Quick Start will get you up and running on a single-node instance of HBase using the local filesystem. The Not-so-quick Start Guide describes setup of HBase in distributed mode running on top of HDFS.

This guide describes setup of a standalone HBase instance that uses the local filesystem. It leads you through creating a table, inserting rows via the HBase Shell, and then cleaning up and shutting down your standalone HBase instance. The below exercise should take no more than ten minutes (not including download time).

Choose a download site from this list of Apache Download Mirrors. Click on suggested top link. This will take you to a mirror of HBase Releases. Click on the folder named stable and then download the file that ends in .tar.gz to your local filesystem; e.g. hbase-.tar.gz. Decompress and untar your download and then change into the unpacked directory. $ tar xfz hbase-.tar.gz $ cd hbase- At this point, you are ready to start HBase. But before starting it, you might want to edit conf/hbase-site.xml and set the directory you want HBase to write to, hbase.rootdir. <?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <name>hbase.rootdir</name> <value>file:///DIRECTORY/hbase</value> </property> </configuration> Replace DIRECTORY in the above with a path to a directory where you want HBase to store its data. By default, hbase.rootdir is set to /tmp/hbase-${user.name} which means you'll lose all your data whenever your server reboots (Most operating systems clear /tmp on restart).

Now start HBase:$ ./bin/start-hbase.sh starting Master, logging to logs/hbase-user-master-example.org.out You should now have a running standalone HBase instance. In standalone mode, HBase runs all daemons in the the one JVM; i.e. both the HBase and ZooKeeper daemons. HBase logs can be found in the logs subdirectory. Check them out especially if HBase had trouble starting. All of the above presumes a 1.6 version of Oracle java is installed on your machine and available on your path; i.e. when you type java, you see output that describes the options the java program takes (HBase requires java 6). If this is not the case, HBase will not start. Install java, edit conf/hbase-env.sh, uncommenting the JAVA_HOME line pointing it to your java install. Then, retry the steps above.

Connect to your running HBase via the HBase Shell. $ ./bin/hbase shell HBase Shell; enter 'help<RETURN>' for list of supported commands. Type "exit<RETURN>" to leave the HBase Shell Version: 0.90.0, r1001068, Fri Sep 24 13:55:42 PDT 2010 hbase(main):001:0> Type help and then <RETURN> to see a listing of shell commands and options. Browse at least the paragraphs at the end of the help emission for the gist of how variables and command arguments are entered into the HBase shell; in particular note how table names, rows, and columns, etc., must be quoted. Create a table named test with a single column family named cf. Verify its creation by listing all tables and then insert some values. hbase(main):003:0> create 'test', 'cf' 0 row(s) in 1.2200 seconds hbase(main):003:0> list 'table' test 1 row(s) in 0.0550 seconds hbase(main):004:0> put 'test', 'row1', 'cf:a', 'value1' 0 row(s) in 0.0560 seconds hbase(main):005:0> put 'test', 'row2', 'cf:b', 'value2' 0 row(s) in 0.0370 seconds hbase(main):006:0> put 'test', 'row3', 'cf:c', 'value3' 0 row(s) in 0.0450 seconds Above we inserted 3 values, one at a time. The first insert is at row1, column cf:a with a value of value1. Columns in HBase are comprised of a column family prefix -- cf in this example -- followed by a colon and then a column qualifier suffix (a in this case). Verify the data insert. Run a scan of the table by doing the following hbase(main):007:0> scan 'test' ROW COLUMN+CELL row1 column=cf:a, timestamp=1288380727188, value=value1 row2 column=cf:b, timestamp=1288380738440, value=value2 row3 column=cf:c, timestamp=1288380747365, value=value3 3 row(s) in 0.0590 seconds Get a single row as follows hbase(main):008:0> get 'test', 'row1' COLUMN CELL cf:a timestamp=1288380727188, value=value1 1 row(s) in 0.0400 seconds Now, disable and drop your table. This will clean up all done above. hbase(main):012:0> disable 'test' 0 row(s) in 1.0930 seconds hbase(main):013:0> drop 'test' 0 row(s) in 0.0770 seconds Exit the shell by typing exit. hbase(main):014:0> exit

Stop your hbase instance by running the stop script. $ ./bin/stop-hbase.sh stopping hbase...............

The above described standalone setup is good for testing and experiments only. Move on to the next section, the Not-so-quick Start Guide where we'll go into depth on the different HBase run modes, requirements and critical configurations needed setting up a distributed HBase deploy.

HBase has the following requirements. Please read the section below carefully and ensure that all requirements have been satisfied. Failure to do so will cause you (and us) grief debugging strange errors and/or data loss.

Just like Hadoop, HBase requires java 6 from Oracle. Usually you'll want to use the latest version available except the problematic u18 (u24 is the latest version as of this writing).

This version of HBase will only run on Hadoop 0.20.x. It will not run on hadoop 0.21.x (nor 0.22.x). HBase will lose data unless it is running on an HDFS that has a durable sync. Currently only the branch-0.20-append branch has this attribute See CHANGES.txt in branch-0.20-append to see list of patches involved adding append on the Hadoop 0.20 branch. . No official releases have been made from this branch up to now so you will have to build your own Hadoop from the tip of this branch. Check it out using this url, branch-0.20-append. Scroll down in the Hadoop How To Release to the section Build Requirements for instruction on how to build Hadoop. Or rather than build your own, you could use Cloudera's CDH3. CDH has the 0.20-append patches needed to add a durable sync (CDH3 betas will suffice; b2, b3, or b4). Because HBase depends on Hadoop, it bundles an instance of the Hadoop jar under its lib directory. The bundled Hadoop was made from the Apache branch-0.20-append branch at the time of this HBase's release. It is critical that the version of Hadoop that is out on your cluster matches what is Hbase match. Replace the hadoop jar found in the HBase lib directory with the hadoop jar you are running out on your cluster to avoid version mismatch issues. Make sure you replace the jar all over your cluster. For example, versions of CDH do not have HDFS-724 whereas Hadoops branch-0.20-append branch does have HDFS-724. This patch changes the RPC version because protocol was changed. Version mismatch issues have various manifestations but often all looks like its hung up. You could do this. It works going by a recent posting up on the mailing list. HBase will run on any Hadoop 0.20.x that incorporates Hadoop security features -- e.g. Y! 0.20S or CDH3B3 -- as long as you do as suggested above and replace the Hadoop jar that ships with HBase with the secure version.

ssh must be installed and sshd must be running to use Hadoop's scripts to manage remote Hadoop and HBase daemons. You must be able to ssh to all nodes, including your local node, using passwordless login (Google "ssh passwordless login").

HBase uses the local hostname to self-report it's IP address. Both forward and reverse DNS resolving should work. If your machine has multiple interfaces, HBase will use the interface that the primary hostname resolves to. If this is insufficient, you can set hbase.regionserver.dns.interface to indicate the primary interface. This only works if your cluster configuration is consistent and every host has the same network interface configuration. Another alternative is setting hbase.regionserver.dns.nameserver to choose a different nameserver than the system wide default.

The clocks on cluster members should be in basic alignments. Some skew is tolerable but wild skew could generate odd behaviors. Run NTP on your cluster, or an equivalent. If you are having problems querying data, or "weird" cluster operations, check system time!

HBase is a database, it uses a lot of files at the same time. The default ulimit -n of 1024 on *nix systems is insufficient. Any significant amount of loading will lead you to FAQ: Why do I see "java.io.IOException...(Too many open files)" in my logs?. You may also notice errors such as 2010-04-06 03:04:37,542 INFO org.apache.hadoop.hdfs.DFSClient: Exception increateBlockOutputStream java.io.EOFException 2010-04-06 03:04:37,542 INFO org.apache.hadoop.hdfs.DFSClient: Abandoning block blk_-6935524980745310745_1391901 Do yourself a favor and change the upper bound on the number of file descriptors. Set it to north of 10k. See the above referenced FAQ for how. To be clear, upping the file descriptors for the user who is running the HBase process is an operating system configuration, not an HBase configuration. Also, a common mistake is that administrators will up the file descriptors for a particular user but for whatever reason, HBase will be running as some one else. HBase prints in its logs as the first line the ulimit its seeing. Ensure its correct. A useful read setting config on you hadoop cluster is Aaron Kimballs' Configuration Parameters: What can you just ignore?

If you are on Ubuntu you will need to make the following changes: In the file /etc/security/limits.conf add a line like: hadoop - nofile 32768 Replace hadoop with whatever user is running Hadoop and HBase. If you have separate users, you will need 2 entries, one for each user. In the file /etc/pam.d/common-session add as the last line in the file: session required pam_limits.so Otherwise the changes in /etc/security/limits.conf won't be applied. Don't forget to log out and back in again for the changes to take effect!

An Hadoop HDFS datanode has an upper bound on the number of files that it will serve at any one time. The upper bound parameter is called xcievers (yes, this is misspelled). Again, before doing any loading, make sure you have configured Hadoop's conf/hdfs-site.xml setting the xceivers value to at least the following: <property> <name>dfs.datanode.max.xcievers</name> <value>4096</value> </property> Be sure to restart your HDFS after making the above configuration. Not having this configuration in place makes for strange looking failures. Eventually you'll see a complain in the datanode logs complaining about the xcievers exceeded, but on the run up to this one manifestation is complaint about missing blocks. For example: 10/12/08 20:10:31 INFO hdfs.DFSClient: Could not obtain block blk_XXXXXXXXXXXXXXXXXXXXXX_YYYYYYYY from any node: java.io.IOException: No live nodes contain current block. Will get new block locations from namenode and retry...

HBase has been little tested running on windows. Running a production install of HBase on top of windows is not recommended. If you are running HBase on Windows, you must install Cygwin to have a *nix-like environment for the shell scripts. The full details are explained in the Windows Installation guide. Also search our user mailing list to pick up latest fixes figured by windows users.

HBase has two run modes: standalone and distributed. Out of the box, HBase runs in standalone mode. To set up a distributed deploy, you will need to configure HBase by editing files in the HBase conf directory. Whatever your mode, you will need to edit conf/hbase-env.sh to tell HBase which java to use. In this file you set HBase environment variables such as the heapsize and other options for the JVM, the preferred location for log files, etc. Set JAVA_HOME to point at the root of your java install.

This is the default mode. Standalone mode is what is described in the quickstart section. In standalone mode, HBase does not use HDFS -- it uses the local filesystem instead -- and it runs all HBase daemons and a local zookeeper all up in the same JVM. Zookeeper binds to a well known port so clients may talk to HBase.

Distributed mode can be subdivided into distributed but all daemons run on a single node -- a.k.a pseudo-distributed-- and fully-distributed where the daemons are spread across all nodes in the cluster The pseudo-distributed vs fully-distributed nomenclature comes from Hadoop. . Distributed modes require an instance of the Hadoop Distributed File System (HDFS). See the Hadoop requirements and instructions for how to set up a HDFS. Before proceeding, ensure you have an appropriate, working HDFS. Below we describe the different distributed setups. Starting, verification and exploration of your install, whether a pseudo-distributed or fully-distributed configuration is described in a section that follows, Running and Confirming your Installation. The same verification script applies to both deploy types.

A pseudo-distributed mode is simply a distributed mode run on a single host. Use this configuration testing and prototyping on HBase. Do not use this configuration for production nor for evaluating HBase performance. Once you have confirmed your HDFS setup, edit conf/hbase-site.xml. This is the file into which you add local customizations and overrides for Default HBase Configurations and HDFS Client Configurations. Point HBase at the running Hadoop HDFS instance by setting the hbase.rootdir property. This property points HBase at the Hadoop filesystem instance to use. For example, adding the properties below to your hbase-site.xml says that HBase should use the /hbase directory in the HDFS whose namenode is at port 9000 on your local machine, and that it should run with one replica only (recommended for pseudo-distributed mode): <configuration> ... <property> <name>hbase.rootdir</name> <value>hdfs://localhost:9000/hbase</value> <description>The directory shared by region servers. </description> </property> <property> <name>dfs.replication</name> <value>1</value> <description>The replication count for HLog & HFile storage. Should not be greater than HDFS datanode count. </description> </property> ... </configuration> Let HBase create the hbase.rootdir directory. If you don't, you'll get warning saying HBase needs a migration run because the directory is missing files expected by HBase (it'll create them if you let it). Above we bind to localhost. This means that a remote client cannot connect. Amend accordingly, if you want to connect from a remote location. Now skip to Running and Confirming your Installation for how to start and verify your pseudo-distributed install. See Pseudo-distributed mode extras for notes on how to start extra Masters and regionservers when running pseudo-distributed.

For running a fully-distributed operation on more than one host, make the following configurations. In hbase-site.xml, add the property hbase.cluster.distributed and set it to true and point the HBase hbase.rootdir at the appropriate HDFS NameNode and location in HDFS where you would like HBase to write data. For example, if you namenode were running at namenode.example.org on port 9000 and you wanted to home your HBase in HDFS at /hbase, make the following configuration. <configuration> ... <property> <name>hbase.rootdir</name> <value>hdfs://namenode.example.org:9000/hbase</value> <description>The directory shared by region servers. </description> </property> <property> <name>hbase.cluster.distributed</name> <value>true</value> <description>The mode the cluster will be in. Possible values are false: standalone and pseudo-distributed setups with managed Zookeeper true: fully-distributed with unmanaged Zookeeper Quorum (see hbase-env.sh) </description> </property> ... </configuration>

In addition, a fully-distributed mode requires that you modify conf/regionservers. The regionservers file lists all hosts that you would have running HRegionServers, one host per line (This file in HBase is like the Hadoop slaves file). All servers listed in this file will be started and stopped when HBase cluster start or stop is run.

A distributed HBase depends on a running ZooKeeper cluster. All participating nodes and clients need to be able to access the running ZooKeeper ensemble. HBase by default manages a ZooKeeper "cluster" for you. It will start and stop the ZooKeeper ensemble as part of the HBase start/stop process. You can also manage the ZooKeeper ensemble independent of HBase and just point HBase at the cluster it should use. To toggle HBase management of ZooKeeper, use the HBASE_MANAGES_ZK variable in conf/hbase-env.sh. This variable, which defaults to true, tells HBase whether to start/stop the ZooKeeper ensemble servers as part of HBase start/stop. When HBase manages the ZooKeeper ensemble, you can specify ZooKeeper configuration using its native zoo.cfg file, or, the easier option is to just specify ZooKeeper options directly in conf/hbase-site.xml. A ZooKeeper configuration option can be set as a property in the HBase hbase-site.xml XML configuration file by prefacing the ZooKeeper option name with hbase.zookeeper.property. For example, the clientPort setting in ZooKeeper can be changed by setting the hbase.zookeeper.property.clientPort property. For all default values used by HBase, including ZooKeeper configuration, see the section Default HBase Configurations. Look for the hbase.zookeeper.property prefix For the full list of ZooKeeper configurations, see ZooKeeper's zoo.cfg. HBase does not ship with a zoo.cfg so you will need to browse the conf directory in an appropriate ZooKeeper download. You must at least list the ensemble servers in hbase-site.xml using the hbase.zookeeper.quorum property. This property defaults to a single ensemble member at localhost which is not suitable for a fully distributed HBase. (It binds to the local machine only and remote clients will not be able to connect). You can run a ZooKeeper ensemble that comprises 1 node only but in production it is recommended that you run a ZooKeeper ensemble of 3, 5 or 7 machines; the more members an ensemble has, the more tolerant the ensemble is of host failures. Also, run an odd number of machines. There can be no quorum if the number of members is an even number. Give each ZooKeeper server around 1GB of RAM, and if possible, its own dedicated disk (A dedicated disk is the best thing you can do to ensure a performant ZooKeeper ensemble). For very heavily loaded clusters, run ZooKeeper servers on separate machines from RegionServers (DataNodes and TaskTrackers). For example, to have HBase manage a ZooKeeper quorum on nodes rs{1,2,3,4,5}.example.com, bound to port 2222 (the default is 2181) ensure HBASE_MANAGE_ZK is commented out or set to true in conf/hbase-env.sh and then edit conf/hbase-site.xml and set hbase.zookeeper.property.clientPort and hbase.zookeeper.quorum. You should also set hbase.zookeeper.property.dataDir to other than the default as the default has ZooKeeper persist data under /tmp which is often cleared on system restart. In the example below we have ZooKeeper persist to /user/local/zookeeper. <configuration> ... <property> <name>hbase.zookeeper.property.clientPort</name> <value>2222</value> <description>Property from ZooKeeper's config zoo.cfg. The port at which the clients will connect. </description> </property> <property> <name>hbase.zookeeper.quorum</name> <value>rs1.example.com,rs2.example.com,rs3.example.com,rs4.example.com,rs5.example.com</value> <description>Comma separated list of servers in the ZooKeeper Quorum. For example, "host1.mydomain.com,host2.mydomain.com,host3.mydomain.com". By default this is set to localhost for local and pseudo-distributed modes of operation. For a fully-distributed setup, this should be set to a full list of ZooKeeper quorum servers. If HBASE_MANAGES_ZK is set in hbase-env.sh this is the list of servers which we will start/stop ZooKeeper on. </description> </property> <property> <name>hbase.zookeeper.property.dataDir</name> <value>/usr/local/zookeeper</value> <description>Property from ZooKeeper's config zoo.cfg. The directory where the snapshot is stored. </description> </property> ... </configuration>

To point HBase at an existing ZooKeeper cluster, one that is not managed by HBase, set HBASE_MANAGES_ZK in conf/hbase-env.sh to false ... # Tell HBase whether it should manage it's own instance of Zookeeper or not. export HBASE_MANAGES_ZK=false Next set ensemble locations and client port, if non-standard, in hbase-site.xml, or add a suitably configured zoo.cfg to HBase's CLASSPATH. HBase will prefer the configuration found in zoo.cfg over any settings in hbase-site.xml. When HBase manages ZooKeeper, it will start/stop the ZooKeeper servers as a part of the regular start/stop scripts. If you would like to run ZooKeeper yourself, independent of HBase start/stop, you would do the following ${HBASE_HOME}/bin/hbase-daemons.sh {start,stop} zookeeper Note that you can use HBase in this manner to spin up a ZooKeeper cluster, unrelated to HBase. Just make sure to set HBASE_MANAGES_ZK to false if you want it to stay up across HBase restarts so that when HBase shuts down, it doesn't take ZooKeeper down with it. For more information about running a distinct ZooKeeper cluster, see the ZooKeeper Getting Started Guide.

Of note, if you have made HDFS client configuration on your Hadoop cluster -- i.e. configuration you want HDFS clients to use as opposed to server-side configurations -- HBase will not see this configuration unless you do one of the following: Add a pointer to your HADOOP_CONF_DIR to the HBASE_CLASSPATH environment variable in hbase-env.sh. Add a copy of hdfs-site.xml (or hadoop-site.xml) or, better, symlinks, under ${HBASE_HOME}/conf, or if only a small set of HDFS client configurations, add them to hbase-site.xml. An example of such an HDFS client configuration is dfs.replication. If for example, you want to run with a replication factor of 5, hbase will create files with the default of 3 unless you do the above to make the configuration available to HBase.

Make sure HDFS is running first. Start and stop the Hadoop HDFS daemons by running bin/start-hdfs.sh over in the HADOOP_HOME directory. You can ensure it started properly by testing the put and get of files into the Hadoop filesystem. HBase does not normally use the mapreduce daemons. These do not need to be started. If you are managing your own ZooKeeper, start it and confirm its running else, HBase will start up ZooKeeper for you as part of its start process. Start HBase with the following command: bin/start-hbase.sh Run the above from the HBASE_HOME directory. You should now have a running HBase instance. HBase logs can be found in the logs subdirectory. Check them out especially if HBase had trouble starting. HBase also puts up a UI listing vital attributes. By default its deployed on the Master host at port 60010 (HBase RegionServers listen on port 60020 by default and put up an informational http server at 60030). If the Master were running on a host named master.example.org on the default port, to see the Master's homepage you'd point your browser at http://master.example.org:60010. Once HBase has started, see the Shell Exercises section for how to create tables, add data, scan your insertions, and finally disable and drop your tables. To stop HBase after exiting the HBase shell enter $ ./bin/stop-hbase.sh stopping hbase............... Shutdown can take a moment to complete. It can take longer if your cluster is comprised of many machines. If you are running a distributed operation, be sure to wait until HBase has shut down completely before stopping the Hadoop daemons.

Here is an example basic configuration for a distributed ten node cluster. The nodes are named example0, example1, etc., through node example9 in this example. The HBase Master and the HDFS namenode are running on the node example0. RegionServers run on nodes example1-example9. A 3-node ZooKeeper ensemble runs on example1, example2, and example3 on the default ports. ZooKeeper data is persisted to the directory /export/zookeeper. Below we show what the main configuration files -- hbase-site.xml, regionservers, and hbase-env.sh -- found in the HBase conf directory might look like.

<?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <name>hbase.zookeeper.quorum</name> <value>example1,example2,example3</value> <description>The directory shared by region servers. </description> </property> <property> <name>hbase.zookeeper.property.dataDir</name> <value>/export/zookeeper</value> <description>Property from ZooKeeper's config zoo.cfg. The directory where the snapshot is stored. </description> </property> <property> <name>hbase.rootdir</name> <value>hdfs://example0:9000/hbase</value> <description>The directory shared by region servers. </description> </property> <property> <name>hbase.cluster.distributed</name> <value>true</value> <description>The mode the cluster will be in. Possible values are false: standalone and pseudo-distributed setups with managed Zookeeper true: fully-distributed with unmanaged Zookeeper Quorum (see hbase-env.sh) </description> </property> </configuration>

In this file you list the nodes that will run regionservers. In our case we run regionservers on all but the head node example1 which is carrying the HBase Master and the HDFS namenode example1 example3 example4 example5 example6 example7 example8 example9

Below we use a diff to show the differences from default in the hbase-env.sh file. Here we are setting the HBase heap to be 4G instead of the default 1G. $ git diff hbase-env.sh diff --git a/conf/hbase-env.sh b/conf/hbase-env.sh index e70ebc6..96f8c27 100644 --- a/conf/hbase-env.sh +++ b/conf/hbase-env.sh @@ -31,7 +31,7 @@ export JAVA_HOME=/usr/lib//jvm/java-6-sun/ # export HBASE_CLASSPATH= # The maximum amount of heap to use, in MB. Default is 1000. -# export HBASE_HEAPSIZE=1000 +export HBASE_HEAPSIZE=4096 # Extra Java runtime options. # Below are what we set by default. May only work with SUN JVM. Use rsync to copy the content of the conf directory to all nodes of the cluster.