the region server without the need to restart. However,
an already loaded filter/co-processor class would not be un-loaded. See
HBASE-1936 for more details.
</para><formalpara><title>Default</title><para><varname>${hbase.rootdir}/lib</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.security.authentication"><glossterm><varname>hbase.security.authentication</varname></glossterm><glossdef><para>
Controls whether or not secure authentication is enabled for HBase.
Possible values are 'simple' (no authentication), and 'kerberos'.
</para><formalpara><title>Default</title><para><varname>simple</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.rest.filter.classes"><glossterm><varname>hbase.rest.filter.classes</varname></glossterm><glossdef><para>
Servlet filters for REST service.
</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.rest.filter.GzipFilter</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.master.loadbalancer.class"><glossterm><varname>hbase.master.loadbalancer.class</varname></glossterm><glossdef><para>
Class used to execute the regions balancing when the period occurs.
See the class comment for more on how it works
http://hbase.apache.org/devapidocs/org/apache/hadoop/hbase/master/balancer/StochasticLoadBalancer.html
It replaces the DefaultLoadBalancer as the default (since renamed
as the SimpleLoadBalancer).
</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.master.balancer.StochasticLoadBalancer</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.security.exec.permission.checks"><glossterm><varname>hbase.security.exec.permission.checks</varname></glossterm><glossdef><para>
If this setting is enabled and ACL based access control is active (the
AccessController coprocessor is installed either as a system coprocessor
or on a table as a table coprocessor) then you must grant all relevant
users EXEC privilege if they require the ability to execute coprocessor
endpoint calls. EXEC privilege, like any other permission, can be
granted globally to a user, or to a user on a per table or per namespace
basis. For more information on coprocessor endpoints, see the coprocessor
section of the HBase online manual. For more information on granting or
revoking permissions using the AccessController, see the security
section of the HBase online manual.
</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.procedure.regionserver.classes"><glossterm><varname>hbase.procedure.regionserver.classes</varname></glossterm><glossdef><para>A comma-separated list of
org.apache.hadoop.hbase.procedure.RegionServerProcedureManager procedure managers that are
loaded by default on the active HRegionServer process. The lifecycle methods (init/start/stop)
will be called by the active HRegionServer process to perform the specific globally barriered
procedure. After implementing your own RegionServerProcedureManager, just put it in
HBase's classpath and add the fully qualified class name here.
</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.procedure.master.classes"><glossterm><varname>hbase.procedure.master.classes</varname></glossterm><glossdef><para>A comma-separated list of
org.apache.hadoop.hbase.procedure.MasterProcedureManager procedure managers that are
loaded by default on the active HMaster process. A procedure is identified by its signature and
users can use the signature and an instant name to trigger an execution of a globally barriered
procedure. After implementing your own MasterProcedureManager, just put it in HBase's classpath
and add the fully qualified class name here.</para><formalpara><title>Default</title><para><varname/></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.coordinated.state.manager.class"><glossterm><varname>hbase.coordinated.state.manager.class</varname></glossterm><glossdef><para>Fully qualified name of class implementing coordinated state manager.</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.coordination.ZkCoordinatedStateManager</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.regionserver.storefile.refresh.period"><glossterm><varname>hbase.regionserver.storefile.refresh.period</varname></glossterm><glossdef><para>
The period (in milliseconds) for refreshing the store files for the secondary regions. 0
means this feature is disabled. Secondary regions sees new files (from flushes and
compactions) from primary once the secondary region refreshes the list of files in the
region (there is no notification mechanism). But too frequent refreshes might cause
extra Namenode pressure. If the files cannot be refreshed for longer than HFile TTL
(hbase.master.hfilecleaner.ttl) the requests are rejected. Configuring HFile TTL to a larger
value is also recommended with this setting.
</para><formalpara><title>Default</title><para><varname>0</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.region.replica.replication.enabled"><glossterm><varname>hbase.region.replica.replication.enabled</varname></glossterm><glossdef><para>
Whether asynchronous WAL replication to the secondary region replicas is enabled or not.
If this is enabled, a replication peer named "region_replica_replication" will be created
which will tail the logs and replicate the mutatations to region replicas for tables that
have region replication &gt; 1. If this is enabled once, disabling this replication also
requires disabling the replication peer using shell or ReplicationAdmin java class.
Replication to secondary region replicas works over standard inter-cluster replication.
So replication, if disabled explicitly, also has to be enabled by setting "hbase.replication"
to true for this feature to work.
</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.http.filter.initializers"><glossterm><varname>hbase.http.filter.initializers</varname></glossterm><glossdef><para>
A comma separated list of class names. Each class in the list must extend
org.apache.hadoop.hbase.http.FilterInitializer. The corresponding Filter will
be initialized. Then, the Filter will be applied to all user facing jsp
and servlet web pages.
The ordering of the list defines the ordering of the filters.
The default StaticUserWebFilter add a user principal as defined by the
hbase.http.staticuser.user property.
</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.http.lib.StaticUserWebFilter</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.security.visibility.mutations.checkauths"><glossterm><varname>hbase.security.visibility.mutations.checkauths</varname></glossterm><glossdef><para>
This property if enabled, will check whether the labels in the visibility expression are associated
with the user issuing the mutation
</para><formalpara><title>Default</title><para><varname>false</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.http.max.threads"><glossterm><varname>hbase.http.max.threads</varname></glossterm><glossdef><para>
The maximum number of threads that the HTTP Server will create in its
ThreadPool.
</para><formalpara><title>Default</title><para><varname>10</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.replication.rpc.codec"><glossterm><varname>hbase.replication.rpc.codec</varname></glossterm><glossdef><para>
The codec that is to be used when replication is enabled so that
the tags are also replicated. This is used along with HFileV3 which
supports tags in them. If tags are not used or if the hfile version used
is HFileV2 then KeyValueCodec can be used as the replication codec. Note that
using KeyValueCodecWithTags for replication when there are no tags causes no harm.
</para><formalpara><title>Default</title><para><varname>org.apache.hadoop.hbase.codec.KeyValueCodecWithTags</varname></para></formalpara></glossdef></glossentry><glossentry xml:id="hbase.http.staticuser.user"><glossterm><varname>hbase.http.staticuser.user</varname></glossterm><glossdef><para>
The user name to filter as, on static web filters
while rendering content. An example use is the HDFS
web UI (user to be used for browsing files).
</para><formalpara><title>Default</title><para><varname>dr.stack</varname></para></formalpara></glossdef></glossentry></glossary>

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<?xml version="1.0" encoding="UTF-8"?>
<appendix
xml:id="hbase.history"
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">
<!--/**
* Licensed to the Apache Software Foundation (ASF) under one
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* 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.
*/
-->
<title>HBase History</title>
<itemizedlist>
<listitem><para>2006: <link xlink:href="http://research.google.com/archive/bigtable.html">BigTable</link> paper published by Google.
</para></listitem>
<listitem><para>2006 (end of year): HBase development starts.
</para></listitem>
<listitem><para>2008: HBase becomes Hadoop sub-project.
</para></listitem>
<listitem><para>2010: HBase becomes Apache top-level project.
</para></listitem>
</itemizedlist>
</appendix>

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<?xml version="1.0" encoding="UTF-8"?>
<appendix
xml:id="hbck.in.depth"
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">
<!--/**
* 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.
*/
-->
<title>hbck In Depth</title>
<para>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.
</para>
<section>
<title>Running hbck to identify inconsistencies</title>
<para>To check to see if your HBase cluster has corruptions, run hbck against your HBase cluster:</para>
<programlisting language="bourne">
$ ./bin/hbase hbck
</programlisting>
<para>
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 <code>-details</code> option will report more details including a representative
listing of all the splits present in all the tables.
</para>
<programlisting language="bourne">
$ ./bin/hbase hbck -details
</programlisting>
<para>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.</para>
<programlisting language="bourne">
$ ./bin/hbase hbck TableFoo TableBar
</programlisting>
</section>
<section><title>Inconsistencies</title>
<para>
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.
</para>
<para>
There are two invariants that when violated create inconsistencies in HBase:
</para>
<itemizedlist>
<listitem><para>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.</para>
</listitem>
<listitem><para>HBase’s table integrity invariant is satisfied if for each table, every possible row key
resolves to exactly one region.</para>
</listitem>
</itemizedlist>
<para>
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 <code>-fix</code> 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.
</para>
<para>
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 &lt;=0.90.6 and versions
&lt;=0.92.1 may require restarting the master or failing over to a backup master.
</para>
</section>
<section><title>Localized repairs</title>
<para>
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:
<itemizedlist>
<listitem><para><code>-fixAssignments</code> (equivalent to the 0.90 <code>-fix</code> option) repairs unassigned, incorrectly
assigned or multiply assigned regions.</para>
</listitem>
<listitem><para><code>-fixMeta</code> 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.</para>
</listitem>
</itemizedlist>
To fix deployment and assignment problems you can run this command:
</para>
<programlisting language="bourne">
$ ./bin/hbase hbck -fixAssignments
</programlisting>
<para>To fix deployment and assignment problems as well as repairing incorrect meta rows you can
run this command:</para>
<programlisting language="bourne">
$ ./bin/hbase hbck -fixAssignments -fixMeta
</programlisting>
<para>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:</para>
<itemizedlist>
<listitem><para><code>-fixHdfsHoles</code> 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.</para>
</listitem>
</itemizedlist>
<programlisting language="bourne">
$ ./bin/hbase hbck -fixAssignments -fixMeta -fixHdfsHoles
</programlisting>
<para>Since this is a common operation, we’ve added a the <code>-repairHoles</code> flag that is equivalent to the
previous command:</para>
<programlisting language="bourne">
$ ./bin/hbase hbck -repairHoles
</programlisting>
<para>If inconsistencies still remain after these steps, you most likely have table integrity problems
related to orphaned or overlapping regions.</para>
</section>
<section><title>Region Overlap Repairs</title>
<para>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 <code>hbck -details</code>
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:</para>
<itemizedlist>
<listitem><para><code>-fixHdfsOrphans</code> option for “adopting” a region directory that is missing a region
metadata file (the .regioninfo file).</para>
</listitem>
<listitem><para><code>-fixHdfsOverlaps</code> ability for fixing overlapping regions</para>
</listitem>
</itemizedlist>
<para>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.</para>
<itemizedlist>
<listitem><para><code>-maxMerge &lt;n&gt;</code> maximum number of overlapping regions to merge</para>
</listitem>
<listitem><para><code>-sidelineBigOverlaps</code> if more than maxMerge regions are overlapping, sideline attempt
to sideline the regions overlapping with the most other regions.</para>
</listitem>
<listitem><para><code>-maxOverlapsToSideline &lt;n&gt;</code> if sidelining large overlapping regions, sideline at most n
regions.</para>
</listitem>
</itemizedlist>
<para>Since often times you would just want to get the tables repaired, you can use this option to turn
on all repair options:</para>
<itemizedlist>
<listitem><para><code>-repair</code> includes all the region consistency options and only the hole repairing table
integrity options.</para>
</listitem>
</itemizedlist>
<para>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.</para>
<screen language="bourne">
$ ./bin/hbase hbck -repair TableFoo TableBar
</screen>
<section><title>Special cases: Meta is not properly assigned</title>
<para>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 <code>-fixMetaOnly</code> option that can try to fix meta assignments.</para>
<screen language="bourne">
$ ./bin/hbase hbck -fixMetaOnly -fixAssignments
</screen>
</section>
<section><title>Special cases: HBase version file is missing</title>
<para>HBase’s data on the file system requires a version file in order to start. If this flie is missing, you
can use the <code>-fixVersionFile</code> 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.</para>
</section>
<section><title>Special case: Root and META are corrupt.</title>
<para>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.</para>
<screen language="bourne">
$ ./bin/hbase org.apache.hadoop.hbase.util.hbck.OfflineMetaRepair
</screen>
<para>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.</para>
</section>
<section><title>Special cases: Offline split parent</title>
<para>
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 <code>-fixSplitParents</code> 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.
</para>
<para>
This option should not normally be used, and it is not in <code>-fixAll</code>.
</para>
</section>
</section>
</appendix>

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<?xml version="1.0" encoding="UTF-8"?>
<chapter
xml:id="mapreduce"
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">
<!--/**
* 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.
*/
-->
<title>HBase and MapReduce</title>
<para>Apache MapReduce is a software framework used to analyze large amounts of data, and is
the framework used most often with <link
xlink:href="http://hadoop.apache.org/">Apache Hadoop</link>. MapReduce itself is out of the
scope of this document. A good place to get started with MapReduce is <link
xlink:href="http://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html" />. MapReduce version
2 (MR2)is now part of <link
xlink:href="http://hadoop.apache.org/docs/r2.3.0/hadoop-yarn/hadoop-yarn-site/">YARN</link>. </para>
<para> 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.
<note>
<title>mapred and mapreduce</title>
<para>There are two mapreduce packages in HBase as in MapReduce itself: <filename>org.apache.hadoop.hbase.mapred</filename>
and <filename>org.apache.hadoop.hbase.mapreduce</filename>. 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
<filename>org.apache.hadoop.hbase.mapreduce</filename>. 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.
</para>
</note>
</para>
<section
xml:id="hbase.mapreduce.classpath">
<title>HBase, MapReduce, and the CLASSPATH</title>
<para>By default, MapReduce jobs deployed to a MapReduce cluster do not have access to either
the HBase configuration under <envar>$HBASE_CONF_DIR</envar> or the HBase classes.</para>
<para>To give the MapReduce jobs the access they need, you could add
<filename>hbase-site.xml</filename> to the
<filename><replaceable>$HADOOP_HOME</replaceable>/conf/</filename> directory and add the
HBase JARs to the <filename><replaceable>HADOOP_HOME</replaceable>/conf/</filename>
directory, then copy these changes across your cluster. You could add hbase-site.xml to
$HADOOP_HOME/conf and add HBase jars to the $HADOOP_HOME/lib. You would then need to copy
these changes across your cluster or edit
<filename><replaceable>$HADOOP_HOME</replaceable>conf/hadoop-env.sh</filename> and add
them to the <envar>HADOOP_CLASSPATH</envar> 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.</para>
<para> 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
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/RowCounter.html">RowCounter</link>
MapReduce job against a table named <systemitem>usertable</systemitem> If you have not set
the environment variables expected in the command (the parts prefixed by a
<literal>$</literal> sign and curly braces), you can use the actual system paths instead.
Be sure to use the correct version of the HBase JAR for your system. The backticks
(<literal>`</literal> symbols) cause ths shell to execute the sub-commands, setting the
CLASSPATH as part of the command. This example assumes you use a BASH-compatible shell. </para>
<screen language="bourne">$ <userinput>HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-server-VERSION.jar rowcounter usertable</userinput></screen>
<para>When the command runs, internally, the HBase JAR finds the dependencies it needs for
zookeeper, guava, and its other dependencies on the passed <envar>HADOOP_CLASSPATH</envar>
and adds the JARs to the MapReduce job configuration. See the source at
TableMapReduceUtil#addDependencyJars(org.apache.hadoop.mapreduce.Job) for how this is done. </para>
<note>
<para> The example may not work if you are running HBase from its build directory rather
than an installed location. You may see an error like the following:</para>
<screen>java.lang.RuntimeException: java.lang.ClassNotFoundException: org.apache.hadoop.hbase.mapreduce.RowCounter$RowCounterMapper</screen>
<para>If this occurs, try modifying the command as follows, so that it uses the HBase JARs
from the <filename>target/</filename> directory within the build environment.</para>
<screen language="bourne">$ <userinput>HADOOP_CLASSPATH=${HBASE_HOME}/hbase-server/target/hbase-server-VERSION-SNAPSHOT.jar:`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-server/target/hbase-server-VERSION-SNAPSHOT.jar rowcounter usertable</userinput></screen>
</note>
<caution>
<title>Notice to Mapreduce users of HBase 0.96.1 and above</title>
<para>Some mapreduce jobs that use HBase fail to launch. The symptom is an exception similar
to the following:</para>
<screen>
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)
...
</screen>
<para>This is caused by an optimization introduced in <link
xlink:href="https://issues.apache.org/jira/browse/HBASE-9867">HBASE-9867</link> that
inadvertently introduced a classloader dependency. </para>
<para>This affects both jobs using the <code>-libjars</code> option and "fat jar," those
which package their runtime dependencies in a nested <code>lib</code> folder.</para>
<para>In order to satisfy the new classloader requirements, hbase-protocol.jar must be
included in Hadoop's classpath. See <xref
linkend="hbase.mapreduce.classpath" /> for current recommendations for resolving
classpath errors. The following is included for historical purposes.</para>
<para>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.</para>
<para>This can also be achieved on a per-job launch basis by including it in the
<code>HADOOP_CLASSPATH</code> environment variable at job submission time. When
launching jobs that package their dependencies, all three of the following job launching
commands satisfy this requirement:</para>
<screen language="bourne">
$ <userinput>HADOOP_CLASSPATH=/path/to/hbase-protocol.jar:/path/to/hbase/conf hadoop jar MyJob.jar MyJobMainClass</userinput>
$ <userinput>HADOOP_CLASSPATH=$(hbase mapredcp):/path/to/hbase/conf hadoop jar MyJob.jar MyJobMainClass</userinput>
$ <userinput>HADOOP_CLASSPATH=$(hbase classpath) hadoop jar MyJob.jar MyJobMainClass</userinput>
</screen>
<para>For jars that do not package their dependencies, the following command structure is
necessary:</para>
<screen language="bourne">
$ <userinput>HADOOP_CLASSPATH=$(hbase mapredcp):/etc/hbase/conf hadoop jar MyApp.jar MyJobMainClass -libjars $(hbase mapredcp | tr ':' ',')</userinput> ...
</screen>
<para>See also <link
xlink:href="https://issues.apache.org/jira/browse/HBASE-10304">HBASE-10304</link> for
further discussion of this issue.</para>
</caution>
</section>
<section>
<title>MapReduce Scan Caching</title>
<para>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
xlink:href="https://issues.apache.org/jira/browse/HBASE-11558">HBASE-11558</link>), which
is fixed for HBase 0.98.5 and 0.96.3. The priority order for choosing the scanner caching is
as follows:</para>
<orderedlist>
<listitem>
<para>Caching settings which are set on the scan object.</para>
</listitem>
<listitem>
<para>Caching settings which are specified via the configuration option
<option>hbase.client.scanner.caching</option>, which can either be set manually in
<filename>hbase-site.xml</filename> or via the helper method
<code>TableMapReduceUtil.setScannerCaching()</code>.</para>
</listitem>
<listitem>
<para>The default value <code>HConstants.DEFAULT_HBASE_CLIENT_SCANNER_CACHING</code>, which is set to
<literal>100</literal>.</para>
</listitem>
</orderedlist>
<para>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.</para>
<para>The list of priorities mentioned above allows you to set a reasonable default, and
override it for specific operations.</para>
<para>See the API documentation for <link
xlink:href="https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html"
>Scan</link> for more details.</para>
</section>
<section>
<title>Bundled HBase MapReduce Jobs</title>
<para>The HBase JAR also serves as a Driver for some bundled mapreduce jobs. To learn about
the bundled MapReduce jobs, run the following command.</para>
<screen language="bourne">$ <userinput>${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-server-VERSION.jar</userinput>
<computeroutput>An example program must be given as the first argument.
Valid program names are:
copytable: Export a table from local cluster to peer cluster
completebulkload: Complete a bulk data load.
export: Write table data to HDFS.
import: Import data written by Export.
importtsv: Import data in TSV format.
rowcounter: Count rows in HBase table</computeroutput>
</screen>
<para>Each of the valid program names are bundled MapReduce jobs. To run one of the jobs,
model your command after the following example.</para>
<screen language="bourne">$ <userinput>${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-server-VERSION.jar rowcounter myTable</userinput></screen>
</section>
<section>
<title>HBase as a MapReduce Job Data Source and Data Sink</title>
<para>HBase can be used as a data source, <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableInputFormat.html">TableInputFormat</link>,
and data sink, <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableOutputFormat.html">TableOutputFormat</link>
or <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/MultiTableOutputFormat.html">MultiTableOutputFormat</link>,
for MapReduce jobs. Writing MapReduce jobs that read or write HBase, it is advisable to
subclass <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableMapper.html">TableMapper</link>
and/or <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableReducer.html">TableReducer</link>.
See the do-nothing pass-through classes <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/IdentityTableMapper.html">IdentityTableMapper</link>
and <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/IdentityTableReducer.html">IdentityTableReducer</link>
for basic usage. For a more involved example, see <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/RowCounter.html">RowCounter</link>
or review the <code>org.apache.hadoop.hbase.mapreduce.TestTableMapReduce</code> unit test. </para>
<para>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.</para>
<para>When you read from HBase, the <code>TableInputFormat</code> requests the list of regions
from HBase and makes a map, which is either a <code>map-per-region</code> or
<code>mapreduce.job.maps</code> map, whichever is smaller. If your job only has two maps,
raise <code>mapreduce.job.maps</code> to a number greater than the number of regions. Maps
will run on the adjacent TaskTracker if you are running a TaskTracer 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, you myour map might emit counts of records processed for
reporting at the end of the jobj, 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.</para>
<para>A new HBase partitioner, the <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/HRegionPartitioner.html">HRegionPartitioner</link>,
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. </para>
</section>
<section>
<title>Writing HFiles Directly During Bulk Import</title>
<para>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 <xref
linkend="arch.bulk.load" />.</para>
</section>
<section>
<title>RowCounter Example</title>
<para>The included <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/RowCounter.html">RowCounter</link>
MapReduce job uses <code>TableInputFormat</code> and does a count of all rows in the specified
table. To run it, use the following command: </para>
<screen language="bourne">$ <userinput>./bin/hadoop jar hbase-X.X.X.jar</userinput></screen>
<para>This will
invoke the HBase MapReduce Driver class. Select <literal>rowcounter</literal> from the choice of jobs
offered. This will print rowcouner usage advice to standard output. Specify the tablename,
column to count, and output
directory. If you have classpath errors, see <xref linkend="hbase.mapreduce.classpath" />.</para>
</section>
<section
xml:id="splitter">
<title>Map-Task Splitting</title>
<section
xml:id="splitter.default">
<title>The Default HBase MapReduce Splitter</title>
<para>When <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableInputFormat.html">TableInputFormat</link>
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.</para>
</section>
<section
xml:id="splitter.custom">
<title>Custom Splitters</title>
<para>For those interested in implementing custom splitters, see the method
<code>getSplits</code> in <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableInputFormatBase.html">TableInputFormatBase</link>.
That is where the logic for map-task assignment resides. </para>
</section>
</section>
<section
xml:id="mapreduce.example">
<title>HBase MapReduce Examples</title>
<section
xml:id="mapreduce.example.read">
<title>HBase MapReduce Read Example</title>
<para>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...</para>
<programlisting language="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!");
}
</programlisting>
<para>...and the mapper instance would extend <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableMapper.html">TableMapper</link>...</para>
<programlisting language="java">
public static class MyMapper extends TableMapper&lt;Text, Text&gt; {
public void map(ImmutableBytesWritable row, Result value, Context context) throws InterruptedException, IOException {
// process data for the row from the Result instance.
}
}
</programlisting>
</section>
<section
xml:id="mapreduce.example.readwrite">
<title>HBase MapReduce Read/Write Example</title>
<para>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.</para>
<programlisting language="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!");
}
</programlisting>
<para>An explanation is required of what <classname>TableMapReduceUtil</classname> is doing,
especially with the reducer. <link
xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableOutputFormat.html">TableOutputFormat</link>
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 <classname>ImmutableBytesWritable</classname> and reducer value to
<classname>Writable</classname>. These could be set by the programmer on the job and
conf, but <classname>TableMapReduceUtil</classname> tries to make things easier.</para>
<para>The following is the example mapper, which will create a <classname>Put</classname>
and matching the input <classname>Result</classname> and emit it. Note: this is what the
CopyTable utility does. </para>
<programlisting language="java">
public static class MyMapper extends TableMapper&lt;ImmutableBytesWritable, Put&gt; {
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;
}
}
</programlisting>
<para>There isn't actually a reducer step, so <classname>TableOutputFormat</classname> takes
care of sending the <classname>Put</classname> to the target table. </para>
<para>This is just an example, developers could choose not to use
<classname>TableOutputFormat</classname> and connect to the target table themselves.
</para>
</section>
<section
xml:id="mapreduce.example.readwrite.multi">
<title>HBase MapReduce Read/Write Example With Multi-Table Output</title>
<para>TODO: example for <classname>MultiTableOutputFormat</classname>. </para>
</section>
<section
xml:id="mapreduce.example.summary">
<title>HBase MapReduce Summary to HBase Example</title>
<para>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.
<programlisting language="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!");
}
</programlisting>
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
<classname>IntWritable</classname> represents an instance counter.
<programlisting language="java">
public static class MyMapper extends TableMapper&lt;Text, IntWritable&gt; {
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);
}
}
</programlisting>
In the reducer, the "ones" are counted (just like any other MR example that does this),
and then emits a <classname>Put</classname>.
<programlisting language="java">
public static class MyTableReducer extends TableReducer&lt;Text, IntWritable, ImmutableBytesWritable&gt; {
public static final byte[] CF = "cf".getBytes();
public static final byte[] COUNT = "count".getBytes();
public void reduce(Text key, Iterable&lt;IntWritable&gt; 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);
}
}
</programlisting>
</para>
</section>
<section
xml:id="mapreduce.example.summary.file">
<title>HBase MapReduce Summary to File Example</title>
<para>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. </para>
<programlisting language="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!");
}
</programlisting>
<para>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.</para>
<programlisting language="java">
public static class MyReducer extends Reducer&lt;Text, IntWritable, Text, IntWritable&gt; {
public void reduce(Text key, Iterable&lt;IntWritable&gt; values, Context context) throws IOException, InterruptedException {
int i = 0;
for (IntWritable val : values) {
i += val.get();
}
context.write(key, new IntWritable(i));
}
}
</programlisting>
</section>
<section
xml:id="mapreduce.example.summary.noreducer">
<title>HBase MapReduce Summary to HBase Without Reducer</title>
<para>It is also possible to perform summaries without a reducer - if you use HBase as the
reducer. </para>
<para>An HBase target table would need to exist for the job summary. The Table method
<code>incrementColumnValue</code> 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 incremeneted for each map-task, and make one update per key at during the <code>
cleanup</code> method of the mapper. However, your milage may vary depending on the
number of rows to be processed and unique keys. </para>
<para>In the end, the summary results are in HBase. </para>
</section>
<section
xml:id="mapreduce.example.summary.rdbms">
<title>HBase MapReduce Summary to RDBMS</title>
<para>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
<code>setup</code> 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. </para>
<para>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. </para>
<programlisting language="java">
public static class MyRdbmsReducer extends Reducer&lt;Text, IntWritable, Text, IntWritable&gt; {
private Connection c = null;
public void setup(Context context) {
// create DB connection...
}
public void reduce(Text key, Iterable&lt;IntWritable&gt; 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
}
}
</programlisting>
<para>In the end, the summary results are written to your RDBMS table/s. </para>
</section>
</section>
<!-- mr examples -->
<section
xml:id="mapreduce.htable.access">
<title>Accessing Other HBase Tables in a MapReduce Job</title>
<para>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.
<programlisting language="java">public class MyMapper extends TableMapper&lt;Text, LongWritable&gt; {
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
}
</programlisting>
</para>
</section>
<section
xml:id="mapreduce.specex">
<title>Speculative Execution</title>
<para>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. </para>
<para>See <xref
linkend="spec.ex" /> for more information. </para>
</section>
</chapter>

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<?xml version="1.0" encoding="UTF-8"?>
<appendix
xml:id="orca"
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">
<!--/**
* 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.
*/
-->
<title>Apache HBase Orca</title>
<figure>
<title>Apache HBase Orca</title>
<mediaobject>
<imageobject>
<imagedata align="center" valign="right"
fileref="jumping-orca_rotated_25percent.png"/>
</imageobject>
</mediaobject>
</figure>
<para><link xlink:href="https://issues.apache.org/jira/browse/HBASE-4920">An Orca is the Apache
HBase mascot.</link>
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.
</para>
</appendix>

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xml:id="other.info"
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"
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xmlns:m="http://www.w3.org/1998/Math/MathML"
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* 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
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* limitations under the License.
*/
-->
<title>Other Information About HBase</title>
<section xml:id="other.info.videos"><title>HBase Videos</title>
<para>Introduction to HBase
<itemizedlist>
<listitem><para><link xlink:href="http://www.cloudera.com/content/cloudera/en/resources/library/presentation/chicago_data_summit_apache_hbase_an_introduction_todd_lipcon.html">Introduction to HBase</link> by Todd Lipcon (Chicago Data Summit 2011).
</para></listitem>
<listitem><para><link xlink:href="http://www.cloudera.com/videos/intorduction-hbase-todd-lipcon">Introduction to HBase</link> by Todd Lipcon (2010).
</para></listitem>
</itemizedlist>
</para>
<para><link xlink:href="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</link> by Jonathan Gray (Hadoop World 2011).
</para>
<para><link xlink:href="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</link> by JD Cryans (Hadoop World 2010).
</para>
</section>
<section xml:id="other.info.pres"><title>HBase Presentations (Slides)</title>
<para><link xlink:href="http://www.cloudera.com/content/cloudera/en/resources/library/hadoopworld/hadoop-world-2011-presentation-video-advanced-hbase-schema-design.html">Advanced HBase Schema Design</link> by Lars George (Hadoop World 2011).
</para>
<para><link xlink:href="http://www.slideshare.net/cloudera/chicago-data-summit-apache-hbase-an-introduction">Introduction to HBase</link> by Todd Lipcon (Chicago Data Summit 2011).
</para>
<para><link xlink:href="http://www.slideshare.net/cloudera/hw09-practical-h-base-getting-the-most-from-your-h-base-install">Getting The Most From Your HBase Install</link> by Ryan Rawson, Jonathan Gray (Hadoop World 2009).
</para>
</section>
<section xml:id="other.info.papers"><title>HBase Papers</title>
<para><link xlink:href="http://research.google.com/archive/bigtable.html">BigTable</link> by Google (2006).
</para>
<para><link xlink:href="http://www.larsgeorge.com/2010/05/hbase-file-locality-in-hdfs.html">HBase and HDFS Locality</link> by Lars George (2010).
</para>
<para><link xlink:href="http://ianvarley.com/UT/MR/Varley_MastersReport_Full_2009-08-07.pdf">No Relation: The Mixed Blessings of Non-Relational Databases</link> by Ian Varley (2009).
</para>
</section>
<section xml:id="other.info.sites"><title>HBase Sites</title>
<para><link xlink:href="http://www.cloudera.com/blog/category/hbase/">Cloudera's HBase Blog</link> has a lot of links to useful HBase information.
<itemizedlist>
<listitem><para><link xlink:href="http://www.cloudera.com/blog/2010/04/cap-confusion-problems-with-partition-tolerance/">CAP Confusion</link> is a relevant entry for background information on
distributed storage systems.</para>
</listitem>
</itemizedlist>
</para>
<para><link xlink:href="http://wiki.apache.org/hadoop/HBase/HBasePresentations">HBase Wiki</link> has a page with a number of presentations.
</para>
<para><link xlink:href="http://refcardz.dzone.com/refcardz/hbase">HBase RefCard</link> from DZone.
</para>
</section>
<section xml:id="other.info.books"><title>HBase Books</title>
<para><link xlink:href="http://shop.oreilly.com/product/0636920014348.do">HBase: The Definitive Guide</link> by Lars George.
</para>
</section>
<section xml:id="other.info.books.hadoop"><title>Hadoop Books</title>
<para><link xlink:href="http://shop.oreilly.com/product/9780596521981.do">Hadoop: The Definitive Guide</link> by Tom White.
</para>
</section>
</appendix>

2
src/main/docbkx/performance.xml
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@ -273,7 +273,7 @@ tableDesc.addFamily(cfDesc);
If there is enough RAM, increasing this can help. If there is enough RAM, increasing this can help.
</para> </para>
</section> </section>
<section xml:id="hbase.regionserver.checksum.verify"> <section xml:id="hbase.regionserver.checksum.verify.performance">
<title><varname>hbase.regionserver.checksum.verify</varname></title> <title><varname>hbase.regionserver.checksum.verify</varname></title>
<para>Have HBase write the checksum into the datablock and save <para>Have HBase write the checksum into the datablock and save
having to do the checksum seek whenever you read.</para> having to do the checksum seek whenever you read.</para>

40
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<?xml version="1.0" encoding="UTF-8"?>
<appendix
xml:id="sql"
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">
<!--/**
* 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.
*/
-->
<title>SQL over HBase</title>
<section xml:id="phoenix">
<title>Apache Phoenix</title>
<para><link xlink:href="http://phoenix.apache.org">Apache Phoenix</link></para>
</section>
<section xml:id="trafodion">
<title>Trafodion</title>
<para><link xlink:href="https://wiki.trafodion.org/">Trafodion: Transactional SQL-on-HBase</link></para>
</section>
</appendix>

2
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@ -240,7 +240,7 @@
</table> </table>
</section> </section>
<section xml:id="hbase.client.api"> <section xml:id="hbase.client.api.surface">
<title>HBase API surface</title> <title>HBase API surface</title>
<para> 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 <para> 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 xlink:href="https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-common/Compatibility.html">Hadoop's Interface classification</link>. HBase's Interface classification classes can be found <link xlink:href="https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/classification/package-summary.html"> here</link>. <link xlink:href="https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-common/Compatibility.html">Hadoop's Interface classification</link>. HBase's Interface classification classes can be found <link xlink:href="https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/classification/package-summary.html"> here</link>.

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<?xml version="1.0" encoding="UTF-8"?>
<appendix xml:id="ycsb" 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">
<!--/**
* 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.
*/
-->
<title>YCSB</title>
<para><link xlink:href="https://github.com/brianfrankcooper/YCSB/">YCSB: The
Yahoo! Cloud Serving Benchmark</link> and HBase</para>
<para>TODO: Describe how YCSB is poor for putting up a decent cluster load.</para>
<para>TODO: Describe setup of YCSB for HBase. In particular, presplit your tables before you
start a run. See <link xlink:href="https://issues.apache.org/jira/browse/HBASE-4163"
>HBASE-4163 Create Split Strategy for YCSB Benchmark</link> for why and a little shell
command for how to do it.</para>
<para>Ted Dunning redid YCSB so it's mavenized and added facility for verifying workloads. See
<link xlink:href="https://github.com/tdunning/YCSB">Ted Dunning's YCSB</link>.</para>
</appendix>