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Preface

This is the official reference guide for the HBase version it ships with.

Herein you will find either the definitive documentation on an HBase topic as of its standing when the referenced HBase version shipped, or it will point to the location in Javadoc or JIRA where the pertinent information can be found.

About This Guide

This reference guide is a work in progress. The source for this guide can be found in the _src/main/asciidoc directory of the HBase source. This reference guide is marked up using AsciiDoc from which the finished guide is generated as part of the 'site' build target. Run

mvn site

to generate this documentation. Amendments and improvements to the documentation are welcomed. Click this link to file a new documentation bug against Apache HBase with some values pre-selected.

Contributing to the Documentation

For an overview of AsciiDoc and suggestions to get started contributing to the documentation, see the relevant section later in this documentation.

Heads-up if this is your first foray into the world of distributed computing…​

If this is your first foray into the wonderful world of Distributed Computing, then you are in for some interesting times. First off, distributed systems are hard; making a distributed system hum requires a disparate skillset that spans systems (hardware and software) and networking.

Your cluster’s operation can hiccup because of any of a myriad set of reasons from bugs in HBase itself through misconfigurations — misconfiguration of HBase but also operating system misconfigurations — through to hardware problems whether it be a bug in your network card drivers or an underprovisioned RAM bus (to mention two recent examples of hardware issues that manifested as "HBase is slow"). You will also need to do a recalibration if up to this your computing has been bound to a single box. Here is one good starting point: Fallacies of Distributed Computing.

That said, you are welcome.
It’s a fun place to be.
Yours, the HBase Community.

Reporting Bugs

Please use JIRA to report non-security-related bugs.

To protect existing HBase installations from new vulnerabilities, please do not use JIRA to report security-related bugs. Instead, send your report to the mailing list [email protected], which allows anyone to send messages, but restricts who can read them. Someone on that list will contact you to follow up on your report.

Support and Testing Expectations

The phrases /supported/, /not supported/, /tested/, and /not tested/ occur several places throughout this guide. In the interest of clarity, here is a brief explanation of what is generally meant by these phrases, in the context of HBase.

Commercial technical support for Apache HBase is provided by many Hadoop vendors. This is not the sense in which the term /support/ is used in the context of the Apache HBase project. The Apache HBase team assumes no responsibility for your HBase clusters, your configuration, or your data.
Supported

In the context of Apache HBase, /supported/ means that HBase is designed to work in the way described, and deviation from the defined behavior or functionality should be reported as a bug.

Not Supported

In the context of Apache HBase, /not supported/ means that a use case or use pattern is not expected to work and should be considered an antipattern. If you think this designation should be reconsidered for a given feature or use pattern, file a JIRA or start a discussion on one of the mailing lists.

Tested

In the context of Apache HBase, /tested/ means that a feature is covered by unit or integration tests, and has been proven to work as expected.

Not Tested

In the context of Apache HBase, /not tested/ means that a feature or use pattern may or may not work in a given way, and may or may not corrupt your data or cause operational issues. It is an unknown, and there are no guarantees. If you can provide proof that a feature designated as /not tested/ does work in a given way, please submit the tests and/or the metrics so that other users can gain certainty about such features or use patterns.

Getting Started

1. Introduction

Quickstart will get you up and running on a single-node, standalone instance of HBase.

2. Quick Start - Standalone HBase

This section describes the setup of a single-node standalone HBase. A standalone instance has all HBase daemons — the Master, RegionServers, and ZooKeeper — running in a single JVM persisting to the local filesystem. It is our most basic deploy profile. We will show you how to create a table in HBase using the hbase shell CLI, insert rows into the table, perform put and scan operations against the table, enable or disable the table, and start and stop HBase.

Apart from downloading HBase, this procedure should take less than 10 minutes.

2.1. JDK Version Requirements

HBase requires that a JDK be installed. See Java for information about supported JDK versions.

2.2. Get Started with HBase

Procedure: Download, Configure, and Start HBase in Standalone Mode

  1. Choose a download site from this list of Apache Download Mirrors. Click on the suggested top link. This will take you to a mirror of HBase Releases. Click on the folder named stable and then download the binary file that ends in .tar.gz to your local filesystem. Do not download the file ending in src.tar.gz for now.

  2. Extract the downloaded file, and change to the newly-created directory.

    $ tar xzvf hbase-4.0.0-alpha-1-SNAPSHOT-bin.tar.gz
$ cd hbase-4.0.0-alpha-1-SNAPSHOT/

  3. You must set the JAVA_HOME environment variable before starting HBase. To make this easier, HBase lets you set it within the conf/hbase-env.sh file. You must locate where Java is installed on your machine, and one way to find this is by using the whereis java command. Once you have the location, edit the conf/hbase-env.sh file and uncomment the line starting with #export JAVA_HOME=, and then set it to your Java installation path.

    Example extract from hbase-env.sh where JAVA_HOME is set
    # Set environment variables here.
# The java implementation to use.
export JAVA_HOME=/usr/jdk64/jdk1.8.0_112

  4. The bin/start-hbase.sh script is provided as a convenient way to start HBase. Issue the command, and if all goes well, a message is logged to standard output showing that HBase started successfully. You can use the jps command to verify that you have one running process called HMaster. In standalone mode HBase runs all daemons within this single JVM, i.e. the HMaster, a single HRegionServer, and the ZooKeeper daemon. Go to http://localhost:16010 to view the HBase Web UI.

Procedure: Use HBase For the First Time

  1. Connect to HBase.

    Connect to your running instance of HBase using the hbase shell command, located in the bin/ directory of your HBase install. In this example, some usage and version information that is printed when you start HBase Shell has been omitted. The HBase Shell prompt ends with a > character.

    $ ./bin/hbase shell
hbase(main):001:0>

  2. Display HBase Shell Help Text.

    Type help and press Enter, to display some basic usage information for HBase Shell, as well as several example commands. Notice that table names, rows, columns all must be enclosed in quote characters.

  3. Create a table.

    Use the create command to create a new table. You must specify the table name and the ColumnFamily name.

    hbase(main):001:0> create 'test', 'cf'
0 row(s) in 0.4170 seconds

=> Hbase::Table - test

  4. List Information About your Table

    Use the list command to confirm your table exists

    hbase(main):002:0> list 'test'
TABLE
test
1 row(s) in 0.0180 seconds

=> ["test"]

    Now use the describe command to see details, including configuration defaults

    hbase(main):003:0> describe 'test'
Table test is ENABLED
test
COLUMN FAMILIES DESCRIPTION
{NAME => 'cf', VERSIONS => '1', EVICT_BLOCKS_ON_CLOSE => 'false', NEW_VERSION_BEHAVIOR => 'false', KEEP_DELETED_CELLS => 'FALSE', CACHE_DATA_ON_WRITE =>
'false', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', MIN_VERSIONS => '0', REPLICATION_SCOPE => '0', BLOOMFILTER => 'ROW', CACHE_INDEX_ON_WRITE => 'f
alse', IN_MEMORY => 'false', CACHE_BLOOMS_ON_WRITE => 'false', PREFETCH_BLOCKS_ON_OPEN => 'false', COMPRESSION => 'NONE', BLOCKCACHE => 'true', BLOCKSIZE
 => '65536'}
1 row(s)
Took 0.9998 seconds

  5. Put data into your table.

    To put data into your table, use the put command.

    hbase(main):003:0> put 'test', 'row1', 'cf:a', 'value1'
0 row(s) in 0.0850 seconds

hbase(main):004:0> put 'test', 'row2', 'cf:b', 'value2'
0 row(s) in 0.0110 seconds

hbase(main):005:0> put 'test', 'row3', 'cf:c', 'value3'
0 row(s) in 0.0100 seconds

    Here, we insert three values, one at a time. The first insert is at row1, column cf:a, with a value of value1. Columns in HBase are comprised of a column family prefix, cf in this example, followed by a colon and then a column qualifier suffix, a in this case.

  6. Scan the table for all data at once.

    One of the ways to get data from HBase is to scan. Use the scan command to scan the table for data. You can limit your scan, but for now, all data is fetched.

    hbase(main):006:0> scan 'test'
ROW                                      COLUMN+CELL
 row1                                    column=cf:a, timestamp=1421762485768, value=value1
 row2                                    column=cf:b, timestamp=1421762491785, value=value2
 row3                                    column=cf:c, timestamp=1421762496210, value=value3
3 row(s) in 0.0230 seconds

  7. Get a single row of data.

    To get a single row of data at a time, use the get command.

    hbase(main):007:0> get 'test', 'row1'
COLUMN                                   CELL
 cf:a                                    timestamp=1421762485768, value=value1
1 row(s) in 0.0350 seconds

  8. Disable a table.

    If you want to delete a table or change its settings, as well as in some other situations, you need to disable the table first, using the disable command. You can re-enable it using the enable command.

    hbase(main):008:0> disable 'test'
0 row(s) in 1.1820 seconds

hbase(main):009:0> enable 'test'
0 row(s) in 0.1770 seconds

    Disable the table again if you tested the enable command above:

    hbase(main):010:0> disable 'test'
0 row(s) in 1.1820 seconds

  9. Drop the table.

    To drop (delete) a table, use the drop command.

    hbase(main):011:0> drop 'test'
0 row(s) in 0.1370 seconds

  10. Exit the HBase Shell.

    To exit the HBase Shell and disconnect from your cluster, use the quit command. HBase is still running in the background.

Procedure: Stop HBase

  1. In the same way that the bin/start-hbase.sh script is provided to conveniently start all HBase daemons, the bin/stop-hbase.sh script stops them.

    $ ./bin/stop-hbase.sh
stopping hbase....................
$

  2. After issuing the command, it can take several minutes for the processes to shut down. Use the jps to be sure that the HMaster and HRegionServer processes are shut down.

The above has shown you how to start and stop a standalone instance of HBase. In the next sections we give a quick overview of other modes of hbase deploy.

2.3. Pseudo-Distributed for Local Testing

After working your way through quickstart standalone mode, you can re-configure HBase to run in pseudo-distributed mode. Pseudo-distributed mode means that HBase still runs completely on a single host, but each HBase daemon (HMaster, HRegionServer, and ZooKeeper) runs as a separate process: in standalone mode all daemons ran in one jvm process/instance. By default, unless you configure the hbase.rootdir property as described in quickstart, your data is still stored in /tmp/. In this walk-through, we store your data in HDFS instead, assuming you have HDFS available. You can skip the HDFS configuration to continue storing your data in the local filesystem.

Hadoop Configuration

This procedure assumes that you have configured Hadoop and HDFS on your local system and/or a remote system, and that they are running and available. It also assumes you are using Hadoop 2. The guide on Setting up a Single Node Cluster in the Hadoop documentation is a good starting point.

  1. Stop HBase if it is running.

    If you have just finished quickstart and HBase is still running, stop it. This procedure will create a totally new directory where HBase will store its data, so any databases you created before will be lost.

  2. Configure HBase.

    Edit the hbase-site.xml configuration. First, add the following property which directs HBase to run in distributed mode, with one JVM instance per daemon.

    <property>
  <name>hbase.cluster.distributed</name>
  <value>true</value>
</property>

    Next, add a configuration for hbase.rootdir, pointing to the address of your HDFS instance, using the hdfs://// URI syntax. In this example, HDFS is running on the localhost at port 8020.

    <property>
  <name>hbase.rootdir</name>
  <value>hdfs://localhost:9000/hbase</value>
</property>

    You do not need to create the directory in HDFS. HBase will do this for you. If you create the directory, HBase will attempt to do a migration, which is not what you want.

    Finally, remove existing configuration for hbase.tmp.dir and hbase.unsafe.stream.capability.enforce,

  3. Start HBase.

    Use the bin/start-hbase.sh command to start HBase. If your system is configured correctly, the jps command should show the HMaster and HRegionServer processes running.

  4. Check the HBase directory in HDFS.

    If everything worked correctly, HBase created its directory in HDFS. In the configuration above, it is stored in /hbase/ on HDFS. You can use the hadoop fs command in Hadoop’s bin/ directory to list this directory.

    $ ./bin/hadoop fs -ls /hbase
Found 7 items
drwxr-xr-x   - hbase users          0 2014-06-25 18:58 /hbase/.tmp
drwxr-xr-x   - hbase users          0 2014-06-25 21:49 /hbase/WALs
drwxr-xr-x   - hbase users          0 2014-06-25 18:48 /hbase/corrupt
drwxr-xr-x   - hbase users          0 2014-06-25 18:58 /hbase/data
-rw-r--r--   3 hbase users         42 2014-06-25 18:41 /hbase/hbase.id
-rw-r--r--   3 hbase users          7 2014-06-25 18:41 /hbase/hbase.version
drwxr-xr-x   - hbase users          0 2014-06-25 21:49 /hbase/oldWALs

  5. Create a table and populate it with data.

    You can use the HBase Shell to create a table, populate it with data, scan and get values from it, using the same procedure as in shell exercises.

  6. Start and stop a backup HBase Master (HMaster) server.

    Running multiple HMaster instances on the same hardware does not make sense in a production environment, in the same way that running a pseudo-distributed cluster does not make sense for production. This step is offered for testing and learning purposes only.

    The HMaster server controls the HBase cluster. You can start up to 9 backup HMaster servers, which makes 10 total HMasters, counting the primary. To start a backup HMaster, use the local-master-backup.sh. For each backup master you want to start, add a parameter representing the port offset for that master. Each HMaster uses two ports (16000 and 16010 by default). The port offset is added to these ports, so using an offset of 2, the backup HMaster would use ports 16002 and 16012. The following command starts 3 backup servers using ports 16002/16012, 16003/16013, and 16005/16015.

    $ ./bin/local-master-backup.sh start 2 3 5

    To kill a backup master without killing the entire cluster, you need to find its process ID (PID). The PID is stored in a file with a name like /tmp/hbase-USER-X-master.pid. The only contents of the file is the PID. You can use the kill -9 command to kill that PID. The following command will kill the master with port offset 1, but leave the cluster running:

    $ cat /tmp/hbase-testuser-1-master.pid |xargs kill -9

  7. Start and stop additional RegionServers

    The HRegionServer manages the data in its StoreFiles as directed by the HMaster. Generally, one HRegionServer runs per node in the cluster. Running multiple HRegionServers on the same system can be useful for testing in pseudo-distributed mode. The local-regionservers.sh command allows you to run multiple RegionServers. It works in a similar way to the local-master-backup.sh command, in that each parameter you provide represents the port offset for an instance. Each RegionServer requires two ports, and the default ports are 16020 and 16030. Since HBase version 1.1.0, HMaster doesn’t use region server ports, this leaves 10 ports (16020 to 16029 and 16030 to 16039) to be used for RegionServers. For supporting additional RegionServers, set environment variables HBASE_RS_BASE_PORT and HBASE_RS_INFO_BASE_PORT to appropriate values before running script local-regionservers.sh. e.g. With values 16200 and 16300 for base ports, 99 additional RegionServers can be supported, on a server. The following command starts four additional RegionServers, running on sequential ports starting at 16022/16032 (base ports 16020/16030 plus 2).

    $ ./bin/local-regionservers.sh start 2 3 4 5

    To stop a RegionServer manually, use the local-regionservers.sh command with the stop parameter and the offset of the server to stop.

    $ ./bin/local-regionservers.sh stop 3

  8. Stop HBase.

    You can stop HBase the same way as in the quickstart procedure, using the bin/stop-hbase.sh command.

2.4. Fully Distributed for Production

In reality, you need a fully-distributed configuration to fully test HBase and to use it in real-world scenarios. In a distributed configuration, the cluster contains multiple nodes, each of which runs one or more HBase daemon. These include primary and backup Master instances, multiple ZooKeeper nodes, and multiple RegionServer nodes.

This advanced quickstart adds two more nodes to your cluster. The architecture will be as follows:

Table 1. Distributed Cluster Demo Architecture
Node Name Master ZooKeeper RegionServer

node-a.example.com

yes

yes

no

node-b.example.com

backup

yes

yes

node-c.example.com

no

yes

yes

This quickstart assumes that each node is a virtual machine and that they are all on the same network. It builds upon the previous quickstart, Pseudo-Distributed for Local Testing, assuming that the system you configured in that procedure is now node-a. Stop HBase on node-a before continuing.

Be sure that all the nodes have full access to communicate, and that no firewall rules are in place which could prevent them from talking to each other. If you see any errors like no route to host, check your firewall.
Procedure: Configure Passwordless SSH Access

node-a needs to be able to log into node-b and node-c (and to itself) in order to start the daemons. The easiest way to accomplish this is to use the same username on all hosts, and configure password-less SSH login from node-a to each of the others.

  1. On node-a, generate a key pair.

    While logged in as the user who will run HBase, generate a SSH key pair, using the following command:

    $ ssh-keygen -t rsa

    If the command succeeds, the location of the key pair is printed to standard output. The default name of the public key is id_rsa.pub.

  2. Create the directory that will hold the shared keys on the other nodes.

    On node-b and node-c, log in as the HBase user and create a .ssh/ directory in the user’s home directory, if it does not already exist. If it already exists, be aware that it may already contain other keys.

  3. Copy the public key to the other nodes.

    Securely copy the public key from node-a to each of the nodes, by using the scp or some other secure means. On each of the other nodes, create a new file called .ssh/authorized_keys if it does not already exist, and append the contents of the id_rsa.pub file to the end of it. Note that you also need to do this for node-a itself.

    $ cat id_rsa.pub >> ~/.ssh/authorized_keys

  4. Test password-less login.

    If you performed the procedure correctly, you should not be prompted for a password when you SSH from node-a to either of the other nodes using the same username.

  5. Since node-b will run a backup Master, repeat the procedure above, substituting node-b everywhere you see node-a. Be sure not to overwrite your existing .ssh/authorized_keys files, but concatenate the new key onto the existing file using the >> operator rather than the > operator.

Procedure: Prepare node-a

node-a will run your primary master and ZooKeeper processes, but no RegionServers. Stop the RegionServer from starting on node-a.

  1. Edit conf/regionservers and remove the line which contains localhost. Add lines with the hostnames or IP addresses for node-b and node-c.

    Even if you did want to run a RegionServer on node-a, you should refer to it by the hostname the other servers would use to communicate with it. In this case, that would be node-a.example.com. This enables you to distribute the configuration to each node of your cluster any hostname conflicts. Save the file.

  2. Configure HBase to use node-b as a backup master.

    Create a new file in conf/ called backup-masters, and add a new line to it with the hostname for node-b. In this demonstration, the hostname is node-b.example.com.

  3. Configure ZooKeeper

    In reality, you should carefully consider your ZooKeeper configuration. You can find out more about configuring ZooKeeper in zookeeper section. This configuration will direct HBase to start and manage a ZooKeeper instance on each node of the cluster.

    On node-a, edit conf/hbase-site.xml and add the following properties.

    <property>
  <name>hbase.zookeeper.quorum</name>
  <value>node-a.example.com,node-b.example.com,node-c.example.com</value>
</property>
<property>
  <name>hbase.zookeeper.property.dataDir</name>
  <value>/usr/local/zookeeper</value>
</property>

  4. Everywhere in your configuration that you have referred to node-a as localhost, change the reference to point to the hostname that the other nodes will use to refer to node-a. In these examples, the hostname is node-a.example.com.

Procedure: Prepare node-b and node-c

node-b will run a backup master server and a ZooKeeper instance.

  1. Download and unpack HBase.

    Download and unpack HBase to node-b, just as you did for the standalone and pseudo-distributed quickstarts.

  2. Copy the configuration files from node-a to node-b.and node-c.

    Each node of your cluster needs to have the same configuration information. Copy the contents of the conf/ directory to the conf/ directory on node-b and node-c.

Procedure: Start and Test Your Cluster

  1. Be sure HBase is not running on any node.

    If you forgot to stop HBase from previous testing, you will have errors. Check to see whether HBase is running on any of your nodes by using the jps command. Look for the processes HMaster, HRegionServer, and HQuorumPeer. If they exist, kill them.

  2. Start the cluster.

    On node-a, issue the start-hbase.sh command. Your output will be similar to that below.

    $ bin/start-hbase.sh
node-c.example.com: starting zookeeper, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-zookeeper-node-c.example.com.out
node-a.example.com: starting zookeeper, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-zookeeper-node-a.example.com.out
node-b.example.com: starting zookeeper, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-zookeeper-node-b.example.com.out
starting master, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-master-node-a.example.com.out
node-c.example.com: starting regionserver, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-regionserver-node-c.example.com.out
node-b.example.com: starting regionserver, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-regionserver-node-b.example.com.out
node-b.example.com: starting master, logging to /home/hbuser/hbase-0.98.3-hadoop2/bin/../logs/hbase-hbuser-master-nodeb.example.com.out

    ZooKeeper starts first, followed by the master, then the RegionServers, and finally the backup masters.

  3. Verify that the processes are running.

    On each node of the cluster, run the jps command and verify that the correct processes are running on each server. You may see additional Java processes running on your servers as well, if they are used for other purposes.

    node-a jps Output
    $ jps
20355 Jps
20071 HQuorumPeer
20137 HMaster
    node-b jps Output
    $ jps
15930 HRegionServer
16194 Jps
15838 HQuorumPeer
16010 HMaster
    node-c jps Output
    $ jps
13901 Jps
13639 HQuorumPeer
13737 HRegionServer
    ZooKeeper Process Name

    The HQuorumPeer process is a ZooKeeper instance which is controlled and started by HBase. If you use ZooKeeper this way, it is limited to one instance per cluster node and is appropriate for testing only. If ZooKeeper is run outside of HBase, the process is called QuorumPeer. For more about ZooKeeper configuration, including using an external ZooKeeper instance with HBase, see zookeeper section.

  4. Browse to the Web UI.

    If everything is set up correctly, you should be able to connect to the UI for the Master http://node-a.example.com:16010/ or the secondary master at http://node-b.example.com:16010/ using a web browser. If you can connect via localhost but not from another host, check your firewall rules. You can see the web UI for each of the RegionServers at port 16030 of their IP addresses, or by clicking their links in the web UI for the Master.

  5. Test what happens when nodes or services disappear.

    With a three-node cluster you have configured, things will not be very resilient. You can still test the behavior of the primary Master or a RegionServer by killing the associated processes and watching the logs.

2.5. Where to go next

The next chapter, configuration, gives more information about the different HBase run modes, system requirements for running HBase, and critical configuration areas for setting up a distributed HBase cluster.

Apache HBase Configuration

This chapter expands upon the Getting Started chapter to further explain configuration of Apache HBase. Please read this chapter carefully, especially the Basic Prerequisites to ensure that your HBase testing and deployment goes smoothly. Familiarize yourself with Support and Testing Expectations as well.

3. Configuration Files

Apache HBase uses the same configuration system as Apache Hadoop. All configuration files are located in the conf/ directory, which needs to be kept in sync for each node on your cluster.

HBase Configuration File Descriptions
backup-masters

Not present by default. A plain-text file which lists hosts on which the Master should start a backup Master process, one host per line.

hadoop-metrics2-hbase.properties

Used to connect HBase Hadoop’s Metrics2 framework. See the Hadoop Wiki entry for more information on Metrics2. Contains only commented-out examples by default.

hbase-env.cmd and hbase-env.sh

Script for Windows and Linux / Unix environments to set up the working environment for HBase, including the location of Java, Java options, and other environment variables. The file contains many commented-out examples to provide guidance.

hbase-policy.xml

The default policy configuration file used by RPC servers to make authorization decisions on client requests. Only used if HBase security is enabled.

hbase-site.xml

The main HBase configuration file. This file specifies configuration options which override HBase’s default configuration. You can view (but do not edit) the default configuration file at hbase-common/src/main/resources/hbase-default.xml. You can also view the entire effective configuration for your cluster (defaults and overrides) in the HBase Configuration tab of the HBase Web UI.

log4j2.properties

Configuration file for HBase logging via log4j2.

regionservers

A plain-text file containing a list of hosts which should run a RegionServer in your HBase cluster. By default, this file contains the single entry localhost. It should contain a list of hostnames or IP addresses, one per line, and should only contain localhost if each node in your cluster will run a RegionServer on its localhost interface.

Checking XML Validity

When you edit XML, it is a good idea to use an XML-aware editor to be sure that your syntax is correct and your XML is well-formed. You can also use the xmllint utility to check that your XML is well-formed. By default, xmllint re-flows and prints the XML to standard output. To check for well-formedness and only print output if errors exist, use the command xmllint -noout filename.xml.
Keep Configuration In Sync Across the Cluster

When running in distributed mode, after you make an edit to an HBase configuration, make sure you copy the contents of the conf/ directory to all nodes of the cluster. HBase will not do this for you. Use a configuration management tool for managing and copying the configuration files to your nodes. For most configurations, a restart is needed for servers to pick up changes. Dynamic configuration is an exception to this, to be described later below.

4. Basic Prerequisites

This section lists required services and some required system configuration.

Java

HBase runs on the Java Virtual Machine, thus all HBase deployments require a JVM runtime.

The following table summarizes the recommendations of the HBase community with respect to running on various Java versions. The symbol indicates a base level of testing and willingness to help diagnose and address issues you might run into; these are the expected deployment combinations. An entry of means that there may be challenges with this combination, and you should look for more information before deciding to pursue this as your deployment strategy. The means this combination does not work; either an older Java version is considered deprecated by the HBase community, or this combination is known to not work. For combinations of newer JDK with older HBase releases, it’s likely there are known compatibility issues that cannot be addressed under our compatibility guarantees, making the combination impossible. In some cases, specific guidance on limitations (e.g. whether compiling / unit tests work, specific operational issues, etc) are also noted. Assume any combination not listed here is considered .

Long-Term Support JDKs are Recommended

HBase recommends downstream users rely only on JDK releases that are marked as Long-Term Supported (LTS), either from the OpenJDK project or vendors. At the time of this writing, the following JDK releases are NOT LTS releases and are NOT tested or advocated for use by the Apache HBase community: JDK9, JDK10, JDK12, JDK13, and JDK14. Community discussion around this decision is recorded on HBASE-20264.
HotSpot vs. OpenJ9

At this time, all testing performed by the Apache HBase project runs on the HotSpot variant of the JVM. When selecting your JDK distribution, please take this into consideration.
Table 2. Java support by release line
HBase Version JDK 6 JDK 7 JDK 8 JDK 11 JDK 17

HBase 2.6

HBase 2.5

*

HBase 2.4

HBase 2.3

*

HBase 2.0-2.2

HBase 1.2+

HBase 1.0-1.1

HBase 0.98

HBase 0.94

A Note on JDK11/JDK17 *

Preliminary support for JDK11 is introduced with HBase 2.3.0, and for JDK17 is introduced with HBase 2.5.x. We will compile and run test suites with JDK11/17 in pre commit checks and nightly checks. We will mark the support as as long as we have run some ITs with the JDK version and also there are users in the community use the JDK version in real production clusters.

For JDK11/JDK17 support in HBase, please refer to HBASE-22972 and HBASE-26038

For JDK11/JDK17 support in Hadoop, which may also affect HBase, please refer to HADOOP-15338 and HADOOP-17177
You must set JAVA_HOME on each node of your cluster. hbase-env.sh provides a handy mechanism to do this.
Operating System Utilities
ssh

HBase uses the Secure Shell (ssh) command and utilities extensively to communicate between cluster nodes. Each server in the cluster must be running ssh so that the Hadoop and HBase daemons can be managed. You must be able to connect to all nodes via SSH, including the local node, from the Master as well as any backup Master, using a shared key rather than a password. You can see the basic methodology for such a set-up in Linux or Unix systems at "Procedure: Configure Passwordless SSH Access". If your cluster nodes use OS X, see the section, SSH: Setting up Remote Desktop and Enabling Self-Login on the Hadoop wiki.

DNS

HBase uses the local hostname to self-report its IP address.

NTP

The clocks on cluster nodes should be synchronized. A small amount of variation is acceptable, but larger amounts of skew can cause erratic and unexpected behavior. Time synchronization is one of the first things to check if you see unexplained problems in your cluster. It is recommended that you run a Network Time Protocol (NTP) service, or another time-synchronization mechanism on your cluster and that all nodes look to the same service for time synchronization. See the Basic NTP Configuration at The Linux Documentation Project (TLDP) to set up NTP.

Limits on Number of Files and Processes (ulimit)

Apache HBase is a database. It requires the ability to open a large number of files at once. Many Linux distributions limit the number of files a single user is allowed to open to 1024 (or 256 on older versions of OS X). You can check this limit on your servers by running the command ulimit -n when logged in as the user which runs HBase. See the Troubleshooting section for some of the problems you may experience if the limit is too low. You may also notice errors such as the following:

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

It is recommended to raise the ulimit to at least 10,000, but more likely 10,240, because the value is usually expressed in multiples of 1024. Each ColumnFamily has at least one StoreFile, and possibly more than six StoreFiles if the region is under load. The number of open files required depends upon the number of ColumnFamilies and the number of regions. The following is a rough formula for calculating the potential number of open files on a RegionServer.

Calculate the Potential Number of Open Files
(StoreFiles per ColumnFamily) x (regions per RegionServer)

For example, assuming that a schema had 3 ColumnFamilies per region with an average of 3 StoreFiles per ColumnFamily, and there are 100 regions per RegionServer, the JVM will open 3 * 3 * 100 = 900 file descriptors, not counting open JAR files, configuration files, and others. Opening a file does not take many resources, and the risk of allowing a user to open too many files is minimal.

Another related setting is the number of processes a user is allowed to run at once. In Linux and Unix, the number of processes is set using the ulimit -u command. This should not be confused with the nproc command, which controls the number of CPUs available to a given user. Under load, a ulimit -u that is too low can cause OutOfMemoryError exceptions.

Configuring the maximum number of file descriptors and processes for the user who is running the HBase process is an operating system configuration, rather than an HBase configuration. It is also important to be sure that the settings are changed for the user that actually runs HBase. To see which user started HBase, and that user’s ulimit configuration, look at the first line of the HBase log for that instance.

Example 1. ulimit Settings on Ubuntu

To configure ulimit settings on Ubuntu, edit /etc/security/limits.conf, which is a space-delimited file with four columns. Refer to the man page for limits.conf for details about the format of this file. In the following example, the first line sets both soft and hard limits for the number of open files (nofile) to 32768 for the operating system user with the username hadoop. The second line sets the number of processes to 32000 for the same user.

hadoop  -       nofile  32768
hadoop  -       nproc   32000

The settings are only applied if the Pluggable Authentication Module (PAM) environment is directed to use them. To configure PAM to use these limits, be sure that the /etc/pam.d/common-session file contains the following line:

session required  pam_limits.so
Linux Shell

All of the shell scripts that come with HBase rely on the GNU Bash shell.

Windows

Running production systems on Windows machines is not recommended.

4.1. Hadoop

The following table summarizes the versions of Hadoop supported with each version of HBase. Older versions not appearing in this table are considered unsupported and likely missing necessary features, while newer versions are untested but may be suitable.

Based on the version of HBase, you should select the most appropriate version of Hadoop. You can use Apache Hadoop, or a vendor’s distribution of Hadoop. No distinction is made here. See the Hadoop wiki for information about vendors of Hadoop.

Hadoop 3.x is recommended.

Comparing to Hadoop 1.x, Hadoop 2.x is faster and includes features, such as short-circuit reads (see Leveraging local data), which will help improve your HBase random read profile. Hadoop 2.x also includes important bug fixes that will improve your overall HBase experience. HBase does not support running with earlier versions of Hadoop. See the table below for requirements specific to different HBase versions.

Today, Hadoop 3.x is recommended as the last Hadoop 2.x release 2.10.2 was released years ago, and there is no release for Hadoop 2.x for a very long time, although the Hadoop community does not officially EOL Hadoop 2.x yet.

Use the following legend to interpret these tables:

  • = Tested to be fully-functional

  • = Known to not be fully-functional, or there are CVEs so we drop the support in newer minor releases

  • = Not tested, may/may-not function

Table 3. Hadoop version support matrix for active release lines
HBase-2.5.x HBase-2.6.x

Hadoop-2.10.[0-1]

Hadoop-2.10.2+

Hadoop-3.1.0

Hadoop-3.1.1+

Hadoop-3.2.[0-2]

Hadoop-3.2.3+

Hadoop-3.3.[0-1]

Hadoop-3.3.[2-4]

Hadoop-3.3.5+

Hadoop-3.4.0+

(2.5.11+)

(2.6.2+)
Table 4. Hadoop version support matrix for EOM 2.3+ release lines
HBase-2.3.x HBase-2.4.x

Hadoop-2.10.x

Hadoop-3.1.0

Hadoop-3.1.1+

Hadoop-3.2.x

Hadoop-3.3.x

Table 5. Hadoop version support matrix for EOM 2.x release lines
HBase-2.0.x HBase-2.1.x HBase-2.2.x

Hadoop-2.6.1+

Hadoop-2.7.[0-6]

Hadoop-2.7.7+

Hadoop-2.8.[0-2]

Hadoop-2.8.[3-4]

Hadoop-2.8.5+

Hadoop-2.9.[0-1]

Hadoop-2.9.2+

Hadoop-3.0.[0-2]

Hadoop-3.0.3+

Hadoop-3.1.0

Hadoop-3.1.1+

Table 6. Hadoop version support matrix for EOM 1.5+ release lines
HBase-1.5.x HBase-1.6.x HBase-1.7.x

Hadoop-2.7.7+

Hadoop-2.8.[0-4]

Hadoop-2.8.5+

Hadoop-2.9.[0-1]

Hadoop-2.9.2+

Hadoop-2.10.x

Table 7. Hadoop version support matrix for EOM 1.x release lines
HBase-1.0.x (Hadoop 1.x is NOT supported) HBase-1.1.x HBase-1.2.x HBase-1.3.x HBase-1.4.x

Hadoop-2.4.x

Hadoop-2.5.x

Hadoop-2.6.0

Hadoop-2.6.1+

Hadoop-2.7.0

Hadoop-2.7.1+

Table 8. Hadoop version support matrix for EOM pre-1.0 release lines
HBase-0.92.x HBase-0.94.x HBase-0.96.x HBase-0.98.x (Support for Hadoop 1.1+ is deprecated.)

Hadoop-0.20.205

Hadoop-0.22.x

Hadoop-1.0.x

Hadoop-1.1.x

Hadoop-0.23.x

Hadoop-2.0.x-alpha

Hadoop-2.1.0-beta

Hadoop-2.2.0

Hadoop-2.3.x

Hadoop-2.4.x

Hadoop-2.5.x

Hadoop 2.y.0 Releases

Starting around the time of Hadoop version 2.7.0, the Hadoop PMC got into the habit of calling out new minor releases on their major version 2 release line as not stable / production ready. As such, HBase expressly advises downstream users to avoid running on top of these releases. Note that additionally the 2.8.1 release was given the same caveat by the Hadoop PMC. For reference, see the release announcements for Apache Hadoop 2.7.0, Apache Hadoop 2.8.0, Apache Hadoop 2.8.1, and Apache Hadoop 2.9.0.
Hadoop 3.1.0 Release

The Hadoop PMC called out the 3.1.0 release as not stable / production ready. As such, HBase expressly advises downstream users to avoid running on top of this release. For reference, see the release announcement for Hadoop 3.1.0.
Replace the Hadoop Bundled With HBase!

Because HBase depends on Hadoop, it bundles Hadoop jars under its lib directory. The bundled jars are ONLY for use in stand-alone mode. In distributed mode, it is critical that the version of Hadoop that is out on your cluster match what is under HBase. Replace the hadoop jars found in the HBase lib directory with the equivalent hadoop jars from the version you are running on your cluster to avoid version mismatch issues. Make sure you replace the jars under HBase across your whole cluster. Hadoop version mismatch issues have various manifestations. Check for mismatch if HBase appears hung.

4.1.1. Hadoop 3 Support for the HBase Binary Releases and Maven Artifacts

For HBase 2.5.1 and earlier, the official HBase binary releases and Maven artifacts were built with Hadoop 2.x.

Starting with HBase 2.5.2, HBase provides binary releases and Maven artifacts built with both Hadoop 2.x and Hadoop 3.x. The Hadoop 2 artifacts do not have any version suffix, the Hadoop 3 artifacts add the -hadoop-3 suffix to the version. i.e. hbase-2.5.2-bin.tar.gz.asc is the Binary release built with Hadoop2, and hbase-2.5.2-hadoop3-bin.tar.gz is the release built with Hadoop 3.

4.1.2. Hadoop 3 version policy

Each HBase release has a default Hadoop 3 version. This is used when the Hadoop 3 version is not specified during build, and for building the official binary releases and artifacts. Generally when a new minor version is released (i.e. 2.5.0) the default version is set to the latest supported Hadoop 3 version at the start of the release process.

Up to HBase 2.5.10 and 2.6.1 even if HBase added support for newer Hadoop 3 releases in a patch release, the default Hadoop 3 version (and the one used in the official binary releases) was not updated. This simplified upgrading, but meant that HBase releases often included old unfixed CVEs both from Hadoop and Hadoop’s dependencies, even when newer Hadoop releases with fixes were available.

Starting with HBase 2.5.11 and 2.6.2, the default Hadoop 3 version is always set to the latest supported Hadoop 3 version, and is also used for the -hadoop3 binary releases and artifacts. This will drastically reduce the number of known CVEs shipped in the HBase binary releases, and make sure that all fixes and improvements in Hadoop are included.

4.1.3. dfs.datanode.max.transfer.threads

An HDFS DataNode has an upper bound on the number of files that it will serve at any one time. Before doing any loading, make sure you have configured Hadoop’s conf/hdfs-site.xml, setting the dfs.datanode.max.transfer.threads value to at least the following:

<property>
  <name>dfs.datanode.max.transfer.threads</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. One manifestation is a 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...

See also casestudies.max.transfer.threads and note that this property was previously known as dfs.datanode.max.xcievers (e.g. Hadoop HDFS: Deceived by Xciever).

4.2. ZooKeeper Requirements

An Apache ZooKeeper quorum is required. The exact version depends on your version of HBase, though the minimum ZooKeeper version is 3.4.x due to the useMulti feature made default in 1.0.0 (see HBASE-16598).

5. HBase run modes: Standalone and Distributed

HBase has two run modes: standalone and distributed. Out of the box, HBase runs in standalone mode. Whatever your mode, you will need to configure HBase by editing files in the HBase conf directory. At a minimum, you must 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.

5.1. Standalone HBase

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.

5.1.1. Standalone HBase over HDFS

A sometimes useful variation on standalone hbase has all daemons running inside the one JVM but rather than persist to the local filesystem, instead they persist to an HDFS instance.

You might consider this profile when you are intent on a simple deploy profile, the loading is light, but the data must persist across node comings and goings. Writing to HDFS where data is replicated ensures the latter.

To configure this standalone variant, edit your hbase-site.xml setting hbase.rootdir to point at a directory in your HDFS instance but then set hbase.cluster.distributed to false. For example:

<configuration>
  <property>
    <name>hbase.rootdir</name>
    <value>hdfs://namenode.example.org:9000/hbase</value>
  </property>
  <property>
    <name>hbase.cluster.distributed</name>
    <value>false</value>
  </property>
</configuration>

5.2. Distributed

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.

Pseudo-distributed mode can run against the local filesystem or it can run against an instance of the Hadoop Distributed File System (HDFS). Fully-distributed mode can ONLY run on HDFS. See the Hadoop documentation for how to set up HDFS. A good walk-through for setting up HDFS on Hadoop 2 can be found at https://web.archive.org/web/20221007121526/https://www.alexjf.net/blog/distributed-systems/hadoop-yarn-installation-definitive-guide/.

5.2.1. Pseudo-distributed

Pseudo-Distributed Quickstart

A quickstart has been added to the quickstart chapter. See quickstart-pseudo. Some of the information that was originally in this section has been moved there.

A pseudo-distributed mode is simply a fully-distributed mode run on a single host. Use this HBase configuration for testing and prototyping purposes only. Do not use this configuration for production or for performance evaluation.

5.3. Fully-distributed

By default, HBase runs in stand-alone mode. Both stand-alone mode and pseudo-distributed mode are provided for the purposes of small-scale testing. For a production environment, distributed mode is advised. In distributed mode, multiple instances of HBase daemons run on multiple servers in the cluster.

Just as in pseudo-distributed mode, a fully distributed configuration requires that you set the hbase.cluster.distributed property to true. Typically, the hbase.rootdir is configured to point to a highly-available HDFS filesystem.

In addition, the cluster is configured so that multiple cluster nodes enlist as RegionServers, ZooKeeper QuorumPeers, and backup HMaster servers. These configuration basics are all demonstrated in quickstart-fully-distributed.

Distributed RegionServers

Typically, your cluster will contain multiple RegionServers all running on different servers, as well as primary and backup Master and ZooKeeper daemons. The conf/regionservers file on the master server contains a list of hosts whose RegionServers are associated with this cluster. Each host is on a separate line. All hosts listed in this file will have their RegionServer processes started and stopped when the master server starts or stops.

ZooKeeper and HBase

See the ZooKeeper section for ZooKeeper setup instructions for HBase.

Example 2. Example Distributed HBase Cluster

This is a bare-bones conf/hbase-site.xml for a distributed HBase cluster. A cluster that is used for real-world work would contain more custom configuration parameters. Most HBase configuration directives have default values, which are used unless the value is overridden in the hbase-site.xml. See "Configuration Files" for more information.

<configuration>
  <property>
    <name>hbase.rootdir</name>
    <value>hdfs://namenode.example.org:9000/hbase</value>
  </property>
  <property>
    <name>hbase.cluster.distributed</name>
    <value>true</value>
  </property>
  <property>
    <name>hbase.zookeeper.quorum</name>
    <value>node-a.example.com,node-b.example.com,node-c.example.com</value>
  </property>
</configuration>

This is an example conf/regionservers file, which contains a list of nodes that should run a RegionServer in the cluster. These nodes need HBase installed and they need to use the same contents of the conf/ directory as the Master server.

node-a.example.com
node-b.example.com
node-c.example.com

This is an example conf/backup-masters file, which contains a list of each node that should run a backup Master instance. The backup Master instances will sit idle unless the main Master becomes unavailable.

node-b.example.com
node-c.example.com
Distributed HBase Quickstart

See quickstart-fully-distributed for a walk-through of a simple three-node cluster configuration with multiple ZooKeeper, backup HMaster, and RegionServer instances.

Procedure: HDFS Client Configuration

  1. Of note, if you have made HDFS client configuration changes on your Hadoop cluster, such as configuration directives for HDFS clients, as opposed to server-side configurations, you must use one of the following methods to enable HBase to see and use these configuration changes:

    1. Add a pointer to your HADOOP_CONF_DIR to the HBASE_CLASSPATH environment variable in hbase-env.sh.

    2. Add a copy of hdfs-site.xml (or hadoop-site.xml) or, better, symlinks, under ${HBASE_HOME}/conf, or

    3. 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.

5.4. Choosing between the Classic Package and the BYO Hadoop Package

Starting with HBase 3.0, HBase includes two binary packages. The classic package includes both the HBase and Hadoop components, while the Hadoop-less "Bring Your Own Hadoop" package omits the Hadoop components, and uses the files from an existing Hadoop installation. The classic binary package filename is named hbase-<version>-bin.tar.gz i.e. hbase-3.0.0-bin.tar.gz , while the Hadoop-less package is hbase-byo-hadoop-<version>-bin.tar.gz i.e. hbase-byo-hadoop-3.0.0-bin.tar.gz.

If the cluster nodes already have Hadoop installed, you can use the Hadoop-less package. In this case you need to make sure that the HADOOP_HOME environment variable is set and points to the Hadoop installation. The easiest way to ensure this is to set it in hbase-env.sh. You still need to make sure that the Hadoop configuration files are present on the HBase classpath, as described above.

Advantages of the BYO Hadoop package

  • There is no need to replace the Hadoop libraries, as noted above.

  • It is easier to upgrade Hadoop and HBase independently (as long as compatible versions are used).

  • Both the package and installed size are about 100 MB smaller.

6. Running and Confirming Your Installation

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 or YARN daemons. These do not need to be started.

If you are managing your own ZooKeeper, start it and confirm it’s 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 it’s deployed on the Master host at port 16010 (HBase RegionServers listen on port 16020 by default and put up an informational HTTP server at port 16030). If the Master is running on a host named master.example.org on the default port, point your browser at http://master.example.org:16010 to see the web interface.

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.

7. Default Configuration

7.1. hbase-site.xml and hbase-default.xml

Just as in Hadoop where you add site-specific HDFS configuration to the hdfs-site.xml file, for HBase, site specific customizations go into the file conf/hbase-site.xml. For the list of configurable properties, see hbase default configurations below or view the raw hbase-default.xml source file in the HBase source code at src/main/resources.

Not all configuration options make it out to hbase-default.xml. Some configurations would only appear in source code; the only way to identify these changes are through code review.

Currently, changes here will require a cluster restart for HBase to notice the change.

7.2. HBase Default Configuration

The documentation below is generated using the default hbase configuration file, hbase-default.xml, as source.

hbase.tmp.dir
Description

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.

Default

${java.io.tmpdir}/hbase-${user.name}

hbase.rootdir
Description

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.

Default

${hbase.tmp.dir}/hbase

hbase.cluster.distributed
Description

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.

Default

false

hbase.zookeeper.quorum
Description

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.property.clientPort config. and pass it into zookeeper constructor as the connectString parameter.

Default

127.0.0.1

zookeeper.recovery.retry.maxsleeptime
Description

Max sleep time before retry zookeeper operations in milliseconds, a max time is needed here so that sleep time won’t grow unboundedly

Default

60000

hbase.local.dir
Description

Directory on the local filesystem to be used as a local storage.

Default

${hbase.tmp.dir}/local/

hbase.master.port
Description

The port the HBase Master should bind to.

Default

16000

hbase.master.info.port
Description

The port for the HBase Master web UI. Set to -1 if you do not want a UI instance run.

Default

16010

hbase.master.info.bindAddress
Description

The bind address for the HBase Master web UI

Default

0.0.0.0

hbase.master.logcleaner.plugins
Description

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.

Default

org.apache.hadoop.hbase.master.cleaner.TimeToLiveLogCleaner,org.apache.hadoop.hbase.master.cleaner.TimeToLiveProcedureWALCleaner,org.apache.hadoop.hbase.master.cleaner.TimeToLiveMasterLocalStoreWALCleaner

hbase.master.logcleaner.ttl
Description

How long a WAL remain in the archive ({hbase.rootdir}/oldWALs) directory, after which it will be cleaned by a Master thread. The value is in milliseconds.

Default

600000

hbase.master.hfilecleaner.plugins
Description

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 hfile cleaners in the list as they will be overwritten in hbase-site.xml.

Default

org.apache.hadoop.hbase.master.cleaner.TimeToLiveHFileCleaner,org.apache.hadoop.hbase.master.cleaner.TimeToLiveMasterLocalStoreHFileCleaner

hbase.master.infoserver.redirect
Description

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. Config. makes sense when Master is serving Regions (not the default).

Default

true

hbase.master.fileSplitTimeout
Description

Splitting a region, how long to wait on the file-splitting step before aborting the attempt. Default: 600000. This setting used to be known as hbase.regionserver.fileSplitTimeout in hbase-1.x. Split is now run master-side hence the rename (If a 'hbase.master.fileSplitTimeout' setting found, will use it to prime the current 'hbase.master.fileSplitTimeout' Configuration.

Default

600000

hbase.regionserver.port
Description

The port the HBase RegionServer binds to.

Default

16020

hbase.regionserver.info.port
Description

The port for the HBase RegionServer web UI Set to -1 if you do not want the RegionServer UI to run.

Default

16030

hbase.regionserver.info.bindAddress
Description

The address for the HBase RegionServer web UI

Default

0.0.0.0

hbase.regionserver.info.port.auto
Description

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.

Default

false

hbase.regionserver.handler.count
Description

Count of RPC Listener instances spun up on RegionServers. Same property is used by the Master for count of master handlers. Too many handlers can be counter-productive. Make it a multiple of CPU count. If mostly read-only, handlers count close to cpu count does well. Start with twice the CPU count and tune from there.

Default

30

hbase.ipc.server.callqueue.handler.factor
Description

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.

Default

0.1

hbase.ipc.server.callqueue.read.ratio
Description

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.

Default

0

hbase.ipc.server.callqueue.scan.ratio
Description

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.

Default

0

hbase.regionserver.msginterval
Description

Interval between messages from the RegionServer to Master in milliseconds.

Default

3000

hbase.regionserver.logroll.period
Description

Period at which we will roll the commit log regardless of how many edits it has.

Default

3600000

hbase.regionserver.logroll.errors.tolerated
Description

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.

Default

2

hbase.regionserver.free.heap.min.memory.size
Description

Defines the minimum amount of heap memory that must remain free for the RegionServer to start, specified in bytes or human-readable formats like '512m' for megabytes or '4g' for gigabytes. If not set, the default is 20% of the total heap size. To disable the check entirely, set this value to 0. If the combined memory usage of memstore and block cache exceeds (total heap - this value), the RegionServer will fail to start.

Default

none

hbase.regionserver.global.memstore.size
Description

Maximum size of all memstores in a region server before new updates are blocked and flushes are forced. Defaults to 40% of heap (0.4). Updates are blocked and flushes are forced until size of all memstores in a region server hits hbase.regionserver.global.memstore.size.lower.limit. The default value in this configuration has been intentionally left empty in order to honor the old hbase.regionserver.global.memstore.upperLimit property if present.

Default

none

hbase.regionserver.global.memstore.size.lower.limit
Description

Maximum size of all memstores in a region server before flushes are forced. Defaults to 95% of hbase.regionserver.global.memstore.size (0.95). A 100% value for this value causes the minimum possible flushing to occur when updates are blocked due to memstore limiting. The default value in this configuration has been intentionally left empty in order to honor the old hbase.regionserver.global.memstore.lowerLimit property if present.

Default

none

hbase.systemtables.compacting.memstore.type
Description

Determines the type of memstore to be used for system tables like META, namespace tables etc. By default NONE is the type and hence we use the default memstore for all the system tables. If we need to use compacting memstore for system tables then set this property to BASIC/EAGER

Default

NONE

hbase.regionserver.optionalcacheflushinterval
Description

Maximum amount of time an edit lives in memory before being automatically flushed. Default 1 hour. Set it to 0 to disable automatic flushing.

Default

3600000

hbase.regionserver.dns.interface
Description

The name of the Network Interface from which a region server should report its IP address.

Default

default

hbase.regionserver.dns.nameserver
Description

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.

Default

default

hbase.regionserver.region.split.policy
Description

A split policy determines when a region should be split. The various other split policies that are available currently are BusyRegionSplitPolicy, ConstantSizeRegionSplitPolicy, DisabledRegionSplitPolicy, DelimitedKeyPrefixRegionSplitPolicy, KeyPrefixRegionSplitPolicy, and SteppingSplitPolicy. DisabledRegionSplitPolicy blocks manual region splitting.

Default

org.apache.hadoop.hbase.regionserver.SteppingSplitPolicy

hbase.regionserver.regionSplitLimit
Description

Limit for the number of regions after which no more region splitting should take place. This is not hard limit for the number of regions but acts as a guideline for the regionserver to stop splitting after a certain limit. Default is set to 1000.

Default

1000

zookeeper.session.timeout
Description

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 https://zookeeper.apache.org/doc/current/zookeeperProgrammers.html#ch_zkSessions. For example, if an 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 maxSessionTimeout that ZK ships with is 40 seconds, which is lower than HBase’s.

Default

90000

zookeeper.znode.parent
Description

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 paths are configured with a relative path, so they will all go under this directory unless changed.

Default

/hbase

zookeeper.znode.acl.parent
Description

Root ZNode for access control lists.

Default

acl

hbase.zookeeper.dns.interface
Description

The name of the Network Interface from which a ZooKeeper server should report its IP address.

Default

default

hbase.zookeeper.dns.nameserver
Description

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.

Default

default

hbase.zookeeper.peerport
Description

Port used by ZooKeeper peers to talk to each other. See https://zookeeper.apache.org/doc/r3.4.10/zookeeperStarted.html#sc_RunningReplicatedZooKeeper for more information.

Default

2888

hbase.zookeeper.leaderport
Description

Port used by ZooKeeper for leader election. See https://zookeeper.apache.org/doc/r3.4.10/zookeeperStarted.html#sc_RunningReplicatedZooKeeper for more information.

Default

3888

hbase.zookeeper.property.initLimit
Description

Property from ZooKeeper’s config zoo.cfg. The number of ticks that the initial synchronization phase can take.

Default

10

hbase.zookeeper.property.syncLimit
Description

Property from ZooKeeper’s config zoo.cfg. The number of ticks that can pass between sending a request and getting an acknowledgment.

Default

5

hbase.zookeeper.property.dataDir
Description

Property from ZooKeeper’s config zoo.cfg. The directory where the snapshot is stored.

Default

${hbase.tmp.dir}/zookeeper

hbase.zookeeper.property.clientPort
Description

Property from ZooKeeper’s config zoo.cfg. The port at which the clients will connect.

Default

2181

hbase.zookeeper.property.maxClientCnxns
Description

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.

Default

300

hbase.client.write.buffer
Description

Default size of the BufferedMutator 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

Default

2097152

hbase.client.pause
Description

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.

Default

100

hbase.client.pause.server.overloaded
Description

Pause time when encountering an exception indicating a server is overloaded, CallQueueTooBigException or CallDroppedException. Set this property to a higher value than hbase.client.pause if you observe frequent CallQueueTooBigException or CallDroppedException from the same RegionServer and the call queue there keeps filling up. This config used to be called hbase.client.pause.cqtbe, which has been deprecated as of 2.5.0.

Default

none

hbase.client.retries.number
Description

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.

Default

15

hbase.client.max.total.tasks
Description

The maximum number of concurrent mutation tasks a single HTable instance will send to the cluster.

Default

100

hbase.client.max.perserver.tasks
Description

The maximum number of concurrent mutation tasks a single HTable instance will send to a single region server.

Default

2

hbase.client.max.perregion.tasks
Description

The maximum number of concurrent mutation tasks 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.

Default

1

hbase.client.perserver.requests.threshold
Description

The max number of concurrent pending requests for one server in all client threads (process level). Exceeding requests will be thrown ServerTooBusyException immediately to prevent user’s threads being occupied and blocked by only one slow region server. If you use a fix number of threads to access HBase in a synchronous way, set this to a suitable value which is related to the number of threads will help you. See https://issues.apache.org/jira/browse/HBASE-16388 for details.

Default

2147483647

hbase.client.scanner.caching
Description

Number of rows that we try to fetch when calling next on a scanner if it is not served from (local, client) memory. This configuration works together with hbase.client.scanner.max.result.size to try and use the network efficiently. The default value is Integer.MAX_VALUE by default so that the network will fill the chunk size defined by hbase.client.scanner.max.result.size rather than be limited by a particular number of rows since the size of rows varies table to table. If you know ahead of time that you will not require more than a certain number of rows from a scan, this configuration should be set to that row limit via Scan#setCaching. 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

Default

2147483647

hbase.client.keyvalue.maxsize
Description

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.

Default

10485760

hbase.server.keyvalue.maxsize
Description

Maximum allowed size of an individual cell, inclusive of value and all key components. A value of 0 or less disables the check. The default value is 10MB. This is a safety setting to protect the server from OOM situations.

Default

10485760

hbase.client.scanner.timeout.period
Description

Client scanner lease period in milliseconds.

Default

60000

hbase.client.localityCheck.threadPoolSize
Default

2

hbase.bulkload.retries.number
Description

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.

Default

10

hbase.compaction.after.bulkload.enable
Description

Request Compaction after bulkload immediately. If bulkload is continuous, the triggered compactions may increase load, bring about performance side effect.

Default

false

hbase.master.balancer.maxRitPercent
Description

The max percent of regions in transition when balancing. The default value is 1.0. So there are no balancer throttling. If set this config to 0.01, It means that there are at most 1% regions in transition when balancing. Then the cluster’s availability is at least 99% when balancing.

Default

1.0

hbase.balancer.period
Description

Period at which the region balancer runs in the Master, in milliseconds.

Default

300000

hbase.master.oldwals.dir.updater.period
Description

Period at which the oldWALs directory size calculator/updater will run in the Master, in milliseconds.

Default

300000

hbase.regions.slop
Description

The load balancer can trigger for several reasons. This value controls one of those reasons. Run the balancer if any regionserver has a region count outside the range of average +/- (average * slop) regions. If the value of slop is negative, disable sloppiness checks. The balancer can still run for other reasons, but sloppiness will not be one of them. If the value of slop is 0, run the balancer if any server has a region count more than 1 from the average. If the value of slop is 100, run the balancer if any server has a region count greater than 101 times the average. The default value of this parameter is 0.2, which runs the balancer if any server has a region count less than 80% of the average, or greater than 120% of the average. Note that for the default StochasticLoadBalancer, this does not guarantee any balancing actions will be taken, but only that the balancer will attempt to run.

Default

0.2

hbase.normalizer.period
Description

Period at which the region normalizer runs in the Master, in milliseconds.

Default

300000

hbase.normalizer.split.enabled
Description

Whether to split a region as part of normalization.

Default

true

hbase.normalizer.merge.enabled
Description

Whether to merge a region as part of normalization.

Default

true

hbase.normalizer.merge.min.region.count
Description

The minimum number of regions in a table to consider it for merge normalization.

Default

3

hbase.normalizer.merge.min_region_age.days
Description

The minimum age for a region to be considered for a merge, in days.

Default

3

hbase.normalizer.merge.min_region_size.mb
Description

The minimum size for a region to be considered for a merge, in whole MBs.

Default

1

hbase.normalizer.merge.merge_request_max_number_of_regions
Description

The maximum number of region count in a merge request for merge normalization.

Default

100

hbase.table.normalization.enabled
Description

This config is used to set default behaviour of normalizer at table level. To override this at table level one can set NORMALIZATION_ENABLED at table descriptor level and that property will be honored

Default

false

hbase.server.thread.wakefrequency
Description

In master side, this config is the period used for FS related behaviors: checking if hdfs is out of safe mode, setting or checking hbase.version file, setting or checking hbase.id file. Using default value should be fine. In regionserver side, this config is used in several places: flushing check interval, compaction check interval, wal rolling check interval. Specially, admin can tune flushing and compaction check interval by hbase.regionserver.flush.check.period and hbase.regionserver.compaction.check.period. (in milliseconds)

Default

10000

hbase.regionserver.flush.check.period
Description

It determines the flushing check period of PeriodicFlusher in regionserver. If unset, it uses hbase.server.thread.wakefrequency as default value. (in milliseconds)

Default

${hbase.server.thread.wakefrequency}

hbase.regionserver.compaction.check.period
Description

It determines the compaction check period of CompactionChecker in regionserver. If unset, it uses hbase.server.thread.wakefrequency as default value. (in milliseconds)

Default

${hbase.server.thread.wakefrequency}

hbase.server.versionfile.writeattempts
Description

How many times to retry attempting to write a version file before just aborting. Each attempt is separated by the hbase.server.thread.wakefrequency milliseconds.

Default

3

hbase.hregion.memstore.flush.size
Description

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.

Default

134217728

hbase.hregion.percolumnfamilyflush.size.lower.bound.min
Description

If FlushLargeStoresPolicy is used and there are multiple column families, then every time that we hit the total memstore limit, we find out all the column families whose memstores exceed a "lower bound" and only flush them while retaining the others in memory. The "lower bound" will be "hbase.hregion.memstore.flush.size / column_family_number" by default unless value of this property is larger than that. If none of the families have their memstore size more than lower bound, all the memstores will be flushed (just as usual).

Default

16777216

hbase.hregion.preclose.flush.size
Description

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.

Default

5242880

hbase.hregion.memstore.block.multiplier
Description

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.

Default

4

hbase.hregion.memstore.mslab.enabled
Description

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.

Default

true

hbase.hregion.memstore.mslab.chunksize
Description

The maximum byte size of a chunk in the MemStoreLAB. Unit: bytes

Default

2097152

hbase.regionserver.offheap.global.memstore.size
Description

The amount of off-heap memory all MemStores in a RegionServer may use. A value of 0 means that no off-heap memory will be used and all chunks in MSLAB will be HeapByteBuffer, otherwise the non-zero value means how many megabyte of off-heap memory will be used for chunks in MSLAB and all chunks in MSLAB will be DirectByteBuffer. Unit: megabytes.

Default

0

hbase.hregion.memstore.mslab.max.allocation
Description

The maximal size of one allocation in the MemStoreLAB, if the desired byte size exceed this threshold then it will be just allocated from JVM heap rather than MemStoreLAB.

Default

262144

hbase.hregion.max.filesize
Description

Maximum file size. If the sum of the sizes of a region’s HFiles has grown to exceed this value, the region is split in two. There are two choices of how this option works, the first is when any store’s size exceed the threshold then split, and the other is overall region’s size exceed the threshold then split, it can be configed by hbase.hregion.split.overallfiles.

Default

10737418240

hbase.hregion.split.overallfiles
Description

If we should sum overall region files size when check to split.

Default

true

hbase.hregion.majorcompaction
Description

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.

Default

604800000

hbase.hregion.majorcompaction.jitter
Description

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.

Default

0.50

hbase.hstore.compactionThreshold
Description

If more than or equal to 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.

Default

3

hbase.regionserver.compaction.enabled
Description

Enable/disable compactions on by setting true/false. We can further switch compactions dynamically with the compaction_switch shell command.

Default

true

hbase.hstore.flusher.count
Description

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.

Default

2

hbase.hstore.blockingStoreFiles
Description

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.

Default

16

hbase.hstore.blockingWaitTime
Description

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.

Default

90000

hbase.hstore.compaction.min
Description

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 (empty value here, results in 3 by code logic). In previous versions of HBase, the parameter hbase.hstore.compaction.min was named hbase.hstore.compactionThreshold.

Default

none

hbase.hstore.compaction.max
Description

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.

Default

10

hbase.hstore.compaction.min.size
Description

A StoreFile (or a selection of StoreFiles, when using ExploringCompactionPolicy) 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.

Default

134217728

hbase.hstore.compaction.max.size
Description

A StoreFile (or a selection of StoreFiles, when using ExploringCompactionPolicy) 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.

Default

9223372036854775807

hbase.hstore.compaction.ratio
Description

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.

Default

1.2F

hbase.hstore.compaction.ratio.offpeak
Description

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.

Default

5.0F

hbase.hstore.time.to.purge.deletes
Description

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.

Default

0

hbase.offpeak.start.hour
Description

The start of off-peak hours, expressed as an integer between 0 and 23, inclusive. Set to -1 to disable off-peak.

Default

-1

hbase.offpeak.end.hour
Description

The end of off-peak hours, expressed as an integer between 0 and 23, inclusive. Set to -1 to disable off-peak.

Default

-1

hbase.regionserver.thread.compaction.throttle
Description

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.

Default

2684354560

hbase.regionserver.majorcompaction.pagecache.drop
Description

Specifies whether to drop pages read/written into the system page cache by major compactions. Setting it to true helps prevent major compactions from polluting the page cache, which is almost always required, especially for clusters with low/moderate memory to storage ratio.

Default

true

hbase.regionserver.minorcompaction.pagecache.drop
Description

Specifies whether to drop pages read/written into the system page cache by minor compactions. Setting it to true helps prevent minor compactions from polluting the page cache, which is most beneficial on clusters with low memory to storage ratio or very write heavy clusters. You may want to set it to false under moderate to low write workload when bulk of the reads are on the most recently written data.

Default

true

hbase.hstore.compaction.kv.max
Description

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.

Default

10

hbase.storescanner.parallel.seek.enable
Description

Enables StoreFileScanner parallel-seeking in StoreScanner, a feature which can reduce response latency under special conditions.

Default

false

hbase.storescanner.parallel.seek.threads
Description

The default thread pool size if parallel-seeking feature enabled.

Default

10

hfile.block.cache.policy
Description

The eviction policy for the L1 block cache (LRU or TinyLFU).

Default

LRU

hfile.block.cache.size
Description

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.

Default

0.4

hfile.block.cache.memory.size
Description

Defines the maximum heap memory allocated for the HFile block cache, specified in bytes or human-readable formats like '10m' for megabytes or '10g' for gigabytes. This configuration allows setting an absolute memory size instead of a percentage of the maximum heap. Takes precedence over hfile.block.cache.size if both are specified.

Default

none

hfile.block.index.cacheonwrite
Description

This allows to put non-root multi-level index blocks into the block cache at the time the index is being written.

Default

false

hfile.index.block.max.size
Description

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.

Default

131072

hbase.bucketcache.ioengine
Description

Where to store the contents of the bucketcache. One of: offheap, file, files, mmap or pmem. If a file or files, set it to file(s):PATH_TO_FILE. mmap means the content will be in an mmaped file. Use mmap:PATH_TO_FILE. 'pmem' is bucket cache over a file on the persistent memory device. Use pmem:PATH_TO_FILE. See http://hbase.apache.org/book.html#offheap.blockcache for more information.

Default

none

hbase.hstore.compaction.throughput.lower.bound
Description

The target lower bound on aggregate compaction throughput, in bytes/sec. Allows you to tune the minimum available compaction throughput when the PressureAwareCompactionThroughputController throughput controller is active. (It is active by default.)

Default

52428800

hbase.hstore.compaction.throughput.higher.bound
Description

The target upper bound on aggregate compaction throughput, in bytes/sec. Allows you to control aggregate compaction throughput demand when the PressureAwareCompactionThroughputController throughput controller is active. (It is active by default.) The maximum throughput will be tuned between the lower and upper bounds when compaction pressure is within the range [0.0, 1.0]. If compaction pressure is 1.0 or greater the higher bound will be ignored until pressure returns to the normal range.

Default

104857600

hbase.bucketcache.size
Description

It is the total capacity in megabytes of BucketCache. Default: 0.0

Default

none

hbase.bucketcache.bucket.sizes
Description

A comma-separated list of sizes for buckets for the bucketcache. Can be multiple sizes. List block sizes in order from smallest to largest. The sizes you use will depend on your data access patterns. Must be a multiple of 256 else you will run into 'java.io.IOException: Invalid HFile block magic' when you go to read from cache. If you specify no values here, then you pick up the default bucketsizes set in code (See BucketAllocator#DEFAULT_BUCKET_SIZES).

Default

none

hfile.format.version
Description

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). Also see the configuration 'hbase.replication.rpc.codec'.

Default

3

hfile.block.bloom.cacheonwrite
Description

Enables cache-on-write for inline blocks of a compound Bloom filter.

Default

false

io.storefile.bloom.block.size
Description

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.

Default

131072

hbase.rs.cacheblocksonwrite
Description

Whether an HFile block should be added to the block cache when the block is finished.

Default

false

hbase.rpc.timeout
Description

This is for the RPC layer to define how long (millisecond) HBase client applications take for a remote call to time out. It uses pings to check connections but will eventually throw a TimeoutException.

Default

60000

hbase.client.operation.timeout
Description

Operation timeout is a top-level restriction (millisecond) that makes sure a blocking operation in Table will not be blocked more than this. In each operation, if rpc request fails because of timeout or other reason, it will retry until success or throw RetriesExhaustedException. But if the total time being blocking reach the operation timeout before retries exhausted, it will break early and throw SocketTimeoutException.

Default

1200000

hbase.client.connection.metacache.invalidate-interval.ms
Description

Interval in milliseconds of checking and invalidating meta cache when table disabled or dropped, when set to zero means disable checking, suggest set it to 24h or a higher value, because disable/delete table usually not very frequently.

Default

0

hbase.cells.scanned.per.heartbeat.check
Description

The number of cells scanned in between heartbeat checks. Heartbeat checks occur during the processing of scans to determine whether or not the server should stop scanning in order to send back a heartbeat message to the client. Heartbeat messages are used to keep the client-server connection alive during long running scans. Small values mean that the heartbeat checks will occur more often and thus will provide a tighter bound on the execution time of the scan. Larger values mean that the heartbeat checks occur less frequently

Default

10000

hbase.rpc.shortoperation.timeout
Description

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.

Default

10000

hbase.unsafe.regionserver.hostname
Description

This config is for experts: don’t set its value unless you really know what you are doing. When set to a non-empty value, this represents the (external facing) hostname for the underlying server. See https://issues.apache.org/jira/browse/HBASE-12954 for details.

Default

none

hbase.unsafe.regionserver.hostname.disable.master.reversedns
Description

This config is for experts: don’t set its value unless you really know what you are doing. When set to true, regionserver will use the current node hostname for the servername and HMaster will skip reverse DNS lookup and use the hostname sent by regionserver instead. Note that this config and hbase.unsafe.regionserver.hostname are mutually exclusive. See https://issues.apache.org/jira/browse/HBASE-18226 for more details.

Default

false

hbase.master.keytab.file
Description

Full path to the kerberos keytab file to use for logging in the configured HMaster server principal.

Default

none

hbase.master.kerberos.principal
Description

Ex. "hbase/[email protected]". 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.

Default

none

hbase.regionserver.keytab.file
Description

Full path to the kerberos keytab file to use for logging in the configured HRegionServer server principal.

Default

none

hbase.regionserver.kerberos.principal
Description

Ex. "hbase/[email protected]". 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

Default

none

hadoop.policy.file
Description

The policy configuration file used by RPC servers to make authorization decisions on client requests. Only used when HBase security is enabled.

Default

hbase-policy.xml

hbase.superuser
Description

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. Group names should be prefixed with "@".

Default

none

hbase.auth.key.update.interval
Description

The update interval for master key for authentication tokens in servers in milliseconds. Only used when HBase security is enabled.

Default

86400000

hbase.auth.token.max.lifetime
Description

The maximum lifetime in milliseconds after which an authentication token expires. Only used when HBase security is enabled.

Default

604800000

hbase.ipc.client.fallback-to-simple-auth-allowed
Description

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.

Default

false

hbase.ipc.server.fallback-to-simple-auth-allowed
Description

When a server is configured to require secure connections, it will reject connection attempts from clients using SASL SIMPLE (unsecure) authentication. This setting allows secure servers to accept SASL SIMPLE connections from clients when the client requests. When false (the default), the server will not allow the fallback to SIMPLE authentication, and will reject the connection. WARNING: This setting should ONLY be used as a temporary measure while converting clients over to secure authentication. It MUST BE DISABLED for secure operation.

Default

false

hbase.unsafe.client.kerberos.hostname.disable.reversedns
Description

This config is for experts: don’t set its value unless you really know what you are doing. When set to true, HBase client using SASL Kerberos will skip reverse DNS lookup and use provided hostname of the destination for the principal instead. See https://issues.apache.org/jira/browse/HBASE-25665 for more details.

Default

false

hbase.display.keys
Description

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.

Default

true

hbase.coprocessor.enabled
Description

Enables or disables coprocessor loading. If 'false' (disabled), any other coprocessor related configuration will be ignored.

Default

true

hbase.coprocessor.user.enabled
Description

Enables or disables user (aka. table) coprocessor loading. If 'false' (disabled), any table coprocessor attributes in table descriptors will be ignored. If "hbase.coprocessor.enabled" is 'false' this setting has no effect.

Default

true

hbase.coprocessor.region.classes
Description

A comma-separated list of region observer or endpoint 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, add it to HBase’s classpath and add the fully qualified class name here. A coprocessor can also be loaded on demand by setting HTableDescriptor or the HBase shell.

Default

none

hbase.coprocessor.master.classes
Description

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.

Default

none

hbase.coprocessor.abortonerror
Description

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.

Default

true

hbase.rest.port
Description

The port for the HBase REST server.

Default

8080

hbase.rest.readonly
Description

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.

Default

false

hbase.rest.threads.max
Description

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.

Default

100

hbase.rest.threads.min
Description

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.

Default

2

hbase.rest.support.proxyuser
Description

Enables running the REST server to support proxy-user mode.

Default

false

hbase.defaults.for.version.skip
Description

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 RuntimeException complaint: "hbase-default.xml file seems to be for and old version of HBase (\${hbase.version}), this version is X.X.X-SNAPSHOT"

Default

false

hbase.table.lock.enable
Description

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.

Default

true

hbase.table.max.rowsize
Description

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.

Default

1073741824

hbase.thrift.minWorkerThreads
Description

The "core size" of the thread pool. New threads are created on every connection until this many threads are created.

Default

16

hbase.thrift.maxWorkerThreads
Description

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.

Default

1000

hbase.thrift.maxQueuedRequests
Description

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.

Default

1000

hbase.regionserver.thrift.framed
Description

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.

Default

false

hbase.regionserver.thrift.framed.max_frame_size_in_mb
Description

Default frame size when using framed transport, in MB

Default

2

hbase.regionserver.thrift.compact
Description

Use Thrift TCompactProtocol binary serialization protocol.

Default

false

hbase.rootdir.perms
Description

FS Permissions for the root data subdirectory in a secure (kerberos) setup. When master starts, it creates the rootdir with this permissions or sets the permissions if it does not match.

Default

700

hbase.wal.dir.perms
Description

FS Permissions for the root WAL directory in a secure(kerberos) setup. When master starts, it creates the WAL dir with this permissions or sets the permissions if it does not match.

Default

700

hbase.data.umask.enable
Description

Enable, if true, that file permissions should be assigned to the files written by the regionserver

Default

false

hbase.data.umask
Description

File permissions that should be used to write data files when hbase.data.umask.enable is true

Default

000

hbase.snapshot.enabled
Description

Set to true to allow snapshots to be taken / restored / cloned.

Default

true

hbase.snapshot.restore.take.failsafe.snapshot
Description

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

Default

true

hbase.snapshot.restore.failsafe.name
Description

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.

Default

hbase-failsafe-{snapshot.name}-{restore.timestamp}

hbase.snapshot.working.dir
Description

Location where the snapshotting process will occur. The location of the completed snapshots will not change, but the temporary directory where the snapshot process occurs will be set to this location. This can be a separate filesystem than the root directory, for performance increase purposes. See HBASE-21098 for more information

Default

none

hbase.server.compactchecker.interval.multiplier
Description

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.

Default

1000

hbase.lease.recovery.timeout
Description

How long we wait on dfs lease recovery in total before giving up.

Default

900000

hbase.lease.recovery.dfs.timeout
Description

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.

Default

64000

hbase.column.max.version
Description

New column family descriptors will use this value as the default number of versions to keep.

Default

1

dfs.client.read.shortcircuit
Description

If set to true, this configuration parameter enables short-circuit local reads.

Default

none

dfs.domain.socket.path
Description

This is a path to a UNIX domain socket that will be used for communication between the DataNode and local HDFS clients, if dfs.client.read.shortcircuit is set to true. If the string "_PORT" is present in this path, it will be replaced by the TCP port of the DataNode. Be careful about permissions for the directory that hosts the shared domain socket; dfsclient will complain if open to other users than the HBase user.

Default

none

hbase.dfs.client.read.shortcircuit.buffer.size
Description

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 > the default hbase block size set in the HColumnDescriptor which is usually 64k.

Default

131072

hbase.regionserver.checksum.verify
Description

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.

Default

true

hbase.hstore.bytes.per.checksum
Description

Number of bytes in a newly created checksum chunk for HBase-level checksums in hfile blocks.

Default

16384

hbase.hstore.checksum.algorithm
Description

Name of an algorithm that is used to compute checksums. Possible values are NULL, CRC32, CRC32C.

Default

CRC32C

hbase.client.scanner.max.result.size
Description

Maximum number of bytes returned when calling a scanner’s next method. Note that when a single row is larger than this limit the row is still returned completely. The default value is 2MB, which is good for 1ge networks. With faster and/or high latency networks this value should be increased.

Default

2097152

hbase.server.scanner.max.result.size
Description

Maximum number of bytes returned when calling a scanner’s next method. Note that when a single row is larger than this limit the row is still returned completely. The default value is 100MB. This is a safety setting to protect the server from OOM situations.

Default

104857600

hbase.status.published
Description

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.

Default

false

hbase.status.publisher.class
Description

Implementation of the status publication with a multicast message.

Default

org.apache.hadoop.hbase.master.ClusterStatusPublisher$MulticastPublisher

hbase.status.listener.class
Description

Implementation of the status listener with a multicast message.

Default

org.apache.hadoop.hbase.client.ClusterStatusListener$MulticastListener

hbase.status.multicast.address.ip
Description

Multicast address to use for the status publication by multicast.

Default

226.1.1.3

hbase.status.multicast.address.port
Description

Multicast port to use for the status publication by multicast.

Default

16100

hbase.dynamic.jars.dir
Description

The directory from which the custom filter 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. Does not apply to coprocessors.

Default

${hbase.rootdir}/lib

hbase.security.authentication
Description

Controls whether or not secure authentication is enabled for HBase. Possible values are 'simple' (no authentication), and 'kerberos'.

Default

simple

hbase.rest.filter.classes
Description

Servlet filters for REST service.

Default

org.apache.hadoop.hbase.rest.filter.GzipFilter

hbase.master.loadbalancer.class
Description

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).

Default

org.apache.hadoop.hbase.master.balancer.StochasticLoadBalancer

hbase.master.loadbalance.bytable
Description

Factor Table name when the balancer runs. Default: false.

Default

false

hbase.master.normalizer.class
Description

Class used to execute the region normalization when the period occurs. See the class comment for more on how it works http://hbase.apache.org/devapidocs/org/apache/hadoop/hbase/master/normalizer/SimpleRegionNormalizer.html

Default

org.apache.hadoop.hbase.master.normalizer.SimpleRegionNormalizer

hbase.rest.csrf.enabled
Description

Set to true to enable protection against cross-site request forgery (CSRF)

Default

false

hbase.rest-csrf.browser-useragents-regex
Description

A comma-separated list of regular expressions used to match against an HTTP request’s User-Agent header when protection against cross-site request forgery (CSRF) is enabled for REST server by setting hbase.rest.csrf.enabled to true. If the incoming User-Agent matches any of these regular expressions, then the request is considered to be sent by a browser, and therefore CSRF prevention is enforced. If the request’s User-Agent does not match any of these regular expressions, then the request is considered to be sent by something other than a browser, such as scripted automation. In this case, CSRF is not a potential attack vector, so the prevention is not enforced. This helps achieve backwards-compatibility with existing automation that has not been updated to send the CSRF prevention header.

Default

Mozilla.,Opera.

hbase.security.exec.permission.checks
Description

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.

Default

false

hbase.procedure.regionserver.classes
Description

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.

Default

none

hbase.procedure.master.classes
Description

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.

Default

none

hbase.coordinated.state.manager.class
Description

Fully qualified name of class implementing coordinated state manager.

Default

org.apache.hadoop.hbase.coordination.ZkCoordinatedStateManager

hbase.regionserver.storefile.refresh.period
Description

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.

Default

0

hbase.region.replica.replication.enabled
Description

Whether asynchronous WAL replication to the secondary region replicas is enabled or not. We have a separated implementation for replicating the WAL without using the general inter-cluster replication framework, so now we will not add any replication peers.

Default

false

hbase.http.filter.initializers
Description

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.

Default

org.apache.hadoop.hbase.http.lib.StaticUserWebFilter

hbase.security.visibility.mutations.checkauths
Description

This property if enabled, will check whether the labels in the visibility expression are associated with the user issuing the mutation

Default

false

hbase.http.max.threads
Description

The maximum number of threads that the HTTP Server will create in its ThreadPool.

Default

16

hbase.http.metrics.servlets
Description

Comma separated list of servlet names to enable for metrics collection. Supported servlets are jmx, metrics, prometheus

Default

jmx,metrics,prometheus

hbase.replication.rpc.codec
Description

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.

Default

org.apache.hadoop.hbase.codec.KeyValueCodecWithTags

hbase.replication.source.maxthreads
Description

The maximum number of threads any replication source will use for shipping edits to the sinks in parallel. This also limits the number of chunks each replication batch is broken into. Larger values can improve the replication throughput between the master and slave clusters. The default of 10 will rarely need to be changed.

Default

10

hbase.http.staticuser.user
Description

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).

Default

dr.stack

hbase.regionserver.handler.abort.on.error.percent
Description

The percent of region server RPC threads failed to abort RS. -1 Disable aborting; 0 Abort if even a single handler has died; 0.x Abort only when this percent of handlers have died; 1 Abort only all of the handers have died.

Default

0.5

hbase.mob.file.cache.size
Description

Number of opened file handlers to cache. A larger value will benefit reads by providing more file handlers per mob file cache and would reduce frequent file opening and closing. However, if this is set too high, this could lead to a "too many opened file handlers" The default value is 1000.

Default

1000

hbase.mob.cache.evict.period
Description

The amount of time in seconds before the mob cache evicts cached mob files. The default value is 3600 seconds.

Default

3600

hbase.mob.cache.evict.remain.ratio
Description

The ratio (between 0.0 and 1.0) of files that remains cached after an eviction is triggered when the number of cached mob files exceeds the hbase.mob.file.cache.size. The default value is 0.5f.

Default

0.5f

hbase.master.mob.cleaner.period
Description

The period that MobFileCleanerChore runs. The unit is second. The default value is one day. The MOB file name uses only the date part of the file creation time in it. We use this time for deciding TTL expiry of the files. So the removal of TTL expired files might be delayed. The max delay might be 24 hrs.

Default

86400

hbase.mob.major.compaction.region.batch.size
Description

The max number of a MOB table regions that is allowed in a batch of the mob compaction. By setting this number to a custom value, users can control the overall effect of a major compaction of a large MOB-enabled table. Default is 0 - means no limit - all regions of a MOB table will be compacted at once

Default

0

hbase.mob.compaction.chore.period
Description

The period that MobCompactionChore runs. The unit is second. The default value is one week.

Default

604800

hbase.snapshot.master.timeout.millis
Description

Timeout for master for the snapshot procedure execution.

Default

300000

hbase.snapshot.region.timeout
Description

Timeout for regionservers to keep threads in snapshot request pool waiting.

Default

300000

hbase.rpc.rows.warning.threshold
Description

Number of rows in a batch operation above which a warning will be logged. If hbase.client.write.buffer.maxmutations is not set, this will be used as fallback for that setting.

Default

5000

hbase.master.wait.on.service.seconds
Description

Default is 5 minutes. Make it 30 seconds for tests. See HBASE-19794 for some context.

Default

30

hbase.master.cleaner.snapshot.interval
Description

Snapshot Cleanup chore interval in milliseconds. The cleanup thread keeps running at this interval to find all snapshots that are expired based on TTL and delete them.

Default

1800000

hbase.master.snapshot.ttl
Description

Default Snapshot TTL to be considered when the user does not specify TTL while creating snapshot. Default value 0 indicates FOREVERE - snapshot should not be automatically deleted until it is manually deleted

Default

0

hbase.master.regions.recovery.check.interval
Description

Regions Recovery Chore interval in milliseconds. This chore keeps running at this interval to find all regions with configurable max store file ref count and reopens them.

Default

1200000

hbase.regions.recovery.store.file.ref.count
Description

Very large number of ref count on a compacted store file indicates that it is a ref leak on that object(compacted store file). Such files can not be removed after it is invalidated via compaction. Only way to recover in such scenario is to reopen the region which can release all resources, like the refcount, leases, etc. This config represents Store files Ref Count threshold value considered for reopening regions. Any region with compacted store files ref count > this value would be eligible for reopening by master. Here, we get the max refCount among all refCounts on all compacted away store files that belong to a particular region. Default value -1 indicates this feature is turned off. Only positive integer value should be provided to enable this feature.

Default

-1

hbase.regionserver.slowlog.ringbuffer.size
Description

Default size of ringbuffer to be maintained by each RegionServer in order to store online slowlog responses. This is an in-memory ring buffer of requests that were judged to be too slow in addition to the responseTooSlow logging. The in-memory representation would be complete. For more details, please look into Doc Section: Get Slow Response Log from shell

Default

256

hbase.regionserver.slowlog.buffer.enabled
Description

Indicates whether RegionServers have ring buffer running for storing Online Slow logs in FIFO manner with limited entries. The size of the ring buffer is indicated by config: hbase.regionserver.slowlog.ringbuffer.size The default value is false, turn this on and get latest slowlog responses with complete data.

Default

false

hbase.regionserver.slowlog.systable.enabled
Description

Should be enabled only if hbase.regionserver.slowlog.buffer.enabled is enabled. If enabled (true), all slow/large RPC logs would be persisted to system table hbase:slowlog (in addition to in-memory ring buffer at each RegionServer). The records are stored in increasing order of time. Operators can scan the table with various combination of ColumnValueFilter. More details are provided in the doc section: "Get Slow/Large Response Logs from System table hbase:slowlog"

Default

false

hbase.master.metafixer.max.merge.count
Description

Maximum regions to merge at a time when we fix overlaps noted in CJ consistency report, but avoid merging 100 regions in one go!

Default

64

hbase.rpc.rows.size.threshold.reject
Description

If value is true, RegionServer will abort batch requests of Put/Delete with number of rows in a batch operation exceeding threshold defined by value of config: hbase.rpc.rows.warning.threshold. The default value is false and hence, by default, only warning will be logged. This config should be turned on to prevent RegionServer from serving very large batch size of rows and this way we can improve CPU usages by discarding too large batch request.

Default

false

hbase.namedqueue.provider.classes
Description

Default values for NamedQueueService implementors. This comma separated full class names represent all implementors of NamedQueueService that we would like to be invoked by LogEvent handler service. One example of NamedQueue service is SlowLogQueueService which is used to store slow/large RPC logs in ringbuffer at each RegionServer. All implementors of NamedQueueService should be found under package: "org.apache.hadoop.hbase.namequeues.impl"

Default

org.apache.hadoop.hbase.namequeues.impl.SlowLogQueueService,org.apache.hadoop.hbase.namequeues.impl.BalancerDecisionQueueService,org.apache.hadoop.hbase.namequeues.impl.BalancerRejectionQueueService,org.apache.hadoop.hbase.namequeues.WALEventTrackerQueueService

hbase.master.balancer.decision.buffer.enabled
Description

Indicates whether active HMaster has ring buffer running for storing balancer decisions in FIFO manner with limited entries. The size of the ring buffer is indicated by config: hbase.master.balancer.decision.queue.size

Default

false

hbase.master.balancer.rejection.buffer.enabled
Description

Indicates whether active HMaster has ring buffer running for storing balancer rejection in FIFO manner with limited entries. The size of the ring buffer is indicated by config: hbase.master.balancer.rejection.queue.size

Default

false

hbase.locality.inputstream.derive.enabled
Description

If true, derive StoreFile locality metrics from the underlying DFSInputStream backing reads for that StoreFile. This value will update as the DFSInputStream’s block locations are updated over time. Otherwise, locality is computed on StoreFile open, and cached until the StoreFile is closed.

Default

false

hbase.locality.inputstream.derive.cache.period
Description

If deriving StoreFile locality metrics from the underlying DFSInputStream, how long should the derived values be cached for. The derivation process may involve hitting the namenode, if the DFSInputStream’s block list is incomplete.

Default

60000

7.3. hbase-env.sh

Set HBase environment variables in this file. Examples include options to pass the JVM on start of an HBase daemon such as heap size and garbage collector configs. You can also set configurations for HBase configuration, log directories, niceness, ssh options, where to locate process pid files, etc. Open the file at conf/hbase-env.sh and peruse its content. Each option is fairly well documented. Add your own environment variables here if you want them read by HBase daemons on startup.

Changes here will require a cluster restart for HBase to notice the change.

7.4. log4j2.properties

Since version 2.5.0, HBase has upgraded to Log4j2, so the configuration file name and format has changed. Read more in Apache Log4j2.

Edit this file to change rate at which HBase files are rolled and to change the level at which HBase logs messages.

Changes here will require a cluster restart for HBase to notice the change though log levels can be changed for particular daemons via the HBase UI.

7.5. Client configuration and dependencies connecting to an HBase cluster

If you are running HBase in standalone mode, you don’t need to configure anything for your client to work provided that they are all on the same machine.

Starting release 3.0.0, the default connection registry has been switched to a rpc based implementation. Refer to Rpc Connection Registry (new as of 2.5.0) for more details about what a connection registry is and implications of this change. Depending on your HBase version, following is the expected minimal client configuration.

7.5.1. Up until 2.x.y releases

In 2.x.y releases, the default connection registry was based on ZooKeeper as the source of truth. This means that the clients always looked up ZooKeeper znodes to fetch the required metadata. For example, if an active master crashed and the a new master is elected, clients looked up the master znode to fetch the active master address (similarly for meta locations). This meant that the clients needed to have access to ZooKeeper and need to know the ZooKeeper ensemble information before they can do anything. This can be configured in the client configuration xml as follows:

<?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> Zookeeper ensemble information</description>
  </property>
</configuration>

7.5.2. Starting from 3.0.0 release

The default implementation was switched to a rpc based connection registry. With this implementation, by default clients contact the active or stand-by master RPC end points to fetch the connection registry information. This means that the clients should have access to the list of active and master end points before they can do anything. This can be configured in the client configuration xml as follows:

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
  <property>
    <name>hbase.masters</name>
    <value>example1,example2,example3</value>
    <description>List of master rpc end points for the hbase cluster.</description>
  </property>
</configuration>

The configuration value for hbase.masters is a comma separated list of host:port values. If no port value is specified, the default of 16000 is assumed.

Of course you are free to specify bootstrap nodes other than masters, like:

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<property>
    <name>hbase.client.bootstrap.servers</name>
    <value>server1:16020,server2:16020,server3:16020</value>
</property>

The configuration value for hbase.client.bootstrap.servers is a comma separated list of host:port values. Notice that port must be specified here.

Usually these configurations are kept out in the hbase-site.xml and is picked up by the client from the CLASSPATH.

If you are configuring an IDE to run an HBase client, you should include the conf/ directory on your classpath so hbase-site.xml settings can be found (or add src/test/resources to pick up the hbase-site.xml used by tests).

For Java applications using Maven, including the hbase-shaded-client module is the recommended dependency when connecting to a cluster:

<dependency>
  <groupId>org.apache.hbase</groupId>
  <artifactId>hbase-shaded-client</artifactId>
  <version>2.0.0</version>
</dependency>

7.5.3. Java client configuration

The configuration used by a Java client is kept in an HBaseConfiguration instance.

The factory method on HBaseConfiguration, HBaseConfiguration.create();, on invocation, will read in the content of the first hbase-site.xml found on the client’s CLASSPATH, if one is present (Invocation will also factor in any hbase-default.xml found; an hbase-default.xml ships inside the hbase.X.X.X.jar). It is also possible to specify configuration directly without having to read from a hbase-site.xml.

For example, to set the ZooKeeper ensemble or bootstrap nodes for the cluster programmatically do as follows:

Configuration config = HBaseConfiguration.create();
config.set("hbase.zookeeper.quorum", "localhost");  // Until 2.x.y versions
// ---- or ----
config.set("hbase.client.bootstrap.servers", "localhost:1234"); // Starting 3.0.0 version

7.6. Timeout settings

HBase provides a wide variety of timeout settings to limit the execution time of various remote operations.

  • hbase.rpc.timeout

  • hbase.rpc.read.timeout

  • hbase.rpc.write.timeout

  • hbase.client.operation.timeout

  • hbase.client.meta.operation.timeout

  • hbase.client.scanner.timeout.period

The hbase.rpc.timeout property limits how long a single RPC call can run before timing out. To fine tune read or write related RPC timeouts set hbase.rpc.read.timeout and hbase.rpc.write.timeout configuration properties. In the absence of these properties hbase.rpc.timeout will be used.

A higher-level timeout is hbase.client.operation.timeout which is valid for each client call. When an RPC call fails for instance for a timeout due to hbase.rpc.timeout it will be retried until hbase.client.operation.timeout is reached. Client operation timeout for system tables can be fine tuned by setting hbase.client.meta.operation.timeout configuration value. When this is not set its value will use hbase.client.operation.timeout.

Timeout for scan operations is controlled differently. Use hbase.client.scanner.timeout.period property to set this timeout.

8. Example Configurations

8.1. Basic Distributed HBase Install

Here is a basic configuration example 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.

8.1.1. hbase-site.xml

<?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 RegionServers.
    </description>
  </property>
  <property>
    <name>hbase.zookeeper.property.dataDir</name>
    <value>/export/zookeeper</value>
    <description>Property from ZooKeeper 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 RegionServers.
    </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>

8.1.2. regionservers

In this file you list the nodes that will run RegionServers. In our case, these nodes are example1-example9.

example1
example2
example3
example4
example5
example6
example7
example8
example9

8.1.3. hbase-env.sh

The following lines in the hbase-env.sh file show how to set the JAVA_HOME environment variable (required for HBase) and set the heap to 4 GB (rather than the default value of 1 GB). If you copy and paste this example, be sure to adjust the JAVA_HOME to suit your environment.

# The java implementation to use.
export JAVA_HOME=/usr/java/jdk1.8.0/

# The maximum amount of heap to use. Default is left to JVM default.
export HBASE_HEAPSIZE=4G

Use rsync to copy the content of the conf directory to all nodes of the cluster.

9. The Important Configurations

Below we list some important configurations. We’ve divided this section into required configuration and worth-a-look recommended configs.

9.1. Required Configurations

Review the os and hadoop sections.

9.1.1. Big Cluster Configurations

If you have a cluster with a lot of regions, it is possible that a Regionserver checks in briefly after the Master starts while all the remaining RegionServers lag behind. This first server to check in will be assigned all regions which is not optimal. To prevent the above scenario from happening, up the hbase.master.wait.on.regionservers.mintostart property from its default value of 1. See HBASE-6389 Modify the conditions to ensure that Master waits for sufficient number of Region Servers before starting region assignments for more detail.

zookeeper.session.timeout

The default timeout is 90 seconds (specified in milliseconds). This means that if a server crashes, it will be 90 seconds before the Master notices the crash and starts recovery. You might need to tune the timeout down to a minute or even less so the Master notices failures sooner. Before changing this value, be sure you have your JVM garbage collection configuration under control, otherwise, a long garbage collection that lasts beyond the ZooKeeper session timeout will take out your RegionServer. (You might be fine with this — you probably want recovery to start on the server if a RegionServer has been in GC for a long period of time).

To change this configuration, edit hbase-site.xml, copy the changed file across the cluster and restart.

We set this value high to save our having to field questions up on the mailing lists asking why a RegionServer went down during a massive import. The usual cause is that their JVM is untuned and they are running into long GC pauses. Our thinking is that while users are getting familiar with HBase, we’d save them having to know all of its intricacies. Later when they’ve built some confidence, then they can play with configuration such as this.

Number of ZooKeeper Instances

See zookeeper.

9.2.2. HDFS Configurations

dfs.datanode.failed.volumes.tolerated

This is the "…​number of volumes that are allowed to fail before a DataNode stops offering service. By default, any volume failure will cause a datanode to shutdown" from the hdfs-default.xml description. You might want to set this to about half the amount of your available disks.

hbase.regionserver.handler.count

This setting defines the number of threads that are kept open to answer incoming requests to user tables. The rule of thumb is to keep this number low when the payload per request approaches the MB (big puts, scans using a large cache) and high when the payload is small (gets, small puts, ICVs, deletes). The total size of the queries in progress is limited by the setting hbase.ipc.server.max.callqueue.size.

It is safe to set that number to the maximum number of incoming clients if their payload is small, the typical example being a cluster that serves a website since puts aren’t typically buffered and most of the operations are gets.

The reason why it is dangerous to keep this setting high is that the aggregate size of all the puts that are currently happening in a region server may impose too much pressure on its memory, or even trigger an OutOfMemoryError. A RegionServer running on low memory will trigger its JVM’s garbage collector to run more frequently up to a point where GC pauses become noticeable (the reason being that all the memory used to keep all the requests' payloads cannot be trashed, no matter how hard the garbage collector tries). After some time, the overall cluster throughput is affected since every request that hits that RegionServer will take longer, which exacerbates the problem even more.

You can get a sense of whether you have too little or too many handlers by rpc.logging on an individual RegionServer then tailing its logs (Queued requests consume memory).

9.2.3. Configuration for large memory machines

HBase ships with a reasonable, conservative configuration that will work on nearly all machine types that people might want to test with. If you have larger machines — HBase has 8G and larger heap — you might find the following configuration options helpful. TODO.

9.2.4. Compression

You should consider enabling ColumnFamily compression. There are several options that are near-frictionless and in most all cases boost performance by reducing the size of StoreFiles and thus reducing I/O.

See compression for more information.

9.2.5. Configuring the size and number of WAL files

HBase uses wal to recover the memstore data that has not been flushed to disk in case of an RS failure. These WAL files should be configured to be slightly smaller than HDFS block (by default a HDFS block is 64Mb and a WAL file is ~60Mb).

HBase also has a limit on the number of WAL files, designed to ensure there’s never too much data that needs to be replayed during recovery. This limit needs to be set according to memstore configuration, so that all the necessary data would fit. It is recommended to allocate enough WAL files to store at least that much data (when all memstores are close to full). For example, with 16Gb RS heap, default memstore settings (0.4), and default WAL file size (~60Mb), 16Gb*0.4/60, the starting point for WAL file count is ~109. However, as all memstores are not expected to be full all the time, less WAL files can be allocated.

9.2.6. Managed Splitting

HBase generally handles splitting of your regions based upon the settings in your hbase-default.xml and hbase-site.xml configuration files. Important settings include hbase.regionserver.region.split.policy, hbase.hregion.max.filesize, hbase.regionserver.regionSplitLimit. A simplistic view of splitting is that when a region grows to hbase.hregion.max.filesize, it is split. For most usage patterns, you should use automatic splitting. See manual region splitting decisions for more information about manual region splitting.

Instead of allowing HBase to split your regions automatically, you can choose to manage the splitting yourself. Manually managing splits works if you know your keyspace well, otherwise let HBase figure where to split for you. Manual splitting can mitigate region creation and movement under load. It also makes it so region boundaries are known and invariant (if you disable region splitting). If you use manual splits, it is easier doing staggered, time-based major compactions to spread out your network IO load.

Disable Automatic Splitting

To disable automatic splitting, you can set region split policy in either cluster configuration or table configuration to be org.apache.hadoop.hbase.regionserver.DisabledRegionSplitPolicy

Automatic Splitting Is Recommended

If you disable automatic splits to diagnose a problem or during a period of fast data growth, it is recommended to re-enable them when your situation becomes more stable. The potential benefits of managing region splits yourself are not undisputed.
Determine the Optimal Number of Pre-Split Regions

The optimal number of pre-split regions depends on your application and environment. A good rule of thumb is to start with 10 pre-split regions per server and watch as data grows over time. It is better to err on the side of too few regions and perform rolling splits later. The optimal number of regions depends upon the largest StoreFile in your region. The size of the largest StoreFile will increase with time if the amount of data grows. The goal is for the largest region to be just large enough that the compaction selection algorithm only compacts it during a timed major compaction. Otherwise, the cluster can be prone to compaction storms with a large number of regions under compaction at the same time. It is important to understand that the data growth causes compaction storms and not the manual split decision.

If the regions are split into too many large regions, you can increase the major compaction interval by configuring HConstants.MAJOR_COMPACTION_PERIOD. The org.apache.hadoop.hbase.util.RegionSplitter utility also provides a network-IO-safe rolling split of all regions.

9.2.7. Managed Compactions

By default, major compactions are scheduled to run once in a 7-day period.

If you need to control exactly when and how often major compaction runs, you can disable managed major compactions. See the entry for hbase.hregion.majorcompaction in the compaction.parameters table for details.

Do Not Disable Major Compactions

Major compactions are absolutely necessary for StoreFile clean-up. Do not disable them altogether. You can run major compactions manually via the HBase shell or via the Admin API.

For more information about compactions and the compaction file selection process, see compaction

9.2.8. Speculative Execution

Speculative Execution of MapReduce tasks is on by default, and for HBase clusters it is generally advised to turn off Speculative Execution at a system-level unless you need it for a specific case, where it can be configured per-job. Set the properties mapreduce.map.speculative and mapreduce.reduce.speculative to false.

9.3. Other Configurations

9.3.1. Balancer

The balancer is a periodic operation which is run on the master to redistribute regions on the cluster. It is configured via hbase.balancer.period and defaults to 300000 (5 minutes).

See master.processes.loadbalancer for more information on the LoadBalancer.

9.3.2. Disabling Blockcache

Do not turn off block cache (You’d do it by setting hfile.block.cache.size to zero). Currently, we do not do well if you do this because the RegionServer will spend all its time loading HFile indices over and over again. If your working set is such that block cache does you no good, at least size the block cache such that HFile indices will stay up in the cache (you can get a rough idea on the size you need by surveying RegionServer UIs; you’ll see index block size accounted near the top of the webpage).

9.3.3. Nagle’s or the small package problem

If a big 40ms or so occasional delay is seen in operations against HBase, try the Nagles' setting. For example, see the user mailing list thread, Inconsistent scan performance with caching set to 1 and the issue cited therein where setting notcpdelay improved scan speeds. You might also see the graphs on the tail of HBASE-7008 Set scanner caching to a better default where our Lars Hofhansl tries various data sizes w/ Nagle’s on and off measuring the effect.

9.3.4. Better Mean Time to Recover (MTTR)

This section is about configurations that will make servers come back faster after a fail. See the Deveraj Das and Nicolas Liochon blog post Introduction to HBase Mean Time to Recover (MTTR) for a brief introduction.

The issue HBASE-8354 forces Namenode into loop with lease recovery requests is messy but has a bunch of good discussion toward the end on low timeouts and how to cause faster recovery including citation of fixes added to HDFS. Read the Varun Sharma comments. The below suggested configurations are Varun’s suggestions distilled and tested. Make sure you are running on a late-version HDFS so you have the fixes he refers to and himself adds to HDFS that help HBase MTTR (e.g. HDFS-3703, HDFS-3712, and HDFS-4791 — Hadoop 2 for sure has them and late Hadoop 1 has some). Set the following in the RegionServer.

<property>
  <name>hbase.lease.recovery.dfs.timeout</name>
  <value>23000</value>
  <description>How much time we allow elapse between calls to recover lease.
  Should be larger than the dfs timeout.</description>
</property>
<property>
  <name>dfs.client.socket-timeout</name>
  <value>10000</value>
  <description>Down the DFS timeout from 60 to 10 seconds.</description>
</property>

And on the NameNode/DataNode side, set the following to enable 'staleness' introduced in HDFS-3703, HDFS-3912.

<property>
  <name>dfs.client.socket-timeout</name>
  <value>10000</value>
  <description>Down the DFS timeout from 60 to 10 seconds.</description>
</property>
<property>
  <name>dfs.datanode.socket.write.timeout</name>
  <value>10000</value>
  <description>Down the DFS timeout from 8 * 60 to 10 seconds.</description>
</property>
<property>
  <name>ipc.client.connect.timeout</name>
  <value>3000</value>
  <description>Down from 60 seconds to 3.</description>
</property>
<property>
  <name>ipc.client.connect.max.retries.on.timeouts</name>
  <value>2</value>
  <description>Down from 45 seconds to 3 (2 == 3 retries).</description>
</property>
<property>
  <name>dfs.namenode.avoid.read.stale.datanode</name>
  <value>true</value>
  <description>Enable stale state in hdfs</description>
</property>
<property>
  <name>dfs.namenode.stale.datanode.interval</name>
  <value>20000</value>
  <description>Down from default 30 seconds</description>
</property>
<property>
  <name>dfs.namenode.avoid.write.stale.datanode</name>
  <value>true</value>
  <description>Enable stale state in hdfs</description>
</property>

9.3.5. JMX

JMX (Java Management Extensions) provides built-in instrumentation that enables you to monitor and manage the Java VM. To enable monitoring and management from remote systems, you need to set system property com.sun.management.jmxremote.port (the port number through which you want to enable JMX RMI connections) when you start the Java VM. See the official documentation for more information. Historically, besides above port mentioned, JMX opens two additional random TCP listening ports, which could lead to port conflict problem. (See HBASE-10289 for details)

As an alternative, you can use the coprocessor-based JMX implementation provided by HBase. To enable it, add below property in hbase-site.xml:

<property>
  <name>hbase.coprocessor.regionserver.classes</name>
  <value>org.apache.hadoop.hbase.JMXListener</value>
</property>
DO NOT set com.sun.management.jmxremote.port for Java VM at the same time.

Currently it supports Master and RegionServer Java VM. By default, the JMX listens on TCP port 10102, you can further configure the port using below properties:

<property>
  <name>regionserver.rmi.registry.port</name>
  <value>61130</value>
</property>
<property>
  <name>regionserver.rmi.connector.port</name>
  <value>61140</value>
</property>

The registry port can be shared with connector port in most cases, so you only need to configure regionserver.rmi.registry.port. However, if you want to use SSL communication, the 2 ports must be configured to different values.

By default the password authentication and SSL communication is disabled. To enable password authentication, you need to update hbase-env.sh like below:

export HBASE_JMX_BASE="-Dcom.sun.management.jmxremote.authenticate=true                  \
                       -Dcom.sun.management.jmxremote.password.file=your_password_file   \
                       -Dcom.sun.management.jmxremote.access.file=your_access_file"

export HBASE_MASTER_OPTS="$HBASE_MASTER_OPTS $HBASE_JMX_BASE "
export HBASE_REGIONSERVER_OPTS="$HBASE_REGIONSERVER_OPTS $HBASE_JMX_BASE "

See example password/access file under $JRE_HOME/lib/management.

To enable SSL communication with password authentication, follow below steps:

#1. generate a key pair, stored in myKeyStore
keytool -genkey -alias jconsole -keystore myKeyStore

#2. export it to file jconsole.cert
keytool -export -alias jconsole -keystore myKeyStore -file jconsole.cert

#3. copy jconsole.cert to jconsole client machine, import it to jconsoleKeyStore
keytool -import -alias jconsole -keystore jconsoleKeyStore -file jconsole.cert

And then update hbase-env.sh like below:

export HBASE_JMX_BASE="-Dcom.sun.management.jmxremote.ssl=true                         \
                       -Djavax.net.ssl.keyStore=/home/tianq/myKeyStore                 \
                       -Djavax.net.ssl.keyStorePassword=your_password_in_step_1        \
                       -Dcom.sun.management.jmxremote.authenticate=true                \
                       -Dcom.sun.management.jmxremote.password.file=your_password file \
                       -Dcom.sun.management.jmxremote.access.file=your_access_file"

export HBASE_MASTER_OPTS="$HBASE_MASTER_OPTS $HBASE_JMX_BASE "
export HBASE_REGIONSERVER_OPTS="$HBASE_REGIONSERVER_OPTS $HBASE_JMX_BASE "

Finally start jconsole on the client using the key store:

jconsole -J-Djavax.net.ssl.trustStore=/home/tianq/jconsoleKeyStore
To enable the HBase JMX implementation on Master, you also need to add below property in hbase-site.xml: 
<property>
  <name>hbase.coprocessor.master.classes</name>
  <value>org.apache.hadoop.hbase.JMXListener</value>
</property>

The corresponding properties for port configuration are master.rmi.registry.port (by default 10101) and master.rmi.connector.port (by default the same as registry.port)

10. Dynamic Configuration

It is possible to change a subset of the configuration without requiring a server restart. In the HBase shell, the operations update_config, update_all_config and update_rsgroup_config will prompt a server, all servers or all servers in the RSGroup to reload configuration.

Only a subset of all configurations can currently be changed in the running server. Here are those configurations:

Table 9. Configurations that support dynamic change
Key

hbase.balancer.tablesOnMaster

hbase.balancer.tablesOnMaster.systemTablesOnly

hbase.cleaner.scan.dir.concurrent.size

hbase.coprocessor.master.classes

hbase.coprocessor.region.classes

hbase.coprocessor.regionserver.classes

hbase.coprocessor.user.region.classes

hbase.hregion.majorcompaction

hbase.hregion.majorcompaction.jitter

hbase.hstore.compaction.date.tiered.incoming.window.min

hbase.hstore.compaction.date.tiered.max.storefile.age.millis

hbase.hstore.compaction.date.tiered.single.output.for.minor.compaction

hbase.hstore.compaction.date.tiered.window.factory.class

hbase.hstore.compaction.date.tiered.window.policy.class

hbase.hstore.compaction.max

hbase.hstore.compaction.max.size

hbase.hstore.compaction.max.size.offpeak

hbase.hstore.compaction.min

hbase.hstore.compaction.min.size

hbase.hstore.compaction.ratio

hbase.hstore.compaction.ratio.offpeak

hbase.hstore.min.locality.to.skip.major.compact

hbase.ipc.server.callqueue.codel.interval

hbase.ipc.server.callqueue.codel.lifo.threshold

hbase.ipc.server.callqueue.codel.target.delay

hbase.ipc.server.callqueue.type

hbase.ipc.server.fallback-to-simple-auth-allowed

hbase.ipc.server.max.callqueue.length

hbase.ipc.server.priority.max.callqueue.length

hbase.master.balancer.stochastic.localityCost

hbase.master.balancer.stochastic.maxMovePercent

hbase.master.balancer.stochastic.maxRunningTime

hbase.master.balancer.stochastic.maxSteps

hbase.master.balancer.stochastic.memstoreSizeCost

hbase.master.balancer.stochastic.minCostNeedBalance

hbase.master.balancer.stochastic.moveCost

hbase.master.balancer.stochastic.moveCost.offpeak

hbase.master.balancer.stochastic.numRegionLoadsToRemember

hbase.master.balancer.stochastic.primaryRegionCountCost

hbase.master.balancer.stochastic.rackLocalityCost

hbase.master.balancer.stochastic.readRequestCost

hbase.master.balancer.stochastic.regionCountCost

hbase.master.balancer.stochastic.regionReplicaHostCostKey

hbase.master.balancer.stochastic.regionReplicaRackCostKey

hbase.master.balancer.stochastic.runMaxSteps

hbase.master.balancer.stochastic.stepsPerRegion

hbase.master.balancer.stochastic.storefileSizeCost

hbase.master.balancer.stochastic.tableSkewCost

hbase.master.balancer.stochastic.writeRequestCost

hbase.master.loadbalance.bytable

hbase.master.regions.recovery.check.interval

hbase.offpeak.end.hour

hbase.offpeak.start.hour

hbase.oldwals.cleaner.thread.check.interval.msec

hbase.oldwals.cleaner.thread.size

hbase.oldwals.cleaner.thread.timeout.msec

hbase.procedure.worker.add.stuck.percentage

hbase.procedure.worker.keep.alive.time.msec

hbase.procedure.worker.monitor.interval.msec

hbase.procedure.worker.stuck.threshold.msec

hbase.regionserver.flush.throughput.controller

hbase.regionserver.hfilecleaner.large.queue.size

hbase.regionserver.hfilecleaner.large.thread.count

hbase.regionserver.hfilecleaner.small.queue.size

hbase.regionserver.hfilecleaner.small.thread.count

hbase.regionserver.hfilecleaner.thread.check.interval.msec

hbase.regionserver.hfilecleaner.thread.timeout.msec

hbase.regionserver.thread.compaction.large

hbase.regionserver.thread.compaction.small

hbase.regionserver.thread.compaction.throttle

hbase.regionserver.thread.hfilecleaner.throttle

hbase.regionserver.thread.split

hbase.regionserver.throughput.controller

hbase.regions.overallSlop

hbase.regions.recovery.store.file.ref.count

hbase.regions.slop

hbase.rsgroup.fallback.enable

hbase.util.ip.to.rack.determiner

Upgrading

You cannot skip major versions when upgrading. If you are upgrading from version 0.98.x to 2.x, you must first go from 0.98.x to 1.2.x and then go from 1.2.x to 2.x.

Review Apache HBase Configuration, in particular Hadoop. Familiarize yourself with Support and Testing Expectations.

11. HBase version number and compatibility

11.1. Aspirational Semantic Versioning

Starting with the 1.0.0 release, HBase is working towards Semantic Versioning for its release versioning. In summary:

Given a version number MAJOR.MINOR.PATCH, increment the:

  • MAJOR version when you make incompatible API changes,

  • MINOR version when you add functionality in a backwards-compatible manner, and

  • PATCH version when you make backwards-compatible bug fixes.

  • Additional labels for pre-release and build metadata are available as extensions to the MAJOR.MINOR.PATCH format.

Compatibility Dimensions

In addition to the usual API versioning considerations HBase has other compatibility dimensions that we need to consider.

Client-Server wire protocol compatibility

  • Allows updating client and server out of sync.

  • We could only allow upgrading the server first. I.e. the server would be backward compatible to an old client, that way new APIs are OK.

  • Example: A user should be able to use an old client to connect to an upgraded cluster.

Server-Server protocol compatibility

  • Servers of different versions can co-exist in the same cluster.

  • The wire protocol between servers is compatible.

  • Workers for distributed tasks, such as replication and log splitting, can co-exist in the same cluster.

  • Dependent protocols (such as using ZK for coordination) will also not be changed.

  • Example: A user can perform a rolling upgrade.

File format compatibility

  • Support file formats backward and forward compatible

  • Example: File, ZK encoding, directory layout is upgraded automatically as part of an HBase upgrade. User can downgrade to the older version and everything will continue to work.

Client API compatibility

  • Allow changing or removing existing client APIs.

  • An API needs to be deprecated for a whole major version before we will change/remove it.

    • An example: An API was deprecated in 2.0.1 and will be marked for deletion in 4.0.0. On the other hand, an API deprecated in 2.0.0 can be removed in 3.0.0.

    • Occasionally mistakes are made and internal classes are marked with a higher access level than they should. In these rare circumstances, we will accelerate the deprecation schedule to the next major version (i.e., deprecated in 2.2.x, marked IA.Private 3.0.0). Such changes are communicated and explained via release note in Jira.

  • APIs available in a patch version will be available in all later patch versions. However, new APIs may be added which will not be available in earlier patch versions.

  • New APIs introduced in a patch version will only be added in a source compatible way [1]: i.e. code that implements public APIs will continue to compile.

    • Example: A user using a newly deprecated API does not need to modify application code with HBase API calls until the next major version. *

Client Binary compatibility

  • Client code written to APIs available in a given patch release can run unchanged (no recompilation needed) against the new jars of later patch versions.

  • Client code written to APIs available in a given patch release might not run against the old jars from an earlier patch version.

    • Example: Old compiled client code will work unchanged with the new jars.

  • If a Client implements an HBase Interface, a recompile MAY be required upgrading to a newer minor version (See release notes for warning about incompatible changes). All effort will be made to provide a default implementation so this case should not arise.

Server-Side Limited API compatibility (taken from Hadoop)

  • Internal APIs are marked as Stable, Evolving, or Unstable

  • This implies binary compatibility for coprocessors and plugins (pluggable classes, including replication) as long as these are only using marked interfaces/classes.

  • Example: Old compiled Coprocessor, Filter, or Plugin code will work unchanged with the new jars.

Dependency Compatibility

  • An upgrade of HBase will not require an incompatible upgrade of a dependent project, except for Apache Hadoop.

  • An upgrade of HBase will not require an incompatible upgrade of the Java runtime.

  • Example: Upgrading HBase to a version that supports Dependency Compatibility won’t require that you upgrade your Apache ZooKeeper service.

  • Example: If your current version of HBase supported running on JDK 8, then an upgrade to a version that supports Dependency Compatibility will also run on JDK 8.

Hadoop Versions

Previously, we tried to maintain dependency compatibility for the underly Hadoop service but over the last few years this has proven untenable. While the HBase project attempts to maintain support for older versions of Hadoop, we drop the "supported" designator for minor versions that fail to continue to see releases. Additionally, the Hadoop project has its own set of compatibility guidelines, which means in some cases having to update to a newer supported minor release might break some of our compatibility promises.
Operational Compatibility

  • Metric changes

  • Behavioral changes of services

  • JMX APIs exposed via the /jmx/ endpoint

Summary

  • A patch upgrade is a drop-in replacement. Any change that is not Java binary and source compatible would not be allowed.[2] Downgrading versions within patch releases may not be compatible.

  • A minor upgrade requires no application/client code modification. Ideally it would be a drop-in replacement but client code, coprocessors, filters, etc might have to be recompiled if new jars are used.

  • A major upgrade allows the HBase community to make breaking changes.

Table 10. Compatibility Matrix [3]

Major

Minor

Patch

Client-Server wire Compatibility

N

Y

Y

Server-Server Compatibility

N

Y

Y

File Format Compatibility

N [4]

Y

Y

Client API Compatibility

N

Y

Y

Client Binary Compatibility

N

N

Y

Server-Side Limited API Compatibility

Stable

N

Y

Y

Evolving

N

N

Y

Unstable

N

N

N

Dependency Compatibility

N

Y

Y

Operational Compatibility

N

N

Y

HBase 1.7.0 release violated client-server wire compatibility guarantees and was subsequently withdrawn after the incompatibilities were reported and fixed in 1.7.1. If you are considering an upgrade to 1.7.x line, see Upgrading to 1.7.1+.

11.1.1. HBase API Surface

HBase has a lot of API points, but for the compatibility matrix above, we differentiate between Client API, Limited Private API, and Private API. HBase uses Apache Yetus Audience Annotations to guide downstream expectations for stability.

  • InterfaceAudience (javadocs): captures the intended audience, possible values include:

    • Public: safe for end users and external projects

    • LimitedPrivate: used for internals we expect to be pluggable, such as coprocessors

    • Private: strictly for use within HBase itself Classes which are defined as IA.Private may be used as parameters or return values for interfaces which are declared IA.LimitedPrivate. Treat the IA.Private object as opaque; do not try to access its methods or fields directly.

  • InterfaceStability (javadocs): describes what types of interface changes are permitted. Possible values include:

    • Stable: the interface is fixed and is not expected to change

    • Evolving: the interface may change in future minor versions

    • Unstable: the interface may change at any time

Please keep in mind the following interactions between the InterfaceAudience and InterfaceStability annotations within the HBase project:

  • IA.Public classes are inherently stable and adhere to our stability guarantees relating to the type of upgrade (major, minor, or patch).

  • IA.LimitedPrivate classes should always be annotated with one of the given InterfaceStability values. If they are not, you should presume they are IS.Unstable.

  • IA.Private classes should be considered implicitly unstable, with no guarantee of stability between releases.

HBase Client API

HBase Client API consists of all the classes or methods that are marked with InterfaceAudience.Public interface. All main classes in hbase-client and dependent modules have either InterfaceAudience.Public, InterfaceAudience.LimitedPrivate, or InterfaceAudience.Private marker. Not all classes in other modules (hbase-server, etc) have the marker. If a class is not annotated with one of these, it is assumed to be a InterfaceAudience.Private class.

HBase LimitedPrivate API

LimitedPrivate annotation comes with a set of target consumers for the interfaces. Those consumers are coprocessors, phoenix, replication endpoint implementations or similar. At this point, HBase only guarantees source and binary compatibility for these interfaces between patch versions.

HBase Private API

All classes annotated with InterfaceAudience.Private or all classes that do not have the annotation are for HBase internal use only. The interfaces and method signatures can change at any point in time. If you are relying on a particular interface that is marked Private, you should open a jira to propose changing the interface to be Public or LimitedPrivate, or an interface exposed for this purpose.

Binary Compatibility

When we say two HBase versions are compatible, we mean that the versions are wire and binary compatible. Compatible HBase versions means that clients can talk to compatible but differently versioned servers. It means too that you can just swap out the jars of one version and replace them with the jars of another, compatible version and all will just work. Unless otherwise specified, HBase point versions are (mostly) binary compatible. You can safely do rolling upgrades between binary compatible versions; i.e. across maintenance releases: e.g. from 1.4.4 to 1.4.6. See Does compatibility between versions also mean binary compatibility? discussion on the HBase dev mailing list.

11.2. Rolling Upgrades

A rolling upgrade is the process by which you update the servers in your cluster a server at a time. You can rolling upgrade across HBase versions if they are binary or wire compatible. See Rolling Upgrade Between Versions that are Binary/Wire Compatible for more on what this means. Coarsely, a rolling upgrade is a graceful stop each server, update the software, and then restart. You do this for each server in the cluster. Usually you upgrade the Master first and then the RegionServers. See Rolling Restart for tools that can help use the rolling upgrade process.

For example, in the below, HBase was symlinked to the actual HBase install. On upgrade, before running a rolling restart over the cluster, we changed the symlink to point at the new HBase software version and then ran

$ HADOOP_HOME=~/hadoop-2.6.0-CRC-SNAPSHOT ~/hbase/bin/rolling-restart.sh --config ~/conf_hbase

The rolling-restart script will first gracefully stop and restart the master, and then each of the RegionServers in turn. Because the symlink was changed, on restart the server will come up using the new HBase version. Check logs for errors as the rolling upgrade proceeds.

Rolling Upgrade Between Versions that are Binary/Wire Compatible

Unless otherwise specified, HBase minor versions are binary compatible. You can do a Rolling Upgrades between HBase point versions. For example, you can go to 1.4.4 from 1.4.6 by doing a rolling upgrade across the cluster replacing the 1.4.4 binary with a 1.4.6 binary.

In the minor version-particular sections below, we call out where the versions are wire/protocol compatible and in this case, it is also possible to do a Rolling Upgrades.

12. Rollback

Sometimes things don’t go as planned when attempting an upgrade. This section explains how to perform a rollback to an earlier HBase release. Note that this should only be needed between Major and some Minor releases. You should always be able to downgrade between HBase Patch releases within the same Minor version. These instructions may require you to take steps before you start the upgrade process, so be sure to read through this section beforehand.

12.1. Caveats

Rollback vs Downgrade

This section describes how to perform a rollback on an upgrade between HBase minor and major versions. In this document, rollback refers to the process of taking an upgraded cluster and restoring it to the old version while losing all changes that have occurred since upgrade. By contrast, a cluster downgrade would restore an upgraded cluster to the old version while maintaining any data written since the upgrade. We currently only offer instructions to rollback HBase clusters. Further, rollback only works when these instructions are followed prior to performing the upgrade.

When these instructions talk about rollback vs downgrade of prerequisite cluster services (i.e. HDFS), you should treat leaving the service version the same as a degenerate case of downgrade.

Replication

Unless you are doing an all-service rollback, the HBase cluster will lose any configured peers for HBase replication. If your cluster is configured for HBase replication, then prior to following these instructions you should document all replication peers. After performing the rollback you should then add each documented peer back to the cluster. For more information on enabling HBase replication, listing peers, and adding a peer see Managing and Configuring Cluster Replication. Note also that data written to the cluster since the upgrade may or may not have already been replicated to any peers. Determining which, if any, peers have seen replication data as well as rolling back the data in those peers is out of the scope of this guide.

Data Locality

Unless you are doing an all-service rollback, going through a rollback procedure will likely destroy all locality for Region Servers. You should expect degraded performance until after the cluster has had time to go through compactions to restore data locality. Optionally, you can force a compaction to speed this process up at the cost of generating cluster load.

Configurable Locations

The instructions below assume default locations for the HBase data directory and the HBase znode. Both of these locations are configurable and you should verify the value used in your cluster before proceeding. In the event that you have a different value, just replace the default with the one found in your configuration * HBase data directory is configured via the key 'hbase.rootdir' and has a default value of '/hbase'. * HBase znode is configured via the key 'zookeeper.znode.parent' and has a default value of '/hbase'.

12.2. All service rollback

If you will be performing a rollback of both the HDFS and ZooKeeper services, then HBase’s data will be rolled back in the process.

Requirements

  • Ability to rollback HDFS and ZooKeeper

Before upgrade

No additional steps are needed pre-upgrade. As an extra precautionary measure, you may wish to use distcp to back up the HBase data off of the cluster to be upgraded. To do so, follow the steps in the 'Before upgrade' section of 'Rollback after HDFS downgrade' but copy to another HDFS instance instead of within the same instance.

Performing a rollback

  1. Stop HBase

  2. Perform a rollback for HDFS and ZooKeeper (HBase should remain stopped)

  3. Change the installed version of HBase to the previous version

  4. Start HBase

  5. Verify HBase contents—use the HBase shell to list tables and scan some known values.

12.3. Rollback after HDFS rollback and ZooKeeper downgrade

If you will be rolling back HDFS but going through a ZooKeeper downgrade, then HBase will be in an inconsistent state. You must ensure the cluster is not started until you complete this process.

Requirements

  • Ability to rollback HDFS

  • Ability to downgrade ZooKeeper

Before upgrade

No additional steps are needed pre-upgrade. As an extra precautionary measure, you may wish to use distcp to back up the HBase data off of the cluster to be upgraded. To do so, follow the steps in the 'Before upgrade' section of 'Rollback after HDFS downgrade' but copy to another HDFS instance instead of within the same instance.

Performing a rollback

  1. Stop HBase

  2. Perform a rollback for HDFS and a downgrade for ZooKeeper (HBase should remain stopped)

  3. Change the installed version of HBase to the previous version

  4. Clean out ZooKeeper information related to HBase. WARNING: This step will permanently destroy all replication peers. Please see the section on HBase Replication under Caveats for more information.

    Clean HBase information out of ZooKeeper
    [hpnewton@gateway_node.example.com ~]$ zookeeper-client -server zookeeper1.example.com:2181,zookeeper2.example.com:2181,zookeeper3.example.com:2181
Welcome to ZooKeeper!
JLine support is disabled
rmr /hbase
quit
Quitting...

  5. Start HBase

  6. Verify HBase contents—use the HBase shell to list tables and scan some known values.

12.4. Rollback after HDFS downgrade

If you will be performing an HDFS downgrade, then you’ll need to follow these instructions regardless of whether ZooKeeper goes through rollback, downgrade, or reinstallation.

Requirements

  • Ability to downgrade HDFS

  • Pre-upgrade cluster must be able to run MapReduce jobs

  • HDFS super user access

  • Sufficient space in HDFS for at least two copies of the HBase data directory

Before upgrade

Before beginning the upgrade process, you must take a complete backup of HBase’s backing data. The following instructions cover backing up the data within the current HDFS instance. Alternatively, you can use the distcp command to copy the data to another HDFS cluster.

  1. Stop the HBase cluster

  2. Copy the HBase data directory to a backup location using the distcp command as the HDFS super user (shown below on a security enabled cluster)

    Using distcp to backup the HBase data directory
    [hpnewton@gateway_node.example.com ~]$ kinit -k -t hdfs.keytab [email protected]
[hpnewton@gateway_node.example.com ~]$ hadoop distcp /hbase /hbase-pre-upgrade-backup

  3. Distcp will launch a mapreduce job to handle copying the files in a distributed fashion. Check the output of the distcp command to ensure this job completed successfully.

Performing a rollback

  1. Stop HBase

  2. Perform a downgrade for HDFS and a downgrade/rollback for ZooKeeper (HBase should remain stopped)

  3. Change the installed version of HBase to the previous version

  4. Restore the HBase data directory from prior to the upgrade as the HDFS super user (shown below on a security enabled cluster). If you backed up your data on another HDFS cluster instead of locally, you will need to use the distcp command to copy it back to the current HDFS cluster.

    Restore the HBase data directory
    [hpnewton@gateway_node.example.com ~]$ kinit -k -t hdfs.keytab [email protected]
[hpnewton@gateway_node.example.com ~]$ hdfs dfs -mv /hbase /hbase-upgrade-rollback
[hpnewton@gateway_node.example.com ~]$ hdfs dfs -mv /hbase-pre-upgrade-backup /hbase

  5. Clean out ZooKeeper information related to HBase. WARNING: This step will permanently destroy all replication peers. Please see the section on HBase Replication under Caveats for more information.

    Clean HBase information out of ZooKeeper
    [hpnewton@gateway_node.example.com ~]$ zookeeper-client -server zookeeper1.example.com:2181,zookeeper2.example.com:2181,zookeeper3.example.com:2181
Welcome to ZooKeeper!
JLine support is disabled
rmr /hbase
quit
Quitting...

  6. Start HBase

  7. Verify HBase contents–use the HBase shell to list tables and scan some known values.

13. Upgrade Paths

13.1. Upgrade from 2.x to 3.x

The RegionServer Grouping feature has been reimplemented. See section Migrating From Old Implementation in Apache HBase Operational Management for more details.

The hbase:namespace table has been removed and fold into hbase:meta. See section About hbase:namespace table in Data Model for more details.

There is no special consideration upgrading to hbase-2.4.x from 2.3.x. And for earlier versions, just follow the Upgrade from 2.0.x-2.2.x to 2.3+ guide. In general, 2.2.x should be rolling upgradeable, for 2.1.x or 2.0.x, you will need to clear the Upgrade from 2.0 or 2.1 to 2.2+ hurdle first.

13.2. Upgrade from 2.0.x-2.2.x to 2.3+

There is no special consideration upgrading to hbase-2.3.x from earlier versions. From 2.2.x, it should be rolling upgradeable. From 2.1.x or 2.0.x, you will need to clear the Upgrade from 2.0 or 2.1 to 2.2+ hurdle first.

13.2.1. Upgraded ZooKeeper Dependency Version

Our dependency on Apache ZooKeeper has been upgraded to 3.5.7 (HBASE-24132), as 3.4.x is EOL. The newer 3.5.x client is compatible with the older 3.4.x server. However, if you’re using HBase in stand-alone mode and perform an in-place upgrade, there are some upgrade steps documented by the ZooKeeper community. This doesn’t impact a production deployment, but would impact a developer’s local environment.

13.2.2. New In-Master Procedure Store

Of note, HBase 2.3.0 changes the in-Master Procedure Store implementation. It was a dedicated custom store (see MasterProcWAL) to instead use a standard HBase Region (HBASE-23326). The migration from the old to new format is automatic run by the new 2.3.0 Master on startup. The old MasterProcWALs dir which hosted the old custom implementation files in ${hbase.rootdir} is deleted on successful migration. A new MasterProc sub-directory replaces it to host the Store files and WALs for the new Procedure Store in-Master Region. The in-Master Region is unusual in that it writes to an alternate location at ${hbase.rootdir}/MasterProc rather than under ${hbase.rootdir}/data in the filesystem and the special Procedure Store in-Master Region is hidden from all clients other than the active Master itself. Otherwise, it is like any other with the Master process running flushes and compactions, archiving WALs when over-flushed, and so on. Its files are readable by standard Region and Store file tooling for triage and analysis as long as they are pointed to the appropriate location in the filesystem.

Notice that, after the migration, you should make sure to not start an active master with old code, as it can not recognize the new procedure store. So it is suggested to upgrade backup master(s) to new 2.3 first, and then upgrade the active master. And unless explicitly mentioned, this is the suggested way for all upgrading, i.e, upgrading backup master(s) first, then active master, and then region servers.

13.3. Upgrade from 2.0 or 2.1 to 2.2+

HBase 2.2+ uses a new Procedure form assigning/unassigning/moving Regions. It does not process HBase 2.1 and 2.0’s Unassign/Assign Procedure types. Upgrade requires that we first drain the Master Procedure Store of old style Procedures before starting the new 2.2 Master. So you need to make sure that before you kill the old version (2.0 or 2.1) Master, there is no region in transition. And once the new version (2.2+) Master is up, you can rolling upgrade RegionServers one by one.

And there is a more safer way if you are running 2.1.1+ or 2.0.3+ cluster. It need four steps to upgrade Master.

  1. Shutdown both active and standby Masters (Your cluster will continue to server reads and writes without interruption).

  2. Set the property hbase.procedure.upgrade-to-2-2 to true in hbase-site.xml for the Master, and start only one Master, still using the 2.1.1+ (or 2.0.3+) version.

  3. Wait until the Master quits. Confirm that there is a 'UPGRADE OK: All existed procedures have been finished, quit…​' message in the Master log as the cause of the shutdown. The Procedure Store is now empty.

  4. Start new Masters with the new 2.2+ version.

Then you can rolling upgrade RegionServers one by one. See HBASE-21075 for more details.

In case these steps are not done, on starting 2.2+ master, you would see the following exception in the master logs:

org.apache.hadoop.hbase.HBaseIOException: Unsupported procedure type class org.apache.hadoop.hbase.master.assignment.UnassignProcedure found

13.4. Upgrading from 1.x to 2.x

In this section we will first call out significant changes compared to the prior stable HBase release and then go over the upgrade process. Be sure to read the former with care so you avoid surprises.

13.4.1. Changes of Note!

First we’ll cover deployment / operational changes that you might hit when upgrading to HBase 2.0+. After that we’ll call out changes for downstream applications. Please note that Coprocessors are covered in the operational section. Also note that this section is not meant to convey information about new features that may be of interest to you. For a complete summary of changes, please see the CHANGES.txt file in the source release artifact for the version you are planning to upgrade to.

Update to basic prerequisite minimums in HBase 2.0+

As noted in the section Basic Prerequisites, HBase 2.0+ requires a minimum of Java 8 and Hadoop 2.6. The HBase community recommends ensuring you have already completed any needed upgrades in prerequisites prior to upgrading your HBase version.

HBCK must match HBase server version

You must not use an HBase 1.x version of HBCK against an HBase 2.0+ cluster. HBCK is strongly tied to the HBase server version. Using the HBCK tool from an earlier release against an HBase 2.0+ cluster will destructively alter said cluster in unrecoverable ways.

As of HBase 2.0, HBCK (A.K.A HBCK1 or hbck1) is a read-only tool that can report the status of some non-public system internals but will often misread state because it does not understand the workings of hbase2.

To read about HBCK’s replacement, see HBase HBCK2 in Apache HBase Operational Management.

Related, before you upgrade, ensure that hbck1 reports no INCONSISTENCIES. Fixing hbase1-type inconsistencies post-upgrade is an involved process.
Configuration settings no longer in HBase 2.0+

The following configuration settings are no longer applicable or available. For details, please see the detailed release notes.

Configuration properties that were renamed in HBase 2.0+

The following properties have been renamed. Attempts to set the old property will be ignored at run time.

Table 11. Renamed properties
Old name New name

hbase.rpc.server.nativetransport

hbase.netty.nativetransport

hbase.netty.rpc.server.worker.count

hbase.netty.worker.count

hbase.hfile.compactions.discharger.interval

hbase.hfile.compaction.discharger.interval

hbase.hregion.percolumnfamilyflush.size.lower.bound

hbase.hregion.percolumnfamilyflush.size.lower.bound.min
Configuration settings with different defaults in HBase 2.0+

The following configuration settings changed their default value. Where applicable, the value to set to restore the behavior of HBase 1.2 is given.

  • hbase.security.authorization now defaults to false. set to true to restore same behavior as previous default.

  • hbase.client.retries.number is now set to 10. Previously it was 35. Downstream users are advised to use client timeouts as described in section Timeout settings instead.

  • hbase.client.serverside.retries.multiplier is now set to 3. Previously it was 10. Downstream users are advised to use client timesout as describe in section Timeout settings instead.

  • hbase.master.fileSplitTimeout is now set to 10 minutes. Previously it was 30 seconds.

  • hbase.regionserver.logroll.multiplier is now set to 0.5. Previously it was 0.95. This change is tied with the following doubling of block size. Combined, these two configuration changes should make for WALs of about the same size as those in hbase-1.x but there should be less incidence of small blocks because we fail to roll the WAL before we hit the blocksize threshold. See HBASE-19148 for discussion.

  • hbase.regionserver.hlog.blocksize defaults to 2x the HDFS default block size for the WAL dir. Previously it was equal to the HDFS default block size for the WAL dir.

  • hbase.client.start.log.errors.counter changed to 5. Previously it was 9.

  • hbase.ipc.server.callqueue.type changed to 'fifo'. In HBase versions 1.0 - 1.2 it was 'deadline'. In prior and later 1.x versions it already defaults to 'fifo'.

  • hbase.hregion.memstore.chunkpool.maxsize is 1.0 by default. Previously it was 0.0. Effectively, this means previously we would not use a chunk pool when our memstore is onheap and now we will. See the section Long GC pauses for more information about the MSLAB chunk pool.

  • hbase.master.cleaner.interval is now set to 10 minutes. Previously it was 1 minute.

  • hbase.master.procedure.threads will now default to 1/4 of the number of available CPUs, but not less than 16 threads. Previously it would be number of threads equal to number of CPUs.

  • hbase.hstore.blockingStoreFiles is now 16. Previously it was 10.

  • hbase.http.max.threads is now 16. Previously it was 10.

  • hbase.client.max.perserver.tasks is now 2. Previously it was 5.

  • hbase.normalizer.period is now 5 minutes. Previously it was 30 minutes.

  • hbase.regionserver.region.split.policy is now SteppingSplitPolicy. Previously it was IncreasingToUpperBoundRegionSplitPolicy.

  • replication.source.ratio is now 0.5. Previously it was 0.1.

"Master hosting regions" feature broken and unsupported

The feature "Master acts as region server" and associated follow-on work available in HBase 1.y is non-functional in HBase 2.y and should not be used in a production setting due to deadlock on Master initialization. Downstream users are advised to treat related configuration settings as experimental and the feature as inappropriate for production settings.

A brief summary of related changes:

  • Master no longer carries regions by default

  • hbase.balancer.tablesOnMaster is a boolean, default false (if it holds an HBase 1.x list of tables, will default to false)

  • hbase.balancer.tablesOnMaster.systemTablesOnly is boolean to keep user tables off master. default false

  • those wishing to replicate old list-of-servers config should deploy a stand-alone RegionServer process and then rel