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Posted to commits@hbase.apache.org by st...@apache.org on 2014/05/28 16:58:59 UTC
[01/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Repository: hbase
Updated Branches:
refs/heads/master ab896f05d -> 63e8304e9
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/zookeeper.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/zookeeper.xml b/src/main/docbkx/zookeeper.xml
index d4d8774..2c80978 100644
--- a/src/main/docbkx/zookeeper.xml
+++ b/src/main/docbkx/zookeeper.xml
@@ -1,13 +1,15 @@
<?xml version="1.0"?>
- <chapter xml:id="zookeeper"
- version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ xml:id="zookeeper"
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -27,474 +29,394 @@
*/
-->
- <title>ZooKeeper<indexterm>
- <primary>ZooKeeper</primary>
- </indexterm></title>
-
- <para>A distributed Apache HBase installation depends on a running ZooKeeper cluster.
- All participating nodes and clients need to be able to access the
- running ZooKeeper ensemble. Apache HBase by default manages a ZooKeeper
- "cluster" for you. It will start and stop the ZooKeeper ensemble
- as part of the HBase start/stop process. You can also manage the
- ZooKeeper ensemble independent of HBase and just point HBase at
- the cluster it should use. To toggle HBase management of
- ZooKeeper, use the <varname>HBASE_MANAGES_ZK</varname> variable in
- <filename>conf/hbase-env.sh</filename>. This variable, which
- defaults to <varname>true</varname>, tells HBase whether to
- start/stop the ZooKeeper ensemble servers as part of HBase
- start/stop.</para>
-
- <para>When HBase manages the ZooKeeper ensemble, you can specify
- ZooKeeper configuration using its native
- <filename>zoo.cfg</filename> file, or, the easier option is to
- just specify ZooKeeper options directly in
- <filename>conf/hbase-site.xml</filename>. A ZooKeeper
- configuration option can be set as a property in the HBase
- <filename>hbase-site.xml</filename> XML configuration file by
- prefacing the ZooKeeper option name with
- <varname>hbase.zookeeper.property</varname>. For example, the
- <varname>clientPort</varname> setting in ZooKeeper can be changed
- by setting the
- <varname>hbase.zookeeper.property.clientPort</varname> property.
- For all default values used by HBase, including ZooKeeper
- configuration, see <xref linkend="hbase_default_configurations" />. Look for the
- <varname>hbase.zookeeper.property</varname> prefix <footnote>
- <para>For the full list of ZooKeeper configurations, see
- ZooKeeper's <filename>zoo.cfg</filename>. HBase does not ship
- with a <filename>zoo.cfg</filename> so you will need to browse
- the <filename>conf</filename> directory in an appropriate
- ZooKeeper download.</para>
- </footnote></para>
-
- <para>You must at least list the ensemble servers in
- <filename>hbase-site.xml</filename> using the
- <varname>hbase.zookeeper.quorum</varname> property. This property
- defaults to a single ensemble member at
- <varname>localhost</varname> which is not suitable for a fully
- distributed HBase. (It binds to the local machine only and remote
- clients will not be able to connect). <note xml:id="how_many_zks">
- <title>How many ZooKeepers should I run?</title>
-
- <para>You can run a ZooKeeper ensemble that comprises 1 node
- only but in production it is recommended that you run a
- ZooKeeper ensemble of 3, 5 or 7 machines; the more members an
- ensemble has, the more tolerant the ensemble is of host
- failures. Also, run an odd number of machines. In ZooKeeper,
- an even number of peers is supported, but it is normally not used
- because an even sized ensemble requires, proportionally, more peers
- to form a quorum than an odd sized ensemble requires. For example, an
- ensemble with 4 peers requires 3 to form a quorum, while an ensemble with
- 5 also requires 3 to form a quorum. Thus, an ensemble of 5 allows 2 peers to
- fail, and thus is more fault tolerant than the ensemble of 4, which allows
- only 1 down peer.
- </para>
- <para>Give each ZooKeeper server around 1GB of RAM, and if possible, its own
- dedicated disk (A dedicated disk is the best thing you can do
- to ensure a performant ZooKeeper ensemble). For very heavily
- loaded clusters, run ZooKeeper servers on separate machines
- from RegionServers (DataNodes and TaskTrackers).</para>
- </note></para>
-
- <para>For example, to have HBase manage a ZooKeeper quorum on
- nodes <emphasis>rs{1,2,3,4,5}.example.com</emphasis>, bound to
- port 2222 (the default is 2181) ensure
- <varname>HBASE_MANAGE_ZK</varname> is commented out or set to
- <varname>true</varname> in <filename>conf/hbase-env.sh</filename>
- and then edit <filename>conf/hbase-site.xml</filename> and set
- <varname>hbase.zookeeper.property.clientPort</varname> and
- <varname>hbase.zookeeper.quorum</varname>. You should also set
- <varname>hbase.zookeeper.property.dataDir</varname> to other than
- the default as the default has ZooKeeper persist data under
- <filename>/tmp</filename> which is often cleared on system
- restart. In the example below we have ZooKeeper persist to
- <filename>/user/local/zookeeper</filename>. <programlisting>
- <configuration>
+ <title>ZooKeeper<indexterm>
+ <primary>ZooKeeper</primary>
+ </indexterm></title>
+
+ <para>A distributed Apache HBase installation depends on a running ZooKeeper cluster. All
+ participating nodes and clients need to be able to access the running ZooKeeper ensemble. Apache
+ HBase by default manages a ZooKeeper "cluster" for you. It will start and stop the ZooKeeper
+ ensemble as part of the HBase start/stop process. You can also manage the ZooKeeper ensemble
+ independent of HBase and just point HBase at the cluster it should use. To toggle HBase
+ management of ZooKeeper, use the <varname>HBASE_MANAGES_ZK</varname> variable in
+ <filename>conf/hbase-env.sh</filename>. This variable, which defaults to
+ <varname>true</varname>, tells HBase whether to start/stop the ZooKeeper ensemble servers as
+ part of HBase start/stop.</para>
+
+ <para>When HBase manages the ZooKeeper ensemble, you can specify ZooKeeper configuration using its
+ native <filename>zoo.cfg</filename> file, or, the easier option is to just specify ZooKeeper
+ options directly in <filename>conf/hbase-site.xml</filename>. A ZooKeeper configuration option
+ can be set as a property in the HBase <filename>hbase-site.xml</filename> XML configuration file
+ by prefacing the ZooKeeper option name with <varname>hbase.zookeeper.property</varname>. For
+ example, the <varname>clientPort</varname> setting in ZooKeeper can be changed by setting the
+ <varname>hbase.zookeeper.property.clientPort</varname> property. For all default values used
+ by HBase, including ZooKeeper configuration, see <xref
+ linkend="hbase_default_configurations" />. Look for the
+ <varname>hbase.zookeeper.property</varname> prefix <footnote>
+ <para>For the full list of ZooKeeper configurations, see ZooKeeper's
+ <filename>zoo.cfg</filename>. HBase does not ship with a <filename>zoo.cfg</filename> so
+ you will need to browse the <filename>conf</filename> directory in an appropriate ZooKeeper
+ download.</para>
+ </footnote></para>
+
+ <para>You must at least list the ensemble servers in <filename>hbase-site.xml</filename> using the
+ <varname>hbase.zookeeper.quorum</varname> property. This property defaults to a single
+ ensemble member at <varname>localhost</varname> which is not suitable for a fully distributed
+ HBase. (It binds to the local machine only and remote clients will not be able to connect). </para>
+ <note
+ xml:id="how_many_zks">
+ <title>How many ZooKeepers should I run?</title>
+
+ <para>You can run a ZooKeeper ensemble that comprises 1 node only but in production it is
+ recommended that you run a ZooKeeper ensemble of 3, 5 or 7 machines; the more members an
+ ensemble has, the more tolerant the ensemble is of host failures. Also, run an odd number of
+ machines. In ZooKeeper, an even number of peers is supported, but it is normally not used
+ because an even sized ensemble requires, proportionally, more peers to form a quorum than an
+ odd sized ensemble requires. For example, an ensemble with 4 peers requires 3 to form a
+ quorum, while an ensemble with 5 also requires 3 to form a quorum. Thus, an ensemble of 5
+ allows 2 peers to fail, and thus is more fault tolerant than the ensemble of 4, which allows
+ only 1 down peer. </para>
+ <para>Give each ZooKeeper server around 1GB of RAM, and if possible, its own dedicated disk (A
+ dedicated disk is the best thing you can do to ensure a performant ZooKeeper ensemble). For
+ very heavily loaded clusters, run ZooKeeper servers on separate machines from RegionServers
+ (DataNodes and TaskTrackers).</para>
+ </note>
+
+ <para>For example, to have HBase manage a ZooKeeper quorum on nodes
+ <emphasis>rs{1,2,3,4,5}.example.com</emphasis>, bound to port 2222 (the default is 2181)
+ ensure <varname>HBASE_MANAGE_ZK</varname> is commented out or set to <varname>true</varname> in
+ <filename>conf/hbase-env.sh</filename> and then edit <filename>conf/hbase-site.xml</filename>
+ and set <varname>hbase.zookeeper.property.clientPort</varname> and
+ <varname>hbase.zookeeper.quorum</varname>. You should also set
+ <varname>hbase.zookeeper.property.dataDir</varname> to other than the default as the default
+ has ZooKeeper persist data under <filename>/tmp</filename> which is often cleared on system
+ restart. In the example below we have ZooKeeper persist to
+ <filename>/user/local/zookeeper</filename>.</para>
+ <programlisting><![CDATA[
+ <configuration>
...
- <property>
- <name>hbase.zookeeper.property.clientPort</name>
- <value>2222</value>
- <description>Property from ZooKeeper's config zoo.cfg.
+ <property>
+ <name>hbase.zookeeper.property.clientPort</name>
+ <value>2222</value>
+ <description>Property from ZooKeeper's config zoo.cfg.
The port at which the clients will connect.
- </description>
- </property>
- <property>
- <name>hbase.zookeeper.quorum</name>
- <value>rs1.example.com,rs2.example.com,rs3.example.com,rs4.example.com,rs5.example.com</value>
- <description>Comma separated list of servers in the ZooKeeper Quorum.
+ </description>
+ </property>
+ <property>
+ <name>hbase.zookeeper.quorum</name>
+ <value>rs1.example.com,rs2.example.com,rs3.example.com,rs4.example.com,rs5.example.com</value>
+ <description>Comma separated list of servers in the ZooKeeper Quorum.
For example, "host1.mydomain.com,host2.mydomain.com,host3.mydomain.com".
By default this is set to localhost for local and pseudo-distributed modes
of operation. For a fully-distributed setup, this should be set to a full
list of ZooKeeper quorum servers. If HBASE_MANAGES_ZK is set in hbase-env.sh
this is the list of servers which we will start/stop ZooKeeper on.
- </description>
- </property>
- <property>
- <name>hbase.zookeeper.property.dataDir</name>
- <value>/usr/local/zookeeper</value>
- <description>Property from ZooKeeper's config zoo.cfg.
+ </description>
+ </property>
+ <property>
+ <name>hbase.zookeeper.property.dataDir</name>
+ <value>/usr/local/zookeeper</value>
+ <description>Property from ZooKeeper's config zoo.cfg.
The directory where the snapshot is stored.
- </description>
- </property>
+ </description>
+ </property>
...
- </configuration></programlisting></para>
- <caution xml:id="zk.version">
- <title>What verion of ZooKeeper should I use?</title>
- <para>The newer version, the better. For example, some folks have been bitten by
- <link xlink:href="https://issues.apache.org/jira/browse/ZOOKEEPER-1277">ZOOKEEPER-1277</link>.
- If running zookeeper 3.5+, you can ask hbase to make use of the new multi operation by
- enabling <xref linkend="hbase.zookeeper.useMulti"/>" in your <filename>hbase-site.xml</filename>.
- </para>
+ </configuration>]]></programlisting>
+ <caution
+ xml:id="zk.version">
+ <title>What verion of ZooKeeper should I use?</title>
+ <para>The newer version, the better. For example, some folks have been bitten by <link
+ xlink:href="https://issues.apache.org/jira/browse/ZOOKEEPER-1277">ZOOKEEPER-1277</link>. If
+ running zookeeper 3.5+, you can ask hbase to make use of the new multi operation by enabling <xref
+ linkend="hbase.zookeeper.useMulti" />" in your <filename>hbase-site.xml</filename>. </para>
</caution>
<caution>
- <title>ZooKeeper Maintenance</title>
- <para>Be sure to set up the data dir cleaner described under
- <link xlink:href="http://zookeeper.apache.org/doc/r3.1.2/zookeeperAdmin.html#sc_maintenance">Zookeeper Maintenance</link> else you could
- have 'interesting' problems a couple of months in; i.e. zookeeper could start
- dropping sessions if it has to run through a directory of hundreds of thousands of
- logs which is wont to do around leader reelection time -- a process rare but run on
- occasion whether because a machine is dropped or happens to hiccup.</para>
+ <title>ZooKeeper Maintenance</title>
+ <para>Be sure to set up the data dir cleaner described under <link
+ xlink:href="http://zookeeper.apache.org/doc/r3.1.2/zookeeperAdmin.html#sc_maintenance">Zookeeper
+ Maintenance</link> else you could have 'interesting' problems a couple of months in; i.e.
+ zookeeper could start dropping sessions if it has to run through a directory of hundreds of
+ thousands of logs which is wont to do around leader reelection time -- a process rare but run
+ on occasion whether because a machine is dropped or happens to hiccup.</para>
</caution>
- <section>
- <title>Using existing ZooKeeper ensemble</title>
+ <section>
+ <title>Using existing ZooKeeper ensemble</title>
- <para>To point HBase at an existing ZooKeeper cluster, one that
- is not managed by HBase, set <varname>HBASE_MANAGES_ZK</varname>
- in <filename>conf/hbase-env.sh</filename> to false
- <programlisting>
+ <para>To point HBase at an existing ZooKeeper cluster, one that is not managed by HBase, set
+ <varname>HBASE_MANAGES_ZK</varname> in <filename>conf/hbase-env.sh</filename> to
+ false</para>
+ <screen>
...
# Tell HBase whether it should manage its own instance of Zookeeper or not.
- export HBASE_MANAGES_ZK=false</programlisting> Next set ensemble locations
- and client port, if non-standard, in
- <filename>hbase-site.xml</filename>, or add a suitably
- configured <filename>zoo.cfg</filename> to HBase's
- <filename>CLASSPATH</filename>. HBase will prefer the
- configuration found in <filename>zoo.cfg</filename> over any
- settings in <filename>hbase-site.xml</filename>.</para>
-
- <para>When HBase manages ZooKeeper, it will start/stop the
- ZooKeeper servers as a part of the regular start/stop scripts.
- If you would like to run ZooKeeper yourself, independent of
- HBase start/stop, you would do the following</para>
-
- <programlisting>
+ export HBASE_MANAGES_ZK=false</screen>
+ <para>Next set ensemble locations and client port, if non-standard, in
+ <filename>hbase-site.xml</filename>, or add a suitably configured
+ <filename>zoo.cfg</filename> to HBase's <filename>CLASSPATH</filename>. HBase will prefer
+ the configuration found in <filename>zoo.cfg</filename> over any settings in
+ <filename>hbase-site.xml</filename>.</para>
+
+ <para>When HBase manages ZooKeeper, it will start/stop the ZooKeeper servers as a part of the
+ regular start/stop scripts. If you would like to run ZooKeeper yourself, independent of HBase
+ start/stop, you would do the following</para>
+
+ <screen>
${HBASE_HOME}/bin/hbase-daemons.sh {start,stop} zookeeper
-</programlisting>
-
- <para>Note that you can use HBase in this manner to spin up a
- ZooKeeper cluster, unrelated to HBase. Just make sure to set
- <varname>HBASE_MANAGES_ZK</varname> to <varname>false</varname>
- if you want it to stay up across HBase restarts so that when
- HBase shuts down, it doesn't take ZooKeeper down with it.</para>
-
- <para>For more information about running a distinct ZooKeeper
- cluster, see the ZooKeeper <link
- xlink:href="http://hadoop.apache.org/zookeeper/docs/current/zookeeperStarted.html">Getting
- Started Guide</link>. Additionally, see the <link xlink:href="http://wiki.apache.org/hadoop/ZooKeeper/FAQ#A7">ZooKeeper Wiki</link> or the
- <link xlink:href="http://zookeeper.apache.org/doc/r3.3.3/zookeeperAdmin.html#sc_zkMulitServerSetup">ZooKeeper documentation</link>
- for more information on ZooKeeper sizing.
- </para>
- </section>
-
-
- <section xml:id="zk.sasl.auth">
- <title>SASL Authentication with ZooKeeper</title>
- <para>Newer releases of Apache HBase (>= 0.92) will
- support connecting to a ZooKeeper Quorum that supports
- SASL authentication (which is available in Zookeeper
- versions 3.4.0 or later).</para>
-
- <para>This describes how to set up HBase to mutually
- authenticate with a ZooKeeper Quorum. ZooKeeper/HBase
- mutual authentication (<link
- xlink:href="https://issues.apache.org/jira/browse/HBASE-2418">HBASE-2418</link>)
- is required as part of a complete secure HBase configuration
- (<link
- xlink:href="https://issues.apache.org/jira/browse/HBASE-3025">HBASE-3025</link>).
-
- For simplicity of explication, this section ignores
- additional configuration required (Secure HDFS and Coprocessor
- configuration). It's recommended to begin with an
- HBase-managed Zookeeper configuration (as opposed to a
- standalone Zookeeper quorum) for ease of learning.
- </para>
-
- <section><title>Operating System Prerequisites</title>
-
- <para>
- You need to have a working Kerberos KDC setup. For
- each <code>$HOST</code> that will run a ZooKeeper
- server, you should have a principle
- <code>zookeeper/$HOST</code>. For each such host,
- add a service key (using the <code>kadmin</code> or
- <code>kadmin.local</code> tool's <code>ktadd</code>
- command) for <code>zookeeper/$HOST</code> and copy
- this file to <code>$HOST</code>, and make it
- readable only to the user that will run zookeeper on
- <code>$HOST</code>. Note the location of this file,
- which we will use below as
- <filename>$PATH_TO_ZOOKEEPER_KEYTAB</filename>.
- </para>
-
- <para>
- Similarly, for each <code>$HOST</code> that will run
- an HBase server (master or regionserver), you should
- have a principle: <code>hbase/$HOST</code>. For each
- host, add a keytab file called
- <filename>hbase.keytab</filename> containing a service
- key for <code>hbase/$HOST</code>, copy this file to
- <code>$HOST</code>, and make it readable only to the
- user that will run an HBase service on
- <code>$HOST</code>. Note the location of this file,
- which we will use below as
- <filename>$PATH_TO_HBASE_KEYTAB</filename>.
- </para>
-
- <para>
- Each user who will be an HBase client should also be
- given a Kerberos principal. This principal should
- usually have a password assigned to it (as opposed to,
- as with the HBase servers, a keytab file) which only
- this user knows. The client's principal's
- <code>maxrenewlife</code> should be set so that it can
- be renewed enough so that the user can complete their
- HBase client processes. For example, if a user runs a
- long-running HBase client process that takes at most 3
- days, we might create this user's principal within
- <code>kadmin</code> with: <code>addprinc -maxrenewlife
- 3days</code>. The Zookeeper client and server
- libraries manage their own ticket refreshment by
- running threads that wake up periodically to do the
- refreshment.
- </para>
-
- <para>On each host that will run an HBase client
- (e.g. <code>hbase shell</code>), add the following
- file to the HBase home directory's <filename>conf</filename>
- directory:</para>
-
- <programlisting>
- Client {
- com.sun.security.auth.module.Krb5LoginModule required
- useKeyTab=false
- useTicketCache=true;
- };
+</screen>
+
+ <para>Note that you can use HBase in this manner to spin up a ZooKeeper cluster, unrelated to
+ HBase. Just make sure to set <varname>HBASE_MANAGES_ZK</varname> to <varname>false</varname>
+ if you want it to stay up across HBase restarts so that when HBase shuts down, it doesn't take
+ ZooKeeper down with it.</para>
+
+ <para>For more information about running a distinct ZooKeeper cluster, see the ZooKeeper <link
+ xlink:href="http://hadoop.apache.org/zookeeper/docs/current/zookeeperStarted.html">Getting
+ Started Guide</link>. Additionally, see the <link
+ xlink:href="http://wiki.apache.org/hadoop/ZooKeeper/FAQ#A7">ZooKeeper Wiki</link> or the <link
+ xlink:href="http://zookeeper.apache.org/doc/r3.3.3/zookeeperAdmin.html#sc_zkMulitServerSetup">ZooKeeper
+ documentation</link> for more information on ZooKeeper sizing. </para>
+ </section>
+
+
+ <section
+ xml:id="zk.sasl.auth">
+ <title>SASL Authentication with ZooKeeper</title>
+ <para>Newer releases of Apache HBase (>= 0.92) will support connecting to a ZooKeeper Quorum
+ that supports SASL authentication (which is available in Zookeeper versions 3.4.0 or
+ later).</para>
+
+ <para>This describes how to set up HBase to mutually authenticate with a ZooKeeper Quorum.
+ ZooKeeper/HBase mutual authentication (<link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-2418">HBASE-2418</link>) is required
+ as part of a complete secure HBase configuration (<link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-3025">HBASE-3025</link>). For
+ simplicity of explication, this section ignores additional configuration required (Secure HDFS
+ and Coprocessor configuration). It's recommended to begin with an HBase-managed Zookeeper
+ configuration (as opposed to a standalone Zookeeper quorum) for ease of learning. </para>
+
+ <section>
+ <title>Operating System Prerequisites</title>
+
+ <para> You need to have a working Kerberos KDC setup. For each <code>$HOST</code> that will
+ run a ZooKeeper server, you should have a principle <code>zookeeper/$HOST</code>. For each
+ such host, add a service key (using the <code>kadmin</code> or <code>kadmin.local</code>
+ tool's <code>ktadd</code> command) for <code>zookeeper/$HOST</code> and copy this file to
+ <code>$HOST</code>, and make it readable only to the user that will run zookeeper on
+ <code>$HOST</code>. Note the location of this file, which we will use below as
+ <filename>$PATH_TO_ZOOKEEPER_KEYTAB</filename>. </para>
+
+ <para> Similarly, for each <code>$HOST</code> that will run an HBase server (master or
+ regionserver), you should have a principle: <code>hbase/$HOST</code>. For each host, add a
+ keytab file called <filename>hbase.keytab</filename> containing a service key for
+ <code>hbase/$HOST</code>, copy this file to <code>$HOST</code>, and make it readable only
+ to the user that will run an HBase service on <code>$HOST</code>. Note the location of this
+ file, which we will use below as <filename>$PATH_TO_HBASE_KEYTAB</filename>. </para>
+
+ <para> Each user who will be an HBase client should also be given a Kerberos principal. This
+ principal should usually have a password assigned to it (as opposed to, as with the HBase
+ servers, a keytab file) which only this user knows. The client's principal's
+ <code>maxrenewlife</code> should be set so that it can be renewed enough so that the user
+ can complete their HBase client processes. For example, if a user runs a long-running HBase
+ client process that takes at most 3 days, we might create this user's principal within
+ <code>kadmin</code> with: <code>addprinc -maxrenewlife 3days</code>. The Zookeeper client
+ and server libraries manage their own ticket refreshment by running threads that wake up
+ periodically to do the refreshment. </para>
+
+ <para>On each host that will run an HBase client (e.g. <code>hbase shell</code>), add the
+ following file to the HBase home directory's <filename>conf</filename> directory:</para>
+
+ <programlisting>
+Client {
+ com.sun.security.auth.module.Krb5LoginModule required
+ useKeyTab=false
+ useTicketCache=true;
+};
</programlisting>
- <para>We'll refer to this JAAS configuration file as
- <filename>$CLIENT_CONF</filename> below.</para>
- </section>
- <section>
- <title>HBase-managed Zookeeper Configuration</title>
-
- <para>On each node that will run a zookeeper, a
- master, or a regionserver, create a <link
- xlink:href="http://docs.oracle.com/javase/1.4.2/docs/guide/security/jgss/tutorials/LoginConfigFile.html">JAAS</link>
- configuration file in the conf directory of the node's
- <filename>HBASE_HOME</filename> directory that looks like the
- following:</para>
-
- <programlisting>
- Server {
- com.sun.security.auth.module.Krb5LoginModule required
- useKeyTab=true
- keyTab="$PATH_TO_ZOOKEEPER_KEYTAB"
- storeKey=true
- useTicketCache=false
- principal="zookeeper/$HOST";
- };
- Client {
- com.sun.security.auth.module.Krb5LoginModule required
- useKeyTab=true
- useTicketCache=false
- keyTab="$PATH_TO_HBASE_KEYTAB"
- principal="hbase/$HOST";
- };
+ <para>We'll refer to this JAAS configuration file as <filename>$CLIENT_CONF</filename>
+ below.</para>
+ </section>
+ <section>
+ <title>HBase-managed Zookeeper Configuration</title>
+
+ <para>On each node that will run a zookeeper, a master, or a regionserver, create a <link
+ xlink:href="http://docs.oracle.com/javase/1.4.2/docs/guide/security/jgss/tutorials/LoginConfigFile.html">JAAS</link>
+ configuration file in the conf directory of the node's <filename>HBASE_HOME</filename>
+ directory that looks like the following:</para>
+
+ <programlisting>
+Server {
+ com.sun.security.auth.module.Krb5LoginModule required
+ useKeyTab=true
+ keyTab="$PATH_TO_ZOOKEEPER_KEYTAB"
+ storeKey=true
+ useTicketCache=false
+ principal="zookeeper/$HOST";
+};
+Client {
+ com.sun.security.auth.module.Krb5LoginModule required
+ useKeyTab=true
+ useTicketCache=false
+ keyTab="$PATH_TO_HBASE_KEYTAB"
+ principal="hbase/$HOST";
+};
</programlisting>
- <para>where the <filename>$PATH_TO_HBASE_KEYTAB</filename> and
- <filename>$PATH_TO_ZOOKEEPER_KEYTAB</filename> files are what
- you created above, and <code>$HOST</code> is the hostname for that
- node.</para>
-
- <para>The <code>Server</code> section will be used by
- the Zookeeper quorum server, while the
- <code>Client</code> section will be used by the HBase
- master and regionservers. The path to this file should
- be substituted for the text <filename>$HBASE_SERVER_CONF</filename>
- in the <filename>hbase-env.sh</filename>
- listing below.</para>
-
- <para>
- The path to this file should be substituted for the
- text <filename>$CLIENT_CONF</filename> in the
- <filename>hbase-env.sh</filename> listing below.
- </para>
-
- <para>Modify your <filename>hbase-env.sh</filename> to include the
- following:</para>
-
- <programlisting>
- export HBASE_OPTS="-Djava.security.auth.login.config=$CLIENT_CONF"
- export HBASE_MANAGES_ZK=true
- export HBASE_ZOOKEEPER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
- export HBASE_MASTER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
- export HBASE_REGIONSERVER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
- </programlisting>
+ <para>where the <filename>$PATH_TO_HBASE_KEYTAB</filename> and
+ <filename>$PATH_TO_ZOOKEEPER_KEYTAB</filename> files are what you created above, and
+ <code>$HOST</code> is the hostname for that node.</para>
- <para>where <filename>$HBASE_SERVER_CONF</filename> and
- <filename>$CLIENT_CONF</filename> are the full paths to the
- JAAS configuration files created above.</para>
-
- <para>Modify your <filename>hbase-site.xml</filename> on each node
- that will run zookeeper, master or regionserver to contain:</para>
-
- <programlisting><![CDATA[
- <configuration>
- <property>
- <name>hbase.zookeeper.quorum</name>
- <value>$ZK_NODES</value>
- </property>
- <property>
- <name>hbase.cluster.distributed</name>
- <value>true</value>
- </property>
- <property>
- <name>hbase.zookeeper.property.authProvider.1</name>
- <value>org.apache.zookeeper.server.auth.SASLAuthenticationProvider</value>
- </property>
- <property>
- <name>hbase.zookeeper.property.kerberos.removeHostFromPrincipal</name>
- <value>true</value>
- </property>
- <property>
- <name>hbase.zookeeper.property.kerberos.removeRealmFromPrincipal</name>
- <value>true</value>
- </property>
- </configuration>
- ]]></programlisting>
+ <para>The <code>Server</code> section will be used by the Zookeeper quorum server, while the
+ <code>Client</code> section will be used by the HBase master and regionservers. The path
+ to this file should be substituted for the text <filename>$HBASE_SERVER_CONF</filename> in
+ the <filename>hbase-env.sh</filename> listing below.</para>
- <para>where <code>$ZK_NODES</code> is the
- comma-separated list of hostnames of the Zookeeper
- Quorum hosts.</para>
+ <para> The path to this file should be substituted for the text
+ <filename>$CLIENT_CONF</filename> in the <filename>hbase-env.sh</filename> listing below. </para>
- <para>Start your hbase cluster by running one or more
- of the following set of commands on the appropriate
- hosts:
- </para>
+ <para>Modify your <filename>hbase-env.sh</filename> to include the following:</para>
- <programlisting>
- bin/hbase zookeeper start
- bin/hbase master start
- bin/hbase regionserver start
+ <programlisting>
+export HBASE_OPTS="-Djava.security.auth.login.config=$CLIENT_CONF"
+export HBASE_MANAGES_ZK=true
+export HBASE_ZOOKEEPER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
+export HBASE_MASTER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
+export HBASE_REGIONSERVER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
</programlisting>
- </section>
-
- <section><title>External Zookeeper Configuration</title>
- <para>Add a JAAS configuration file that looks like:
+ <para>where <filename>$HBASE_SERVER_CONF</filename> and <filename>$CLIENT_CONF</filename> are
+ the full paths to the JAAS configuration files created above.</para>
+
+ <para>Modify your <filename>hbase-site.xml</filename> on each node that will run zookeeper,
+ master or regionserver to contain:</para>
+
+ <programlisting><![CDATA[
+<configuration>
+ <property>
+ <name>hbase.zookeeper.quorum</name>
+ <value>$ZK_NODES</value>
+ </property>
+ <property>
+ <name>hbase.cluster.distributed</name>
+ <value>true</value>
+ </property>
+ <property>
+ <name>hbase.zookeeper.property.authProvider.1</name>
+ <value>org.apache.zookeeper.server.auth.SASLAuthenticationProvider</value>
+ </property>
+ <property>
+ <name>hbase.zookeeper.property.kerberos.removeHostFromPrincipal</name>
+ <value>true</value>
+ </property>
+ <property>
+ <name>hbase.zookeeper.property.kerberos.removeRealmFromPrincipal</name>
+ <value>true</value>
+ </property>
+</configuration>
+ ]]></programlisting>
- <programlisting>
- Client {
- com.sun.security.auth.module.Krb5LoginModule required
- useKeyTab=true
- useTicketCache=false
- keyTab="$PATH_TO_HBASE_KEYTAB"
- principal="hbase/$HOST";
- };
+ <para>where <code>$ZK_NODES</code> is the comma-separated list of hostnames of the Zookeeper
+ Quorum hosts.</para>
+
+ <para>Start your hbase cluster by running one or more of the following set of commands on the
+ appropriate hosts: </para>
+
+ <screen>
+bin/hbase zookeeper start
+bin/hbase master start
+bin/hbase regionserver start
+ </screen>
+
+ </section>
+
+ <section>
+ <title>External Zookeeper Configuration</title>
+ <para>Add a JAAS configuration file that looks like:</para>
+ <programlisting>
+Client {
+ com.sun.security.auth.module.Krb5LoginModule required
+ useKeyTab=true
+ useTicketCache=false
+ keyTab="$PATH_TO_HBASE_KEYTAB"
+ principal="hbase/$HOST";
+};
</programlisting>
-
- where the <filename>$PATH_TO_HBASE_KEYTAB</filename> is the keytab
- created above for HBase services to run on this host, and <code>$HOST</code> is the
- hostname for that node. Put this in the HBase home's
- configuration directory. We'll refer to this file's
- full pathname as <filename>$HBASE_SERVER_CONF</filename> below.</para>
-
- <para>Modify your hbase-env.sh to include the following:</para>
-
- <programlisting>
- export HBASE_OPTS="-Djava.security.auth.login.config=$CLIENT_CONF"
- export HBASE_MANAGES_ZK=false
- export HBASE_MASTER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
- export HBASE_REGIONSERVER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
+ <para>where the <filename>$PATH_TO_HBASE_KEYTAB</filename> is the keytab created above for
+ HBase services to run on this host, and <code>$HOST</code> is the hostname for that node.
+ Put this in the HBase home's configuration directory. We'll refer to this file's full
+ pathname as <filename>$HBASE_SERVER_CONF</filename> below.</para>
+
+ <para>Modify your hbase-env.sh to include the following:</para>
+
+ <programlisting>
+export HBASE_OPTS="-Djava.security.auth.login.config=$CLIENT_CONF"
+export HBASE_MANAGES_ZK=false
+export HBASE_MASTER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
+export HBASE_REGIONSERVER_OPTS="-Djava.security.auth.login.config=$HBASE_SERVER_CONF"
</programlisting>
- <para>Modify your <filename>hbase-site.xml</filename> on each node
- that will run a master or regionserver to contain:</para>
-
- <programlisting><![CDATA[
- <configuration>
- <property>
- <name>hbase.zookeeper.quorum</name>
- <value>$ZK_NODES</value>
- </property>
- <property>
- <name>hbase.cluster.distributed</name>
- <value>true</value>
- </property>
- </configuration>
+ <para>Modify your <filename>hbase-site.xml</filename> on each node that will run a master or
+ regionserver to contain:</para>
+
+ <programlisting><![CDATA[
+<configuration>
+ <property>
+ <name>hbase.zookeeper.quorum</name>
+ <value>$ZK_NODES</value>
+ </property>
+ <property>
+ <name>hbase.cluster.distributed</name>
+ <value>true</value>
+ </property>
+</configuration>
]]>
</programlisting>
- <para>where <code>$ZK_NODES</code> is the
- comma-separated list of hostnames of the Zookeeper
- Quorum hosts.</para>
+ <para>where <code>$ZK_NODES</code> is the comma-separated list of hostnames of the Zookeeper
+ Quorum hosts.</para>
- <para>
- Add a <filename>zoo.cfg</filename> for each Zookeeper Quorum host containing:
- <programlisting>
- authProvider.1=org.apache.zookeeper.server.auth.SASLAuthenticationProvider
- kerberos.removeHostFromPrincipal=true
- kerberos.removeRealmFromPrincipal=true
+ <para> Add a <filename>zoo.cfg</filename> for each Zookeeper Quorum host containing:</para>
+ <programlisting>
+authProvider.1=org.apache.zookeeper.server.auth.SASLAuthenticationProvider
+kerberos.removeHostFromPrincipal=true
+kerberos.removeRealmFromPrincipal=true
</programlisting>
-
- Also on each of these hosts, create a JAAS configuration file containing:
-
- <programlisting>
- Server {
- com.sun.security.auth.module.Krb5LoginModule required
- useKeyTab=true
- keyTab="$PATH_TO_ZOOKEEPER_KEYTAB"
- storeKey=true
- useTicketCache=false
- principal="zookeeper/$HOST";
- };
+ <para>Also on each of these hosts, create a JAAS configuration file containing:</para>
+ <programlisting>
+Server {
+ com.sun.security.auth.module.Krb5LoginModule required
+ useKeyTab=true
+ keyTab="$PATH_TO_ZOOKEEPER_KEYTAB"
+ storeKey=true
+ useTicketCache=false
+ principal="zookeeper/$HOST";
+};
</programlisting>
+ <para>where <code>$HOST</code> is the hostname of each Quorum host. We will refer to the full
+ pathname of this file as <filename>$ZK_SERVER_CONF</filename> below. </para>
- where <code>$HOST</code> is the hostname of each
- Quorum host. We will refer to the full pathname of
- this file as <filename>$ZK_SERVER_CONF</filename> below.
-
- </para>
-
- <para>
- Start your Zookeepers on each Zookeeper Quorum host with:
-
- <programlisting>
- SERVER_JVMFLAGS="-Djava.security.auth.login.config=$ZK_SERVER_CONF" bin/zkServer start
+ <para> Start your Zookeepers on each Zookeeper Quorum host with:</para>
+ <programlisting>
+SERVER_JVMFLAGS="-Djava.security.auth.login.config=$ZK_SERVER_CONF" bin/zkServer start
</programlisting>
- </para>
+ <para> Start your HBase cluster by running one or more of the following set of commands on the
+ appropriate nodes: </para>
- <para>
- Start your HBase cluster by running one or more of the following set of commands on the appropriate nodes:
- </para>
+ <screen>
+bin/hbase master start
+bin/hbase regionserver start
+ </screen>
- <programlisting>
- bin/hbase master start
- bin/hbase regionserver start
- </programlisting>
+ </section>
- </section>
-
- <section>
- <title>Zookeeper Server Authentication Log Output</title>
- <para>If the configuration above is successful,
- you should see something similar to the following in
- your Zookeeper server logs:
- <programlisting>
+ <section>
+ <title>Zookeeper Server Authentication Log Output</title>
+ <para>If the configuration above is successful, you should see something similar to the
+ following in your Zookeeper server logs:</para>
+ <screen>
11/12/05 22:43:39 INFO zookeeper.Login: successfully logged in.
11/12/05 22:43:39 INFO server.NIOServerCnxnFactory: binding to port 0.0.0.0/0.0.0.0:2181
11/12/05 22:43:39 INFO zookeeper.Login: TGT refresh thread started.
@@ -507,18 +429,15 @@ ${HBASE_HOME}/bin/hbase-daemons.sh {start,stop} zookeeper
authorizationID=hbase/ip-10-166-175-249.us-west-1.compute.internal@HADOOP.LOCALDOMAIN.
11/12/05 22:43:59 INFO auth.SaslServerCallbackHandler: Setting authorizedID: hbase
11/12/05 22:43:59 INFO server.ZooKeeperServer: adding SASL authorization for authorizationID: hbase
- </programlisting>
-
- </para>
+ </screen>
- </section>
+ </section>
- <section>
- <title>Zookeeper Client Authentication Log Output</title>
- <para>On the Zookeeper client side (HBase master or regionserver),
- you should see something similar to the following:
-
- <programlisting>
+ <section>
+ <title>Zookeeper Client Authentication Log Output</title>
+ <para>On the Zookeeper client side (HBase master or regionserver), you should see something
+ similar to the following:</para>
+ <screen>
11/12/05 22:43:59 INFO zookeeper.ZooKeeper: Initiating client connection, connectString=ip-10-166-175-249.us-west-1.compute.internal:2181 sessionTimeout=180000 watcher=master:60000
11/12/05 22:43:59 INFO zookeeper.ClientCnxn: Opening socket connection to server /10.166.175.249:2181
11/12/05 22:43:59 INFO zookeeper.RecoverableZooKeeper: The identifier of this process is 14851@ip-10-166-175-249
@@ -530,76 +449,67 @@ ${HBASE_HOME}/bin/hbase-daemons.sh {start,stop} zookeeper
11/12/05 22:43:59 INFO zookeeper.Login: TGT expires: Tue Dec 06 22:43:59 UTC 2011
11/12/05 22:43:59 INFO zookeeper.Login: TGT refresh sleeping until: Tue Dec 06 18:30:37 UTC 2011
11/12/05 22:43:59 INFO zookeeper.ClientCnxn: Session establishment complete on server ip-10-166-175-249.us-west-1.compute.internal/10.166.175.249:2181, sessionid = 0x134106594320000, negotiated timeout = 180000
- </programlisting>
- </para>
- </section>
+ </screen>
+ </section>
- <section>
- <title>Configuration from Scratch</title>
+ <section>
+ <title>Configuration from Scratch</title>
- <para>This has been tested on the current standard Amazon
- Linux AMI. First setup KDC and principals as
- described above. Next checkout code and run a sanity
- check.</para>
+ <para>This has been tested on the current standard Amazon Linux AMI. First setup KDC and
+ principals as described above. Next checkout code and run a sanity check.</para>
- <programlisting>
- git clone git://git.apache.org/hbase.git
- cd hbase
- mvn clean test -Dtest=TestZooKeeperACL
- </programlisting>
+ <screen>
+git clone git://git.apache.org/hbase.git
+cd hbase
+mvn clean test -Dtest=TestZooKeeperACL
+ </screen>
- <para>Then configure HBase as described above.
- Manually edit target/cached_classpath.txt (see below):
-</para>
- <programlisting>
- bin/hbase zookeeper &
- bin/hbase master &
- bin/hbase regionserver &
- </programlisting>
- </section>
-
-
- <section>
- <title>Future improvements</title>
+ <para>Then configure HBase as described above. Manually edit target/cached_classpath.txt (see
+ below): </para>
+ <screen>
+bin/hbase zookeeper &
+bin/hbase master &
+bin/hbase regionserver &
+ </screen>
+ </section>
- <section><title>Fix target/cached_classpath.txt</title>
- <para>
- You must override the standard hadoop-core jar file from the
- <code>target/cached_classpath.txt</code>
- file with the version containing the HADOOP-7070 fix. You can use the following script to do this:
-
- <programlisting>
- echo `find ~/.m2 -name "*hadoop-core*7070*SNAPSHOT.jar"` ':' `cat target/cached_classpath.txt` | sed 's/ //g' > target/tmp.txt
- mv target/tmp.txt target/cached_classpath.txt
- </programlisting>
- </para>
+ <section>
+ <title>Future improvements</title>
- </section>
+ <section>
+ <title>Fix target/cached_classpath.txt</title>
+ <para> You must override the standard hadoop-core jar file from the
+ <code>target/cached_classpath.txt</code> file with the version containing the
+ HADOOP-7070 fix. You can use the following script to do this:</para>
+ <screen>
+echo `find ~/.m2 -name "*hadoop-core*7070*SNAPSHOT.jar"` ':' `cat target/cached_classpath.txt` | sed 's/ //g' > target/tmp.txt
+mv target/tmp.txt target/cached_classpath.txt
+ </screen>
+ </section>
- <section>
- <title>Set JAAS configuration
- programmatically</title>
+ <section>
+ <title>Set JAAS configuration programmatically</title>
- <para>This would avoid the need for a separate Hadoop jar
- that fixes <link xlink:href="https://issues.apache.org/jira/browse/HADOOP-7070">HADOOP-7070</link>.
- </para>
- </section>
+ <para>This would avoid the need for a separate Hadoop jar that fixes <link
+ xlink:href="https://issues.apache.org/jira/browse/HADOOP-7070">HADOOP-7070</link>.
+ </para>
+ </section>
- <section>
- <title>Elimination of
- <code>kerberos.removeHostFromPrincipal</code> and
- <code>kerberos.removeRealmFromPrincipal</code></title>
- <para />
- </section>
+ <section>
+ <title>Elimination of <code>kerberos.removeHostFromPrincipal</code> and
+ <code>kerberos.removeRealmFromPrincipal</code></title>
+ <para />
+ </section>
- </section>
+ </section>
- </section> <!-- SASL Authentication with ZooKeeper -->
+ </section>
+ <!-- SASL Authentication with ZooKeeper -->
- </chapter>
+</chapter>
[12/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/case_studies.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/case_studies.xml b/src/main/docbkx/case_studies.xml
index 15169a8..262f0ee 100644
--- a/src/main/docbkx/case_studies.xml
+++ b/src/main/docbkx/case_studies.xml
@@ -1,5 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="casestudies"
+<chapter
+ version="5.0"
+ xml:id="casestudies"
xmlns="http://docbook.org/ns/docbook"
xmlns:xlink="http://www.w3.org/1999/xlink"
xmlns:xi="http://www.w3.org/2001/XInclude"
@@ -27,86 +29,123 @@
*/
-->
<title>Apache HBase Case Studies</title>
- <section xml:id="casestudies.overview">
+ <section
+ xml:id="casestudies.overview">
<title>Overview</title>
- <para>This chapter will describe a variety of performance and troubleshooting case studies that can
- provide a useful blueprint on diagnosing Apache HBase cluster issues.</para>
- <para>For more information on Performance and Troubleshooting, see <xref linkend="performance"/> and <xref linkend="trouble"/>.
- </para>
+ <para> This chapter will describe a variety of performance and troubleshooting case studies that
+ can provide a useful blueprint on diagnosing Apache HBase cluster issues. </para>
+ <para> For more information on Performance and Troubleshooting, see <xref
+ linkend="performance" /> and <xref
+ linkend="trouble" />. </para>
</section>
-
- <section xml:id="casestudies.schema">
+
+ <section
+ xml:id="casestudies.schema">
<title>Schema Design</title>
- <para>See the schema design case studies here: <xref linkend="schema.casestudies"/>
+ <para>See the schema design case studies here: <xref
+ linkend="schema.casestudies" />
</para>
-
- </section> <!-- schema design -->
-
- <section xml:id="casestudies.perftroub">
+
+ </section>
+ <!-- schema design -->
+
+ <section
+ xml:id="casestudies.perftroub">
<title>Performance/Troubleshooting</title>
-
- <section xml:id="casestudies.slownode">
+
+ <section
+ xml:id="casestudies.slownode">
<title>Case Study #1 (Performance Issue On A Single Node)</title>
- <section><title>Scenario</title>
- <para>Following a scheduled reboot, one data node began exhibiting unusual behavior. Routine MapReduce
- jobs run against HBase tables which regularly completed in five or six minutes began taking 30 or 40 minutes
- to finish. These jobs were consistently found to be waiting on map and reduce tasks assigned to the troubled data node
- (e.g., the slow map tasks all had the same Input Split).
- The situation came to a head during a distributed copy, when the copy was severely prolonged by the lagging node.
- </para>
+ <section>
+ <title>Scenario</title>
+ <para> Following a scheduled reboot, one data node began exhibiting unusual behavior.
+ Routine MapReduce jobs run against HBase tables which regularly completed in five or six
+ minutes began taking 30 or 40 minutes to finish. These jobs were consistently found to be
+ waiting on map and reduce tasks assigned to the troubled data node (e.g., the slow map
+ tasks all had the same Input Split). The situation came to a head during a distributed
+ copy, when the copy was severely prolonged by the lagging node. </para>
</section>
- <section><title>Hardware</title>
- <para>Datanodes:
- <itemizedlist>
- <listitem><para>Two 12-core processors</para></listitem>
- <listitem><para>Six Enerprise SATA disks</para></listitem>
- <listitem><para>24GB of RAM</para></listitem>
- <listitem><para>Two bonded gigabit NICs</para></listitem>
- </itemizedlist>
- </para>
- <para>Network:
- <itemizedlist>
- <listitem><para>10 Gigabit top-of-rack switches</para></listitem>
- <listitem><para>20 Gigabit bonded interconnects between racks.</para></listitem>
- </itemizedlist>
- </para>
+ <section>
+ <title>Hardware</title>
+ <itemizedlist>
+ <title>Datanodes:</title>
+ <listitem>
+ <para>Two 12-core processors</para>
+ </listitem>
+ <listitem>
+ <para>Six Enerprise SATA disks</para>
+ </listitem>
+ <listitem>
+ <para>24GB of RAM</para>
+ </listitem>
+ <listitem>
+ <para>Two bonded gigabit NICs</para>
+ </listitem>
+ </itemizedlist>
+ <itemizedlist>
+ <title>Network:</title>
+ <listitem>
+ <para>10 Gigabit top-of-rack switches</para>
+ </listitem>
+ <listitem>
+ <para>20 Gigabit bonded interconnects between racks.</para>
+ </listitem>
+ </itemizedlist>
</section>
- <section><title>Hypotheses</title>
- <section><title>HBase "Hot Spot" Region</title>
- <para>We hypothesized that we were experiencing a familiar point of pain: a "hot spot" region in an HBase table,
- where uneven key-space distribution can funnel a huge number of requests to a single HBase region, bombarding the RegionServer
- process and cause slow response time. Examination of the HBase Master status page showed that the number of HBase requests to the
- troubled node was almost zero. Further, examination of the HBase logs showed that there were no region splits, compactions, or other region transitions
- in progress. This effectively ruled out a "hot spot" as the root cause of the observed slowness.
- </para>
+ <section>
+ <title>Hypotheses</title>
+ <section>
+ <title>HBase "Hot Spot" Region</title>
+ <para> We hypothesized that we were experiencing a familiar point of pain: a "hot spot"
+ region in an HBase table, where uneven key-space distribution can funnel a huge number
+ of requests to a single HBase region, bombarding the RegionServer process and cause slow
+ response time. Examination of the HBase Master status page showed that the number of
+ HBase requests to the troubled node was almost zero. Further, examination of the HBase
+ logs showed that there were no region splits, compactions, or other region transitions
+ in progress. This effectively ruled out a "hot spot" as the root cause of the observed
+ slowness. </para>
+ </section>
+ <section>
+ <title>HBase Region With Non-Local Data</title>
+ <para> Our next hypothesis was that one of the MapReduce tasks was requesting data from
+ HBase that was not local to the datanode, thus forcing HDFS to request data blocks from
+ other servers over the network. Examination of the datanode logs showed that there were
+ very few blocks being requested over the network, indicating that the HBase region was
+ correctly assigned, and that the majority of the necessary data was located on the node.
+ This ruled out the possibility of non-local data causing a slowdown. </para>
+ </section>
+ <section>
+ <title>Excessive I/O Wait Due To Swapping Or An Over-Worked Or Failing Hard Disk</title>
+ <para> After concluding that the Hadoop and HBase were not likely to be the culprits, we
+ moved on to troubleshooting the datanode's hardware. Java, by design, will periodically
+ scan its entire memory space to do garbage collection. If system memory is heavily
+ overcommitted, the Linux kernel may enter a vicious cycle, using up all of its resources
+ swapping Java heap back and forth from disk to RAM as Java tries to run garbage
+ collection. Further, a failing hard disk will often retry reads and/or writes many times
+ before giving up and returning an error. This can manifest as high iowait, as running
+ processes wait for reads and writes to complete. Finally, a disk nearing the upper edge
+ of its performance envelope will begin to cause iowait as it informs the kernel that it
+ cannot accept any more data, and the kernel queues incoming data into the dirty write
+ pool in memory. However, using <code>vmstat(1)</code> and <code>free(1)</code>, we could
+ see that no swap was being used, and the amount of disk IO was only a few kilobytes per
+ second. </para>
</section>
- <section><title>HBase Region With Non-Local Data</title>
- <para>Our next hypothesis was that one of the MapReduce tasks was requesting data from HBase that was not local to the datanode, thus
- forcing HDFS to request data blocks from other servers over the network. Examination of the datanode logs showed that there were very
- few blocks being requested over the network, indicating that the HBase region was correctly assigned, and that the majority of the necessary
- data was located on the node. This ruled out the possibility of non-local data causing a slowdown.
- </para>
- </section>
- <section><title>Excessive I/O Wait Due To Swapping Or An Over-Worked Or Failing Hard Disk</title>
- <para>After concluding that the Hadoop and HBase were not likely to be the culprits, we moved on to troubleshooting the datanode's hardware.
- Java, by design, will periodically scan its entire memory space to do garbage collection. If system memory is heavily overcommitted, the Linux
- kernel may enter a vicious cycle, using up all of its resources swapping Java heap back and forth from disk to RAM as Java tries to run garbage
- collection. Further, a failing hard disk will often retry reads and/or writes many times before giving up and returning an error. This can manifest
- as high iowait, as running processes wait for reads and writes to complete. Finally, a disk nearing the upper edge of its performance envelope will
- begin to cause iowait as it informs the kernel that it cannot accept any more data, and the kernel queues incoming data into the dirty write pool in memory.
- However, using <code>vmstat(1)</code> and <code>free(1)</code>, we could see that no swap was being used, and the amount of disk IO was only a few kilobytes per second.
- </para>
+ <section>
+ <title>Slowness Due To High Processor Usage</title>
+ <para> Next, we checked to see whether the system was performing slowly simply due to very
+ high computational load. <code>top(1)</code> showed that the system load was higher than
+ normal, but <code>vmstat(1)</code> and <code>mpstat(1)</code> showed that the amount of
+ processor being used for actual computation was low. </para>
</section>
- <section><title>Slowness Due To High Processor Usage</title>
- <para>Next, we checked to see whether the system was performing slowly simply due to very high computational load. <code>top(1)</code> showed that the system load
- was higher than normal, but <code>vmstat(1)</code> and <code>mpstat(1)</code> showed that the amount of processor being used for actual computation was low.
- </para>
- </section>
- <section><title>Network Saturation (The Winner)</title>
- <para>Since neither the disks nor the processors were being utilized heavily, we moved on to the performance of the network interfaces. The datanode had two
- gigabit ethernet adapters, bonded to form an active-standby interface. <code>ifconfig(8)</code> showed some unusual anomalies, namely interface errors, overruns, framing errors.
- While not unheard of, these kinds of errors are exceedingly rare on modern hardware which is operating as it should:
- <programlisting>
+ <section>
+ <title>Network Saturation (The Winner)</title>
+ <para> Since neither the disks nor the processors were being utilized heavily, we moved on
+ to the performance of the network interfaces. The datanode had two gigabit ethernet
+ adapters, bonded to form an active-standby interface. <code>ifconfig(8)</code> showed
+ some unusual anomalies, namely interface errors, overruns, framing errors. While not
+ unheard of, these kinds of errors are exceedingly rare on modern hardware which is
+ operating as it should: </para>
+ <screen>
$ /sbin/ifconfig bond0
bond0 Link encap:Ethernet HWaddr 00:00:00:00:00:00
inet addr:10.x.x.x Bcast:10.x.x.255 Mask:255.255.255.0
@@ -115,12 +154,13 @@ RX packets:2990700159 errors:12 dropped:0 overruns:1 frame:6 <--- Lo
TX packets:3443518196 errors:0 dropped:0 overruns:0 carrier:0
collisions:0 txqueuelen:0
RX bytes:2416328868676 (2.4 TB) TX bytes:3464991094001 (3.4 TB)
-</programlisting>
- </para>
- <para>These errors immediately lead us to suspect that one or more of the ethernet interfaces might have negotiated the wrong line speed. This was confirmed both by running an ICMP ping
- from an external host and observing round-trip-time in excess of 700ms, and by running <code>ethtool(8)</code> on the members of the bond interface and discovering that the active interface
- was operating at 100Mbs/, full duplex.
- <programlisting>
+ </screen>
+ <para> These errors immediately lead us to suspect that one or more of the ethernet
+ interfaces might have negotiated the wrong line speed. This was confirmed both by
+ running an ICMP ping from an external host and observing round-trip-time in excess of
+ 700ms, and by running <code>ethtool(8)</code> on the members of the bond interface and
+ discovering that the active interface was operating at 100Mbs/, full duplex. </para>
+ <screen>
$ sudo ethtool eth0
Settings for eth0:
Supported ports: [ TP ]
@@ -147,45 +187,53 @@ Supports Wake-on: umbg
Wake-on: g
Current message level: 0x00000003 (3)
Link detected: yes
-</programlisting>
- </para>
- <para>In normal operation, the ICMP ping round trip time should be around 20ms, and the interface speed and duplex should read, "1000MB/s", and, "Full", respectively.
- </para>
+ </screen>
+ <para> In normal operation, the ICMP ping round trip time should be around 20ms, and the
+ interface speed and duplex should read, "1000MB/s", and, "Full", respectively. </para>
</section>
- </section>
- <section><title>Resolution</title>
- <para>After determining that the active ethernet adapter was at the incorrect speed, we used the <code>ifenslave(8)</code> command to make the standby interface
- the active interface, which yielded an immediate improvement in MapReduce performance, and a 10 times improvement in network throughput:
- </para>
- <para>On the next trip to the datacenter, we determined that the line speed issue was ultimately caused by a bad network cable, which was replaced.
- </para>
</section>
- </section> <!-- case study -->
- <section xml:id="casestudies.perf.1">
+ <section>
+ <title>Resolution</title>
+ <para> After determining that the active ethernet adapter was at the incorrect speed, we
+ used the <code>ifenslave(8)</code> command to make the standby interface the active
+ interface, which yielded an immediate improvement in MapReduce performance, and a 10 times
+ improvement in network throughput: </para>
+ <para> On the next trip to the datacenter, we determined that the line speed issue was
+ ultimately caused by a bad network cable, which was replaced. </para>
+ </section>
+ </section>
+ <!-- case study -->
+ <section
+ xml:id="casestudies.perf.1">
<title>Case Study #2 (Performance Research 2012)</title>
- <para>Investigation results of a self-described "we're not sure what's wrong, but it seems slow" problem.
- <link xlink:href="http://gbif.blogspot.com/2012/03/hbase-performance-evaluation-continued.html">http://gbif.blogspot.com/2012/03/hbase-performance-evaluation-continued.html</link>
+ <para> Investigation results of a self-described "we're not sure what's wrong, but it seems
+ slow" problem. <link
+ xlink:href="http://gbif.blogspot.com/2012/03/hbase-performance-evaluation-continued.html">http://gbif.blogspot.com/2012/03/hbase-performance-evaluation-continued.html</link>
</para>
</section>
-
- <section xml:id="casestudies.perf.2">
+
+ <section
+ xml:id="casestudies.perf.2">
<title>Case Study #3 (Performance Research 2010))</title>
- <para>
- Investigation results of general cluster performance from 2010. Although this research is on an older version of the codebase, this writeup
- is still very useful in terms of approach.
- <link xlink:href="http://hstack.org/hbase-performance-testing/">http://hstack.org/hbase-performance-testing/</link>
+ <para> Investigation results of general cluster performance from 2010. Although this research
+ is on an older version of the codebase, this writeup is still very useful in terms of
+ approach. <link
+ xlink:href="http://hstack.org/hbase-performance-testing/">http://hstack.org/hbase-performance-testing/</link>
</para>
</section>
-
- <section xml:id="casestudies.xceivers">
+
+ <section
+ xml:id="casestudies.xceivers">
<title>Case Study #4 (xcievers Config)</title>
- <para>Case study of configuring <code>xceivers</code>, and diagnosing errors from mis-configurations.
- <link xlink:href="http://www.larsgeorge.com/2012/03/hadoop-hbase-and-xceivers.html">http://www.larsgeorge.com/2012/03/hadoop-hbase-and-xceivers.html</link>
- </para>
- <para>See also <xref linkend="dfs.datanode.max.transfer.threads"/>.
+ <para> Case study of configuring <code>xceivers</code>, and diagnosing errors from
+ mis-configurations. <link
+ xlink:href="http://www.larsgeorge.com/2012/03/hadoop-hbase-and-xceivers.html">http://www.larsgeorge.com/2012/03/hadoop-hbase-and-xceivers.html</link>
</para>
+ <para> See also <xref
+ linkend="dfs.datanode.max.transfer.threads" />. </para>
</section>
-
- </section> <!-- performance/troubleshooting -->
-
+
+ </section>
+ <!-- performance/troubleshooting -->
+
</chapter>
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/community.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/community.xml b/src/main/docbkx/community.xml
index ae5573f..9bdaa39 100644
--- a/src/main/docbkx/community.xml
+++ b/src/main/docbkx/community.xml
@@ -1,13 +1,15 @@
<?xml version="1.0"?>
- <chapter xml:id="community"
- version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ xml:id="community"
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -26,132 +28,125 @@
* limitations under the License.
*/
-->
- <title>Community</title>
- <section xml:id="decisions">
- <title>Decisions</title>
- <section xml:id="feature_branches">
- <title>Feature Branches</title>
- <para>Feature Branches are easy to make. You do not have to be a committer to make one. Just request the name of your branch be added to JIRA up on the
- developer's mailing list and a committer will add it for you. Thereafter you can file issues against your feature branch in Apache HBase JIRA. Your code you
- keep elsewhere -- it should be public so it can be observed -- and you can update dev mailing list on progress. When the feature is ready for commit,
- 3 +1s from committers will get your feature merged<footnote><para>See <link xlink:href="http://search-hadoop.com/m/asM982C5FkS1">HBase, mail # dev - Thoughts about large feature dev branches</link></para></footnote>
- </para>
- </section>
- <section xml:id="patchplusonepolicy">
- <title>Patch +1 Policy</title>
- <para>
-The below policy is something we put in place 09/2012. It is a
-suggested policy rather than a hard requirement. We want to try it
-first to see if it works before we cast it in stone.
- </para>
-<para>
-Apache HBase is made of
-<link xlink:href="https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel">components</link>.
-Components have one or more <xref linkend="OWNER" />s. See the 'Description' field on the
-<link xlink:href="https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel">components</link>
-JIRA page for who the current owners are by component.
-</para>
-<para>
-Patches that fit within the scope of a single Apache HBase component require,
-at least, a +1 by one of the component's owners before commit. If
-owners are absent -- busy or otherwise -- two +1s by non-owners will
-suffice.
-</para>
-<para>
-Patches that span components need at least two +1s before they can be
-committed, preferably +1s by owners of components touched by the
-x-component patch (TODO: This needs tightening up but I think fine for
-first pass).
-</para>
-<para>
-Any -1 on a patch by anyone vetos a patch; it cannot be committed
-until the justification for the -1 is addressed.
-</para>
- </section>
- <section xml:id="hbase.fix.version.in.JIRA">
- <title>How to set fix version in JIRA on issue resolve</title>
- <para>Here is how <link xlink:href="http://search-hadoop.com/m/azemIi5RCJ1">we agreed</link> to set versions in JIRA when we
- resolve an issue. If trunk is going to be 0.98.0 then:
- <itemizedlist>
- <listitem><para>
- Commit only to trunk: Mark with 0.98
- </para></listitem>
- <listitem><para>
- Commit to 0.95 and trunk : Mark with 0.98, and 0.95.x
- </para></listitem>
- <listitem><para>
- Commit to 0.94.x and 0.95, and trunk: Mark with 0.98, 0.95.x, and 0.94.x
- </para></listitem>
- <listitem><para>
- Commit to 89-fb: Mark with 89-fb.
- </para></listitem>
- <listitem><para>
- Commit site fixes: no version
- </para></listitem>
- </itemizedlist>
- </para>
- </section>
- <section xml:id="hbase.when.to.close.JIRA">
- <title>Policy on when to set a RESOLVED JIRA as CLOSED</title>
- <para>We <link xlink:href="http://search-hadoop.com/m/4cIKs1iwXMS1">agreed</link>
- that for issues that list multiple releases in their <emphasis>Fix Version/s</emphasis> field,
- CLOSE the issue on the release of any of the versions listed; subsequent change
- to the issue must happen in a new JIRA.
- </para>
- </section>
- <section xml:id="no.permanent.state.in.zk">
- <title>Only transient state in ZooKeeper!</title>
- <para>
-You should be able to kill the data in zookeeper and hbase should ride over it recreating the zk content as it goes.
-This is an old adage around these parts. We just made note of it now. We also are currently in violation of this
-basic tenet -- replication at least keeps permanent state in zk -- but we are working to undo this breaking of a
-golden rule.
- </para>
- </section>
+ <title>Community</title>
+ <section
+ xml:id="decisions">
+ <title>Decisions</title>
+ <section
+ xml:id="feature_branches">
+ <title>Feature Branches</title>
+ <para>Feature Branches are easy to make. You do not have to be a committer to make one. Just
+ request the name of your branch be added to JIRA up on the developer's mailing list and a
+ committer will add it for you. Thereafter you can file issues against your feature branch in
+ Apache HBase JIRA. Your code you keep elsewhere -- it should be public so it can be observed
+ -- and you can update dev mailing list on progress. When the feature is ready for commit, 3
+ +1s from committers will get your feature merged<footnote>
+ <para>See <link
+ xlink:href="http://search-hadoop.com/m/asM982C5FkS1">HBase, mail # dev - Thoughts
+ about large feature dev branches</link></para>
+ </footnote>
+ </para>
+ </section>
+ <section
+ xml:id="patchplusonepolicy">
+ <title>Patch +1 Policy</title>
+ <para> The below policy is something we put in place 09/2012. It is a suggested policy rather
+ than a hard requirement. We want to try it first to see if it works before we cast it in
+ stone. </para>
+ <para> Apache HBase is made of <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel">components</link>.
+ Components have one or more <xref
+ linkend="OWNER" />s. See the 'Description' field on the <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel">components</link>
+ JIRA page for who the current owners are by component. </para>
+ <para> Patches that fit within the scope of a single Apache HBase component require, at least,
+ a +1 by one of the component's owners before commit. If owners are absent -- busy or
+ otherwise -- two +1s by non-owners will suffice. </para>
+ <para> Patches that span components need at least two +1s before they can be committed,
+ preferably +1s by owners of components touched by the x-component patch (TODO: This needs
+ tightening up but I think fine for first pass). </para>
+ <para> Any -1 on a patch by anyone vetos a patch; it cannot be committed until the
+ justification for the -1 is addressed. </para>
</section>
- <section xml:id="community.roles">
- <title>Community Roles</title>
- <section xml:id="OWNER">
- <title>Component Owner/Lieutenant</title>
- <para>
-Component owners are listed in the description field on this Apache HBase JIRA <link xlink:href="https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel">components</link>
-page. The owners are listed in the 'Description' field rather than in the 'Component
-Lead' field because the latter only allows us list one individual
-whereas it is encouraged that components have multiple owners.
- </para>
-<para>
-Owners or component lieutenants are volunteers who are (usually, but not necessarily) expert in
-their component domain and may have an agenda on how they think their
-Apache HBase component should evolve.
-</para>
-<para>
-Duties include:
-<orderedlist>
-<listitem>
-<para>
-Owners will try and review patches that land within their component's scope.
-</para>
-</listitem>
-<listitem>
-<para>
-If applicable, if an owner has an agenda, they will publish their
-goals or the design toward which they are driving their component
-</para>
-</listitem>
-</orderedlist>
-</para>
-<para>
-If you would like to be volunteer as a component owner, just write the
-dev list and we'll sign you up. Owners do not need to be committers.
-</para>
- </section>
+ <section
+ xml:id="hbase.fix.version.in.JIRA">
+ <title>How to set fix version in JIRA on issue resolve</title>
+ <para>Here is how <link
+ xlink:href="http://search-hadoop.com/m/azemIi5RCJ1">we agreed</link> to set versions in
+ JIRA when we resolve an issue. If trunk is going to be 0.98.0 then: </para>
+ <itemizedlist>
+ <listitem>
+ <para> Commit only to trunk: Mark with 0.98 </para>
+ </listitem>
+ <listitem>
+ <para> Commit to 0.95 and trunk : Mark with 0.98, and 0.95.x </para>
+ </listitem>
+ <listitem>
+ <para> Commit to 0.94.x and 0.95, and trunk: Mark with 0.98, 0.95.x, and 0.94.x </para>
+ </listitem>
+ <listitem>
+ <para> Commit to 89-fb: Mark with 89-fb. </para>
+ </listitem>
+ <listitem>
+ <para> Commit site fixes: no version </para>
+ </listitem>
+ </itemizedlist>
</section>
- <section xml:id="hbase.commit.msg.format">
- <title>Commit Message format</title>
- <para>We <link xlink:href="http://search-hadoop.com/m/Gwxwl10cFHa1">agreed</link>
- to the following SVN commit message format:
-<programlisting>HBASE-xxxxx <title>. (<contributor>)</programlisting>
-If the person making the commit is the contributor, leave off the '(<contributor>)' element.
+ <section
+ xml:id="hbase.when.to.close.JIRA">
+ <title>Policy on when to set a RESOLVED JIRA as CLOSED</title>
+ <para>We <link
+ xlink:href="http://search-hadoop.com/m/4cIKs1iwXMS1">agreed</link> that for issues that
+ list multiple releases in their <emphasis>Fix Version/s</emphasis> field, CLOSE the issue on
+ the release of any of the versions listed; subsequent change to the issue must happen in a
+ new JIRA. </para>
+ </section>
+ <section
+ xml:id="no.permanent.state.in.zk">
+ <title>Only transient state in ZooKeeper!</title>
+ <para> You should be able to kill the data in zookeeper and hbase should ride over it
+ recreating the zk content as it goes. This is an old adage around these parts. We just made
+ note of it now. We also are currently in violation of this basic tenet -- replication at
+ least keeps permanent state in zk -- but we are working to undo this breaking of a golden
+ rule. </para>
+ </section>
+ </section>
+ <section
+ xml:id="community.roles">
+ <title>Community Roles</title>
+ <section
+ xml:id="OWNER">
+ <title>Component Owner/Lieutenant</title>
+ <para> Component owners are listed in the description field on this Apache HBase JIRA <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE#selectedTab=com.atlassian.jira.plugin.system.project%3Acomponents-panel">components</link>
+ page. The owners are listed in the 'Description' field rather than in the 'Component Lead'
+ field because the latter only allows us list one individual whereas it is encouraged that
+ components have multiple owners. </para>
+ <para> Owners or component lieutenants are volunteers who are (usually, but not necessarily)
+ expert in their component domain and may have an agenda on how they think their Apache HBase
+ component should evolve. </para>
+ <orderedlist>
+ <title>Component Owner Duties</title>
+ <listitem>
+ <para> Owners will try and review patches that land within their component's scope.
</para>
- </section>
- </chapter>
+ </listitem>
+ <listitem>
+ <para> If applicable, if an owner has an agenda, they will publish their goals or the
+ design toward which they are driving their component </para>
+ </listitem>
+ </orderedlist>
+ <para> If you would like to be volunteer as a component owner, just write the dev list and
+ we'll sign you up. Owners do not need to be committers. </para>
+ </section>
+ </section>
+ <section
+ xml:id="hbase.commit.msg.format">
+ <title>Commit Message format</title>
+ <para>We <link
+ xlink:href="http://search-hadoop.com/m/Gwxwl10cFHa1">agreed</link> to the following SVN
+ commit message format:
+ <programlisting>HBASE-xxxxx <title>. (<contributor>)</programlisting> If the person
+ making the commit is the contributor, leave off the '(<contributor>)' element. </para>
+ </section>
+</chapter>
[03/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/troubleshooting.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/troubleshooting.xml b/src/main/docbkx/troubleshooting.xml
index 749d3fa..03a0659 100644
--- a/src/main/docbkx/troubleshooting.xml
+++ b/src/main/docbkx/troubleshooting.xml
@@ -1,13 +1,15 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="trouble"
- xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ version="5.0"
+ xml:id="trouble"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -27,100 +29,105 @@
*/
-->
<title>Troubleshooting and Debugging Apache HBase</title>
- <section xml:id="trouble.general">
- <title>General Guidelines</title>
- <para>
- Always start with the master log (TODO: Which lines?).
- Normally it’s just printing the same lines over and over again.
- If not, then there’s an issue.
- Google or <link xlink:href="http://search-hadoop.com">search-hadoop.com</link>
- should return some hits for those exceptions you’re seeing.
- </para>
- <para>
- An error rarely comes alone in Apache HBase, usually when something gets screwed up what will
- follow may be hundreds of exceptions and stack traces coming from all over the place.
- The best way to approach this type of problem is to walk the log up to where it all
- began, for example one trick with RegionServers is that they will print some
- metrics when aborting so grepping for <emphasis>Dump</emphasis>
- should get you around the start of the problem.
- </para>
- <para>
- RegionServer suicides are “normal”, as this is what they do when something goes wrong.
- For example, if ulimit and xcievers (the two most important initial settings, see <xref linkend="ulimit" />)
- aren’t changed, it will make it impossible at some point for DataNodes to create new threads
- that from the HBase point of view is seen as if HDFS was gone. Think about what would happen if your
- MySQL database was suddenly unable to access files on your local file system, well it’s the same with
- HBase and HDFS. Another very common reason to see RegionServers committing seppuku is when they enter
- prolonged garbage collection pauses that last longer than the default ZooKeeper session timeout.
- For more information on GC pauses, see the
- <link xlink:href="http://www.cloudera.com/blog/2011/02/avoiding-full-gcs-in-hbase-with-memstore-local-allocation-buffers-part-1/">3 part blog post</link> by Todd Lipcon
- and <xref linkend="gcpause" /> above.
- </para>
+ <section
+ xml:id="trouble.general">
+ <title>General Guidelines</title>
+ <para> Always start with the master log (TODO: Which lines?). Normally it’s just printing the
+ same lines over and over again. If not, then there’s an issue. Google or <link
+ xlink:href="http://search-hadoop.com">search-hadoop.com</link> should return some hits for
+ those exceptions you’re seeing. </para>
+ <para> An error rarely comes alone in Apache HBase, usually when something gets screwed up what
+ will follow may be hundreds of exceptions and stack traces coming from all over the place. The
+ best way to approach this type of problem is to walk the log up to where it all began, for
+ example one trick with RegionServers is that they will print some metrics when aborting so
+ grepping for <emphasis>Dump</emphasis> should get you around the start of the problem. </para>
+ <para> RegionServer suicides are “normal”, as this is what they do when something goes wrong.
+ For example, if ulimit and xcievers (the two most important initial settings, see <xref
+ linkend="ulimit" />) aren’t changed, it will make it impossible at some point for DataNodes
+ to create new threads that from the HBase point of view is seen as if HDFS was gone. Think
+ about what would happen if your MySQL database was suddenly unable to access files on your
+ local file system, well it’s the same with HBase and HDFS. Another very common reason to see
+ RegionServers committing seppuku is when they enter prolonged garbage collection pauses that
+ last longer than the default ZooKeeper session timeout. For more information on GC pauses, see
+ the <link
+ xlink:href="http://www.cloudera.com/blog/2011/02/avoiding-full-gcs-in-hbase-with-memstore-local-allocation-buffers-part-1/">3
+ part blog post</link> by Todd Lipcon and <xref
+ linkend="gcpause" /> above. </para>
+ </section>
+ <section
+ xml:id="trouble.log">
+ <title>Logs</title>
+ <para> The key process logs are as follows... (replace <user> with the user that started
+ the service, and <hostname> for the machine name) </para>
+ <para> NameNode:
+ <filename>$HADOOP_HOME/logs/hadoop-<user>-namenode-<hostname>.log</filename>
+ </para>
+ <para> DataNode:
+ <filename>$HADOOP_HOME/logs/hadoop-<user>-datanode-<hostname>.log</filename>
+ </para>
+ <para> JobTracker:
+ <filename>$HADOOP_HOME/logs/hadoop-<user>-jobtracker-<hostname>.log</filename>
+ </para>
+ <para> TaskTracker:
+ <filename>$HADOOP_HOME/logs/hadoop-<user>-tasktracker-<hostname>.log</filename>
+ </para>
+ <para> HMaster:
+ <filename>$HBASE_HOME/logs/hbase-<user>-master-<hostname>.log</filename>
+ </para>
+ <para> RegionServer:
+ <filename>$HBASE_HOME/logs/hbase-<user>-regionserver-<hostname>.log</filename>
+ </para>
+ <para> ZooKeeper: <filename>TODO</filename>
+ </para>
+ <section
+ xml:id="trouble.log.locations">
+ <title>Log Locations</title>
+ <para>For stand-alone deployments the logs are obviously going to be on a single machine,
+ however this is a development configuration only. Production deployments need to run on a
+ cluster.</para>
+ <section
+ xml:id="trouble.log.locations.namenode">
+ <title>NameNode</title>
+ <para>The NameNode log is on the NameNode server. The HBase Master is typically run on the
+ NameNode server, and well as ZooKeeper.</para>
+ <para>For smaller clusters the JobTracker is typically run on the NameNode server as
+ well.</para>
+ </section>
+ <section
+ xml:id="trouble.log.locations.datanode">
+ <title>DataNode</title>
+ <para>Each DataNode server will have a DataNode log for HDFS, as well as a RegionServer log
+ for HBase.</para>
+ <para>Additionally, each DataNode server will also have a TaskTracker log for MapReduce task
+ execution.</para>
+ </section>
</section>
- <section xml:id="trouble.log">
- <title>Logs</title>
- <para>
- The key process logs are as follows... (replace <user> with the user that started the service, and <hostname> for the machine name)
- </para>
- <para>
- NameNode: <filename>$HADOOP_HOME/logs/hadoop-<user>-namenode-<hostname>.log</filename>
- </para>
- <para>
- DataNode: <filename>$HADOOP_HOME/logs/hadoop-<user>-datanode-<hostname>.log</filename>
- </para>
- <para>
- JobTracker: <filename>$HADOOP_HOME/logs/hadoop-<user>-jobtracker-<hostname>.log</filename>
- </para>
- <para>
- TaskTracker: <filename>$HADOOP_HOME/logs/hadoop-<user>-tasktracker-<hostname>.log</filename>
- </para>
- <para>
- HMaster: <filename>$HBASE_HOME/logs/hbase-<user>-master-<hostname>.log</filename>
- </para>
- <para>
- RegionServer: <filename>$HBASE_HOME/logs/hbase-<user>-regionserver-<hostname>.log</filename>
- </para>
- <para>
- ZooKeeper: <filename>TODO</filename>
- </para>
- <section xml:id="trouble.log.locations">
- <title>Log Locations</title>
- <para>For stand-alone deployments the logs are obviously going to be on a single machine, however this is a development configuration only.
- Production deployments need to run on a cluster.</para>
- <section xml:id="trouble.log.locations.namenode">
- <title>NameNode</title>
- <para>The NameNode log is on the NameNode server. The HBase Master is typically run on the NameNode server, and well as ZooKeeper.</para>
- <para>For smaller clusters the JobTracker is typically run on the NameNode server as well.</para>
- </section>
- <section xml:id="trouble.log.locations.datanode">
- <title>DataNode</title>
- <para>Each DataNode server will have a DataNode log for HDFS, as well as a RegionServer log for HBase.</para>
- <para>Additionally, each DataNode server will also have a TaskTracker log for MapReduce task execution.</para>
- </section>
- </section>
- <section xml:id="trouble.log.levels">
- <title>Log Levels</title>
- <section xml:id="rpc.logging"><title>Enabling RPC-level logging</title>
- <para>Enabling the RPC-level logging on a RegionServer can often given
- insight on timings at the server. Once enabled, the amount of log
- spewed is voluminous. It is not recommended that you leave this
- logging on for more than short bursts of time. To enable RPC-level
- logging, browse to the RegionServer UI and click on
- <emphasis>Log Level</emphasis>. Set the log level to <varname>DEBUG</varname> for the package
- <classname>org.apache.hadoop.ipc</classname> (Thats right, for
- <classname>hadoop.ipc</classname>, NOT, <classname>hbase.ipc</classname>). Then tail the RegionServers log. Analyze.</para>
- <para>To disable, set the logging level back to <varname>INFO</varname> level.
- </para>
- </section>
- </section>
- <section xml:id="trouble.log.gc">
- <title>JVM Garbage Collection Logs</title>
- <para>HBase is memory intensive, and using the default GC you can see long pauses in all threads including the <emphasis>Juliet Pause</emphasis> aka "GC of Death".
- To help debug this or confirm this is happening GC logging can be turned on in the Java virtual machine.
- </para>
- <para>
- To enable, in <filename>hbase-env.sh</filename>, uncomment one of the below lines :
- <programlisting>
+ <section
+ xml:id="trouble.log.levels">
+ <title>Log Levels</title>
+ <section
+ xml:id="rpc.logging">
+ <title>Enabling RPC-level logging</title>
+ <para>Enabling the RPC-level logging on a RegionServer can often given insight on timings at
+ the server. Once enabled, the amount of log spewed is voluminous. It is not recommended
+ that you leave this logging on for more than short bursts of time. To enable RPC-level
+ logging, browse to the RegionServer UI and click on <emphasis>Log Level</emphasis>. Set
+ the log level to <varname>DEBUG</varname> for the package
+ <classname>org.apache.hadoop.ipc</classname> (Thats right, for
+ <classname>hadoop.ipc</classname>, NOT, <classname>hbase.ipc</classname>). Then tail the
+ RegionServers log. Analyze.</para>
+ <para>To disable, set the logging level back to <varname>INFO</varname> level. </para>
+ </section>
+ </section>
+ <section
+ xml:id="trouble.log.gc">
+ <title>JVM Garbage Collection Logs</title>
+ <para>HBase is memory intensive, and using the default GC you can see long pauses in all
+ threads including the <emphasis>Juliet Pause</emphasis> aka "GC of Death". To help debug
+ this or confirm this is happening GC logging can be turned on in the Java virtual machine. </para>
+ <para> To enable, in <filename>hbase-env.sh</filename>, uncomment one of the below lines
+ :</para>
+ <programlisting>
# This enables basic gc logging to the .out file.
# export SERVER_GC_OPTS="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps"
@@ -132,22 +139,18 @@
# If <FILE-PATH> is not replaced, the log file(.gc) would be generated in the HBASE_LOG_DIR.
</programlisting>
- </para>
- <para>
- At this point you should see logs like so:
- <programlisting>
+ <para> At this point you should see logs like so:</para>
+ <programlisting>
64898.952: [GC [1 CMS-initial-mark: 2811538K(3055704K)] 2812179K(3061272K), 0.0007360 secs] [Times: user=0.00 sys=0.00, real=0.00 secs]
64898.953: [CMS-concurrent-mark-start]
64898.971: [GC 64898.971: [ParNew: 5567K->576K(5568K), 0.0101110 secs] 2817105K->2812715K(3061272K), 0.0102200 secs] [Times: user=0.07 sys=0.00, real=0.01 secs]
</programlisting>
- </para>
- <para>
- In this section, the first line indicates a 0.0007360 second pause for the CMS to initially mark. This pauses the entire VM, all threads for that period of time.
- </para>
- <para>
- The third line indicates a "minor GC", which pauses the VM for 0.0101110 seconds - aka 10 milliseconds. It has reduced the "ParNew" from about 5.5m to 576k.
- Later on in this cycle we see:
- <programlisting>
+ <para> In this section, the first line indicates a 0.0007360 second pause for the CMS to
+ initially mark. This pauses the entire VM, all threads for that period of time. </para>
+ <para> The third line indicates a "minor GC", which pauses the VM for 0.0101110 seconds - aka
+ 10 milliseconds. It has reduced the "ParNew" from about 5.5m to 576k. Later on in this cycle
+ we see:</para>
+ <programlisting>
64901.445: [CMS-concurrent-mark: 1.542/2.492 secs] [Times: user=10.49 sys=0.33, real=2.49 secs]
64901.445: [CMS-concurrent-preclean-start]
64901.453: [GC 64901.453: [ParNew: 5505K->573K(5568K), 0.0062440 secs] 2868746K->2864292K(3061272K), 0.0063360 secs] [Times: user=0.05 sys=0.00, real=0.01 secs]
@@ -163,44 +166,40 @@
64901.616: [GC[YG occupancy: 645 K (5568 K)]64901.616: [Rescan (parallel) , 0.0020210 secs]64901.618: [weak refs processing, 0.0027950 secs] [1 CMS-remark: 2866753K(3055704K)] 2867399K(3061272K), 0.0049380 secs] [Times: user=0.00 sys=0.01, real=0.01 secs]
64901.621: [CMS-concurrent-sweep-start]
</programlisting>
- </para>
- <para>
- The first line indicates that the CMS concurrent mark (finding garbage) has taken 2.4 seconds. But this is a _concurrent_ 2.4 seconds, Java has not been paused at any point in time.
- </para>
- <para>
- There are a few more minor GCs, then there is a pause at the 2nd last line:
- <programlisting>
+ <para> The first line indicates that the CMS concurrent mark (finding garbage) has taken 2.4
+ seconds. But this is a _concurrent_ 2.4 seconds, Java has not been paused at any point in
+ time. </para>
+ <para> There are a few more minor GCs, then there is a pause at the 2nd last line:
+ <programlisting>
64901.616: [GC[YG occupancy: 645 K (5568 K)]64901.616: [Rescan (parallel) , 0.0020210 secs]64901.618: [weak refs processing, 0.0027950 secs] [1 CMS-remark: 2866753K(3055704K)] 2867399K(3061272K), 0.0049380 secs] [Times: user=0.00 sys=0.01, real=0.01 secs]
</programlisting>
- </para>
- <para>
- The pause here is 0.0049380 seconds (aka 4.9 milliseconds) to 'remark' the heap.
- </para>
- <para>
- At this point the sweep starts, and you can watch the heap size go down:
- <programlisting>
+ </para>
+ <para> The pause here is 0.0049380 seconds (aka 4.9 milliseconds) to 'remark' the heap. </para>
+ <para> At this point the sweep starts, and you can watch the heap size go down:</para>
+ <programlisting>
64901.637: [GC 64901.637: [ParNew: 5501K->569K(5568K), 0.0097350 secs] 2871958K->2867441K(3061272K), 0.0098370 secs] [Times: user=0.05 sys=0.00, real=0.01 secs]
... lines removed ...
64904.936: [GC 64904.936: [ParNew: 5532K->568K(5568K), 0.0070720 secs] 1365024K->1360689K(3061272K), 0.0071930 secs] [Times: user=0.05 sys=0.00, real=0.01 secs]
64904.953: [CMS-concurrent-sweep: 2.030/3.332 secs] [Times: user=9.57 sys=0.26, real=3.33 secs]
</programlisting>
- At this point, the CMS sweep took 3.332 seconds, and heap went from about ~ 2.8 GB to 1.3 GB (approximate).
- </para>
- <para>
- The key points here is to keep all these pauses low. CMS pauses are always low, but if your ParNew starts growing, you can see minor GC pauses approach 100ms, exceed 100ms and hit as high at 400ms.
- </para>
- <para>
- This can be due to the size of the ParNew, which should be relatively small. If your ParNew is very large after running HBase for a while, in one example a ParNew was about 150MB, then you might have to constrain the size of ParNew (The larger it is, the longer the collections take but if its too small, objects are promoted to old gen too quickly). In the below we constrain new gen size to 64m.
- </para>
- <para>
- Add the below line in <filename>hbase-env.sh</filename>:
- <programlisting>
+ <para>At this point, the CMS sweep took 3.332 seconds, and heap went from about ~ 2.8 GB to
+ 1.3 GB (approximate). </para>
+ <para> The key points here is to keep all these pauses low. CMS pauses are always low, but if
+ your ParNew starts growing, you can see minor GC pauses approach 100ms, exceed 100ms and hit
+ as high at 400ms. </para>
+ <para> This can be due to the size of the ParNew, which should be relatively small. If your
+ ParNew is very large after running HBase for a while, in one example a ParNew was about
+ 150MB, then you might have to constrain the size of ParNew (The larger it is, the longer the
+ collections take but if its too small, objects are promoted to old gen too quickly). In the
+ below we constrain new gen size to 64m. </para>
+ <para> Add the below line in <filename>hbase-env.sh</filename>:
+ <programlisting>
export SERVER_GC_OPTS="$SERVER_GC_OPTS -XX:NewSize=64m -XX:MaxNewSize=64m"
</programlisting>
- </para>
- <para>
- Similarly, to enable GC logging for client processes, uncomment one of the below lines in <filename>hbase-env.sh</filename>:
- <programlisting>
+ </para>
+ <para> Similarly, to enable GC logging for client processes, uncomment one of the below lines
+ in <filename>hbase-env.sh</filename>:</para>
+ <programlisting>
# This enables basic gc logging to the .out file.
# export CLIENT_GC_OPTS="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps"
@@ -212,77 +211,92 @@ export SERVER_GC_OPTS="$SERVER_GC_OPTS -XX:NewSize=64m -XX:MaxNewSize=64m"
# If <FILE-PATH> is not replaced, the log file(.gc) would be generated in the HBASE_LOG_DIR .
</programlisting>
- </para>
- <para>
- For more information on GC pauses, see the <link xlink:href="http://www.cloudera.com/blog/2011/02/avoiding-full-gcs-in-hbase-with-memstore-local-allocation-buffers-part-1/">3 part blog post</link> by Todd Lipcon
- and <xref linkend="gcpause" /> above.
- </para>
- </section>
+ <para> For more information on GC pauses, see the <link
+ xlink:href="http://www.cloudera.com/blog/2011/02/avoiding-full-gcs-in-hbase-with-memstore-local-allocation-buffers-part-1/">3
+ part blog post</link> by Todd Lipcon and <xref
+ linkend="gcpause" /> above. </para>
</section>
- <section xml:id="trouble.resources">
- <title>Resources</title>
- <section xml:id="trouble.resources.searchhadoop">
- <title>search-hadoop.com</title>
- <para>
- <link xlink:href="http://search-hadoop.com">search-hadoop.com</link> indexes all the mailing lists and is great for historical searches.
- Search here first when you have an issue as its more than likely someone has already had your problem.
- </para>
- </section>
- <section xml:id="trouble.resources.lists">
- <title>Mailing Lists</title>
- <para>Ask a question on the <link xlink:href="http://hbase.apache.org/mail-lists.html">Apache HBase mailing lists</link>.
- The 'dev' mailing list is aimed at the community of developers actually building Apache HBase and for features currently under development, and 'user'
- is generally used for questions on released versions of Apache HBase. Before going to the mailing list, make sure your
- question has not already been answered by searching the mailing list archives first. Use
- <xref linkend="trouble.resources.searchhadoop" />.
- Take some time crafting your question<footnote><para>See <link xlink:href="http://www.mikeash.com/getting_answers.html">Getting Answers</link></para></footnote>; a quality question that includes all context and
- exhibits evidence the author has tried to find answers in the manual and out on lists
- is more likely to get a prompt response.
- </para>
- </section>
- <section xml:id="trouble.resources.irc">
- <title>IRC</title>
- <para>#hbase on irc.freenode.net</para>
+ </section>
+ <section
+ xml:id="trouble.resources">
+ <title>Resources</title>
+ <section
+ xml:id="trouble.resources.searchhadoop">
+ <title>search-hadoop.com</title>
+ <para>
+ <link
+ xlink:href="http://search-hadoop.com">search-hadoop.com</link> indexes all the mailing
+ lists and is great for historical searches. Search here first when you have an issue as its
+ more than likely someone has already had your problem. </para>
+ </section>
+ <section
+ xml:id="trouble.resources.lists">
+ <title>Mailing Lists</title>
+ <para>Ask a question on the <link
+ xlink:href="http://hbase.apache.org/mail-lists.html">Apache HBase mailing lists</link>.
+ The 'dev' mailing list is aimed at the community of developers actually building Apache
+ HBase and for features currently under development, and 'user' is generally used for
+ questions on released versions of Apache HBase. Before going to the mailing list, make sure
+ your question has not already been answered by searching the mailing list archives first.
+ Use <xref
+ linkend="trouble.resources.searchhadoop" />. Take some time crafting your question<footnote>
+ <para>See <link
+ xlink:href="http://www.mikeash.com/getting_answers.html">Getting Answers</link></para>
+ </footnote>; a quality question that includes all context and exhibits evidence the author
+ has tried to find answers in the manual and out on lists is more likely to get a prompt
+ response. </para>
+ </section>
+ <section
+ xml:id="trouble.resources.irc">
+ <title>IRC</title>
+ <para>#hbase on irc.freenode.net</para>
+ </section>
+ <section
+ xml:id="trouble.resources.jira">
+ <title>JIRA</title>
+ <para>
+ <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE">JIRA</link> is also really
+ helpful when looking for Hadoop/HBase-specific issues. </para>
+ </section>
+ </section>
+ <section
+ xml:id="trouble.tools">
+ <title>Tools</title>
+ <section
+ xml:id="trouble.tools.builtin">
+ <title>Builtin Tools</title>
+ <section
+ xml:id="trouble.tools.builtin.webmaster">
+ <title>Master Web Interface</title>
+ <para>The Master starts a web-interface on port 16010 by default. (Up to and including 0.98
+ this was port 60010) </para>
+ <para>The Master web UI lists created tables and their definition (e.g., ColumnFamilies,
+ blocksize, etc.). Additionally, the available RegionServers in the cluster are listed
+ along with selected high-level metrics (requests, number of regions, usedHeap, maxHeap).
+ The Master web UI allows navigation to each RegionServer's web UI. </para>
</section>
- <section xml:id="trouble.resources.jira">
- <title>JIRA</title>
- <para>
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE">JIRA</link> is also really helpful when looking for Hadoop/HBase-specific issues.
- </para>
+ <section
+ xml:id="trouble.tools.builtin.webregion">
+ <title>RegionServer Web Interface</title>
+ <para>RegionServers starts a web-interface on port 16030 by default. (Up to an including
+ 0.98 this was port 60030) </para>
+ <para>The RegionServer web UI lists online regions and their start/end keys, as well as
+ point-in-time RegionServer metrics (requests, regions, storeFileIndexSize,
+ compactionQueueSize, etc.). </para>
+ <para>See <xref
+ linkend="hbase_metrics" /> for more information in metric definitions. </para>
</section>
- </section>
- <section xml:id="trouble.tools">
- <title>Tools</title>
- <section xml:id="trouble.tools.builtin">
- <title>Builtin Tools</title>
- <section xml:id="trouble.tools.builtin.webmaster">
- <title>Master Web Interface</title>
- <para>The Master starts a web-interface on port 16010 by default.
- (Up to and including 0.98 this was port 60010)
- </para>
- <para>The Master web UI lists created tables and their definition (e.g., ColumnFamilies, blocksize, etc.). Additionally,
- the available RegionServers in the cluster are listed along with selected high-level metrics (requests, number of regions, usedHeap, maxHeap).
- The Master web UI allows navigation to each RegionServer's web UI.
- </para>
- </section>
- <section xml:id="trouble.tools.builtin.webregion">
- <title>RegionServer Web Interface</title>
- <para>RegionServers starts a web-interface on port 16030 by default.
- (Up to an including 0.98 this was port 60030)
- </para>
- <para>The RegionServer web UI lists online regions and their start/end keys, as well as point-in-time RegionServer metrics (requests, regions, storeFileIndexSize, compactionQueueSize, etc.).
- </para>
- <para>See <xref linkend="hbase_metrics"/> for more information in metric definitions.
- </para>
- </section>
- <section xml:id="trouble.tools.builtin.zkcli">
- <title>zkcli</title>
- <para><code>zkcli</code> is a very useful tool for investigating ZooKeeper-related issues. To invoke:
-<programlisting>
+ <section
+ xml:id="trouble.tools.builtin.zkcli">
+ <title>zkcli</title>
+ <para><code>zkcli</code> is a very useful tool for investigating ZooKeeper-related issues.
+ To invoke:
+ <programlisting>
./hbase zkcli -server host:port <cmd> <args>
</programlisting>
- The commands (and arguments) are:
-<programlisting>
+ The commands (and arguments) are:</para>
+ <programlisting>
connect host:port
get path [watch]
ls path [watch]
@@ -304,21 +318,28 @@ export SERVER_GC_OPTS="$SERVER_GC_OPTS -XX:NewSize=64m -XX:MaxNewSize=64m"
delete path [version]
setquota -n|-b val path
</programlisting>
- </para>
- </section>
- </section>
- <section xml:id="trouble.tools.external">
- <title>External Tools</title>
- <section xml:id="trouble.tools.tail">
+ </section>
+ </section>
+ <section
+ xml:id="trouble.tools.external">
+ <title>External Tools</title>
+ <section
+ xml:id="trouble.tools.tail">
<title>tail</title>
<para>
- <code>tail</code> is the command line tool that lets you look at the end of a file. Add the “-f” option and it will refresh when new data is available. It’s useful when you are wondering what’s happening, for example, when a cluster is taking a long time to shutdown or startup as you can just fire a new terminal and tail the master log (and maybe a few RegionServers).
- </para>
+ <code>tail</code> is the command line tool that lets you look at the end of a file. Add
+ the “-f” option and it will refresh when new data is available. It’s useful when you are
+ wondering what’s happening, for example, when a cluster is taking a long time to shutdown
+ or startup as you can just fire a new terminal and tail the master log (and maybe a few
+ RegionServers). </para>
</section>
- <section xml:id="trouble.tools.top">
+ <section
+ xml:id="trouble.tools.top">
<title>top</title>
<para>
- <code>top</code> is probably one of the most important tool when first trying to see what’s running on a machine and how the resources are consumed. Here’s an example from production system:
+ <code>top</code> is probably one of the most important tool when first trying to see
+ what’s running on a machine and how the resources are consumed. Here’s an example from
+ production system:</para>
<programlisting>
top - 14:46:59 up 39 days, 11:55, 1 user, load average: 3.75, 3.57, 3.84
Tasks: 309 total, 1 running, 308 sleeping, 0 stopped, 0 zombie
@@ -332,21 +353,29 @@ Swap: 16008732k total, 14348k used, 15994384k free, 11106908k cached
8895 hadoop 18 -2 1581m 497m 3420 S 11 2.1 4002:32 java
…
</programlisting>
- </para>
- <para>
- Here we can see that the system load average during the last five minutes is 3.75, which very roughly means that on average 3.75 threads were waiting for CPU time during these 5 minutes. In general, the “perfect” utilization equals to the number of cores, under that number the machine is under utilized and over that the machine is over utilized. This is an important concept, see this article to understand it more: <link xlink:href="http://www.linuxjournal.com/article/9001">http://www.linuxjournal.com/article/9001</link>.
- </para>
- <para>
- Apart from load, we can see that the system is using almost all its available RAM but most of it is used for the OS cache (which is good). The swap only has a few KBs in it and this is wanted, high numbers would indicate swapping activity which is the nemesis of performance of Java systems. Another way to detect swapping is when the load average goes through the roof (although this could also be caused by things like a dying disk, among others).
- </para>
- <para>
- The list of processes isn’t super useful by default, all we know is that 3 java processes are using about 111% of the CPUs. To know which is which, simply type “c” and each line will be expanded. Typing “1” will give you the detail of how each CPU is used instead of the average for all of them like shown here.
- </para>
+ <para> Here we can see that the system load average during the last five minutes is 3.75,
+ which very roughly means that on average 3.75 threads were waiting for CPU time during
+ these 5 minutes. In general, the “perfect” utilization equals to the number of cores,
+ under that number the machine is under utilized and over that the machine is over
+ utilized. This is an important concept, see this article to understand it more: <link
+ xlink:href="http://www.linuxjournal.com/article/9001">http://www.linuxjournal.com/article/9001</link>. </para>
+ <para> Apart from load, we can see that the system is using almost all its available RAM but
+ most of it is used for the OS cache (which is good). The swap only has a few KBs in it and
+ this is wanted, high numbers would indicate swapping activity which is the nemesis of
+ performance of Java systems. Another way to detect swapping is when the load average goes
+ through the roof (although this could also be caused by things like a dying disk, among
+ others). </para>
+ <para> The list of processes isn’t super useful by default, all we know is that 3 java
+ processes are using about 111% of the CPUs. To know which is which, simply type “c” and
+ each line will be expanded. Typing “1” will give you the detail of how each CPU is used
+ instead of the average for all of them like shown here. </para>
</section>
- <section xml:id="trouble.tools.jps">
+ <section
+ xml:id="trouble.tools.jps">
<title>jps</title>
<para>
- <code>jps</code> is shipped with every JDK and gives the java process ids for the current user (if root, then it gives the ids for all users). Example:
+ <code>jps</code> is shipped with every JDK and gives the java process ids for the current
+ user (if root, then it gives the ids for all users). Example:</para>
<programlisting>
hadoop@sv4borg12:~$ jps
1322 TaskTracker
@@ -358,82 +387,101 @@ hadoop@sv4borg12:~$ jps
19750 ThriftServer
18776 jmx
</programlisting>
- In order, we see a:
+ <para>In order, we see a: </para>
<itemizedlist>
- <listitem><para>Hadoop TaskTracker, manages the local Childs</para></listitem>
- <listitem><para>HBase RegionServer, serves regions</para></listitem>
- <listitem><para>Child, its MapReduce task, cannot tell which type exactly</para></listitem>
- <listitem><para>Hadoop TaskTracker, manages the local Childs</para></listitem>
- <listitem><para>Hadoop DataNode, serves blocks</para></listitem>
- <listitem><para>HQuorumPeer, a ZooKeeper ensemble member</para></listitem>
- <listitem><para>Jps, well… it’s the current process</para></listitem>
- <listitem><para>ThriftServer, it’s a special one will be running only if thrift was started</para></listitem>
- <listitem><para>jmx, this is a local process that’s part of our monitoring platform ( poorly named maybe). You probably don’t have that.</para></listitem>
+ <listitem>
+ <para>Hadoop TaskTracker, manages the local Childs</para>
+ </listitem>
+ <listitem>
+ <para>HBase RegionServer, serves regions</para>
+ </listitem>
+ <listitem>
+ <para>Child, its MapReduce task, cannot tell which type exactly</para>
+ </listitem>
+ <listitem>
+ <para>Hadoop TaskTracker, manages the local Childs</para>
+ </listitem>
+ <listitem>
+ <para>Hadoop DataNode, serves blocks</para>
+ </listitem>
+ <listitem>
+ <para>HQuorumPeer, a ZooKeeper ensemble member</para>
+ </listitem>
+ <listitem>
+ <para>Jps, well… it’s the current process</para>
+ </listitem>
+ <listitem>
+ <para>ThriftServer, it’s a special one will be running only if thrift was started</para>
+ </listitem>
+ <listitem>
+ <para>jmx, this is a local process that’s part of our monitoring platform ( poorly named
+ maybe). You probably don’t have that.</para>
+ </listitem>
</itemizedlist>
- </para>
- <para>
- You can then do stuff like checking out the full command line that started the process:
+ <para> You can then do stuff like checking out the full command line that started the
+ process:</para>
<programlisting>
hadoop@sv4borg12:~$ ps aux | grep HRegionServer
hadoop 17789 155 35.2 9067824 8604364 ? S<l Mar04 9855:48 /usr/java/jdk1.6.0_14/bin/java -Xmx8000m -XX:+DoEscapeAnalysis -XX:+AggressiveOpts -XX:+UseConcMarkSweepGC -XX:NewSize=64m -XX:MaxNewSize=64m -XX:CMSInitiatingOccupancyFraction=88 -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -Xloggc:/export1/hadoop/logs/gc-hbase.log -Dcom.sun.management.jmxremote.port=10102 -Dcom.sun.management.jmxremote.authenticate=true -Dcom.sun.management.jmxremote.ssl=false -Dcom.sun.management.jmxremote.password.file=/home/hadoop/hbase/conf/jmxremote.password -Dcom.sun.management.jmxremote -Dhbase.log.dir=/export1/hadoop/logs -Dhbase.log.file=hbase-hadoop-regionserver-sv4borg12.log -Dhbase.home.dir=/home/hadoop/hbase -Dhbase.id.str=hadoop -Dhbase.root.logger=INFO,DRFA -Djava.library.path=/home/hadoop/hbase/lib/native/Linux-amd64-64 -classpath /home/hadoop/hbase/bin/../conf:[many jars]:/home/hadoop/hadoop/conf org.apache.hadoop.hbase.regionserver.HRegionServer start
</programlisting>
- </para>
</section>
- <section xml:id="trouble.tools.jstack">
+ <section
+ xml:id="trouble.tools.jstack">
<title>jstack</title>
<para>
- <code>jstack</code> is one of the most important tools when trying to figure out what a java process is doing apart from looking at the logs. It has to be used in conjunction with jps in order to give it a process id. It shows a list of threads, each one has a name, and they appear in the order that they were created (so the top ones are the most recent threads). Here’s a few example:
- </para>
- <para>
- The main thread of a RegionServer that’s waiting for something to do from the master:
+ <code>jstack</code> is one of the most important tools when trying to figure out what a
+ java process is doing apart from looking at the logs. It has to be used in conjunction
+ with jps in order to give it a process id. It shows a list of threads, each one has a
+ name, and they appear in the order that they were created (so the top ones are the most
+ recent threads). Here’s a few example: </para>
+ <para> The main thread of a RegionServer that’s waiting for something to do from the
+ master:</para>
<programlisting>
- "regionserver60020" prio=10 tid=0x0000000040ab4000 nid=0x45cf waiting on condition [0x00007f16b6a96000..0x00007f16b6a96a70]
- java.lang.Thread.State: TIMED_WAITING (parking)
- at sun.misc.Unsafe.park(Native Method)
- - parking to wait for <0x00007f16cd5c2f30> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
- at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:198)
- at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:1963)
- at java.util.concurrent.LinkedBlockingQueue.poll(LinkedBlockingQueue.java:395)
- at org.apache.hadoop.hbase.regionserver.HRegionServer.run(HRegionServer.java:647)
- at java.lang.Thread.run(Thread.java:619)
+"regionserver60020" prio=10 tid=0x0000000040ab4000 nid=0x45cf waiting on condition [0x00007f16b6a96000..0x00007f16b6a96a70]
+java.lang.Thread.State: TIMED_WAITING (parking)
+ at sun.misc.Unsafe.park(Native Method)
+ - parking to wait for <0x00007f16cd5c2f30> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+ at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:198)
+ at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:1963)
+ at java.util.concurrent.LinkedBlockingQueue.poll(LinkedBlockingQueue.java:395)
+ at org.apache.hadoop.hbase.regionserver.HRegionServer.run(HRegionServer.java:647)
+ at java.lang.Thread.run(Thread.java:619)
- The MemStore flusher thread that is currently flushing to a file:
+ The MemStore flusher thread that is currently flushing to a file:
"regionserver60020.cacheFlusher" daemon prio=10 tid=0x0000000040f4e000 nid=0x45eb in Object.wait() [0x00007f16b5b86000..0x00007f16b5b87af0]
- java.lang.Thread.State: WAITING (on object monitor)
- at java.lang.Object.wait(Native Method)
- at java.lang.Object.wait(Object.java:485)
- at org.apache.hadoop.ipc.Client.call(Client.java:803)
- - locked <0x00007f16cb14b3a8> (a org.apache.hadoop.ipc.Client$Call)
- at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:221)
- at $Proxy1.complete(Unknown Source)
- at sun.reflect.GeneratedMethodAccessor38.invoke(Unknown Source)
- at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
- at java.lang.reflect.Method.invoke(Method.java:597)
- at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:82)
- at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:59)
- at $Proxy1.complete(Unknown Source)
- at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.closeInternal(DFSClient.java:3390)
- - locked <0x00007f16cb14b470> (a org.apache.hadoop.hdfs.DFSClient$DFSOutputStream)
- at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.close(DFSClient.java:3304)
- at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.close(FSDataOutputStream.java:61)
- at org.apache.hadoop.fs.FSDataOutputStream.close(FSDataOutputStream.java:86)
- at org.apache.hadoop.hbase.io.hfile.HFile$Writer.close(HFile.java:650)
- at org.apache.hadoop.hbase.regionserver.StoreFile$Writer.close(StoreFile.java:853)
- at org.apache.hadoop.hbase.regionserver.Store.internalFlushCache(Store.java:467)
- - locked <0x00007f16d00e6f08> (a java.lang.Object)
- at org.apache.hadoop.hbase.regionserver.Store.flushCache(Store.java:427)
- at org.apache.hadoop.hbase.regionserver.Store.access$100(Store.java:80)
- at org.apache.hadoop.hbase.regionserver.Store$StoreFlusherImpl.flushCache(Store.java:1359)
- at org.apache.hadoop.hbase.regionserver.HRegion.internalFlushcache(HRegion.java:907)
- at org.apache.hadoop.hbase.regionserver.HRegion.internalFlushcache(HRegion.java:834)
- at org.apache.hadoop.hbase.regionserver.HRegion.flushcache(HRegion.java:786)
- at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.flushRegion(MemStoreFlusher.java:250)
- at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.flushRegion(MemStoreFlusher.java:224)
- at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.run(MemStoreFlusher.java:146)
+java.lang.Thread.State: WAITING (on object monitor)
+ at java.lang.Object.wait(Native Method)
+ at java.lang.Object.wait(Object.java:485)
+ at org.apache.hadoop.ipc.Client.call(Client.java:803)
+ - locked <0x00007f16cb14b3a8> (a org.apache.hadoop.ipc.Client$Call)
+ at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:221)
+ at $Proxy1.complete(Unknown Source)
+ at sun.reflect.GeneratedMethodAccessor38.invoke(Unknown Source)
+ at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
+ at java.lang.reflect.Method.invoke(Method.java:597)
+ at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:82)
+ at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:59)
+ at $Proxy1.complete(Unknown Source)
+ at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.closeInternal(DFSClient.java:3390)
+ - locked <0x00007f16cb14b470> (a org.apache.hadoop.hdfs.DFSClient$DFSOutputStream)
+ at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.close(DFSClient.java:3304)
+ at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.close(FSDataOutputStream.java:61)
+ at org.apache.hadoop.fs.FSDataOutputStream.close(FSDataOutputStream.java:86)
+ at org.apache.hadoop.hbase.io.hfile.HFile$Writer.close(HFile.java:650)
+ at org.apache.hadoop.hbase.regionserver.StoreFile$Writer.close(StoreFile.java:853)
+ at org.apache.hadoop.hbase.regionserver.Store.internalFlushCache(Store.java:467)
+ - locked <0x00007f16d00e6f08> (a java.lang.Object)
+ at org.apache.hadoop.hbase.regionserver.Store.flushCache(Store.java:427)
+ at org.apache.hadoop.hbase.regionserver.Store.access$100(Store.java:80)
+ at org.apache.hadoop.hbase.regionserver.Store$StoreFlusherImpl.flushCache(Store.java:1359)
+ at org.apache.hadoop.hbase.regionserver.HRegion.internalFlushcache(HRegion.java:907)
+ at org.apache.hadoop.hbase.regionserver.HRegion.internalFlushcache(HRegion.java:834)
+ at org.apache.hadoop.hbase.regionserver.HRegion.flushcache(HRegion.java:786)
+ at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.flushRegion(MemStoreFlusher.java:250)
+ at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.flushRegion(MemStoreFlusher.java:224)
+ at org.apache.hadoop.hbase.regionserver.MemStoreFlusher.run(MemStoreFlusher.java:146)
</programlisting>
- </para>
- <para>
- A handler thread that’s waiting for stuff to do (like put, delete, scan, etc):
+ <para> A handler thread that’s waiting for stuff to do (like put, delete, scan, etc):</para>
<programlisting>
"IPC Server handler 16 on 60020" daemon prio=10 tid=0x00007f16b011d800 nid=0x4a5e waiting on condition [0x00007f16afefd000..0x00007f16afefd9f0]
java.lang.Thread.State: WAITING (parking)
@@ -444,9 +492,8 @@ hadoop 17789 155 35.2 9067824 8604364 ? S<l Mar04 9855:48 /usr/java/j
at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:358)
at org.apache.hadoop.hbase.ipc.HBaseServer$Handler.run(HBaseServer.java:1013)
</programlisting>
- </para>
- <para>
- And one that’s busy doing an increment of a counter (it’s in the phase where it’s trying to create a scanner in order to read the last value):
+ <para> And one that’s busy doing an increment of a counter (it’s in the phase where it’s
+ trying to create a scanner in order to read the last value):</para>
<programlisting>
"IPC Server handler 66 on 60020" daemon prio=10 tid=0x00007f16b006e800 nid=0x4a90 runnable [0x00007f16acb77000..0x00007f16acb77cf0]
java.lang.Thread.State: RUNNABLE
@@ -466,9 +513,7 @@ hadoop 17789 155 35.2 9067824 8604364 ? S<l Mar04 9855:48 /usr/java/j
at org.apache.hadoop.hbase.ipc.HBaseRPC$Server.call(HBaseRPC.java:560)
at org.apache.hadoop.hbase.ipc.HBaseServer$Handler.run(HBaseServer.java:1027)
</programlisting>
- </para>
- <para>
- A thread that receives data from HDFS:
+ <para> A thread that receives data from HDFS:</para>
<programlisting>
"IPC Client (47) connection to sv4borg9/10.4.24.40:9000 from hadoop" daemon prio=10 tid=0x00007f16a02d0000 nid=0x4fa3 runnable [0x00007f16b517d000..0x00007f16b517dbf0]
java.lang.Thread.State: RUNNABLE
@@ -493,10 +538,8 @@ hadoop 17789 155 35.2 9067824 8604364 ? S<l Mar04 9855:48 /usr/java/j
at org.apache.hadoop.ipc.Client$Connection.receiveResponse(Client.java:569)
at org.apache.hadoop.ipc.Client$Connection.run(Client.java:477)
</programlisting>
- </para>
- <para>
- And here is a master trying to recover a lease after a RegionServer died:
- <programlisting>
+ <para> And here is a master trying to recover a lease after a RegionServer died:</para>
+ <programlisting>
"LeaseChecker" daemon prio=10 tid=0x00000000407ef800 nid=0x76cd waiting on condition [0x00007f6d0eae2000..0x00007f6d0eae2a70]
--
java.lang.Thread.State: WAITING (on object monitor)
@@ -518,84 +561,116 @@ hadoop 17789 155 35.2 9067824 8604364 ? S<l Mar04 9855:48 /usr/java/j
at org.apache.hadoop.hbase.master.HMaster.joinCluster(HMaster.java:572)
at org.apache.hadoop.hbase.master.HMaster.run(HMaster.java:503)
</programlisting>
- </para>
- </section>
- <section xml:id="trouble.tools.opentsdb">
- <title>OpenTSDB</title>
- <para>
- <link xlink:href="http://opentsdb.net">OpenTSDB</link> is an excellent alternative to Ganglia as it uses Apache HBase to store all the time series and doesn’t have to downsample. Monitoring your own HBase cluster that hosts OpenTSDB is a good exercise.
- </para>
- <para>
- Here’s an example of a cluster that’s suffering from hundreds of compactions launched almost all around the same time, which severely affects the IO performance: (TODO: insert graph plotting compactionQueueSize)
- </para>
- <para>
- It’s a good practice to build dashboards with all the important graphs per machine and per cluster so that debugging issues can be done with a single quick look. For example, at StumbleUpon there’s one dashboard per cluster with the most important metrics from both the OS and Apache HBase. You can then go down at the machine level and get even more detailed metrics.
- </para>
- </section>
- <section xml:id="trouble.tools.clustersshtop">
+ </section>
+ <section
+ xml:id="trouble.tools.opentsdb">
+ <title>OpenTSDB</title>
+ <para>
+ <link
+ xlink:href="http://opentsdb.net">OpenTSDB</link> is an excellent alternative to Ganglia
+ as it uses Apache HBase to store all the time series and doesn’t have to downsample.
+ Monitoring your own HBase cluster that hosts OpenTSDB is a good exercise. </para>
+ <para> Here’s an example of a cluster that’s suffering from hundreds of compactions launched
+ almost all around the same time, which severely affects the IO performance: (TODO: insert
+ graph plotting compactionQueueSize) </para>
+ <para> It’s a good practice to build dashboards with all the important graphs per machine
+ and per cluster so that debugging issues can be done with a single quick look. For
+ example, at StumbleUpon there’s one dashboard per cluster with the most important metrics
+ from both the OS and Apache HBase. You can then go down at the machine level and get even
+ more detailed metrics. </para>
+ </section>
+ <section
+ xml:id="trouble.tools.clustersshtop">
<title>clusterssh+top</title>
- <para>
- clusterssh+top, it’s like a poor man’s monitoring system and it can be quite useful when you have only a few machines as it’s very easy to setup. Starting clusterssh will give you one terminal per machine and another terminal in which whatever you type will be retyped in every window. This means that you can type “top” once and it will start it for all of your machines at the same time giving you full view of the current state of your cluster. You can also tail all the logs at the same time, edit files, etc.
- </para>
- </section>
- </section>
+ <para> clusterssh+top, it’s like a poor man’s monitoring system and it can be quite useful
+ when you have only a few machines as it’s very easy to setup. Starting clusterssh will
+ give you one terminal per machine and another terminal in which whatever you type will be
+ retyped in every window. This means that you can type “top” once and it will start it for
+ all of your machines at the same time giving you full view of the current state of your
+ cluster. You can also tail all the logs at the same time, edit files, etc. </para>
+ </section>
</section>
+ </section>
- <section xml:id="trouble.client">
- <title>Client</title>
- <para>For more information on the HBase client, see <xref linkend="client"/>.
- </para>
- <section xml:id="trouble.client.scantimeout">
- <title>ScannerTimeoutException or UnknownScannerException</title>
- <para>This is thrown if the time between RPC calls from the client to RegionServer exceeds the scan timeout.
- For example, if <code>Scan.setCaching</code> is set to 500, then there will be an RPC call to fetch the next batch of rows every 500 <code>.next()</code> calls on the ResultScanner
- because data is being transferred in blocks of 500 rows to the client. Reducing the setCaching value may be an option, but setting this value too low makes for inefficient
- processing on numbers of rows.
- </para>
- <para>See <xref linkend="perf.hbase.client.caching"/>.
- </para>
- </section>
- <section xml:id="trouble.client.lease.exception">
- <title><classname>LeaseException</classname> when calling <classname>Scanner.next</classname></title>
- <para>
-In some situations clients that fetch data from a RegionServer get a LeaseException instead of the usual
-<xref linkend="trouble.client.scantimeout" />. Usually the source of the exception is
-<classname>org.apache.hadoop.hbase.regionserver.Leases.removeLease(Leases.java:230)</classname> (line number may vary).
-It tends to happen in the context of a slow/freezing RegionServer#next call.
-It can be prevented by having <varname>hbase.rpc.timeout</varname> > <varname>hbase.regionserver.lease.period</varname>.
-Harsh J investigated the issue as part of the mailing list thread
-<link xlink:href="http://mail-archives.apache.org/mod_mbox/hbase-user/201209.mbox/%3CCAOcnVr3R-LqtKhFsk8Bhrm-YW2i9O6J6Fhjz2h7q6_sxvwd2yw%40mail.gmail.com%3E">HBase, mail # user - Lease does not exist exceptions</link>
- </para>
- </section>
- <section xml:id="trouble.client.scarylogs">
- <title>Shell or client application throws lots of scary exceptions during normal operation</title>
- <para>Since 0.20.0 the default log level for <code>org.apache.hadoop.hbase.*</code>is DEBUG. </para>
- <para>
- On your clients, edit <filename>$HBASE_HOME/conf/log4j.properties</filename> and change this: <code>log4j.logger.org.apache.hadoop.hbase=DEBUG</code> to this: <code>log4j.logger.org.apache.hadoop.hbase=INFO</code>, or even <code>log4j.logger.org.apache.hadoop.hbase=WARN</code>.
- </para>
- </section>
- <section xml:id="trouble.client.longpauseswithcompression">
- <title>Long Client Pauses With Compression</title>
- <para>This is a fairly frequent question on the Apache HBase dist-list. The scenario is that a client is typically inserting a lot of data into a
- relatively un-optimized HBase cluster. Compression can exacerbate the pauses, although it is not the source of the problem.</para>
- <para>See <xref linkend="precreate.regions"/> on the pattern for pre-creating regions and confirm that the table isn't starting with a single region.</para>
- <para>See <xref linkend="perf.configurations"/> for cluster configuration, particularly <code>hbase.hstore.blockingStoreFiles</code>, <code>hbase.hregion.memstore.block.multiplier</code>,
- <code>MAX_FILESIZE</code> (region size), and <code>MEMSTORE_FLUSHSIZE.</code> </para>
- <para>A slightly longer explanation of why pauses can happen is as follows: Puts are sometimes blocked on the MemStores which are blocked by the flusher thread which is blocked because there are
- too many files to compact because the compactor is given too many small files to compact and has to compact the same data repeatedly. This situation can occur even with minor compactions.
- Compounding this situation, Apache HBase doesn't compress data in memory. Thus, the 64MB that lives in the MemStore could become a 6MB file after compression - which results in a smaller StoreFile. The upside is that
- more data is packed into the same region, but performance is achieved by being able to write larger files - which is why HBase waits until the flushize before writing a new StoreFile. And smaller StoreFiles
- become targets for compaction. Without compression the files are much bigger and don't need as much compaction, however this is at the expense of I/O.
- </para>
- <para>
- For additional information, see this thread on <link xlink:href="http://search-hadoop.com/m/WUnLM6ojHm1/Long+client+pauses+with+compression&subj=Long+client+pauses+with+compression">Long client pauses with compression</link>.
- </para>
+ <section
+ xml:id="trouble.client">
+ <title>Client</title>
+ <para>For more information on the HBase client, see <xref
+ linkend="client" />. </para>
+ <section
+ xml:id="trouble.client.scantimeout">
+ <title>ScannerTimeoutException or UnknownScannerException</title>
+ <para>This is thrown if the time between RPC calls from the client to RegionServer exceeds the
+ scan timeout. For example, if <code>Scan.setCaching</code> is set to 500, then there will be
+ an RPC call to fetch the next batch of rows every 500 <code>.next()</code> calls on the
+ ResultScanner because data is being transferred in blocks of 500 rows to the client.
+ Reducing the setCaching value may be an option, but setting this value too low makes for
+ inefficient processing on numbers of rows. </para>
+ <para>See <xref
+ linkend="perf.hbase.client.caching" />. </para>
+ </section>
+ <section
+ xml:id="trouble.client.lease.exception">
+ <title><classname>LeaseException</classname> when calling
+ <classname>Scanner.next</classname></title>
+ <para> In some situations clients that fetch data from a RegionServer get a LeaseException
+ instead of the usual <xref
+ linkend="trouble.client.scantimeout" />. Usually the source of the exception is
+ <classname>org.apache.hadoop.hbase.regionserver.Leases.removeLease(Leases.java:230)</classname>
+ (line number may vary). It tends to happen in the context of a slow/freezing
+ RegionServer#next call. It can be prevented by having <varname>hbase.rpc.timeout</varname> >
+ <varname>hbase.regionserver.lease.period</varname>. Harsh J investigated the issue as part
+ of the mailing list thread <link
+ xlink:href="http://mail-archives.apache.org/mod_mbox/hbase-user/201209.mbox/%3CCAOcnVr3R-LqtKhFsk8Bhrm-YW2i9O6J6Fhjz2h7q6_sxvwd2yw%40mail.gmail.com%3E">HBase,
+ mail # user - Lease does not exist exceptions</link>
+ </para>
+ </section>
+ <section
+ xml:id="trouble.client.scarylogs">
+ <title>Shell or client application throws lots of scary exceptions during normal
+ operation</title>
+ <para>Since 0.20.0 the default log level for <code>org.apache.hadoop.hbase.*</code>is DEBUG. </para>
+ <para> On your clients, edit <filename>$HBASE_HOME/conf/log4j.properties</filename> and change
+ this: <code>log4j.logger.org.apache.hadoop.hbase=DEBUG</code> to this:
+ <code>log4j.logger.org.apache.hadoop.hbase=INFO</code>, or even
+ <code>log4j.logger.org.apache.hadoop.hbase=WARN</code>. </para>
+ </section>
+ <section
+ xml:id="trouble.client.longpauseswithcompression">
+ <title>Long Client Pauses With Compression</title>
+ <para>This is a fairly frequent question on the Apache HBase dist-list. The scenario is that a
+ client is typically inserting a lot of data into a relatively un-optimized HBase cluster.
+ Compression can exacerbate the pauses, although it is not the source of the problem.</para>
+ <para>See <xref
+ linkend="precreate.regions" /> on the pattern for pre-creating regions and confirm that
+ the table isn't starting with a single region.</para>
+ <para>See <xref
+ linkend="perf.configurations" /> for cluster configuration, particularly
+ <code>hbase.hstore.blockingStoreFiles</code>,
+ <code>hbase.hregion.memstore.block.multiplier</code>, <code>MAX_FILESIZE</code> (region
+ size), and <code>MEMSTORE_FLUSHSIZE.</code>
+ </para>
+ <para>A slightly longer explanation of why pauses can happen is as follows: Puts are sometimes
+ blocked on the MemStores which are blocked by the flusher thread which is blocked because
+ there are too many files to compact because the compactor is given too many small files to
+ compact and has to compact the same data repeatedly. This situation can occur even with
+ minor compactions. Compounding this situation, Apache HBase doesn't compress data in memory.
+ Thus, the 64MB that lives in the MemStore could become a 6MB file after compression - which
+ results in a smaller StoreFile. The upside is that more data is packed into the same region,
+ but performance is achieved by being able to write larger files - which is why HBase waits
+ until the flushize before writing a new StoreFile. And smaller StoreFiles become targets for
+ compaction. Without compression the files are much bigger and don't need as much compaction,
+ however this is at the expense of I/O. </para>
+ <para> For additional information, see this thread on <link
+ xlink:href="http://search-hadoop.com/m/WUnLM6ojHm1/Long+client+pauses+with+compression&subj=Long+client+pauses+with+compression">Long
+ client pauses with compression</link>. </para>
- </section>
- <section xml:id="trouble.client.zookeeper">
- <title>ZooKeeper Client Connection Errors</title>
- <para>Errors like this...
-<programlisting>
+ </section>
+ <section
+ xml:id="trouble.client.zookeeper">
+ <title>ZooKeeper Client Connection Errors</title>
+ <para>Errors like this...</para>
+ <programlisting>
11/07/05 11:26:41 WARN zookeeper.ClientCnxn: Session 0x0 for server null,
unexpected error, closing socket connection and attempting reconnect
java.net.ConnectException: Connection refused: no further information
@@ -613,67 +688,81 @@ Harsh J investigated the issue as part of the mailing list thread
11/07/05 11:26:45 INFO zookeeper.ClientCnxn: Opening socket connection to
server localhost/127.0.0.1:2181
</programlisting>
- ... are either due to ZooKeeper being down, or unreachable due to network issues.
- </para>
- <para>The utility <xref linkend="trouble.tools.builtin.zkcli"/> may help investigate ZooKeeper issues.
- </para>
- </section>
- <section xml:id="trouble.client.oome.directmemory.leak">
- <title>Client running out of memory though heap size seems to be stable (but the off-heap/direct heap keeps growing)</title>
- <para>
-You are likely running into the issue that is described and worked through in
-the mail thread <link xlink:href="http://search-hadoop.com/m/ubhrX8KvcH/Suspected+memory+leak&subj=Re+Suspected+memory+leak">HBase, mail # user - Suspected memory leak</link>
-and continued over in <link xlink:href="http://search-hadoop.com/m/p2Agc1Zy7Va/MaxDirectMemorySize+Was%253A+Suspected+memory+leak&subj=Re+FeedbackRe+Suspected+memory+leak">HBase, mail # dev - FeedbackRe: Suspected memory leak</link>.
-A workaround is passing your client-side JVM a reasonable value for <code>-XX:MaxDirectMemorySize</code>. By default,
-the <varname>MaxDirectMemorySize</varname> is equal to your <code>-Xmx</code> max heapsize setting (if <code>-Xmx</code> is set).
-Try seting it to something smaller (for example, one user had success setting it to <code>1g</code> when
-they had a client-side heap of <code>12g</code>). If you set it too small, it will bring on <code>FullGCs</code> so keep
-it a bit hefty. You want to make this setting client-side only especially if you are running the new experiemental
-server-side off-heap cache since this feature depends on being able to use big direct buffers (You may have to keep
-separate client-side and server-side config dirs).
- </para>
-
- </section>
- <section xml:id="trouble.client.slowdown.admin">
- <title>Client Slowdown When Calling Admin Methods (flush, compact, etc.)</title>
- <para>
-This is a client issue fixed by <link xlink:href="https://issues.apache.org/jira/browse/HBASE-5073">HBASE-5073</link> in 0.90.6.
-There was a ZooKeeper leak in the client and the client was getting pummeled by ZooKeeper events with each additional
-invocation of the admin API.
- </para>
- </section>
+ <para>... are either due to ZooKeeper being down, or unreachable due to network issues. </para>
+ <para>The utility <xref
+ linkend="trouble.tools.builtin.zkcli" /> may help investigate ZooKeeper issues. </para>
+ </section>
+ <section
+ xml:id="trouble.client.oome.directmemory.leak">
+ <title>Client running out of memory though heap size seems to be stable (but the
+ off-heap/direct heap keeps growing)</title>
+ <para> You are likely running into the issue that is described and worked through in the mail
+ thread <link
+ xlink:href="http://search-hadoop.com/m/ubhrX8KvcH/Suspected+memory+leak&subj=Re+Suspected+memory+leak">HBase,
+ mail # user - Suspected memory leak</link> and continued over in <link
+ xlink:href="http://search-hadoop.com/m/p2Agc1Zy7Va/MaxDirectMemorySize+Was%253A+Suspected+memory+leak&subj=Re+FeedbackRe+Suspected+memory+leak">HBase,
+ mail # dev - FeedbackRe: Suspected memory leak</link>. A workaround is passing your
+ client-side JVM a reasonable value for <code>-XX:MaxDirectMemorySize</code>. By default, the
+ <varname>MaxDirectMemorySize</varname> is equal to your <code>-Xmx</code> max heapsize
+ setting (if <code>-Xmx</code> is set). Try seting it to something smaller (for example, one
+ user had success setting it to <code>1g</code> when they had a client-side heap of
+ <code>12g</code>). If you set it too small, it will bring on <code>FullGCs</code> so keep
+ it a bit hefty. You want to make this setting client-side only especially if you are running
+ the new experiemental server-side off-heap cache since this feature depends on being able to
+ use big direct buffers (You may have to keep separate client-side and server-side config
+ dirs). </para>
- <section xml:id="trouble.client.security.rpc">
- <title>Secure Client Cannot Connect ([Caused by GSSException: No valid credentials provided (Mechanism level: Failed to find any Kerberos tgt)])</title>
- <para>
-There can be several causes that produce this symptom.
- </para>
- <para>
-First, check that you have a valid Kerberos ticket. One is required in order to set up communication with a secure Apache HBase cluster. Examine the ticket currently in the credential cache, if any, by running the klist command line utility. If no ticket is listed, you must obtain a ticket by running the kinit command with either a keytab specified, or by interactively entering a password for the desired principal.
- </para>
- <para>
-Then, consult the <link xlink:href="http://docs.oracle.com/javase/1.5.0/docs/guide/security/jgss/tutorials/Troubleshooting.html">Java Security Guide troubleshooting section</link>. The most common problem addressed there is resolved by setting javax.security.auth.useSubjectCredsOnly system property value to false.
- </para>
- <para>
-Because of a change in the format in which MIT Kerberos writes its credentials cache, there is a bug in the Oracle JDK 6 Update 26 and earlier that causes Java to be unable to read the Kerberos credentials cache created by versions of MIT Kerberos 1.8.1 or higher. If you have this problematic combination of components in your environment, to work around this problem, first log in with kinit and then immediately refresh the credential cache with kinit -R. The refresh will rewrite the credential cache without the problematic formatting.
- </para>
- <para>
-Finally, depending on your Kerberos configuration, you may need to install the <link xlink:href="http://docs.oracle.com/javase/1.4.2/docs/guide/security/jce/JCERefGuide.html">Java Cryptography Extension</link>, or JCE. Insure the JCE jars are on the classpath on both server and client systems.
- </para>
- <para>
-You may also need to download the <link xlink:href="http://www.oracle.com/technetwork/java/javase/downloads/jce-6-download-429243.html">unlimited strength JCE policy files</link>. Uncompress and extract the downloaded file, and install the policy jars into <java-home>/lib/security.
- </para>
- </section>
+ </section>
+ <section
+ xml:id="trouble.client.slowdown.admin">
+ <title>Client Slowdown When Calling Admin Methods (flush, compact, etc.)</title>
+ <para> This is a client issue fixed by <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-5073">HBASE-5073</link> in 0.90.6.
+ There was a ZooKeeper leak in the client and the client was getting pummeled by ZooKeeper
+ events with each additional invocation of the admin API. </para>
+ </section>
+ <section
+ xml:id="trouble.client.security.rpc">
+ <title>Secure Client Cannot Connect ([Caused by GSSException: No valid credentials provided
+ (Mechanism level: Failed to find any Kerberos tgt)])</title>
+ <para> There can be several causes that produce this symptom. </para>
+ <para> First, check that you have a valid Kerberos ticket. One is required in order to set up
+ communication with a secure Apache HBase cluster. Examine the ticket currently in the
+ credential cache, if any, by running the klist command line utility. If no ticket is listed,
+ you must obtain a ticket by running the kinit command with either a keytab specified, or by
+ interactively entering a password for the desired principal. </para>
+ <para> Then, consult the <link
+ xlink:href="http://docs.oracle.com/javase/1.5.0/docs/guide/security/jgss/tutorials/Troubleshooting.html">Java
+ Security Guide troubleshooting section</link>. The most common problem addressed there is
+ resolved by setting javax.security.auth.useSubjectCredsOnly system property value to false. </para>
+ <para> Because of a change in the format in which MIT Kerberos writes its credentials cache,
+ there is a bug in the Oracle JDK 6 Update 26 and earlier that causes Java to be unable to
+ read the Kerberos credentials cache created by versions of MIT Kerberos 1.8.1 or higher. If
+ you have this problematic combination of components in your environment, to work around this
+ problem, first log in with kinit and then immediately refresh the credential cache with
+ kinit -R. The refresh will rewrite the credential cache without the problematic formatting. </para>
+ <para> Finally, depending on your Kerberos configuration, you may need to install the <link
+ xlink:href="http://docs.oracle.com/javase/1.4.2/docs/guide/security/jce/JCERefGuide.html">Java
+ Cryptography Extension</link>, or JCE. Insure the JCE jars are on the classpath on both
+ server and client systems. </para>
+ <para> You may also need to download the <link
+ xlink:href="http://www.oracle.com/technetwork/java/javase/downloads/jce-6-download-429243.html">unlimited
+ strength JCE policy files</link>. Uncompress and extract the downloaded file, and install
+ the policy jars into <java-home>/lib/security. </para>
</section>
- <section xml:id="trouble.mapreduce">
- <title>MapReduce</title>
- <section xml:id="trouble.mapreduce.local">
- <title>You Think You're On The Cluster, But You're Actually Local</title>
- <para>This following stacktrace happened using <code>ImportTsv</code>, but things like this
- can happen on any job with a mis-configuration.
-<programlisting>
+ </section>
+
+ <section
+ xml:id="trouble.mapreduce">
+ <title>MapReduce</title>
+ <section
+ xml:id="trouble.mapreduce.local">
+ <title>You Think You're On The Cluster, But You're Actually Local</title>
+ <para>This following stacktrace happened using <code>ImportTsv</code>, but things like this
+ can happen on any job with a mis-configuration.</para>
+ <programlisting>
WARN mapred.LocalJobRunner: job_local_0001
java.lang.IllegalArgumentException: Can't read partitions file
at org.apache.hadoop.hbase.mapreduce.hadoopbackport.TotalOrderPartitioner.setConf(TotalOrderPartitioner.java:111)
@@ -691,219 +780,238 @@ Caused by: java.io.FileNotFoundException: File _partition.lst does not exist.
at org.apache.hadoop.io.SequenceFile$Reader.<init>(SequenceFile.java:1419)
at org.apache.hadoop.hbase.mapreduce.hadoopbackport.TotalOrderPartitioner.readPartitions(TotalOrderPartitioner.java:296)
</programlisting>
- .. see the critical portion of the stack? It's...
-<programlisting>
- at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:210)
+ <para>.. see the critical portion of the stack? It's...</para>
+ <programlisting>
+at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:210)
</programlisting>
- LocalJobRunner means the job is running locally, not on the cluster.
- </para>
+ <para>LocalJobRunner means the job is running locally, not on the cluster. </para>
<para>To solve this problem, you should run your MR job with your
- <code>HADOOP_CLASSPATH</code> set to include the HBase dependencies.
- The "hbase classpath" utility can be used to do this easily.
- For example (substitute VERSION with your HBase version):
+ <code>HADOOP_CLASSPATH</code> set to include the HBase dependencies. The "hbase classpath"
+ utility can be used to do this easily. For example (substitute VERSION with your HBase
+ version):</para>
<programlisting>
HADOOP_CLASSPATH=`hbase classpath` hadoop jar $HBASE_HOME/hbase-VERSION.jar rowcounter usertable
</programlisting>
- </para>
- <para>See
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/package-summary.html#classpath">
- http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/package-summary.html#classpath</link> for more
- information on HBase MapReduce jobs and classpaths.
- </para>
- </section>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/package-summary.html#classpath">
+ http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/package-summary.html#classpath</link>
+ for more information on HBase MapReduce jobs and classpaths. </para>
</section>
+ </section>
- <section xml:id="trouble.namenode">
- <title>NameNode</title>
- <para>For more information on the NameNode, see <xref linkend="arch.hdfs"/>.
- </para>
- <section xml:id="trouble.namenode.disk">
- <title>HDFS Utilization of Tables and Regions</title>
- <para>To determine how much space HBase is using on HDFS use the <code>hadoop</code> shell commands from the NameNode. For example... </para>
- <para><programlisting>hadoop fs -dus /hbase/</programlisting> ...returns the summarized disk utilization for all HBase objects. </para>
- <para><programlisting>hadoop fs -dus /hbase/myTable</programlisting> ...returns the summarized disk utilization for the HBase table 'myTable'. </para>
- <para><programlisting>hadoop fs -du /hbase/myTable</programlisting> ...returns a list of the regions under the HBase table 'myTable' and their disk utilization. </para>
- <para>For more information on HDFS shell commands, see the <link xlink:href="http://hadoop.apache.org/common/docs/current/file_system_shell.html">HDFS FileSystem Shell documentation</link>.
- </para>
- </section>
- <section xml:id="trouble.namenode.hbase.objects">
- <title>Browsing HDFS for HBase Objects</title>
- <para>Sometimes it will be necessary to explore the HBase objects that exist on HDFS.
- These objects could include the WALs (Write Ahead Logs), tables, regions, StoreFiles, etc.
- The easiest way to do this is with the NameNode web application that runs on port 50070. The
+ <section
+ xml:id="trouble.namenode">
+ <title>NameNode</title>
+ <para>For more information on the NameNode, see <xref
+ linkend="arch.hdfs" />. </para>
+ <section
+ xml:id="trouble.namenode.disk">
+ <title>HDFS Utilization of Tables and Regions</title>
+ <para>To determine how much space HBase is using on HDFS use the <code>hadoop</code> shell
+ commands from the NameNode. For example... </para>
+ <para><programlisting>hadoop fs -dus /hbase/</programlisting> ...returns the summarized disk
+ utilization for all HBase objects. </para>
+ <para><programlisting>hadoop fs -dus /hbase/myTable</programlisting> ...returns the summarized
+ disk utilization for the HBase table 'myTable'. </para>
+ <para><programlisting>hadoop fs -du /hbase/myTable</programlisting> ...returns a list of the
+ regions under the HBase table 'myTable' and their disk utilization. </para>
+ <para>For more information on HDFS shell commands, see the <link
+ xlink:href="http://hadoop.apache.org/common/docs/current/file_system_shell.html">HDFS
+ FileSystem Shell documentation</link>. </para>
+ </section>
+ <section
+ xml:id="trouble.namenode.hbase.objects">
+ <title>Browsing HDFS for HBase Objects</title>
+ <para>Sometimes it will be necessary to explore the HBase objects that exist on HDFS. These
+ objects could include the WALs (Write Ahead Logs), tables, regions, StoreFiles, etc. The
+ easiest way to do this is with the NameNode web application that runs on port 50070. The
NameNode web application will provide links to the all the DataNodes in the cluster so that
they can be browsed seamlessly. </para>
- <para>The HDFS directory structure of HBase tables in the cluster is...
- <programlisting>
+ <para>The HDFS directory structure of HBase tables in the cluster is...
+ <programlisting>
<filename>/hbase</filename>
<filename>/<Table></filename> (Tables in the cluster)
<filename>/<Region></filename> (Regions for the table)
<filename>/<ColumnFamily></filename> (ColumnFamilies for the Region for the table)
<filename>/<StoreFile></filename> (StoreFiles for the ColumnFamily for the Regions for the table)
</programlisting>
- </para>
- <para>The HDFS directory structure of HBase WAL is..
- <programlisting>
+ </para>
+ <para>The HDFS directory structure of HBase WAL is..
+ <programlisting>
<filename>/hbase</filename>
<filename>/.logs</filename>
<filename>/<RegionServer></filename> (RegionServers)
<filename>/<HLog></filename> (WAL HLog files for the RegionServer)
</programlisting>
- </para>
- <para>See the <link xlink:href="http://hadoop.apache.org/common/docs/current/hdfs_user_guide.html">HDFS User Guide</link> for other non-shell diagnostic
- utilities like <code>fsck</code>.
- </para>
- <section xml:id="trouble.namenode.0size.hlogs">
- <title>Zero size HLogs with data in them</title>
- <para>Problem: when getting a listing of all the files in a region server's .logs directory, one file has a size of 0 but it contains data.</para>
- <para>Answer: It's an HDFS quirk. A file that's currently being to will appear to have a size of 0 but once it's closed it will show its true size</para>
- </section>
- <section xml:id="trouble.namenode.uncompaction">
- <title>Use Cases</title>
- <para>Two common use-cases for querying HDFS for HBase objects is research the degree of uncompaction of a table. If there are a large number of StoreFiles for each ColumnFamily it could
- indicate the need for a major compaction. Additionally, after a major compaction if the resulting StoreFile is "small" it could indicate the need for a reduction of ColumnFamilies for
- the table.
- </para>
- </section>
-
- </section>
- </section>
-
- <section xml:id="trouble.network">
- <title>Network</title>
- <section xml:id="trouble.network.spikes">
- <title>Network Spikes</title>
- <para>If you are seeing periodic network spikes you might want to check the <code>compactionQueues</code> to see if major
- compactions are happening.
- </para>
- <para>See <xref linkend="managed.compactions"/> for more information on managing compactions.
- </para>
+ </para>
+ <para>See the <link
+ xlink:href="http://hadoop.apache.org/common/docs/current/hdfs_user_guide.html">HDFS User
+ Guide</link> for other non-shell diagnostic utilities like <code>fsck</code>. </para>
+ <section
+ xml:id="trouble.namenode.0size.hlogs">
+ <title>Zero size HLogs with data in them</title>
+ <para>Problem: when getting a listing of all the files in a region server's .logs directory,
+ one file has a size of 0 but it contains data.</para>
+ <para>Answer: It's an HDFS quirk. A file that's currently being to will appear to have a
+ size of 0 but once it's closed it will show its true size</para>
</section>
- <section xml:id="trouble.network.loopback">
- <title>Loopback IP</title>
- <para>HBase expects the loopback IP Address to be 127.0.0.1. See the Getting Started section on <xref linkend="loopback.ip" />.
- </para>
- </section>
- <section xml:id="trouble.network.ints">
- <title>Network Interfaces</title>
- <para>Are all the network interfaces functioning correctly? Are you sure? See the Troubleshooting Case Study in <xref linkend="trouble.casestudy"/>.
- </para>
+ <section
+ xml:id="trouble.namenode.uncompaction">
+ <title>Use Cases</title>
+ <para>Two common use-cases for querying HDFS for HBase objects is research the degree of
+ uncompaction of a table. If there are a large number of StoreFiles for each ColumnFamily
+ it could indicate the need for a major compaction. Additionally, after a major compaction
+ if the resulting StoreFile is "small" it could indicate the need for a reduction of
+ ColumnFamilies for the table. </para>
</section>
</section>
+ </section>
- <section xml:id="trouble.rs">
- <title>RegionServer</title>
- <para>For more information on the RegionServers, see <xref linkend="regionserver.arch"/>.
- </para>
- <section xml:id="trouble.rs.startup">
- <title>Startup Errors</title>
- <section xml:id="trouble.rs.startup.master-no-region">
- <title>Master Starts, But RegionServers Do Not</title>
- <para>The Master believes the RegionServers have the IP of 127.0.0.1 - which is localhost and resolves to the master's own localhost.
- </para>
- <para>The RegionServers are erroneously informing the Master that their IP addresses are 127.0.0.1.
- </para>
- <para>Modify <filename>/etc/hosts</filename> on the region servers, from...
- <programlisting>
+ <section
+ xml:id="trouble.network">
+ <title>Network</title>
+ <section
+ xml:id="trouble.network.spikes">
+ <title>Network Spikes</title>
+ <para>If you are seeing periodic network spikes you might want to check the
+ <code>compactionQueues</code> to see if major compactions are happening. </para>
+ <para>See <xref
+ linkend="managed.compactions" /> for more information on managing compactions. </para>
+ </section>
+ <section
+ xml:id="trouble.network.loopback">
+ <title>Loopback IP</title>
+ <para>HBase expects the loopback IP Address to be 127.0.0.1. See the Getting Started section
+ on <xref
+ linkend="loopback.ip" />. </para>
+ </section>
+ <section
+ xml:id="trouble.network.ints">
+ <title>Network Interfaces</title>
+ <para>Are all the network interfaces functioning correctly? Are you sure? See the
+ Troubleshooting Case Study in <xref
+ linkend="trouble.casestudy" />. </para>
+ </section>
+
+ </section>
+
+ <section
+ xml:id="trouble.rs">
+ <title>RegionServer</title>
+ <para>For more information on the RegionServers, see <xref
+ linkend="regionserver.arch" />. </para>
+ <section
+ xml:id="trouble.rs.startup">
+ <title>Startup Errors</title>
+ <section
+ xml:id="trouble.rs.startup.master-no-region">
+ <title>Master Starts, But RegionServers Do Not</title>
+ <para>The Master believes the RegionServers have the IP of 127.0.0.1 - which is localhost
+ and resolves to the master's own localhost. </para>
+ <para>The RegionServers are erroneously informing the Master that their IP addresses are
+ 127.0.0.1. </para>
+ <para>Modify <filename>/etc/hosts</filename> on the region servers, from...</para>
+ <programlisting>
# Do not remove the following line, or various programs
# that require network functionality will fail.
127.0.0.1 fully.qualified.regionservername regionservername localhost.localdomain localhost
::1 localhost6.localdomain6 localhost6
</programlisting>
- ... to (removing the master node's name from localhost)...
- <programlisting>
+ <para>... to (removing the master node's name from localhost)...</para>
+ <programlisting>
# Do not remove the following line, or various programs
# that require network functionality will fail.
127.0.0.1 localhost.localdomain localhost
::1 localhost6.localdomain6 localhost6
</programlisting>
- </para>
- </section>
+ </section>
- <section xml:id="trouble.rs.startup.compression">
- <title>Compression Link Errors</title>
- <para>
- Since compression algorithms such as LZO need to be installed and configured on each cluster this is a frequent source of startup error. If you see messages like this...
- <programlisting>
+ <section
+ xml:id="trouble.rs.startup.compression">
+ <title>Compression Link Errors</title>
+ <para> Since compression algorithms such as LZO need to be installed and configured on each
+ cluster this is a frequent source of startup error. If you see messages like
+ this...</para>
+ <programlisting>
11/02/20 01:32:15 ERROR lzo.GPLNativeCodeLoader: Could not load native gpl library
java.lang.UnsatisfiedLinkError: no gplcompression in java.library.path
at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1734)
at java.lang.Runtime.loadLibrary0(Runtime.java:823)
at java.lang.System.loadLibrary(System.java:1028)
</programlisting>
- .. then there is a path issue with the compression libraries. See the Configuration section on <link linkend="lzo.compression">LZO compression configuration</link>.
- </para>
- </section>
+ <para>.. then there is a
<TRUNCATED>
[09/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/ops_mgt.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/ops_mgt.xml b/src/main/docbkx/ops_mgt.xml
index 34c5471..0fdc1f2 100644
--- a/src/main/docbkx/ops_mgt.xml
+++ b/src/main/docbkx/ops_mgt.xml
@@ -1,8 +1,14 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="ops_mgt" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg" xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml" xmlns:db="http://docbook.org/ns/docbook">
+<chapter
+ version="5.0"
+ xml:id="ops_mgt"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
<!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
@@ -24,15 +30,18 @@
-->
<title>Apache HBase Operational Management</title>
<para> This chapter will cover operational tools and practices required of a running Apache HBase
- cluster. The subject of operations is related to the topics of <xref linkend="trouble"/>, <xref
- linkend="performance"/>, and <xref linkend="configuration"/> but is a distinct topic in
- itself. </para>
+ cluster. The subject of operations is related to the topics of <xref
+ linkend="trouble" />, <xref
+ linkend="performance" />, and <xref
+ linkend="configuration" /> but is a distinct topic in itself. </para>
- <section xml:id="tools">
+ <section
+ xml:id="tools">
<title>HBase Tools and Utilities</title>
<para>Here we list HBase tools for administration, analysis, fixup, and debugging.</para>
- <section xml:id="canary">
+ <section
+ xml:id="canary">
<title>Canary</title>
<para> There is a Canary class can help users to canary-test the HBase cluster status, with
every column-family for every regions or regionservers granularity. To see the usage, use
@@ -61,10 +70,20 @@ private static final int ERROR_EXIT_CODE = 4;</programlisting>
the 3 regionservers. see following table. </para>
<informaltable>
- <tgroup cols="3" align="center" colsep="1" rowsep="1">
- <colspec colname="regionserver" align="center"/>
- <colspec colname="test-01" align="center"/>
- <colspec colname="test-02" align="center"/>
+ <tgroup
+ cols="3"
+ align="center"
+ colsep="1"
+ rowsep="1">
+ <colspec
+ colname="regionserver"
+ align="center" />
+ <colspec
+ colname="test-01"
+ align="center" />
+ <colspec
+ colname="test-02"
+ align="center" />
<thead>
<row>
<entry>RegionServer</entry>
@@ -81,7 +100,7 @@ private static final int ERROR_EXIT_CODE = 4;</programlisting>
<row>
<entry>rs2</entry>
<entry>r2</entry>
- <entry/>
+ <entry />
</row>
<row>
<entry>rs3</entry>
@@ -94,7 +113,7 @@ private static final int ERROR_EXIT_CODE = 4;</programlisting>
<para> Following are some examples based on the previous given case. </para>
<section>
<title>Canary test for every column family (store) of every region of every table</title>
- <programlisting>$ ${HBASE_HOME}/bin/hbase org.apache.hadoop.hbase.tool.Canary
+ <screen>$ ${HBASE_HOME}/bin/hbase org.apache.hadoop.hbase.tool.Canary
3/12/09 03:26:32 INFO tool.Canary: read from region test-01,,1386230156732.0e3c7d77ffb6361ea1b996ac1042ca9a. column family cf1 in 2ms
13/12/09 03:26:32 INFO tool.Canary: read from region test-01,,1386230156732.0e3c7d77ffb6361ea1b996ac1042ca9a. column family cf2 in 2ms
@@ -105,7 +124,7 @@ private static final int ERROR_EXIT_CODE = 4;</programlisting>
13/12/09 03:26:32 INFO tool.Canary: read from region test-02,,1386559511167.aa2951a86289281beee480f107bb36ee. column family cf2 in 3ms
13/12/09 03:26:32 INFO tool.Canary: read from region test-02,0004883,1386559511167.cbda32d5e2e276520712d84eaaa29d84. column family cf1 in 31ms
13/12/09 03:26:32 INFO tool.Canary: read from region test-02,0004883,1386559511167.cbda32d5e2e276520712d84eaaa29d84. column family cf2 in 8ms
-</programlisting>
+</screen>
<para> So you can see, table test-01 has two regions and two column families, so the Canary
tool will pick 4 small piece of data from 4 (2 region * 2 store) different stores. This is
a default behavior of the this tool does. </para>
@@ -115,23 +134,23 @@ private static final int ERROR_EXIT_CODE = 4;</programlisting>
<title>Canary test for every column family (store) of every region of specific
table(s)</title>
<para> You can also test one or more specific tables.</para>
- <programlisting>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary test-01 test-02</programlisting>
+ <screen>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary test-01 test-02</screen>
</section>
<section>
<title>Canary test with regionserver granularity</title>
<para> This will pick one small piece of data from each regionserver, and can also put your
resionserver name as input options for canary-test specific regionservers.</para>
- <programlisting>$ ${HBASE_HOME}/bin/hbase org.apache.hadoop.hbase.tool.Canary -regionserver
+ <screen>$ ${HBASE_HOME}/bin/hbase org.apache.hadoop.hbase.tool.Canary -regionserver
13/12/09 06:05:17 INFO tool.Canary: Read from table:test-01 on region server:rs2 in 72ms
13/12/09 06:05:17 INFO tool.Canary: Read from table:test-02 on region server:rs3 in 34ms
-13/12/09 06:05:17 INFO tool.Canary: Read from table:test-01 on region server:rs1 in 56ms</programlisting>
+13/12/09 06:05:17 INFO tool.Canary: Read from table:test-01 on region server:rs1 in 56ms</screen>
</section>
<section>
<title>Canary test with regular expression pattern</title>
<para> This will test both table test-01 and test-02.</para>
- <programlisting>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary -e test-0[1-2]</programlisting>
+ <screen>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary -e test-0[1-2]</screen>
</section>
<section>
@@ -139,10 +158,10 @@ private static final int ERROR_EXIT_CODE = 4;</programlisting>
<para> Run repeatedly with interval defined in option -interval whose default value is 6
seconds. This daemon will stop itself and return non-zero error code if any error occurs,
due to the default value of option -f is true.</para>
- <programlisting>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary -daemon</programlisting>
+ <screen>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary -daemon</screen>
<para>Run repeatedly with internal 5 seconds and will not stop itself even error occurs in
the test.</para>
- <programlisting>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary -daemon -interval 50000 -f false</programlisting>
+ <screen>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary -daemon -interval 50000 -f false</screen>
</section>
<section>
@@ -152,23 +171,26 @@ private static final int ERROR_EXIT_CODE = 4;</programlisting>
Master, which would bring the clients hung. So we provide the timeout option to kill the
canary test forcefully and return non-zero error code as well. This run sets the timeout
value to 60 seconds, the default value is 600 seconds.</para>
- <programlisting>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary -t 600000</programlisting>
+ <screen>$ ${HBASE_HOME}/bin/hbase orghapache.hadoop.hbase.tool.Canary -t 600000</screen>
</section>
</section>
- <section xml:id="health.check">
+ <section
+ xml:id="health.check">
<title>Health Checker</title>
<para>You can configure HBase to run a script on a period and if it fails N times
- (configurable), have the server exit. See <link xlink:href="">HBASE-7351 Periodic health
- check script</link> for configurations and detail. </para>
+ (configurable), have the server exit. See <link
+ xlink:href="">HBASE-7351 Periodic health check script</link> for configurations and
+ detail. </para>
</section>
- <section xml:id="driver">
+ <section
+ xml:id="driver">
<title>Driver</title>
<para>There is a <code>Driver</code> class that is executed by the HBase jar can be used to
invoke frequently accessed utilities. For example,</para>
- <programlisting>HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-VERSION.jar
+ <screen>HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-VERSION.jar
An example program must be given as the first argument.
Valid program names are:
@@ -179,45 +201,52 @@ Valid program names are:
importtsv: Import data in TSV format.
rowcounter: Count rows in HBase table
verifyrep: Compare the data from tables in two different clusters. WARNING: It doesn't work for incrementColumnValues'd cells since the timestamp is chan
-</programlisting>
+ </screen>
</section>
- <section xml:id="hbck">
+ <section
+ xml:id="hbck">
<title>HBase <application>hbck</application></title>
<subtitle>An <command>fsck</command> for your HBase install</subtitle>
<para>To run <application>hbck</application> against your HBase cluster run <command>$
./bin/hbase hbck</command> At the end of the command's output it prints
- <screen>OK</screen> or <screen>INCONSISTENCY</screen>. If your cluster reports
+ <literal>OK</literal> or <literal>INCONSISTENCY</literal>. If your cluster reports
inconsistencies, pass <command>-details</command> to see more detail emitted. If
inconsistencies, run <command>hbck</command> a few times because the inconsistency may be
transient (e.g. cluster is starting up or a region is splitting). Passing
<command>-fix</command> may correct the inconsistency (This latter is an experimental
feature). </para>
- <para>For more information, see <xref linkend="hbck.in.depth"/>. </para>
+ <para>For more information, see <xref
+ linkend="hbck.in.depth" />. </para>
</section>
- <section xml:id="hfile_tool2">
+ <section
+ xml:id="hfile_tool2">
<title>HFile Tool</title>
- <para>See <xref linkend="hfile_tool"/>.</para>
+ <para>See <xref
+ linkend="hfile_tool" />.</para>
</section>
- <section xml:id="wal_tools">
+ <section
+ xml:id="wal_tools">
<title>WAL Tools</title>
- <section xml:id="hlog_tool">
+ <section
+ xml:id="hlog_tool">
<title><classname>FSHLog</classname> tool</title>
<para>The main method on <classname>FSHLog</classname> offers manual split and dump
facilities. Pass it WALs or the product of a split, the content of the
<filename>recovered.edits</filename>. directory.</para>
- <para>You can get a textual dump of a WAL file content by doing the
- following:<programlisting> <code>$ ./bin/hbase org.apache.hadoop.hbase.regionserver.wal.FSHLog --dump hdfs://example.org:8020/hbase/.logs/example.org,60020,1283516293161/10.10.21.10%3A60020.1283973724012</code> </programlisting>The
- return code will be non-zero if issues with the file so you can test wholesomeness of file
- by redirecting <varname>STDOUT</varname> to <code>/dev/null</code> and testing the program
- return.</para>
+ <para>You can get a textual dump of a WAL file content by doing the following:</para>
+ <screen> $ ./bin/hbase org.apache.hadoop.hbase.regionserver.wal.FSHLog --dump hdfs://example.org:8020/hbase/.logs/example.org,60020,1283516293161/10.10.21.10%3A60020.1283973724012 </screen>
+ <para>The return code will be non-zero if issues with the file so you can test wholesomeness
+ of file by redirecting <varname>STDOUT</varname> to <code>/dev/null</code> and testing the
+ program return.</para>
- <para>Similarly you can force a split of a log file directory by
- doing:<programlisting> $ ./<code>bin/hbase org.apache.hadoop.hbase.regionserver.wal.FSHLog --split hdfs://example.org:8020/hbase/.logs/example.org,60020,1283516293161/</code></programlisting></para>
+ <para>Similarly you can force a split of a log file directory by doing:</para>
+ <screen> $ ./bin/hbase org.apache.hadoop.hbase.regionserver.wal.FSHLog --split hdfs://example.org:8020/hbase/.logs/example.org,60020,1283516293161/</screen>
- <section xml:id="hlog_tool.prettyprint">
+ <section
+ xml:id="hlog_tool.prettyprint">
<title><classname>HLogPrettyPrinter</classname></title>
<para><classname>HLogPrettyPrinter</classname> is a tool with configurable options to
print the contents of an HLog. </para>
@@ -225,46 +254,67 @@ Valid program names are:
</section>
</section>
- <section xml:id="compression.tool">
+ <section
+ xml:id="compression.tool">
<title>Compression Tool</title>
- <para>See <xref linkend="compression.test"/>.</para>
+ <para>See <xref
+ linkend="compression.test" />.</para>
</section>
- <section xml:id="copytable">
+ <section
+ xml:id="copytable">
<title>CopyTable</title>
<para> CopyTable is a utility that can copy part or of all of a table, either to the same
cluster or another cluster. The target table must first exist. The usage is as
follows:</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.CopyTable [--starttime=X] [--endtime=Y] [--new.name=NEW] [--peer.adr=ADR] tablename
-</programlisting>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.CopyTable [--starttime=X] [--endtime=Y] [--new.name=NEW] [--peer.adr=ADR] tablename
+</screen>
- <itemizedlist>
+ <variablelist>
<title>Options</title>
- <listitem>
- <para><varname>starttime</varname> Beginning of the time range. Without endtime means
- starttime to forever.</para>
- </listitem>
- <listitem>
- <para><varname>endtime</varname> End of the time range. Without endtime means starttime to
- forever.</para>
- </listitem>
- <listitem>
- <para><varname>versions</varname> Number of cell versions to copy.</para>
- </listitem>
- <listitem>
- <para><varname>new.name</varname> New table's name.</para>
- </listitem>
- <listitem>
- <para><varname>peer.adr</varname> Address of the peer cluster given in the format
- hbase.zookeeper.quorum:hbase.zookeeper.client.port:zookeeper.znode.parent</para>
- </listitem>
- <listitem>
- <para><varname>families</varname> Comma-separated list of ColumnFamilies to copy.</para>
- </listitem>
- <listitem>
- <para><varname>all.cells</varname> Also copy delete markers and uncollected deleted cells
- (advanced option).</para>
- </listitem>
- </itemizedlist>
+ <varlistentry>
+ <term>starttime</term>
+ <listitem>
+ <para>Beginning of the time range. Without endtime means starttime to forever.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>endtime</term>
+ <listitem>
+ <para>End of the time range. Without endtime means starttime to forever.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>versions</term>
+ <listitem>
+ <para>Number of cell versions to copy.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>new.name</term>
+ <listitem>
+ <para>New table's name.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>peer.adr</term>
+ <listitem>
+ <para>Address of the peer cluster given in the format
+ hbase.zookeeper.quorum:hbase.zookeeper.client.port:zookeeper.znode.parent</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>families</term>
+ <listitem>
+ <para>Comma-separated list of ColumnFamilies to copy.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>all.cells</term>
+ <listitem>
+ <para>Also copy delete markers and uncollected deleted cells (advanced option).</para>
+ </listitem>
+ </varlistentry>
+ </variablelist>
<itemizedlist>
<title>Args:</title>
<listitem>
@@ -273,9 +323,9 @@ Valid program names are:
</itemizedlist>
<para>Example of copying 'TestTable' to a cluster that uses replication for a 1 hour
window:</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.CopyTable
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.CopyTable
--starttime=1265875194289 --endtime=1265878794289
---peer.adr=server1,server2,server3:2181:/hbase TestTable</programlisting>
+--peer.adr=server1,server2,server3:2181:/hbase TestTable</screen>
<note>
<title>Scanner Caching</title>
<para>Caching for the input Scan is configured via <code>hbase.client.scanner.caching</code>
@@ -287,49 +337,54 @@ Valid program names are:
<code>--versions=n</code> is explicitly specified in the command. </para>
</note>
<para> See Jonathan Hsieh's <link
- xlink:href="http://www.cloudera.com/blog/2012/06/online-hbase-backups-with-copytable-2/"
- >Online HBase Backups with CopyTable</link> blog post for more on
- <command>CopyTable</command>. </para>
+ xlink:href="http://www.cloudera.com/blog/2012/06/online-hbase-backups-with-copytable-2/">Online
+ HBase Backups with CopyTable</link> blog post for more on <command>CopyTable</command>.
+ </para>
</section>
- <section xml:id="export">
+ <section
+ xml:id="export">
<title>Export</title>
<para>Export is a utility that will dump the contents of table to HDFS in a sequence file.
Invoke via:</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.Export <tablename> <outputdir> [<versions> [<starttime> [<endtime>]]]
-</programlisting>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.Export <tablename> <outputdir> [<versions> [<starttime> [<endtime>]]]
+</screen>
<para>Note: caching for the input Scan is configured via
<code>hbase.client.scanner.caching</code> in the job configuration. </para>
</section>
- <section xml:id="import">
+ <section
+ xml:id="import">
<title>Import</title>
<para>Import is a utility that will load data that has been exported back into HBase. Invoke
via:</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.Import <tablename> <inputdir>
-</programlisting>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.Import <tablename> <inputdir>
+</screen>
<para>To import 0.94 exported files in a 0.96 cluster or onwards, you need to set system
property "hbase.import.version" when running the import command as below:</para>
- <programlisting>$ bin/hbase -Dhbase.import.version=0.94 org.apache.hadoop.hbase.mapreduce.Import <tablename> <inputdir>
-</programlisting>
+ <screen>$ bin/hbase -Dhbase.import.version=0.94 org.apache.hadoop.hbase.mapreduce.Import <tablename> <inputdir>
+</screen>
</section>
- <section xml:id="importtsv">
+ <section
+ xml:id="importtsv">
<title>ImportTsv</title>
<para>ImportTsv is a utility that will load data in TSV format into HBase. It has two distinct
usages: loading data from TSV format in HDFS into HBase via Puts, and preparing StoreFiles
to be loaded via the <code>completebulkload</code>. </para>
<para>To load data via Puts (i.e., non-bulk loading):</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.ImportTsv -Dimporttsv.columns=a,b,c <tablename> <hdfs-inputdir>
-</programlisting>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.ImportTsv -Dimporttsv.columns=a,b,c <tablename> <hdfs-inputdir>
+</screen>
<para>To generate StoreFiles for bulk-loading:</para>
<programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.ImportTsv -Dimporttsv.columns=a,b,c -Dimporttsv.bulk.output=hdfs://storefile-outputdir <tablename> <hdfs-data-inputdir>
</programlisting>
- <para>These generated StoreFiles can be loaded into HBase via <xref linkend="completebulkload"
- />. </para>
- <section xml:id="importtsv.options">
+ <para>These generated StoreFiles can be loaded into HBase via <xref
+ linkend="completebulkload" />. </para>
+ <section
+ xml:id="importtsv.options">
<title>ImportTsv Options</title>
- <para>Running ImportTsv with no arguments prints brief usage information:</para>
- <programlisting>
+ <para>Running <command>ImportTsv</command> with no arguments prints brief usage
+ information:</para>
+ <screen>
Usage: importtsv -Dimporttsv.columns=a,b,c <tablename> <inputdir>
Imports the given input directory of TSV data into the specified table.
@@ -352,14 +407,15 @@ Other options that may be specified with -D include:
'-Dimporttsv.separator=|' - eg separate on pipes instead of tabs
-Dimporttsv.timestamp=currentTimeAsLong - use the specified timestamp for the import
-Dimporttsv.mapper.class=my.Mapper - A user-defined Mapper to use instead of org.apache.hadoop.hbase.mapreduce.TsvImporterMapper
-</programlisting>
+ </screen>
</section>
- <section xml:id="importtsv.example">
+ <section
+ xml:id="importtsv.example">
<title>ImportTsv Example</title>
<para>For example, assume that we are loading data into a table called 'datatsv' with a
ColumnFamily called 'd' with two columns "c1" and "c2". </para>
<para>Assume that an input file exists as follows:
- <programlisting>
+ <screen>
row1 c1 c2
row2 c1 c2
row3 c1 c2
@@ -370,51 +426,56 @@ row7 c1 c2
row8 c1 c2
row9 c1 c2
row10 c1 c2
-</programlisting>
+ </screen>
</para>
<para>For ImportTsv to use this imput file, the command line needs to look like this:</para>
- <programlisting>
+ <screen>
HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-VERSION.jar importtsv -Dimporttsv.columns=HBASE_ROW_KEY,d:c1,d:c2 -Dimporttsv.bulk.output=hdfs://storefileoutput datatsv hdfs://inputfile
- </programlisting>
+ </screen>
<para> ... and in this example the first column is the rowkey, which is why the
HBASE_ROW_KEY is used. The second and third columns in the file will be imported as "d:c1"
and "d:c2", respectively. </para>
</section>
- <section xml:id="importtsv.warning">
+ <section
+ xml:id="importtsv.warning">
<title>ImportTsv Warning</title>
<para>If you have preparing a lot of data for bulk loading, make sure the target HBase table
is pre-split appropriately. </para>
</section>
- <section xml:id="importtsv.also">
+ <section
+ xml:id="importtsv.also">
<title>See Also</title>
<para>For more information about bulk-loading HFiles into HBase, see <xref
- linkend="arch.bulk.load"/></para>
+ linkend="arch.bulk.load" /></para>
</section>
</section>
- <section xml:id="completebulkload">
+ <section
+ xml:id="completebulkload">
<title>CompleteBulkLoad</title>
<para>The <code>completebulkload</code> utility will move generated StoreFiles into an HBase
- table. This utility is often used in conjunction with output from <xref linkend="importtsv"
- />. </para>
+ table. This utility is often used in conjunction with output from <xref
+ linkend="importtsv" />. </para>
<para>There are two ways to invoke this utility, with explicit classname and via the
driver:</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles <hdfs://storefileoutput> <tablename>
-</programlisting>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles <hdfs://storefileoutput> <tablename>
+</screen>
<para> .. and via the Driver..</para>
- <programlisting>HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-VERSION.jar completebulkload <hdfs://storefileoutput> <tablename>
-</programlisting>
- <section xml:id="completebulkload.warning">
+ <screen>HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-VERSION.jar completebulkload <hdfs://storefileoutput> <tablename>
+</screen>
+ <section
+ xml:id="completebulkload.warning">
<title>CompleteBulkLoad Warning</title>
<para>Data generated via MapReduce is often created with file permissions that are not
compatible with the running HBase process. Assuming you're running HDFS with permissions
enabled, those permissions will need to be updated before you run CompleteBulkLoad.</para>
<para>For more information about bulk-loading HFiles into HBase, see <xref
- linkend="arch.bulk.load"/>. </para>
+ linkend="arch.bulk.load" />. </para>
</section>
</section>
- <section xml:id="walplayer">
+ <section
+ xml:id="walplayer">
<title>WALPlayer</title>
<para>WALPlayer is a utility to replay WAL files into HBase. </para>
<para>The WAL can be replayed for a set of tables or all tables, and a timerange can be
@@ -423,32 +484,32 @@ row10 c1 c2
<para>WALPlayer can also generate HFiles for later bulk importing, in that case only a single
table and no mapping can be specified. </para>
<para>Invoke via:</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.WALPlayer [options] <wal inputdir> <tables> [<tableMappings>]>
-</programlisting>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.WALPlayer [options] <wal inputdir> <tables> [<tableMappings>]>
+</screen>
<para>For example:</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.WALPlayer /backuplogdir oldTable1,oldTable2 newTable1,newTable2
-</programlisting>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.WALPlayer /backuplogdir oldTable1,oldTable2 newTable1,newTable2
+</screen>
<para> WALPlayer, by default, runs as a mapreduce job. To NOT run WALPlayer as a mapreduce job
on your cluster, force it to run all in the local process by adding the flags
<code>-Dmapreduce.jobtracker.address=local</code> on the command line. </para>
</section>
- <section xml:id="rowcounter">
+ <section
+ xml:id="rowcounter">
<title>RowCounter and CellCounter</title>
<para><link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/RowCounter.html"
- >RowCounter</link> is a mapreduce job to count all the rows of a table. This is a good
- utility to use as a sanity check to ensure that HBase can read all the blocks of a table if
- there are any concerns of metadata inconsistency. It will run the mapreduce all in a single
- process but it will run faster if you have a MapReduce cluster in place for it to
- exploit.</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.RowCounter <tablename> [<column1> <column2>...]
-</programlisting>
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/RowCounter.html">RowCounter</link>
+ is a mapreduce job to count all the rows of a table. This is a good utility to use as a
+ sanity check to ensure that HBase can read all the blocks of a table if there are any
+ concerns of metadata inconsistency. It will run the mapreduce all in a single process but it
+ will run faster if you have a MapReduce cluster in place for it to exploit.</para>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.RowCounter <tablename> [<column1> <column2>...]
+</screen>
<para>Note: caching for the input Scan is configured via
<code>hbase.client.scanner.caching</code> in the job configuration. </para>
<para>HBase ships another diagnostic mapreduce job called <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/CellCounter.html"
- >CellCounter</link>. Like RowCounter, it gathers more fine-grained statistics about your
- table. The statistics gathered by RowCounter are more fine-grained and include: </para>
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/CellCounter.html">CellCounter</link>.
+ Like RowCounter, it gathers more fine-grained statistics about your table. The statistics
+ gathered by RowCounter are more fine-grained and include: </para>
<itemizedlist>
<listitem>
<para>Total number of rows in the table.</para>
@@ -472,11 +533,12 @@ row10 c1 c2
<para>The program allows you to limit the scope of the run. Provide a row regex or prefix to
limit the rows to analyze. Use <code>hbase.mapreduce.scan.column.family</code> to specify
scanning a single column family.</para>
- <programlisting>$ bin/hbase org.apache.hadoop.hbase.mapreduce.CellCounter <tablename> <outputDir> [regex or prefix]</programlisting>
+ <screen>$ bin/hbase org.apache.hadoop.hbase.mapreduce.CellCounter <tablename> <outputDir> [regex or prefix]</screen>
<para>Note: just like RowCounter, caching for the input Scan is configured via
<code>hbase.client.scanner.caching</code> in the job configuration. </para>
</section>
- <section xml:id="mlockall">
+ <section
+ xml:id="mlockall">
<title>mlockall</title>
<para>It is possible to optionally pin your servers in physical memory making them less likely
to be swapped out in oversubscribed environments by having the servers call <link
@@ -485,11 +547,12 @@ row10 c1 c2
start RS as root and call mlockall</link> for how to build the optional library and have
it run on startup. </para>
</section>
- <section xml:id="compaction.tool">
+ <section
+ xml:id="compaction.tool">
<title>Offline Compaction Tool</title>
<para>See the usage for the <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/regionserver/CompactionTool.html"
- >Compaction Tool</link>. Run it like this <command>./bin/hbase
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/regionserver/CompactionTool.html">Compaction
+ Tool</link>. Run it like this <command>./bin/hbase
org.apache.hadoop.hbase.regionserver.CompactionTool</command>
</para>
</section>
@@ -497,17 +560,19 @@ row10 c1 c2
</section>
<!-- tools -->
- <section xml:id="ops.regionmgt">
+ <section
+ xml:id="ops.regionmgt">
<title>Region Management</title>
- <section xml:id="ops.regionmgt.majorcompact">
+ <section
+ xml:id="ops.regionmgt.majorcompact">
<title>Major Compaction</title>
<para>Major compactions can be requested via the HBase shell or <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HBaseAdmin.html#majorCompact%28java.lang.String%29"
- >HBaseAdmin.majorCompact</link>. </para>
- <para>Note: major compactions do NOT do region merges. See <xref linkend="compaction"/> for
- more information about compactions. </para>
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HBaseAdmin.html#majorCompact%28java.lang.String%29">HBaseAdmin.majorCompact</link>. </para>
+ <para>Note: major compactions do NOT do region merges. See <xref
+ linkend="compaction" /> for more information about compactions. </para>
</section>
- <section xml:id="ops.regionmgt.merge">
+ <section
+ xml:id="ops.regionmgt.merge">
<title>Merge</title>
<para>Merge is a utility that can merge adjoining regions in the same table (see
org.apache.hadoop.hbase.util.Merge).</para>
@@ -527,13 +592,15 @@ row10 c1 c2
</section>
</section>
- <section xml:id="node.management">
+ <section
+ xml:id="node.management">
<title>Node Management</title>
- <section xml:id="decommission">
+ <section
+ xml:id="decommission">
<title>Node Decommission</title>
<para>You can stop an individual RegionServer by running the following script in the HBase
directory on the particular node:</para>
- <programlisting>$ ./bin/hbase-daemon.sh stop regionserver</programlisting>
+ <screen>$ ./bin/hbase-daemon.sh stop regionserver</screen>
<para> The RegionServer will first close all regions and then shut itself down. On shutdown,
the RegionServer's ephemeral node in ZooKeeper will expire. The master will notice the
RegionServer gone and will treat it as a 'crashed' server; it will reassign the nodes the
@@ -542,8 +609,8 @@ row10 c1 c2
<title>Disable the Load Balancer before Decommissioning a node</title>
<para>If the load balancer runs while a node is shutting down, then there could be
contention between the Load Balancer and the Master's recovery of the just decommissioned
- RegionServer. Avoid any problems by disabling the balancer first. See <xref linkend="lb"/>
- below. </para>
+ RegionServer. Avoid any problems by disabling the balancer first. See <xref
+ linkend="lb" /> below. </para>
</note>
<para> A downside to the above stop of a RegionServer is that regions could be offline for a
good period of time. Regions are closed in order. If many regions on the server, the first
@@ -551,14 +618,14 @@ row10 c1 c2
the RegionServer's znode gone. In Apache HBase 0.90.2, we added facility for having a node
gradually shed its load and then shutdown itself down. Apache HBase 0.90.2 added the
<filename>graceful_stop.sh</filename> script. Here is its usage:</para>
- <programlisting>$ ./bin/graceful_stop.sh
+ <screen>$ ./bin/graceful_stop.sh
Usage: graceful_stop.sh [--config &conf-dir>] [--restart] [--reload] [--thrift] [--rest] &hostname>
thrift If we should stop/start thrift before/after the hbase stop/start
rest If we should stop/start rest before/after the hbase stop/start
restart If we should restart after graceful stop
reload Move offloaded regions back on to the stopped server
debug Move offloaded regions back on to the stopped server
- hostname Hostname of server we are to stop</programlisting>
+ hostname Hostname of server we are to stop</screen>
<para> To decommission a loaded RegionServer, run the following: <command>$
./bin/graceful_stop.sh HOSTNAME</command> where <varname>HOSTNAME</varname> is the host
carrying the RegionServer you would decommission. </para>
@@ -581,7 +648,8 @@ Usage: graceful_stop.sh [--config &conf-dir>] [--restart] [--reload] [--thri
master will at this point notice the RegionServer gone but all regions will have already
been redeployed and because the RegionServer went down cleanly, there will be no WAL logs to
split. </para>
- <note xml:id="lb">
+ <note
+ xml:id="lb">
<title>Load Balancer</title>
<para> It is assumed that the Region Load Balancer is disabled while the
<command>graceful_stop</command> script runs (otherwise the balancer and the
@@ -600,7 +668,8 @@ false
<command>graceful_stop</command> reenabling it after you are done w/ graceful_stop.
</para>
</note>
- <section xml:id="draining.servers">
+ <section
+ xml:id="draining.servers">
<title>Decommissioning several Regions Servers concurrently</title>
<para>If you have a large cluster, you may want to decommission more than one machine at a
time by gracefully stopping mutiple RegionServers concurrently. To gracefully drain
@@ -614,25 +683,27 @@ false
that are also draining. Marking RegionServers to be in the draining state prevents this
from happening<footnote>
<para>See this <link
- xlink:href="http://inchoate-clatter.blogspot.com/2012/03/hbase-ops-automation.html"
- >blog post</link> for more details.</para>
+ xlink:href="http://inchoate-clatter.blogspot.com/2012/03/hbase-ops-automation.html">blog
+ post</link> for more details.</para>
</footnote>. </para>
</section>
- <section xml:id="bad.disk">
+ <section
+ xml:id="bad.disk">
<title>Bad or Failing Disk</title>
- <para>It is good having <xref linkend="dfs.datanode.failed.volumes.tolerated"/> set if you
- have a decent number of disks per machine for the case where a disk plain dies. But
- usually disks do the "John Wayne" -- i.e. take a while to go down spewing errors in
- <filename>dmesg</filename> -- or for some reason, run much slower than their companions.
- In this case you want to decommission the disk. You have two options. You can <link
- xlink:href="http://wiki.apache.org/hadoop/FAQ#I_want_to_make_a_large_cluster_smaller_by_taking_out_a_bunch_of_nodes_simultaneously._How_can_this_be_done.3F"
- >decommission the datanode</link> or, less disruptive in that only the bad disks data
- will be rereplicated, can stop the datanode, unmount the bad volume (You can't umount a
- volume while the datanode is using it), and then restart the datanode (presuming you have
- set dfs.datanode.failed.volumes.tolerated > 0). The regionserver will throw some errors in
- its logs as it recalibrates where to get its data from -- it will likely roll its WAL log
- too -- but in general but for some latency spikes, it should keep on chugging. </para>
+ <para>It is good having <xref
+ linkend="dfs.datanode.failed.volumes.tolerated" /> set if you have a decent number of
+ disks per machine for the case where a disk plain dies. But usually disks do the "John
+ Wayne" -- i.e. take a while to go down spewing errors in <filename>dmesg</filename> -- or
+ for some reason, run much slower than their companions. In this case you want to
+ decommission the disk. You have two options. You can <link
+ xlink:href="http://wiki.apache.org/hadoop/FAQ#I_want_to_make_a_large_cluster_smaller_by_taking_out_a_bunch_of_nodes_simultaneously._How_can_this_be_done.3F">decommission
+ the datanode</link> or, less disruptive in that only the bad disks data will be
+ rereplicated, can stop the datanode, unmount the bad volume (You can't umount a volume
+ while the datanode is using it), and then restart the datanode (presuming you have set
+ dfs.datanode.failed.volumes.tolerated > 0). The regionserver will throw some errors in its
+ logs as it recalibrates where to get its data from -- it will likely roll its WAL log too
+ -- but in general but for some latency spikes, it should keep on chugging. </para>
<note>
<title>Short Circuit Reads</title>
<para>If you are doing short-circuit reads, you will have to move the regions off the
@@ -643,13 +714,13 @@ false
</note>
</section>
</section>
- <section xml:id="rolling">
+ <section
+ xml:id="rolling">
<title>Rolling Restart</title>
<para> You can also ask this script to restart a RegionServer after the shutdown AND move its
old regions back into place. The latter you might do to retain data locality. A primitive
rolling restart might be effected by running something like the following:</para>
- <screen>$ for i in `cat conf/regionservers|sort`; do ./bin/graceful_stop.sh --restart --reload --debug $i; done &> /tmp/log.txt &
- </screen>
+ <screen>$ for i in `cat conf/regionservers|sort`; do ./bin/graceful_stop.sh --restart --reload --debug $i; done &> /tmp/log.txt &</screen>
<para> Tail the output of <filename>/tmp/log.txt</filename> to follow the scripts progress.
The above does RegionServers only. The script will also disable the load balancer before
moving the regions. You'd need to do the master update separately. Do it before you run the
@@ -689,7 +760,8 @@ false
multiple regions go offline simultaneously as they are re-assigned to other nodes. Depending
on your usage patterns, this might not be desirable. </para>
</section>
- <section xml:id="adding.new.node">
+ <section
+ xml:id="adding.new.node">
<title>Adding a New Node</title>
<para>Adding a new regionserver in HBase is essentially free, you simply start it like this:
<command>$ ./bin/hbase-daemon.sh start regionserver</command> and it will register itself
@@ -713,126 +785,151 @@ false
</section>
<!-- node mgt -->
- <section xml:id="hbase_metrics">
+ <section
+ xml:id="hbase_metrics">
<title>HBase Metrics</title>
- <section xml:id="metric_setup">
+ <section
+ xml:id="metric_setup">
<title>Metric Setup</title>
- <para>See <link xlink:href="http://hbase.apache.org/metrics.html">Metrics</link> for an
- introduction and how to enable Metrics emission. Still valid for HBase 0.94.x. </para>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/metrics.html">Metrics</link> for an introduction and
+ how to enable Metrics emission. Still valid for HBase 0.94.x. </para>
<para>For HBase 0.95.x and up, see <link
- xlink:href="http://hadoop.apache.org/docs/current/api/org/apache/hadoop/metrics2/package-summary.html"
- />
+ xlink:href="http://hadoop.apache.org/docs/current/api/org/apache/hadoop/metrics2/package-summary.html" />
</para>
</section>
- <section xml:id="rs_metrics_ganglia">
+ <section
+ xml:id="rs_metrics_ganglia">
<title>Warning To Ganglia Users</title>
<para>Warning to Ganglia Users: by default, HBase will emit a LOT of metrics per RegionServer
which may swamp your installation. Options include either increasing Ganglia server
capacity, or configuring HBase to emit fewer metrics. </para>
</section>
- <section xml:id="rs_metrics">
+ <section
+ xml:id="rs_metrics">
<title>Most Important RegionServer Metrics</title>
- <section xml:id="hbase.regionserver.blockCacheHitCachingRatio">
+ <section
+ xml:id="hbase.regionserver.blockCacheHitCachingRatio">
<title><varname>blockCacheExpressCachingRatio (formerly
blockCacheHitCachingRatio)</varname></title>
<para>Block cache hit caching ratio (0 to 100). The cache-hit ratio for reads configured to
look in the cache (i.e., cacheBlocks=true). </para>
</section>
- <section xml:id="hbase.regionserver.callQueueLength">
+ <section
+ xml:id="hbase.regionserver.callQueueLength">
<title><varname>callQueueLength</varname></title>
<para>Point in time length of the RegionServer call queue. If requests arrive faster than
the RegionServer handlers can process them they will back up in the callQueue.</para>
</section>
- <section xml:id="hbase.regionserver.compactionQueueSize">
+ <section
+ xml:id="hbase.regionserver.compactionQueueSize">
<title><varname>compactionQueueLength (formerly compactionQueueSize)</varname></title>
<para>Point in time length of the compaction queue. This is the number of Stores in the
RegionServer that have been targeted for compaction.</para>
</section>
- <section xml:id="hbase.regionserver.flushQueueSize">
+ <section
+ xml:id="hbase.regionserver.flushQueueSize">
<title><varname>flushQueueSize</varname></title>
<para>Point in time number of enqueued regions in the MemStore awaiting flush.</para>
</section>
- <section xml:id="hbase.regionserver.hdfsBlocksLocalityIndex">
+ <section
+ xml:id="hbase.regionserver.hdfsBlocksLocalityIndex">
<title><varname>hdfsBlocksLocalityIndex</varname></title>
<para>Point in time percentage of HDFS blocks that are local to this RegionServer. The
higher the better. </para>
</section>
- <section xml:id="hbase.regionserver.memstoreSizeMB">
+ <section
+ xml:id="hbase.regionserver.memstoreSizeMB">
<title><varname>memstoreSizeMB</varname></title>
<para>Point in time sum of all the memstore sizes in this RegionServer (MB). Watch for this
nearing or exceeding the configured high-watermark for MemStore memory in the
RegionServer. </para>
</section>
- <section xml:id="hbase.regionserver.regions">
+ <section
+ xml:id="hbase.regionserver.regions">
<title><varname>numberOfOnlineRegions</varname></title>
<para>Point in time number of regions served by the RegionServer. This is an important
metric to track for RegionServer-Region density. </para>
</section>
- <section xml:id="hbase.regionserver.readRequestsCount">
+ <section
+ xml:id="hbase.regionserver.readRequestsCount">
<title><varname>readRequestsCount</varname></title>
<para>Number of read requests for this RegionServer since startup. Note: this is a 32-bit
integer and can roll. </para>
</section>
- <section xml:id="hbase.regionserver.slowHLogAppendCount">
+ <section
+ xml:id="hbase.regionserver.slowHLogAppendCount">
<title><varname>slowHLogAppendCount</varname></title>
<para>Number of slow HLog append writes for this RegionServer since startup, where "slow" is
> 1 second. This is a good "canary" metric for HDFS. </para>
</section>
- <section xml:id="hbase.regionserver.usedHeapMB">
+ <section
+ xml:id="hbase.regionserver.usedHeapMB">
<title><varname>usedHeapMB</varname></title>
<para>Point in time amount of memory used by the RegionServer (MB).</para>
</section>
- <section xml:id="hbase.regionserver.writeRequestsCount">
+ <section
+ xml:id="hbase.regionserver.writeRequestsCount">
<title><varname>writeRequestsCount</varname></title>
<para>Number of write requests for this RegionServer since startup. Note: this is a 32-bit
integer and can roll. </para>
</section>
</section>
- <section xml:id="rs_metrics_other">
+ <section
+ xml:id="rs_metrics_other">
<title>Other RegionServer Metrics</title>
- <section xml:id="hbase.regionserver.blockCacheCount">
+ <section
+ xml:id="hbase.regionserver.blockCacheCount">
<title><varname>blockCacheCount</varname></title>
<para>Point in time block cache item count in memory. This is the number of blocks of
StoreFiles (HFiles) in the cache.</para>
</section>
- <section xml:id="hbase.regionserver.blockCacheEvictedCount">
+ <section
+ xml:id="hbase.regionserver.blockCacheEvictedCount">
<title><varname>blockCacheEvictedCount</varname></title>
<para>Number of blocks that had to be evicted from the block cache due to heap size
constraints by RegionServer since startup.</para>
</section>
- <section xml:id="hbase.regionserver.blockCacheFree">
+ <section
+ xml:id="hbase.regionserver.blockCacheFree">
<title><varname>blockCacheFreeMB</varname></title>
<para>Point in time block cache memory available (MB).</para>
</section>
- <section xml:id="hbase.regionserver.blockCacheHitCount">
+ <section
+ xml:id="hbase.regionserver.blockCacheHitCount">
<title><varname>blockCacheHitCount</varname></title>
<para>Number of blocks of StoreFiles (HFiles) read from the cache by RegionServer since
startup.</para>
</section>
- <section xml:id="hbase.regionserver.blockCacheHitRatio">
+ <section
+ xml:id="hbase.regionserver.blockCacheHitRatio">
<title><varname>blockCacheHitRatio</varname></title>
<para>Block cache hit ratio (0 to 100) from RegionServer startup. Includes all read
requests, although those with cacheBlocks=false will always read from disk and be counted
as a "cache miss", which means that full-scan MapReduce jobs can affect this metric
significantly.</para>
</section>
- <section xml:id="hbase.regionserver.blockCacheMissCount">
+ <section
+ xml:id="hbase.regionserver.blockCacheMissCount">
<title><varname>blockCacheMissCount</varname></title>
<para>Number of blocks of StoreFiles (HFiles) requested but not read from the cache from
RegionServer startup.</para>
</section>
- <section xml:id="hbase.regionserver.blockCacheSize">
+ <section
+ xml:id="hbase.regionserver.blockCacheSize">
<title><varname>blockCacheSizeMB</varname></title>
<para>Point in time block cache size in memory (MB). i.e., memory in use by the
BlockCache</para>
</section>
- <section xml:id="hbase.regionserver.fsPreadLatency">
+ <section
+ xml:id="hbase.regionserver.fsPreadLatency">
<title><varname>fsPreadLatency*</varname></title>
<para>There are several filesystem positional read latency (ms) metrics, all measured from
RegionServer startup.</para>
</section>
- <section xml:id="hbase.regionserver.fsReadLatency">
+ <section
+ xml:id="hbase.regionserver.fsReadLatency">
<title><varname>fsReadLatency*</varname></title>
<para>There are several filesystem read latency (ms) metrics, all measured from RegionServer
startup. The issue with interpretation is that ALL reads go into this metric (e.g.,
@@ -840,25 +937,29 @@ false
metric is only interesting "over time" when comparing major releases of HBase or your own
code.</para>
</section>
- <section xml:id="hbase.regionserver.fsWriteLatency">
+ <section
+ xml:id="hbase.regionserver.fsWriteLatency">
<title><varname>fsWriteLatency*</varname></title>
<para>There are several filesystem write latency (ms) metrics, all measured from
RegionServer startup. The issue with interpretation is that ALL writes go into this metric
(e.g., single-record Puts, full table re-writes due to compaction). This metric is only
interesting "over time" when comparing major releases of HBase or your own code.</para>
</section>
- <section xml:id="hbase.regionserver.stores">
+ <section
+ xml:id="hbase.regionserver.stores">
<title><varname>NumberOfStores</varname></title>
<para>Point in time number of Stores open on the RegionServer. A Store corresponds to a
ColumnFamily. For example, if a table (which contains the column family) has 3 regions on
a RegionServer, there will be 3 stores open for that column family. </para>
</section>
- <section xml:id="hbase.regionserver.storeFiles">
+ <section
+ xml:id="hbase.regionserver.storeFiles">
<title><varname>NumberOfStorefiles</varname></title>
<para>Point in time number of StoreFiles open on the RegionServer. A store may have more
than one StoreFile (HFile).</para>
</section>
- <section xml:id="hbase.regionserver.requests">
+ <section
+ xml:id="hbase.regionserver.requests">
<title><varname>requestsPerSecond</varname></title>
<para>Point in time number of read and write requests. Requests correspond to RegionServer
RPC calls, thus a single Get will result in 1 request, but a Scan with caching set to 1000
@@ -867,16 +968,19 @@ false
readRequestsCount and writeRequestsCount in terms of measuring activity due to this metric
being periodic. </para>
</section>
- <section xml:id="hbase.regionserver.storeFileIndexSizeMB">
+ <section
+ xml:id="hbase.regionserver.storeFileIndexSizeMB">
<title><varname>storeFileIndexSizeMB</varname></title>
<para>Point in time sum of all the StoreFile index sizes in this RegionServer (MB)</para>
</section>
</section>
</section>
- <section xml:id="ops.monitoring">
+ <section
+ xml:id="ops.monitoring">
<title>HBase Monitoring</title>
- <section xml:id="ops.monitoring.overview">
+ <section
+ xml:id="ops.monitoring.overview">
<title>Overview</title>
<para>The following metrics are arguably the most important to monitor for each RegionServer
for "macro monitoring", preferably with a system like <link
@@ -885,7 +989,8 @@ false
<itemizedlist>
<title>HBase:</title>
<listitem>
- <para>See <xref linkend="rs_metrics"/></para>
+ <para>See <xref
+ linkend="rs_metrics" /></para>
</listitem>
</itemizedlist>
@@ -904,10 +1009,12 @@ false
<para>GC</para>
</listitem>
</itemizedlist>
- <para> For more information on HBase metrics, see <xref linkend="hbase_metrics"/>. </para>
+ <para> For more information on HBase metrics, see <xref
+ linkend="hbase_metrics" />. </para>
</section>
- <section xml:id="ops.slow.query">
+ <section
+ xml:id="ops.slow.query">
<title>Slow Query Log</title>
<para>The HBase slow query log consists of parseable JSON structures describing the properties
of those client operations (Gets, Puts, Deletes, etc.) that either took too long to run, or
@@ -988,30 +1095,35 @@ false
</section>
- <section xml:id="cluster_replication">
+ <section
+ xml:id="cluster_replication">
<title>Cluster Replication</title>
- <para>See <link xlink:href="http://hbase.apache.org/replication.html">Cluster
- Replication</link>. </para>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/replication.html">Cluster Replication</link>. </para>
</section>
- <section xml:id="ops.backup">
+ <section
+ xml:id="ops.backup">
<title>HBase Backup</title>
<para>There are two broad strategies for performing HBase backups: backing up with a full
cluster shutdown, and backing up on a live cluster. Each approach has pros and cons. </para>
<para>For additional information, see <link
xlink:href="http://blog.sematext.com/2011/03/11/hbase-backup-options/">HBase Backup
Options</link> over on the Sematext Blog. </para>
- <section xml:id="ops.backup.fullshutdown">
+ <section
+ xml:id="ops.backup.fullshutdown">
<title>Full Shutdown Backup</title>
<para>Some environments can tolerate a periodic full shutdown of their HBase cluster, for
example if it is being used a back-end analytic capacity and not serving front-end
web-pages. The benefits are that the NameNode/Master are RegionServers are down, so there is
no chance of missing any in-flight changes to either StoreFiles or metadata. The obvious con
is that the cluster is down. The steps include: </para>
- <section xml:id="ops.backup.fullshutdown.stop">
+ <section
+ xml:id="ops.backup.fullshutdown.stop">
<title>Stop HBase</title>
<para> </para>
</section>
- <section xml:id="ops.backup.fullshutdown.distcp">
+ <section
+ xml:id="ops.backup.fullshutdown.distcp">
<title>Distcp</title>
<para>Distcp could be used to either copy the contents of the HBase directory in HDFS to
either the same cluster in another directory, or to a different cluster. </para>
@@ -1019,7 +1131,8 @@ false
in-flight edits to files. Distcp-ing of files in the HBase directory is not generally
recommended on a live cluster. </para>
</section>
- <section xml:id="ops.backup.fullshutdown.restore">
+ <section
+ xml:id="ops.backup.fullshutdown.restore">
<title>Restore (if needed)</title>
<para>The backup of the hbase directory from HDFS is copied onto the 'real' hbase directory
via distcp. The act of copying these files creates new HDFS metadata, which is why a
@@ -1028,30 +1141,37 @@ false
the HBase part) not the entire HDFS file-system. </para>
</section>
</section>
- <section xml:id="ops.backup.live.replication">
+ <section
+ xml:id="ops.backup.live.replication">
<title>Live Cluster Backup - Replication</title>
<para>This approach assumes that there is a second cluster. See the HBase page on <link
xlink:href="http://hbase.apache.org/replication.html">replication</link> for more
information. </para>
</section>
- <section xml:id="ops.backup.live.copytable">
+ <section
+ xml:id="ops.backup.live.copytable">
<title>Live Cluster Backup - CopyTable</title>
- <para>The <xref linkend="copytable"/> utility could either be used to copy data from one table
- to another on the same cluster, or to copy data to another table on another cluster. </para>
+ <para>The <xref
+ linkend="copytable" /> utility could either be used to copy data from one table to another
+ on the same cluster, or to copy data to another table on another cluster. </para>
<para>Since the cluster is up, there is a risk that edits could be missed in the copy process.
</para>
</section>
- <section xml:id="ops.backup.live.export">
+ <section
+ xml:id="ops.backup.live.export">
<title>Live Cluster Backup - Export</title>
- <para>The <xref linkend="export"/> approach dumps the content of a table to HDFS on the same
- cluster. To restore the data, the <xref linkend="import"/> utility would be used. </para>
+ <para>The <xref
+ linkend="export" /> approach dumps the content of a table to HDFS on the same cluster. To
+ restore the data, the <xref
+ linkend="import" /> utility would be used. </para>
<para>Since the cluster is up, there is a risk that edits could be missed in the export
process. </para>
</section>
</section>
<!-- backup -->
- <section xml:id="ops.snapshots">
+ <section
+ xml:id="ops.snapshots">
<title>HBase Snapshots</title>
<para>HBase Snapshots allow you to take a snapshot of a table without too much impact on Region
Servers. Snapshot, Clone and restore operations don't involve data copying. Also, Exporting
@@ -1061,7 +1181,8 @@ false
disadvantages of these methods are that you can degrade region server performance (Copy/Export
Table) or you need to disable the table, that means no reads or writes; and this is usually
unacceptable. </para>
- <section xml:id="ops.snapshots.configuration">
+ <section
+ xml:id="ops.snapshots.configuration">
<title>Configuration</title>
<para>To turn on the snapshot support just set the <varname>hbase.snapshot.enabled</varname>
property to true. (Snapshots are enabled by default in 0.95+ and off by default in
@@ -1073,7 +1194,8 @@ false
</property>
</programlisting>
</section>
- <section xml:id="ops.snapshots.takeasnapshot">
+ <section
+ xml:id="ops.snapshots.takeasnapshot">
<title>Take a Snapshot</title>
<para>You can take a snapshot of a table regardless of whether it is enabled or disabled. The
snapshot operation doesn't involve any data copying.</para>
@@ -1082,7 +1204,8 @@ $ ./bin/hbase shell
hbase> snapshot 'myTable', 'myTableSnapshot-122112'
</screen>
</section>
- <section xml:id="ops.snapshots.list">
+ <section
+ xml:id="ops.snapshots.list">
<title>Listing Snapshots</title>
<para>List all snapshots taken (by printing the names and relative information).</para>
<screen>
@@ -1090,7 +1213,8 @@ $ ./bin/hbase shell
hbase> list_snapshots
</screen>
</section>
- <section xml:id="ops.snapshots.delete">
+ <section
+ xml:id="ops.snapshots.delete">
<title>Deleting Snapshots</title>
<para>You can remove a snapshot, and the files retained for that snapshot will be removed if
no longer needed.</para>
@@ -1099,7 +1223,8 @@ $ ./bin/hbase shell
hbase> delete_snapshot 'myTableSnapshot-122112'
</screen>
</section>
- <section xml:id="ops.snapshots.clone">
+ <section
+ xml:id="ops.snapshots.clone">
<title>Clone a table from snapshot</title>
<para>From a snapshot you can create a new table (clone operation) with the same data that you
had when the snapshot was taken. The clone operation, doesn't involve data copies, and a
@@ -1109,7 +1234,8 @@ $ ./bin/hbase shell
hbase> clone_snapshot 'myTableSnapshot-122112', 'myNewTestTable'
</screen>
</section>
- <section xml:id="ops.snapshots.restore">
+ <section
+ xml:id="ops.snapshots.restore">
<title>Restore a snapshot</title>
<para>The restore operation requires the table to be disabled, and the table will be restored
to the state at the time when the snapshot was taken, changing both data and schema if
@@ -1128,15 +1254,17 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
requires the table to be disabled, you can clone the table from the snapshot and use a
Map-Reduce job to copy the data that you need, from the clone to the main one. </para>
</section>
- <section xml:id="ops.snapshots.acls">
+ <section
+ xml:id="ops.snapshots.acls">
<title>Snapshots operations and ACLs</title>
<para>If you are using security with the AccessController Coprocessor (See <xref
- linkend="hbase.accesscontrol.configuration"/>), only a global administrator can take,
+ linkend="hbase.accesscontrol.configuration" />), only a global administrator can take,
clone, or restore a snapshot, and these actions do not capture the ACL rights. This means
that restoring a table preserves the ACL rights of the existing table, while cloning a table
creates a new table that has no ACL rights until the administrator adds them.</para>
</section>
- <section xml:id="ops.snapshots.export">
+ <section
+ xml:id="ops.snapshots.export">
<title>Export to another cluster</title>
<para>The ExportSnapshot tool copies all the data related to a snapshot (hfiles, logs,
snapshot metadata) to another cluster. The tool executes a Map-Reduce job, similar to
@@ -1149,14 +1277,17 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
</section>
<!-- snapshots -->
- <section xml:id="ops.capacity">
+ <section
+ xml:id="ops.capacity">
<title>Capacity Planning and Region Sizing</title>
<para>There are several considerations when planning the capacity for an HBase cluster and
performing the initial configuration. Start with a solid understanding of how HBase handles
data internally.</para>
- <section xml:id="ops.capacity.nodes">
+ <section
+ xml:id="ops.capacity.nodes">
<title>Node count and hardware/VM configuration</title>
- <section xml:id="ops.capacity.nodes.datasize">
+ <section
+ xml:id="ops.capacity.nodes.datasize">
<title>Physical data size</title>
<para>Physical data size on disk is distinct from logical size of your data and is affected
by the following: </para>
@@ -1165,26 +1296,31 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
<para>Increased by HBase overhead</para>
<itemizedlist>
<listitem>
- <para>See <xref linkend="keyvalue"/> and <xref linkend="keysize"/>. At least 24
- bytes per key-value (cell), can be more. Small keys/values means more relative
- overhead.</para>
+ <para>See <xref
+ linkend="keyvalue" /> and <xref
+ linkend="keysize" />. At least 24 bytes per key-value (cell), can be more. Small
+ keys/values means more relative overhead.</para>
</listitem>
<listitem>
<para>KeyValue instances are aggregated into blocks, which are indexed. Indexes also
- have to be stored. Blocksize is configurable on a per-ColumnFamily basis. See
- <xref linkend="regions.arch"/>.</para>
+ have to be stored. Blocksize is configurable on a per-ColumnFamily basis. See <xref
+ linkend="regions.arch" />.</para>
</listitem>
</itemizedlist>
</listitem>
<listitem>
- <para>Decreased by <xref linkend="compression" xrefstyle="template:compression"/> and
- data block encoding, depending on data. See also <link
+ <para>Decreased by <xref
+ linkend="compression"
+ xrefstyle="template:compression" /> and data block encoding, depending on data. See
+ also <link
xlink:href="http://search-hadoop.com/m/lL12B1PFVhp1">this thread</link>. You might
want to test what compression and encoding (if any) make sense for your data.</para>
</listitem>
<listitem>
- <para>Increased by size of region server <xref linkend="wal" xrefstyle="template:WAL"/>
- (usually fixed and negligible - less than half of RS memory size, per RS).</para>
+ <para>Increased by size of region server <xref
+ linkend="wal"
+ xrefstyle="template:WAL" /> (usually fixed and negligible - less than half of RS
+ memory size, per RS).</para>
</listitem>
<listitem>
<para>Increased by HDFS replication - usually x3.</para>
@@ -1192,66 +1328,79 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
</itemizedlist>
<para>Aside from the disk space necessary to store the data, one RS may not be able to serve
arbitrarily large amounts of data due to some practical limits on region count and size
- (see <xref linkend="ops.capacity.regions" xrefstyle="template:below"/>).</para>
+ (see <xref
+ linkend="ops.capacity.regions"
+ xrefstyle="template:below" />).</para>
</section>
<!-- ops.capacity.nodes.datasize -->
- <section xml:id="ops.capacity.nodes.throughput">
+ <section
+ xml:id="ops.capacity.nodes.throughput">
<title>Read/Write throughput</title>
<para>Number of nodes can also be driven by required thoughput for reads and/or writes. The
throughput one can get per node depends a lot on data (esp. key/value sizes) and request
patterns, as well as node and system configuration. Planning should be done for peak load
if it is likely that the load would be the main driver of the increase of the node count.
- PerformanceEvaluation and <xref linkend="ycsb" xrefstyle="template:YCSB"/> tools can be
- used to test single node or a test cluster.</para>
+ PerformanceEvaluation and <xref
+ linkend="ycsb"
+ xrefstyle="template:YCSB" /> tools can be used to test single node or a test
+ cluster.</para>
<para>For write, usually 5-15Mb/s per RS can be expected, since every region server has only
one active WAL. There's no good estimate for reads, as it depends vastly on data,
- requests, and cache hit rate. <xref linkend="perf.casestudy"/> might be helpful.</para>
+ requests, and cache hit rate. <xref
+ linkend="perf.casestudy" /> might be helpful.</para>
</section>
<!-- ops.capacity.nodes.throughput -->
- <section xml:id="ops.capacity.nodes.gc">
+ <section
+ xml:id="ops.capacity.nodes.gc">
<title>JVM GC limitations</title>
<para>RS cannot currently utilize very large heap due to cost of GC. There's also no good
way of running multiple RS-es per server (other than running several VMs per machine).
Thus, ~20-24Gb or less memory dedicated to one RS is recommended. GC tuning is required
- for large heap sizes. See <xref linkend="gcpause"/>, <xref linkend="trouble.log.gc"/> and
- elsewhere (TODO: where?)</para>
+ for large heap sizes. See <xref
+ linkend="gcpause" />, <xref
+ linkend="trouble.log.gc" /> and elsewhere (TODO: where?)</para>
</section>
<!-- ops.capacity.nodes.gc -->
</section>
<!-- ops.capacity.nodes -->
- <section xml:id="ops.capacity.regions">
+ <section
+ xml:id="ops.capacity.regions">
<title>Determining region count and size</title>
<para>Generally less regions makes for a smoother running cluster (you can always manually
split the big regions later (if necessary) to spread the data, or request load, over the
cluster); 20-200 regions per RS is a reasonable range. The number of regions cannot be
- configured directly (unless you go for fully <xref linkend="disable.splitting"
- xrefstyle="template:manual splitting"/>); adjust the region size to achieve the target
+ configured directly (unless you go for fully <xref
+ linkend="disable.splitting"
+ xrefstyle="template:manual splitting" />); adjust the region size to achieve the target
region size given table size.</para>
<para>When configuring regions for multiple tables, note that most region settings can be set
on a per-table basis via <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HTableDescriptor.html"
- >HTableDescriptor</link>, as well as shell commands. These settings will override the ones
- in <varname>hbase-site.xml</varname>. That is useful if your tables have different
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HTableDescriptor.html">HTableDescriptor</link>,
+ as well as shell commands. These settings will override the ones in
+ <varname>hbase-site.xml</varname>. That is useful if your tables have different
workloads/use cases.</para>
- <para>Also note that in the discussion of region sizes here, <emphasis role="bold">HDFS
- replication factor is not (and should not be) taken into account, whereas other factors
- <xref linkend="ops.capacity.nodes.datasize" xrefstyle="template:above"/> should
- be.</emphasis> So, if your data is compressed and replicated 3 ways by HDFS, "9 Gb region"
- means 9 Gb of compressed data. HDFS replication factor only affects your disk usage and is
- invisible to most HBase code.</para>
- <section xml:id="ops.capacity.regions.count">
+ <para>Also note that in the discussion of region sizes here, <emphasis
+ role="bold">HDFS replication factor is not (and should not be) taken into account, whereas
+ other factors <xref
+ linkend="ops.capacity.nodes.datasize"
+ xrefstyle="template:above" /> should be.</emphasis> So, if your data is compressed and
+ replicated 3 ways by HDFS, "9 Gb region" means 9 Gb of compressed data. HDFS replication
+ factor only affects your disk usage and is invisible to most HBase code.</para>
+ <section
+ xml:id="ops.capacity.regions.count">
<title>Number of regions per RS - upper bound</title>
<para>In production scenarios, where you have a lot of data, you are normally concerned with
- the maximum number of regions you can have per server. <xref linkend="too_many_regions"/>
- has technical discussion on the subject; in short, maximum number of regions is mostly
- determined by memstore memory usage. Each region has its own memstores; these grow up to a
- configurable size; usually in 128-256Mb range, see <xref
- linkend="hbase.hregion.memstore.flush.size"/>. There's one memstore per column family
+ the maximum number of regions you can have per server. <xref
+ linkend="too_many_regions" /> has technical discussion on the subject; in short, maximum
+ number of regions is mostly determined by memstore memory usage. Each region has its own
+ memstores; these grow up to a configurable size; usually in 128-256Mb range, see <xref
+ linkend="hbase.hregion.memstore.flush.size" />. There's one memstore per column family
(so there's only one per region if there's one CF in the table). RS dedicates some
- fraction of total memory (see <xref linkend="hbase.regionserver.global.memstore.size"/>)
- to region memstores. If this memory is exceeded (too much memstore usage), undesirable
- consequences such as unresponsive server, or later compaction storms, can result. Thus, a
- good starting point for the number of regions per RS (assuming one table) is:</para>
+ fraction of total memory (see <xref
+ linkend="hbase.regionserver.global.memstore.size" />) to region memstores. If this
+ memory is exceeded (too much memstore usage), undesirable consequences such as
+ unresponsive server, or later compaction storms, can result. Thus, a good starting point
+ for the number of regions per RS (assuming one table) is:</para>
<programlisting>(RS memory)*(total memstore fraction)/((memstore size)*(# column families))</programlisting>
<para> E.g. if RS has 16Gb RAM, with default settings, it is 16384*0.4/128 ~ 51 regions per
@@ -1268,7 +1417,8 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
expense of block cache; this will also allow one to have more regions.</para>
</section>
<!-- ops.capacity.regions.count -->
- <section xml:id="ops.capacity.regions.mincount">
+ <section
+ xml:id="ops.capacity.regions.mincount">
<title>Number of regions per RS - lower bound</title>
<para>HBase scales by having regions across many servers. Thus if you have 2 regions for
16GB data, on a 20 node machine your data will be concentrated on just a few machines -
@@ -1279,7 +1429,8 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
for a larger number of regions to avoid having regions that are too large.</para>
</section>
<!-- ops.capacity.regions.mincount -->
- <section xml:id="ops.capacity.regions.size">
+ <section
+ xml:id="ops.capacity.regions.size">
<title>Maximum region size</title>
<para>For large tables in production scenarios, maximum region size is mostly limited by
compactions - very large compactions, esp. major, can degrade cluster performance.
@@ -1287,17 +1438,19 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
older 0.90.x codebase, the upper-bound of regionsize is about 4Gb, with a default of
256Mb.</para>
<para>The size at which the region is split into two is generally configured via <xref
- linkend="hbase.hregion.max.filesize"/>; for details, see <xref
- linkend="arch.region.splits"/>.</para>
+ linkend="hbase.hregion.max.filesize" />; for details, see <xref
+ linkend="arch.region.splits" />.</para>
<para>If you cannot estimate the size of your tables well, when starting off, it's probably
best to stick to the default region size, perhaps going smaller for hot tables (or
manually split hot regions to spread the load over the cluster), or go with larger region
sizes if your cell sizes tend to be largish (100k and up).</para>
<para>In HBase 0.98, experimental stripe compactions feature was added that would allow for
- larger regions, especially for log data. See <xref linkend="ops.stripe"/>.</para>
+ larger regions, especially for log data. See <xref
+ linkend="ops.stripe" />.</para>
</section>
<!-- ops.capacity.regions.size -->
- <section xml:id="ops.capacity.regions.total">
+ <section
+ xml:id="ops.capacity.regions.total">
<title>Total data size per region server</title>
<para>According to above numbers for region size and number of regions per region server, in
an optimistic estimate 10 GB x 100 regions per RS will give up to 1TB served per region
@@ -1309,42 +1462,50 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
<!-- ops.capacity.regions.total -->
</section>
<!-- ops.capacity.regions -->
- <section xml:id="ops.capacity.config">
+ <section
+ xml:id="ops.capacity.config">
<title>Initial configuration and tuning</title>
- <para>First, see <xref linkend="important_configurations"/>. Note that some configurations,
- more than others, depend on specific scenarios. Pay special attention to:</para>
+ <para>First, see <xref
+ linkend="important_configurations" />. Note that some configurations, more than others,
+ depend on specific scenarios. Pay special attention to:</para>
<itemizedlist>
<listitem>
- <para><xref linkend="hbase.regionserver.handler.count"/> - request handler thread count,
- vital for high-throughput workloads.</para>
+ <para><xref
+ linkend="hbase.regionserver.handler.count" /> - request handler thread count, vital
+ for high-throughput workloads.</para>
</listitem>
<listitem>
- <para><xref linkend="config.wals"/> - the blocking number of WAL files depends on your
- memstore configuration and should be set accordingly to prevent potential blocking when
- doing high volume of writes.</para>
+ <para><xref
+ linkend="config.wals" /> - the blocking number of WAL files depends on your memstore
+ configuration and should be set accordingly to prevent potential blocking when doing
+ high volume of writes.</para>
</listitem>
</itemizedlist>
<para>Then, there are some considerations when setting up your cluster and tables.</para>
- <section xml:id="ops.capacity.config.compactions">
+ <section
+ xml:id="ops.capacity.config.compactions">
<title>Compactions</title>
<para>Depending on read/write volume and latency requirements, optimal compaction settings
- may be different. See <xref linkend="compaction"/> for some details.</para>
+ may be different. See <xref
+ linkend="compaction" /> for some details.</para>
<para>When provisioning for large data sizes, however, it's good to keep in mind that
compactions can affect write throughput. Thus, for write-intensive workloads, you may opt
for less frequent compactions and more store files per regions. Minimum number of files
for compactions (<varname>hbase.hstore.compaction.min</varname>) can be set to higher
- value; <xref linkend="hbase.hstore.blockingStoreFiles"/> should also be increased, as more
- files might accumulate in such case. You may also consider manually managing compactions:
- <xref linkend="managed.compactions"/></para>
+ value; <xref
+ linkend="hbase.hstore.blockingStoreFiles" /> should also be increased, as more files
+ might accumulate in such case. You may also consider manually managing compactions: <xref
+ linkend="managed.compactions" /></para>
</section>
<!-- ops.capacity.config.compactions -->
- <section xml:id="ops.capacity.config.presplit">
+ <section
+ xml:id="ops.capacity.config.presplit">
<title>Pre-splitting the table</title>
<para>Based on the target number of the regions per RS (see <xref
- linkend="ops.capacity.regions.count" xrefstyle="template:above"/>) and number of RSes,
- one can pre-split the table at creation time. This would both avoid some costly splitting
- as the table starts to fill up, and ensure that the table starts out already distributed
- across many servers.</para>
+ linkend="ops.capacity.regions.count"
+ xrefstyle="template:above" />) and number of RSes, one can pre-split the table at
+ creation time. This would both avoid some costly splitting as the table starts to fill up,
+ and ensure that the table starts out already distributed across many servers.</para>
<para>If the table is expected to grow large enough to justify that, at least one region per
RS should be created. It is not recommended to split immediately into the full target
number of regions (e.g. 50 * number of RSes), but a low intermediate value can be chosen.
@@ -1352,14 +1513,16 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
pre-split 1 region per RS at most), especially if you don't know how much each table will
grow. If you split too much, you may end up with too many regions, with some tables having
too many small regions.</para>
- <para>For pre-splitting howto, see <xref linkend="precreate.regions"/>.</para>
+ <para>For pre-splitting howto, see <xref
+ linkend="precreate.regions" />.</para>
</section>
<!-- ops.capacity.config.presplit -->
</section>
<!-- ops.capacity.config -->
</section>
<!-- ops.capacity -->
- <section xml:id="table.rename">
+ <section
+ xml:id="table.rename">
<title>Table Rename</title>
<para>In versions 0.90.x of hbase and earlier, we had a simple script that would rename the hdfs
table directory and then do an edit of the hbase:meta table replacing all mentions of the old
@@ -1368,19 +1531,19 @@ hbase> restore_snapshot 'myTableSnapshot-122112'
performed by the script was brutal. </para>
<para> As of hbase 0.94.x, you can use the snapshot facility renaming a table. Here is how you
would do it using the hbase shell:</para>
- <programlisting>hbase shell> disable 'tableName'
+ <screen><![CDATA[hbase shell> disable 'tableName'
hbase shell> snapshot 'tableName', 'tableSnapshot'
hbase shell> clone_snapshot 'tableSnapshot', 'newTableName'
hbase shell> delete_snapshot 'tableSnapshot'
-hbase shell> drop 'tableName'</programlisting>
+hbase shell> drop 'tableName']]></screen>
<para>or in code it would be as follows:</para>
- <programlisting>void rename(HBaseAdmin admin, String oldTableName, String newTableName) {
-String snapshotName = randomName();
-admin.disableTable(oldTableName);
-admin.snapshot(snapshotName, oldTableName);
-admin.cloneSnapshot(snapshotName, newTableName);
-admin.deleteSnapshot(snapshotName);
-admin.deleteTable(oldTableName);
+ <programlisting role="Java" language="Java">void rename(HBaseAdmin admin, String oldTableName, String newTableName) {
+ String snapshotName = randomName();
+ admin.disableTable(oldTableName);
+ admin.snapshot(snapshotName, oldTableName);
+ admin.cloneSnapshot(snapshotName, newTableName);
+ admin.deleteSnapshot(snapshotName);
+ admin.deleteTable(oldTableName);
}</programlisting>
</section>
[11/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/configuration.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/configuration.xml b/src/main/docbkx/configuration.xml
index 25e1f13..cd86bef 100644
--- a/src/main/docbkx/configuration.xml
+++ b/src/main/docbkx/configuration.xml
@@ -1,13 +1,15 @@
<?xml version="1.0"?>
- <chapter xml:id="configuration"
- version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ xml:id="configuration"
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -26,243 +28,331 @@
* limitations under the License.
*/
-->
- <title>Apache HBase Configuration</title>
- <para>This chapter is the Not-So-Quick start guide to Apache HBase configuration. It goes
- over system requirements, Hadoop setup, the different Apache HBase run modes, and the
- various configurations in HBase. Please read this chapter carefully. At a minimum
- ensure that all <xref linkend="basic.prerequisites" /> have
- been satisfied. Failure to do so will cause you (and us) grief debugging strange errors
- and/or data loss.</para>
-
- <para>
- Apache HBase uses the same configuration system as Apache Hadoop.
- To configure a deploy, edit a file of environment variables
- in <filename>conf/hbase-env.sh</filename> -- this configuration
- is used mostly by the launcher shell scripts getting the cluster
- off the ground -- and then add configuration to an XML file to
- do things like override HBase defaults, tell HBase what Filesystem to
- use, and the location of the ZooKeeper ensemble
- <footnote>
-<para>
-Be careful editing XML. Make sure you close all elements.
-Run your file through <command>xmllint</command> or similar
-to ensure well-formedness of your document after an edit session.
-</para>
- </footnote>
- .
- </para>
-
- <para>When running in distributed mode, after you make
- an edit to an HBase configuration, make sure you copy the
- content of the <filename>conf</filename> directory to
- all nodes of the cluster. HBase will not do this for you.
- Use <command>rsync</command>. For most configuration, a restart is
-needed for servers to pick up changes (caveat dynamic config. to be described later below).</para>
-
- <section xml:id="basic.prerequisites">
+ <title>Apache HBase Configuration</title>
+ <para>This chapter is the Not-So-Quick start guide to Apache HBase configuration. It goes over
+ system requirements, Hadoop setup, the different Apache HBase run modes, and the various
+ configurations in HBase. Please read this chapter carefully. At a minimum ensure that all <xref
+ linkend="basic.prerequisites" /> have been satisfied. Failure to do so will cause you (and us)
+ grief debugging strange errors and/or data loss.</para>
+
+ <para> Apache HBase uses the same configuration system as Apache Hadoop. To configure a deploy,
+ edit a file of environment variables in <filename>conf/hbase-env.sh</filename> -- this
+ configuration is used mostly by the launcher shell scripts getting the cluster off the ground --
+ and then add configuration to an XML file to do things like override HBase defaults, tell HBase
+ what Filesystem to use, and the location of the ZooKeeper ensemble. <footnote>
+ <para> Be careful editing XML. Make sure you close all elements. Run your file through
+ <command>xmllint</command> or similar to ensure well-formedness of your document after an
+ edit session. </para>
+ </footnote></para>
+
+ <para>When running in distributed mode, after you make an edit to an HBase configuration, make
+ sure you copy the content of the <filename>conf</filename> directory to all nodes of the
+ cluster. HBase will not do this for you. Use <command>rsync</command>. For most configuration, a
+ restart is needed for servers to pick up changes (caveat dynamic config. to be described later
+ below).</para>
+
+ <section
+ xml:id="basic.prerequisites">
<title>Basic Prerequisites</title>
- <para>This section lists required services and some required system configuration.
- </para>
+ <para>This section lists required services and some required system configuration. </para>
- <section xml:id="java">
- <title>Java</title>
- <para>Just like Hadoop, HBase requires at least Java 6 from
- <link xlink:href="http://www.java.com/download/">Oracle</link>.
- </para>
+ <section
+ xml:id="java">
+ <title>Java</title>
+ <para>Just like Hadoop, HBase requires at least Java 6 from <link
+ xlink:href="http://www.java.com/download/">Oracle</link>. </para>
</section>
- <section xml:id="os">
- <title>Operating System</title>
- <section xml:id="ssh">
+ <section
+ xml:id="os">
+ <title>Operating System</title>
+ <section
+ xml:id="ssh">
<title>ssh</title>
- <para><command>ssh</command> must be installed and
- <command>sshd</command> must be running to use Hadoop's scripts to
- manage remote Hadoop and HBase daemons. You must be able to ssh to all
- nodes, including your local node, using passwordless login (Google
- "ssh passwordless login"). If on mac osx, see the section,
- <link xlink:href="http://wiki.apache.org/hadoop/Running_Hadoop_On_OS_X_10.5_64-bit_%28Single-Node_Cluster%29">SSH: Setting up Remote Desktop and Enabling Self-Login</link>
- on the hadoop wiki.</para>
+ <para><command>ssh</command> must be installed and <command>sshd</command> must be running
+ to use Hadoop's scripts to manage remote Hadoop and HBase daemons. You must be able to ssh
+ to all nodes, including your local node, using passwordless login (Google "ssh
+ passwordless login"). If on mac osx, see the section, <link
+ xlink:href="http://wiki.apache.org/hadoop/Running_Hadoop_On_OS_X_10.5_64-bit_%28Single-Node_Cluster%29">SSH:
+ Setting up Remote Desktop and Enabling Self-Login</link> on the hadoop wiki.</para>
</section>
- <section xml:id="dns">
+ <section
+ xml:id="dns">
<title>DNS</title>
- <para>HBase uses the local hostname to self-report its IP address.
- Both forward and reverse DNS resolving must work in versions of
- HBase previous to 0.92.0
- <footnote><para>The <link xlink:href="https://github.com/sujee/hadoop-dns-checker">hadoop-dns-checker</link> tool can be used to verify
- DNS is working correctly on the cluster. The project README file provides detailed instructions on usage.
-</para></footnote>.</para>
+ <para>HBase uses the local hostname to self-report its IP address. Both forward and reverse
+ DNS resolving must work in versions of HBase previous to 0.92.0 <footnote>
+ <para>The <link
+ xlink:href="https://github.com/sujee/hadoop-dns-checker">hadoop-dns-checker</link>
+ tool can be used to verify DNS is working correctly on the cluster. The project README
+ file provides detailed instructions on usage. </para>
+ </footnote>.</para>
- <para>If your machine has multiple interfaces, HBase will use the
- interface that the primary hostname resolves to.</para>
+ <para>If your machine has multiple interfaces, HBase will use the interface that the primary
+ hostname resolves to.</para>
<para>If this is insufficient, you can set
- <varname>hbase.regionserver.dns.interface</varname> to indicate the
- primary interface. This only works if your cluster configuration is
- consistent and every host has the same network interface
- configuration.</para>
-
- <para>Another alternative is setting
- <varname>hbase.regionserver.dns.nameserver</varname> to choose a
- different nameserver than the system wide default.</para>
+ <varname>hbase.regionserver.dns.interface</varname> to indicate the primary interface.
+ This only works if your cluster configuration is consistent and every host has the same
+ network interface configuration.</para>
+
+ <para>Another alternative is setting <varname>hbase.regionserver.dns.nameserver</varname> to
+ choose a different nameserver than the system wide default.</para>
</section>
- <section xml:id="loopback.ip">
+ <section
+ xml:id="loopback.ip">
<title>Loopback IP</title>
- <para>Previous to hbase-0.96.0, HBase expects the loopback IP address to be 127.0.0.1. See <xref linkend="loopback.ip"/></para>
- </section>
+ <para>Previous to hbase-0.96.0, HBase expects the loopback IP address to be 127.0.0.1. See <xref
+ linkend="loopback.ip" /></para>
+ </section>
- <section xml:id="ntp">
+ <section
+ xml:id="ntp">
<title>NTP</title>
- <para>The clocks on cluster members should be in basic alignments.
- Some skew is tolerable but wild skew could generate odd behaviors. Run
- <link
- xlink:href="http://en.wikipedia.org/wiki/Network_Time_Protocol">NTP</link>
- on your cluster, or an equivalent.</para>
+ <para>The clocks on cluster members should be in basic alignments. Some skew is tolerable
+ but wild skew could generate odd behaviors. Run <link
+ xlink:href="http://en.wikipedia.org/wiki/Network_Time_Protocol">NTP</link> on your
+ cluster, or an equivalent.</para>
- <para>If you are having problems querying data, or "weird" cluster
- operations, check system time!</para>
+ <para>If you are having problems querying data, or "weird" cluster operations, check system
+ time!</para>
</section>
- <section xml:id="ulimit">
+ <section
+ xml:id="ulimit">
<title>
<varname>ulimit</varname><indexterm>
<primary>ulimit</primary>
- </indexterm>
- and
- <varname>nproc</varname><indexterm>
+ </indexterm> and <varname>nproc</varname><indexterm>
<primary>nproc</primary>
- </indexterm>
+ </indexterm>
</title>
- <para>Apache HBase is a database. It uses a lot of files all at the same time.
- The default ulimit -n -- i.e. user file limit -- of 1024 on most *nix systems
- is insufficient (On mac os x its 256). Any significant amount of loading will
- lead you to <xref linkend="trouble.rs.runtime.filehandles"/>.
- You may also notice errors such as... <programlisting>
- 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
- </programlisting> Do yourself a favor and change the upper bound on the
- number of file descriptors. Set it to north of 10k. The math runs roughly as follows: per ColumnFamily
- there is at least one StoreFile and possibly up to 5 or 6 if the region is under load. Multiply the
- average number of StoreFiles per ColumnFamily times the number of 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, config files, etc.)
- </para>
- <para>You should also up the hbase users'
- <varname>nproc</varname> setting; under load, a low-nproc
- setting could manifest as <classname>OutOfMemoryError</classname>
- <footnote><para>See Jack Levin's <link xlink:href="">major hdfs issues</link>
- note up on the user list.</para></footnote>
- <footnote><para>The requirement that a database requires upping of system limits
- is not peculiar to Apache HBase. See for example the section
- <emphasis>Setting Shell Limits for the Oracle User</emphasis> in
- <link xlink:href="http://www.akadia.com/services/ora_linux_install_10g.html">
- Short Guide to install Oracle 10 on Linux</link>.</para></footnote>.
- </para>
-
- <para>To be clear, upping the file descriptors and nproc for the user who is
- running the HBase process is an operating system configuration, not an
- HBase configuration. Also, a common mistake is that administrators
- will up the file descriptors for a particular user but for whatever
- reason, HBase will be running as some one else. HBase prints in its
- logs as the first line the ulimit its seeing. Ensure its correct.
- <footnote>
- <para>A useful read setting config on you hadoop cluster is Aaron
- Kimballs' <link
- xlink:href="http://www.cloudera.com/blog/2009/03/configuration-parameters-what-can-you-just-ignore/">Configuration
- Parameters: What can you just ignore?</link></para>
+ <para>Apache HBase is a database. It uses a lot of files all at the same time. The default
+ ulimit -n -- i.e. user file limit -- of 1024 on most *nix systems is insufficient (On mac
+ os x its 256). Any significant amount of loading will lead you to <xref
+ linkend="trouble.rs.runtime.filehandles" />. You may also notice errors such as the
+ following:</para>
+ <screen>
+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
+ </screen>
+ <para> Do yourself a favor and change the upper bound on the number of file descriptors. Set
+ it to north of 10k. The math runs roughly as follows: per ColumnFamily there is at least
+ one StoreFile and possibly up to 5 or 6 if the region is under load. Multiply the average
+ number of StoreFiles per ColumnFamily times the number of 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, config files, etc.) </para>
+ <para>You should also up the hbase users' <varname>nproc</varname> setting; under load, a
+ low-nproc setting could manifest as <classname>OutOfMemoryError</classname>. <footnote>
+ <para>See Jack Levin's <link
+ xlink:href="">major hdfs issues</link> note up on the user list.</para>
+ </footnote>
+ <footnote>
+ <para>The requirement that a database requires upping of system limits is not peculiar
+ to Apache HBase. See for example the section <emphasis>Setting Shell Limits for the
+ Oracle User</emphasis> in <link
+ xlink:href="http://www.akadia.com/services/ora_linux_install_10g.html"> Short Guide
+ to install Oracle 10 on Linux</link>.</para>
</footnote></para>
- <section xml:id="ulimit_ubuntu">
- <title><varname>ulimit</varname> on Ubuntu</title>
+ <para>To be clear, upping the file descriptors and nproc for the user who is running the
+ HBase process is an operating system configuration, not an HBase configuration. Also, a
+ common mistake is that administrators will up the file descriptors for a particular user
+ but for whatever reason, HBase will be running as some one else. HBase prints in its logs
+ as the first line the ulimit its seeing. Ensure its correct. <footnote>
+ <para>A useful read setting config on you hadoop cluster is Aaron Kimballs' <link
+ xlink:href="http://www.cloudera.com/blog/2009/03/configuration-parameters-what-can-you-just-ignore/">Configuration
+ Parameters: What can you just ignore?</link></para>
+ </footnote></para>
- <para>If you are on Ubuntu you will need to make the following
- changes:</para>
+ <section
+ xml:id="ulimit_ubuntu">
+ <title><varname>ulimit</varname> on Ubuntu</title>
- <para>In the file <filename>/etc/security/limits.conf</filename> add
- a line like: <programlisting>hadoop - nofile 32768</programlisting>
- Replace <varname>hadoop</varname> with whatever user is running
- Hadoop and HBase. If you have separate users, you will need 2
- entries, one for each user. In the same file set nproc hard and soft
- limits. For example: <programlisting>hadoop soft/hard nproc 32000</programlisting>.</para>
+ <para>If you are on Ubuntu you will need to make the following changes:</para>
- <para>In the file <filename>/etc/pam.d/common-session</filename> add
- as the last line in the file: <programlisting>session required pam_limits.so</programlisting>
- Otherwise the changes in <filename>/etc/security/limits.conf</filename> won't be
- applied.</para>
+ <para>In the file <filename>/etc/security/limits.conf</filename> add a line like:</para>
+ <programlisting>hadoop - nofile 32768</programlisting>
+ <para>Replace <varname>hadoop</varname> with whatever user is running Hadoop and HBase. If
+ you have separate users, you will need 2 entries, one for each user. In the same file
+ set nproc hard and soft limits. For example:</para>
+ <programlisting>hadoop soft/hard nproc 32000</programlisting>
+ <para>In the file <filename>/etc/pam.d/common-session</filename> add as the last line in
+ the file: <programlisting>session required pam_limits.so</programlisting> Otherwise the
+ changes in <filename>/etc/security/limits.conf</filename> won't be applied.</para>
- <para>Don't forget to log out and back in again for the changes to
- take effect!</para>
+ <para>Don't forget to log out and back in again for the changes to take effect!</para>
</section>
</section>
- <section xml:id="windows">
+ <section
+ xml:id="windows">
<title>Windows</title>
<para>Previous to hbase-0.96.0, Apache HBase was little tested running on Windows. Running a
- production install of HBase on top of Windows is not recommended.</para>
+ production install of HBase on top of Windows is not recommended.</para>
<para>If you are running HBase on Windows pre-hbase-0.96.0, you must install <link
- xlink:href="http://cygwin.com/">Cygwin</link> to have a *nix-like
- environment for the shell scripts. The full details are explained in
- the <link xlink:href="http://hbase.apache.org/cygwin.html">Windows
- Installation</link> guide. Also
- <link xlink:href="http://search-hadoop.com/?q=hbase+windows&fc_project=HBase&fc_type=mail+_hash_+dev">search our user mailing list</link> to pick
- up latest fixes figured by Windows users.</para>
- <para>Post-hbase-0.96.0, hbase runs natively on windows with supporting <command>*.cmd</command> scripts bundled.
- </para>
+ xlink:href="http://cygwin.com/">Cygwin</link> to have a *nix-like environment for the
+ shell scripts. The full details are explained in the <link
+ xlink:href="http://hbase.apache.org/cygwin.html">Windows Installation</link> guide. Also <link
+ xlink:href="http://search-hadoop.com/?q=hbase+windows&fc_project=HBase&fc_type=mail+_hash_+dev">search
+ our user mailing list</link> to pick up latest fixes figured by Windows users.</para>
+ <para>Post-hbase-0.96.0, hbase runs natively on windows with supporting
+ <command>*.cmd</command> scripts bundled. </para>
</section>
- </section> <!-- OS -->
-
- <section xml:id="hadoop">
- <title><link
- xlink:href="http://hadoop.apache.org">Hadoop</link><indexterm>
- <primary>Hadoop</primary>
- </indexterm></title>
- <para>The below table shows some information about what versions of Hadoop are supported by various HBase versions.
- Based on the version of HBase, you should select the most appropriate version of Hadoop.
- We are not in the Hadoop distro selection business.
- You can use Hadoop distributions from Apache, or learn about vendor distributions of
- Hadoop at <link xlink:href="http://wiki.apache.org/hadoop/Distributions%20and%20Commercial%20Support"/></para>
- <para>
- <tip><title>Hadoop 2.x is better than Hadoop 1.x</title>
- <para>Hadoop 2.x is faster, with more features such as short-circuit reads which will help improve your
- HBase random read profile as well important bug fixes that will improve your overall HBase experience.
- You should run Hadoop 2 rather than Hadoop 1. HBase 0.98 deprecates use of Hadoop1.
- HBase 1.0 will not support Hadoop1.
- </para>
- </tip>
- <table>
- <title>Hadoop version support matrix</title>
- <tgroup cols='6' align='left' colsep='1' rowsep='1'>
- <colspec colname='c1' align='left'/>
- <colspec colname='c2' align='center'/>
- <colspec colname='c3' align='center'/>
- <colspec colname='c4' align='center'/>
- <colspec colname='c5' align='center'/>
- <colspec colname='c6' align='center'/>
- <thead>
- <row><entry> </entry><entry>HBase-0.92.x</entry><entry>HBase-0.94.x</entry><entry>HBase-0.96.x</entry><entry>HBase-0.98.x<footnote><para>Support for Hadoop 1.x is deprecated.</para></footnote></entry><entry>HBase-1.0.x<footnote><para>Hadoop 1.x is NOT supported</para></footnote></entry></row>
- </thead><tbody>
- <row><entry>Hadoop-0.20.205</entry><entry>S</entry> <entry>X</entry> <entry>X</entry><entry>X</entry><entry>X</entry></row>
- <row><entry>Hadoop-0.22.x </entry><entry>S</entry> <entry>X</entry> <entry>X</entry><entry>X</entry><entry>X</entry></row>
- <row><entry>Hadoop-1.0.0-1.0.2<footnote><para>HBase requires hadoop 1.0.3 at a minimum; there is an issue where we cannot find KerberosUtil compiling against earlier versions of Hadoop.</para></footnote> </entry><entry>X</entry> <entry>X</entry> <entry>X</entry><entry>X</entry><entry>X</entry></row>
- <row><entry>Hadoop-1.0.3+</entry><entry>S</entry> <entry>S</entry> <entry>S</entry><entry>X</entry><entry>X</entry></row>
- <row><entry>Hadoop-1.1.x </entry><entry>NT</entry> <entry>S</entry> <entry>S</entry><entry>X</entry><entry>X</entry></row>
- <row><entry>Hadoop-0.23.x </entry><entry>X</entry> <entry>S</entry> <entry>NT</entry><entry>X</entry><entry>X</entry></row>
- <row><entry>Hadoop-2.0.x-alpha </entry><entry>X</entry> <entry>NT</entry> <entry>X</entry><entry>X</entry><entry>X</entry></row>
- <row><entry>Hadoop-2.1.0-beta </entry><entry>X</entry> <entry>NT</entry> <entry>S</entry><entry>X</entry><entry>X</entry></row>
- <row><entry>Hadoop-2.2.0 </entry><entry>X</entry> <entry>NT<footnote><para>To get 0.94.x to run on hadoop 2.2.0,
- you need to change the hadoop 2 and protobuf versions in the <filename>pom.xml</filename>:
- <para>
- Here is a diff with pom.xml changes:
- </para>
- <programlisting><![CDATA[$ svn diff pom.xml
+ </section>
+ <!-- OS -->
+
+ <section
+ xml:id="hadoop">
+ <title><link
+ xlink:href="http://hadoop.apache.org">Hadoop</link><indexterm>
+ <primary>Hadoop</primary>
+ </indexterm></title>
+ <para>The below table shows some information about what versions of Hadoop are supported by
+ various HBase versions. Based on the version of HBase, you should select the most
+ appropriate version of Hadoop. We are not in the Hadoop distro selection business. You can
+ use Hadoop distributions from Apache, or learn about vendor distributions of Hadoop at <link
+ xlink:href="http://wiki.apache.org/hadoop/Distributions%20and%20Commercial%20Support" /></para>
+ <tip>
+ <title>Hadoop 2.x is better than Hadoop 1.x</title>
+ <para>Hadoop 2.x is faster, with more features such as short-circuit reads which will help
+ improve your HBase random read profile as well important bug fixes that will improve your
+ overall HBase experience. You should run Hadoop 2 rather than Hadoop 1. HBase 0.98
+ deprecates use of Hadoop1. HBase 1.0 will not support Hadoop1. </para>
+ </tip>
+ <para>Use the following legend to interpret this table:</para>
+ <simplelist
+ type="vert"
+ columns="1">
+ <member>S = supported and tested,</member>
+ <member>X = not supported,</member>
+ <member>NT = it should run, but not tested enough.</member>
+ </simplelist>
+
+ <table>
+ <title>Hadoop version support matrix</title>
+ <tgroup
+ cols="6"
+ align="left"
+ colsep="1"
+ rowsep="1">
+ <colspec
+ colname="c1"
+ align="left" />
+ <colspec
+ colname="c2"
+ align="center" />
+ <colspec
+ colname="c3"
+ align="center" />
+ <colspec
+ colname="c4"
+ align="center" />
+ <colspec
+ colname="c5"
+ align="center" />
+ <colspec
+ colname="c6"
+ align="center" />
+ <thead>
+ <row>
+ <entry> </entry>
+ <entry>HBase-0.92.x</entry>
+ <entry>HBase-0.94.x</entry>
+ <entry>HBase-0.96.x</entry>
+ <entry>HBase-0.98.x<footnote>
+ <para>Support for Hadoop 1.x is deprecated.</para>
+ </footnote></entry>
+ <entry>HBase-1.0.x<footnote>
+ <para>Hadoop 1.x is NOT supported</para>
+ </footnote></entry>
+ </row>
+ </thead>
+ <tbody>
+ <row>
+ <entry>Hadoop-0.20.205</entry>
+ <entry>S</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ </row>
+ <row>
+ <entry>Hadoop-0.22.x </entry>
+ <entry>S</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ </row>
+ <row>
+ <entry>Hadoop-1.0.0-1.0.2<footnote>
+ <para>HBase requires hadoop 1.0.3 at a minimum; there is an issue where we cannot
+ find KerberosUtil compiling against earlier versions of Hadoop.</para>
+ </footnote>
+ </entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ </row>
+ <row>
+ <entry>Hadoop-1.0.3+</entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ </row>
+ <row>
+ <entry>Hadoop-1.1.x </entry>
+ <entry>NT</entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ </row>
+ <row>
+ <entry>Hadoop-0.23.x </entry>
+ <entry>X</entry>
+ <entry>S</entry>
+ <entry>NT</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ </row>
+ <row>
+ <entry>Hadoop-2.0.x-alpha </entry>
+ <entry>X</entry>
+ <entry>NT</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ </row>
+ <row>
+ <entry>Hadoop-2.1.0-beta </entry>
+ <entry>X</entry>
+ <entry>NT</entry>
+ <entry>S</entry>
+ <entry>X</entry>
+ <entry>X</entry>
+ </row>
+ <row>
+ <entry>Hadoop-2.2.0 </entry>
+ <entry>X</entry>
+ <entry>NT <footnote>
+ <para>To get 0.94.x to run on hadoop 2.2.0, you need to change the hadoop 2 and
+ protobuf versions in the <filename>pom.xml</filename>: Here is a diff with
+ pom.xml changes: </para>
+ <programlisting><![CDATA[$ svn diff pom.xml
Index: pom.xml
===================================================================
--- pom.xml (revision 1545157)
@@ -284,235 +374,266 @@ Index: pom.xml
+ <hadoop.version>2.2.0</hadoop.version>
<slf4j.version>1.6.1</slf4j.version>
</properties>
- <dependencies>]]></programlisting>
- <para>The next step is to regenerate Protobuf files and assuming that the Protobuf has been installed:</para>
- <itemizedlist>
- <listitem>Go to the hbase root folder, using the command line;</listitem>
- <listitem>
- <para>Type the following commands:</para>
- <para>
- <programlisting><![CDATA[$ protoc -Isrc/main/protobuf --java_out=src/main/java src/main/protobuf/hbase.proto]]></programlisting>
- </para>
- <para>
- <programlisting><![CDATA[$ protoc -Isrc/main/protobuf --java_out=src/main/java src/main/protobuf/ErrorHandling.proto]]></programlisting>
- </para>
- </listitem>
- </itemizedlist>
- <para>
- Building against the hadoop 2 profile by running something like the following command:
- </para>
- <programlisting>$ mvn clean install assembly:single -Dhadoop.profile=2.0 -DskipTests</programlisting>
- </para></footnote></entry> <entry>S</entry><entry>S</entry><entry>NT</entry></row>
- <row><entry>Hadoop-2.3.x</entry><entry>X</entry> <entry>NT</entry> <entry>S</entry><entry>S</entry><entry>NT</entry></row>
- <row><entry>Hadoop-2.4.x</entry><entry>X</entry> <entry>NT</entry> <entry>S</entry><entry>S</entry><entry>S</entry></row>
- <row><entry>Hadoop-2.5.x</entry><entry>X</entry> <entry>NT</entry> <entry>S</entry><entry>S</entry><entry>S</entry></row>
-
- </tbody></tgroup></table>
-
- Where
- <simplelist type='vert' columns='1'>
- <member>S = supported and tested,</member>
- <member>X = not supported,</member>
- <member>NT = it should run, but not tested enough.</member>
- </simplelist>
+ <dependencies>]]>
+ </programlisting>
+ <para>The next step is to regenerate Protobuf files and assuming that the Protobuf
+ has been installed:</para>
+ <itemizedlist>
+ <listitem>
+ <para>Go to the hbase root folder, using the command line;</para>
+ </listitem>
+ <listitem>
+ <para>Type the following commands:</para>
+ <para>
+ <programlisting><![CDATA[$ protoc -Isrc/main/protobuf --java_out=src/main/java src/main/protobuf/hbase.proto]]></programlisting>
+ </para>
+ <para>
+ <programlisting><![CDATA[$ protoc -Isrc/main/protobuf --java_out=src/main/java src/main/protobuf/ErrorHandling.proto]]></programlisting>
+ </para>
+ </listitem>
+ </itemizedlist>
+ <para> Building against the hadoop 2 profile by running something like the
+ following command: </para>
+ <screen>$ mvn clean install assembly:single -Dhadoop.profile=2.0 -DskipTests</screen>
+ </footnote></entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ <entry>NT</entry>
+ </row>
+ <row>
+ <entry>Hadoop-2.3.x</entry>
+ <entry>X</entry>
+ <entry>NT</entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ <entry>NT</entry>
+ </row>
+ <row>
+ <entry>Hadoop-2.4.x</entry>
+ <entry>X</entry>
+ <entry>NT</entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ </row>
+ <row>
+ <entry>Hadoop-2.5.x</entry>
+ <entry>X</entry>
+ <entry>NT</entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ <entry>S</entry>
+ </row>
+
+ </tbody>
+ </tgroup>
+ </table>
+
+ <note
+ xml:id="replace.hadoop">
+ <title>Replace the Hadoop Bundled With HBase!</title>
+ <para> Because HBase depends on Hadoop, it bundles an instance of the Hadoop jar under its
+ <filename>lib</filename> directory. The bundled jar is ONLY for use in standalone mode.
+ In distributed mode, it is <emphasis>critical</emphasis> that the version of Hadoop that
+ is out on your cluster match what is under HBase. Replace the hadoop jar found in the
+ HBase lib directory with the hadoop jar you are running on your cluster to avoid version
+ mismatch issues. Make sure you replace the jar in HBase everywhere on your cluster. Hadoop
+ version mismatch issues have various manifestations but often all looks like its hung up.
</para>
- <note xml:id="replace.hadoop"><title>Replace the Hadoop Bundled With HBase!</title>
- <para>
- Because HBase depends on Hadoop, it bundles an instance of the Hadoop jar under its <filename>lib</filename> directory. The bundled jar is ONLY for use in standalone mode. In distributed mode, it is <emphasis>critical</emphasis> that the version of Hadoop that is out on your cluster match what is under HBase. Replace the hadoop jar found in the HBase lib directory with the hadoop jar you are running on your cluster to avoid version mismatch issues. Make sure you replace the jar in HBase everywhere on your cluster. Hadoop version mismatch issues have various manifestations but often all looks like its hung up.
- </para>
-</note>
- <section xml:id="hadoop.hbase-0.94">
- <title>Apache HBase 0.92 and 0.94</title>
- <para>HBase 0.92 and 0.94 versions can work with Hadoop versions, 0.20.205, 0.22.x, 1.0.x, and 1.1.x. HBase-0.94 can additionally work with Hadoop-0.23.x and 2.x, but you may have to recompile the code using the specific maven profile (see top level pom.xml)</para>
- </section>
-
- <section xml:id="hadoop.hbase-0.96">
- <title>Apache HBase 0.96</title>
- <para>
- As of Apache HBase 0.96.x, Apache Hadoop 1.0.x at least is required. Hadoop 2 is strongly encouraged (faster but also has fixes that help MTTR).
- We will no longer run properly on older Hadoops such as 0.20.205 or branch-0.20-append. Do not move to Apache HBase 0.96.x if you cannot upgrade your Hadoop<footnote><para>See <link xlink:href="http://search-hadoop.com/m/7vFVx4EsUb2">HBase, mail # dev - DISCUSS: Have hbase require at least hadoop 1.0.0 in hbase 0.96.0?</link></para></footnote>.</para>
- </section>
-
- <section xml:id="hadoop.older.versions">
- <title>Hadoop versions 0.20.x - 1.x</title>
- <para>
- HBase will lose data unless it is running on an HDFS that has a durable
- <code>sync</code> implementation. DO NOT use Hadoop 0.20.2, Hadoop 0.20.203.0, and Hadoop 0.20.204.0 which DO NOT have this attribute. Currently only Hadoop versions 0.20.205.x or any release in excess of this version -- this includes hadoop-1.0.0 -- have a working, durable sync
- <footnote>
- <para>The Cloudera blog post <link xlink:href="http://www.cloudera.com/blog/2012/01/an-update-on-apache-hadoop-1-0/">An update on Apache Hadoop 1.0</link>
- by Charles Zedlweski has a nice exposition on how all the Hadoop versions relate.
- Its worth checking out if you are having trouble making sense of the
- Hadoop version morass.
- </para>
- </footnote>. Sync has to be explicitly enabled by setting
- <varname>dfs.support.append</varname> equal
- to true on both the client side -- in <filename>hbase-site.xml</filename>
- -- and on the serverside in <filename>hdfs-site.xml</filename> (The sync
- facility HBase needs is a subset of the append code path).
- <programlisting>
- <property>
- <name>dfs.support.append</name>
- <value>true</value>
- </property>
- </programlisting>
- You will have to restart your cluster after making this edit. Ignore the chicken-little
- comment you'll find in the <filename>hdfs-default.xml</filename> in the
- description for the <varname>dfs.support.append</varname> configuration.
- </para>
- </section>
- <section xml:id="hadoop.security">
- <title>Apache HBase on Secure Hadoop</title>
- <para>Apache HBase will run on any Hadoop 0.20.x that incorporates Hadoop
- security features as long as you do as
- suggested above and replace the Hadoop jar that ships with HBase
- with the secure version. If you want to read more about how to setup
- Secure HBase, see <xref linkend="hbase.secure.configuration" />.</para>
- </section>
-
- <section xml:id="dfs.datanode.max.transfer.threads">
- <title><varname>dfs.datanode.max.transfer.threads</varname><indexterm>
- <primary>xcievers</primary>
- </indexterm></title>
-
- <para>An Hadoop HDFS datanode has an upper bound on the number of
- files that it will serve at any one time. The upper bound parameter is
- called <varname>xcievers</varname> (yes, this is misspelled). Again,
- before doing any loading, make sure you have configured Hadoop's
- <filename>conf/hdfs-site.xml</filename> setting the
- <varname>xceivers</varname> value to at least the following:
- <programlisting>
- <property>
- <name>dfs.datanode.max.transfer.threads</name>
- <value>4096</value>
- </property>
- </programlisting></para>
-
- <para>Be sure to restart your HDFS after making the above
- configuration.</para>
-
- <para>Not having this configuration in place makes for strange looking
- failures. Eventually you'll see a complain in the datanode logs
- complaining about the xcievers exceeded, but on the run up to this one
- manifestation is complaint about missing blocks. For example:
- <code>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...</code>
- <footnote><para>See <link xlink:href="http://ccgtech.blogspot.com/2010/02/hadoop-hdfs-deceived-by-xciever.html">Hadoop HDFS: Deceived by Xciever</link> for an informative rant on xceivering.</para></footnote></para>
- <para>See also <xref linkend="casestudies.xceivers"/>
- </para>
+ </note>
+ <section
+ xml:id="hadoop.hbase-0.94">
+ <title>Apache HBase 0.92 and 0.94</title>
+ <para>HBase 0.92 and 0.94 versions can work with Hadoop versions, 0.20.205, 0.22.x, 1.0.x,
+ and 1.1.x. HBase-0.94 can additionally work with Hadoop-0.23.x and 2.x, but you may have
+ to recompile the code using the specific maven profile (see top level pom.xml)</para>
</section>
- </section> <!-- hadoop -->
- </section>
-
- <section xml:id="standalone_dist">
- <title>HBase run modes: Standalone and Distributed</title>
-
- <para>HBase has two run modes: <xref linkend="standalone" /> and <xref linkend="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 <filename>conf</filename>
- directory. At a minimum, you must edit <code>conf/hbase-env.sh</code> to tell HBase which
- <command>java</command> to use. In this file you set HBase environment
- variables such as the heapsize and other options for the
- <application>JVM</application>, the preferred location for log files,
- etc. Set <varname>JAVA_HOME</varname> to point at the root of your
- <command>java</command> install.</para>
-
- <section xml:id="standalone">
- <title>Standalone HBase</title>
-
- <para>This is the default mode. Standalone mode is what is described
- in the <xref linkend="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.</para>
+ <section
+ xml:id="hadoop.hbase-0.96">
+ <title>Apache HBase 0.96</title>
+ <para> As of Apache HBase 0.96.x, Apache Hadoop 1.0.x at least is required. Hadoop 2 is
+ strongly encouraged (faster but also has fixes that help MTTR). We will no longer run
+ properly on older Hadoops such as 0.20.205 or branch-0.20-append. Do not move to Apache
+ HBase 0.96.x if you cannot upgrade your Hadoop.<footnote>
+ <para>See <link
+ xlink:href="http://search-hadoop.com/m/7vFVx4EsUb2">HBase, mail # dev - DISCUSS:
+ Have hbase require at least hadoop 1.0.0 in hbase 0.96.0?</link></para>
+ </footnote></para>
</section>
- <section xml:id="distributed">
- <title>Distributed</title>
-
- <para>Distributed mode can be subdivided into distributed but all
- daemons run on a single node -- a.k.a
- <emphasis>pseudo-distributed</emphasis>-- and
- <emphasis>fully-distributed</emphasis> where the daemons are spread
- across all nodes in the cluster <footnote>
- <para>The pseudo-distributed vs fully-distributed nomenclature
- comes from Hadoop.</para>
- </footnote>.</para>
-
- <para>Pseudo-distributed mode can run against the local filesystem or
- it can run against an instance of the <emphasis>Hadoop
- Distributed File System</emphasis> (HDFS). Fully-distributed mode can
- ONLY run on HDFS. See the Hadoop <link
- xlink:href="http://hadoop.apache.org/common/docs/r1.1.1/api/overview-summary.html#overview_description">
- requirements and instructions</link> for how to set up HDFS.</para>
-
- <para>Below we describe the different distributed setups. Starting,
- verification and exploration of your install, whether a
- <emphasis>pseudo-distributed</emphasis> or
- <emphasis>fully-distributed</emphasis> configuration is described in a
- section that follows, <xref linkend="confirm" />. The same verification script applies to both
- deploy types.</para>
-
-
-
+ <section
+ xml:id="hadoop.older.versions">
+ <title>Hadoop versions 0.20.x - 1.x</title>
+ <para> HBase will lose data unless it is running on an HDFS that has a durable
+ <code>sync</code> implementation. DO NOT use Hadoop 0.20.2, Hadoop 0.20.203.0, and
+ Hadoop 0.20.204.0 which DO NOT have this attribute. Currently only Hadoop versions
+ 0.20.205.x or any release in excess of this version -- this includes hadoop-1.0.0 -- have
+ a working, durable sync <footnote>
+ <para>The Cloudera blog post <link
+ xlink:href="http://www.cloudera.com/blog/2012/01/an-update-on-apache-hadoop-1-0/">An
+ update on Apache Hadoop 1.0</link> by Charles Zedlweski has a nice exposition on how
+ all the Hadoop versions relate. Its worth checking out if you are having trouble
+ making sense of the Hadoop version morass. </para>
+ </footnote>. Sync has to be explicitly enabled by setting
+ <varname>dfs.support.append</varname> equal to true on both the client side -- in
+ <filename>hbase-site.xml</filename> -- and on the serverside in
+ <filename>hdfs-site.xml</filename> (The sync facility HBase needs is a subset of the
+ append code path).</para>
+ <programlisting><![CDATA[
+<property>
+ <name>dfs.support.append</name>
+ <value>true</value>
+</property>]]></programlisting>
+ <para> You will have to restart your cluster after making this edit. Ignore the
+ chicken-little comment you'll find in the <filename>hdfs-default.xml</filename> in the
+ description for the <varname>dfs.support.append</varname> configuration. </para>
+ </section>
+ <section
+ xml:id="hadoop.security">
+ <title>Apache HBase on Secure Hadoop</title>
+ <para>Apache HBase will run on any Hadoop 0.20.x that incorporates Hadoop security features
+ as long as you do as suggested above and replace the Hadoop jar that ships with HBase with
+ the secure version. If you want to read more about how to setup Secure HBase, see <xref
+ linkend="hbase.secure.configuration" />.</para>
+ </section>
+ <section
+ xml:id="dfs.datanode.max.transfer.threads">
+ <title><varname>dfs.datanode.max.transfer.threads</varname><indexterm>
+ <primary>xcievers</primary>
+ </indexterm></title>
+ <para>An Hadoop HDFS datanode has an upper bound on the number of files that it will serve
+ at any one time. The upper bound parameter is called <varname>xcievers</varname> (yes,
+ this is misspelled). Again, before doing any loading, make sure you have configured
+ Hadoop's <filename>conf/hdfs-site.xml</filename> setting the <varname>xceivers</varname>
+ value to at least the following:</para>
+ <programlisting><![CDATA[
+<property>
+ <name>dfs.datanode.max.transfer.threads</name>
+ <value>4096</value>
+</property>
+ ]]></programlisting>
- <section xml:id="pseudo">
- <title>Pseudo-distributed</title>
+ <para>Be sure to restart your HDFS after making the above configuration.</para>
- <para>A pseudo-distributed mode is simply a fully-distributed mode run on
- a single host. Use this configuration testing and prototyping on
- HBase. Do not use this configuration for production nor for
- evaluating HBase performance.</para>
+ <para>Not having this configuration in place makes for strange looking failures. Eventually
+ you'll see a complain in the datanode logs complaining about the xcievers exceeded, but on
+ the run up to this one manifestation is complaint about missing blocks. For example:<footnote>
+ <para>See <link
+ xlink:href="http://ccgtech.blogspot.com/2010/02/hadoop-hdfs-deceived-by-xciever.html">Hadoop
+ HDFS: Deceived by Xciever</link> for an informative rant on xceivering.</para>
+ </footnote></para>
+ <para>See also <xref
+ linkend="casestudies.xceivers" />
+ </para>
+ <screen>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...</screen>
- <para>First, if you want to run on HDFS rather than on the local filesystem,
- setup your HDFS. You can set up HDFS also in pseudo-distributed mode
- (TODO: Add pointer to HOWTO doc; the hadoop site doesn't have any any more).
- Ensure you have a working HDFS before proceeding.
- </para>
+ </section>
+ </section>
+ <!-- hadoop -->
+ </section>
+
+ <section
+ xml:id="standalone_dist">
+ <title>HBase run modes: Standalone and Distributed</title>
+
+ <para>HBase has two run modes: <xref
+ linkend="standalone" /> and <xref
+ linkend="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 <filename>conf</filename>
+ directory. At a minimum, you must edit <code>conf/hbase-env.sh</code> to tell HBase which
+ <command>java</command> to use. In this file you set HBase environment variables such as the
+ heapsize and other options for the <application>JVM</application>, the preferred location for
+ log files, etc. Set <varname>JAVA_HOME</varname> to point at the root of your
+ <command>java</command> install.</para>
+
+ <section
+ xml:id="standalone">
+ <title>Standalone HBase</title>
+
+ <para>This is the default mode. Standalone mode is what is described in the <xref
+ linkend="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.</para>
+ </section>
- <para>Next, configure HBase. Edit <filename>conf/hbase-site.xml</filename>.
- This is the file into which you add local customizations and overrides.
- At a minimum, you must tell HBase to run in (pseudo-)distributed mode rather than
- in default standalone mode. To do this, set the <varname>hbase.cluster.distributed</varname>
- property to true (Its default is <varname>false</varname>). The absolute bare-minimum
- <filename>hbase-site.xml</filename> is therefore as follows:
-<programlisting>
-<configuration>
- <property>
- <name>hbase.cluster.distributed</name>
- <value>true</value>
- </property>
-</configuration>
-</programlisting>
-With this configuration, HBase will start up an HBase Master process, a ZooKeeper server,
-and a RegionServer process running against the
-local filesystem writing to wherever your operating system stores temporary files into a directory
-named <filename>hbase-YOUR_USER_NAME</filename>.</para>
-
-<para>Such a setup, using the local filesystem and
-writing to the operating systems's temporary directory is an ephemeral setup; the Hadoop
-local filesystem -- which is what HBase uses when it is writing the local filesytem does not
-support <command>sync</command> so unless the system is shutdown properly, the data will be lost. Writing to
-the operating system's temporary directory can also make for data loss when the machine
-is restarted as this directory is usually cleared on reboot. For a more permanent
-setup, see the next example where we make use of an instance of HDFS; HBase data will
-be written to the Hadoop distributed filesystem rather than to the local filesystem's
-tmp directory.</para>
-<para>In this <filename>conf/hbase-site.xml</filename> example, the
-<varname>hbase.rootdir</varname> property points to the local HDFS instance
-homed on the node <varname>h-24-30.example.com</varname>.
- <note>
- <title>Let HBase create <filename>${hbase.rootdir}</filename></title>
- <para>Let HBase create the <varname>hbase.rootdir</varname>
- directory. If you don't, you'll get warning saying HBase needs a
- migration run because the directory is missing files expected by
- HBase (it'll create them if you let it).</para>
- </note>
-<programlisting>
+ <section
+ xml:id="distributed">
+ <title>Distributed</title>
+
+ <para>Distributed mode can be subdivided into distributed but all daemons run on a single node
+ -- a.k.a <emphasis>pseudo-distributed</emphasis>-- and
+ <emphasis>fully-distributed</emphasis> where the daemons are spread across all nodes in
+ the cluster <footnote>
+ <para>The pseudo-distributed vs fully-distributed nomenclature comes from Hadoop.</para>
+ </footnote>.</para>
+
+ <para>Pseudo-distributed mode can run against the local filesystem or it can run against an
+ instance of the <emphasis>Hadoop Distributed File System</emphasis> (HDFS).
+ Fully-distributed mode can ONLY run on HDFS. See the Hadoop <link
+ xlink:href="http://hadoop.apache.org/common/docs/r1.1.1/api/overview-summary.html#overview_description">
+ requirements and instructions</link> for how to set up HDFS.</para>
+
+ <para>Below we describe the different distributed setups. Starting, verification and
+ exploration of your install, whether a <emphasis>pseudo-distributed</emphasis> or
+ <emphasis>fully-distributed</emphasis> configuration is described in a section that
+ follows, <xref
+ linkend="confirm" />. The same verification script applies to both deploy types.</para>
+ <section
+ xml:id="pseudo">
+ <title>Pseudo-distributed</title>
+
+ <para>A pseudo-distributed mode is simply a fully-distributed mode run on a single host. Use
+ this configuration testing and prototyping on HBase. Do not use this configuration for
+ production nor for evaluating HBase performance.</para>
+
+ <para>First, if you want to run on HDFS rather than on the local filesystem, setup your
+ HDFS. You can set up HDFS also in pseudo-distributed mode (TODO: Add pointer to HOWTO doc;
+ the hadoop site doesn't have any any more). Ensure you have a working HDFS before
+ proceeding. </para>
+
+ <para>Next, configure HBase. Edit <filename>conf/hbase-site.xml</filename>. This is the file
+ into which you add local customizations and overrides. At a minimum, you must tell HBase
+ to run in (pseudo-)distributed mode rather than in default standalone mode. To do this,
+ set the <varname>hbase.cluster.distributed</varname> property to true (Its default is
+ <varname>false</varname>). The absolute bare-minimum <filename>hbase-site.xml</filename>
+ is therefore as follows:</para>
+ <programlisting><![CDATA[
+<configuration>
+ <property>
+ <name>hbase.cluster.distributed</name>
+ <value>true</value>
+ </property>
+</configuration>
+]]>
+ </programlisting>
+ <para>With this configuration, HBase will start up an HBase Master process, a ZooKeeper
+ server, and a RegionServer process running against the local filesystem writing to
+ wherever your operating system stores temporary files into a directory named
+ <filename>hbase-YOUR_USER_NAME</filename>.</para>
+
+ <para>Such a setup, using the local filesystem and writing to the operating systems's
+ temporary directory is an ephemeral setup; the Hadoop local filesystem -- which is what
+ HBase uses when it is writing the local filesytem does not support <command>sync</command>
+ so unless the system is shutdown properly, the data will be lost. Writing to the operating
+ system's temporary directory can also make for data loss when the machine is restarted as
+ this directory is usually cleared on reboot. For a more permanent setup, see the next
+ example where we make use of an instance of HDFS; HBase data will be written to the Hadoop
+ distributed filesystem rather than to the local filesystem's tmp directory.</para>
+ <para>In this <filename>conf/hbase-site.xml</filename> example, the
+ <varname>hbase.rootdir</varname> property points to the local HDFS instance homed on the
+ node <varname>h-24-30.example.com</varname>.</para>
+ <note>
+ <title>Let HBase create <filename>${hbase.rootdir}</filename></title>
+ <para>Let HBase create the <varname>hbase.rootdir</varname> directory. If you don't,
+ you'll get warning saying HBase needs a migration run because the directory is missing
+ files expected by HBase (it'll create them if you let it).</para>
+ </note>
+ <programlisting>
<configuration>
<property>
<name>hbase.rootdir</name>
@@ -523,315 +644,296 @@ homed on the node <varname>h-24-30.example.com</varname>.
<value>true</value>
</property>
</configuration>
-</programlisting>
-</para>
- <para>Now skip to <xref linkend="confirm" /> for how to start and verify your
- pseudo-distributed install. <footnote>
- <para>See <xref linkend="pseudo.extras"/> for notes on how to start extra Masters and
- RegionServers when running pseudo-distributed.</para>
- </footnote></para>
-
- <section xml:id="pseudo.extras">
- <title>Pseudo-distributed Extras</title>
-
- <section xml:id="pseudo.extras.start">
- <title>Startup</title>
- <para>To start up the initial HBase cluster...
- <programlisting>% bin/start-hbase.sh</programlisting>
- </para>
- <para>To start up an extra backup master(s) on the same server run...
- <programlisting>% bin/local-master-backup.sh start 1</programlisting>
- ... the '1' means use ports 16001 & 16011, and this backup master's
- logfile will be at
- <filename>logs/hbase-${USER}-1-master-${HOSTNAME}.log</filename>.
- </para>
- <para>To startup multiple backup masters run... <programlisting>% bin/local-master-backup.sh start 2 3</programlisting> You can start up to 9 backup masters (10 total).
- </para>
- <para>To start up more regionservers...
- <programlisting>% bin/local-regionservers.sh start 1</programlisting>
- ... where '1' means use ports 16201 & 16301 and its logfile will be at
- `<filename>logs/hbase-${USER}-1-regionserver-${HOSTNAME}.log</filename>.
- </para>
- <para>To add 4 more regionservers in addition to the one you just started by running... <programlisting>% bin/local-regionservers.sh start 2 3 4 5</programlisting>
- This supports up to 99 extra regionservers (100 total).
- </para>
- </section>
- <section xml:id="pseudo.options.stop">
- <title>Stop</title>
- <para>Assuming you want to stop master backup # 1, run...
- <programlisting>% cat /tmp/hbase-${USER}-1-master.pid |xargs kill -9</programlisting>
- Note that bin/local-master-backup.sh stop 1 will try to stop the cluster along with the master.
- </para>
- <para>To stop an individual regionserver, run...
- <programlisting>% bin/local-regionservers.sh stop 1
- </programlisting>
- </para>
- </section>
-
- </section>
-
- </section>
-
-
-
-
-
- <section xml:id="fully_dist">
- <title>Fully-distributed</title>
+ </programlisting>
- <para>For running a fully-distributed operation on more than one
- host, make the following configurations. In
- <filename>hbase-site.xml</filename>, add the property
- <varname>hbase.cluster.distributed</varname> and set it to
- <varname>true</varname> and point the HBase
- <varname>hbase.rootdir</varname> at the appropriate HDFS NameNode
- and location in HDFS where you would like HBase to write data. For
- example, if you namenode were running at namenode.example.org on
- port 8020 and you wanted to home your HBase in HDFS at
- <filename>/hbase</filename>, make the following
- configuration.</para>
+ <para>Now skip to <xref
+ linkend="confirm" /> for how to start and verify your pseudo-distributed install. <footnote>
+ <para>See <xref
+ linkend="pseudo.extras" /> for notes on how to start extra Masters and RegionServers
+ when running pseudo-distributed.</para>
+ </footnote></para>
- <programlisting>
-<configuration>
- ...
- <property>
- <name>hbase.rootdir</name>
- <value>hdfs://namenode.example.org:8020/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>
-</programlisting>
-
- <section xml:id="regionserver">
- <title><filename>regionservers</filename></title>
-
- <para>In addition, a fully-distributed mode requires that you
- modify <filename>conf/regionservers</filename>. The
- <xref linkend="regionservers" /> file
- lists all hosts that you would have running
- <application>HRegionServer</application>s, one host per line (This
- file in HBase is like the Hadoop <filename>slaves</filename>
- file). All servers listed in this file will be started and stopped
- when HBase cluster start or stop is run.</para>
+ <section
+ xml:id="pseudo.extras">
+ <title>Pseudo-distributed Extras</title>
+
+ <section
+ xml:id="pseudo.extras.start">
+ <title>Startup</title>
+ <para>To start up the initial HBase cluster...</para>
+ <screen>% bin/start-hbase.sh</screen>
+ <para>To start up an extra backup master(s) on the same server run...</para>
+ <screen>% bin/local-master-backup.sh start 1</screen>
+ <para>... the '1' means use ports 16001 & 16011, and this backup master's logfile
+ will be at <filename>logs/hbase-${USER}-1-master-${HOSTNAME}.log</filename>. </para>
+ <para>To startup multiple backup masters run...</para>
+ <screen>% bin/local-master-backup.sh start 2 3</screen>
+ <para>You can start up to 9 backup masters (10 total). </para>
+ <para>To start up more regionservers...</para>
+ <screen>% bin/local-regionservers.sh start 1</screen>
+ <para>... where '1' means use ports 16201 & 16301 and its logfile will be at
+ `<filename>logs/hbase-${USER}-1-regionserver-${HOSTNAME}.log</filename>. </para>
+ <para>To add 4 more regionservers in addition to the one you just started by
+ running...</para>
+ <screen>% bin/local-regionservers.sh start 2 3 4 5</screen>
+ <para>This supports up to 99 extra regionservers (100 total). </para>
</section>
-
- <section xml:id="hbase.zookeeper">
- <title>ZooKeeper and HBase</title>
- <para>See section <xref linkend="zookeeper"/> for ZooKeeper setup for HBase.</para>
+ <section
+ xml:id="pseudo.options.stop">
+ <title>Stop</title>
+ <para>Assuming you want to stop master backup # 1, run...</para>
+ <screen>% cat /tmp/hbase-${USER}-1-master.pid |xargs kill -9</screen>
+ <para>Note that bin/local-master-backup.sh stop 1 will try to stop the cluster along
+ with the master. </para>
+ <para>To stop an individual regionserver, run...</para>
+ <screen>% bin/local-regionservers.sh stop 1</screen>
</section>
- <section xml:id="hdfs_client_conf">
- <title>HDFS Client Configuration</title>
-
- <para>Of note, if you have made <emphasis>HDFS client
- configuration</emphasis> on your Hadoop cluster -- i.e.
- configuration you want HDFS clients to use as opposed to
- server-side configurations -- HBase will not see this
- configuration unless you do one of the following:</para>
-
- <itemizedlist>
- <listitem>
- <para>Add a pointer to your <varname>HADOOP_CONF_DIR</varname>
- to the <varname>HBASE_CLASSPATH</varname> environment variable
- in <filename>hbase-env.sh</filename>.</para>
- </listitem>
-
- <listitem>
- <para>Add a copy of <filename>hdfs-site.xml</filename> (or
- <filename>hadoop-site.xml</filename>) or, better, symlinks,
- under <filename>${HBASE_HOME}/conf</filename>, or</para>
- </listitem>
-
- <listitem>
- <para>if only a small set of HDFS client configurations, add
- them to <filename>hbase-site.xml</filename>.</para>
- </listitem>
- </itemizedlist>
-
- <para>An example of such an HDFS client configuration is
- <varname>dfs.replication</varname>. 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.</para>
- </section>
</section>
- </section>
-
- <section xml:id="confirm">
- <title>Running and Confirming Your Installation</title>
-
-
-
- <para>Make sure HDFS is running first. Start and stop the Hadoop HDFS
- daemons by running <filename>bin/start-hdfs.sh</filename> over in the
- <varname>HADOOP_HOME</varname> directory. You can ensure it started
- properly by testing the <command>put</command> and
- <command>get</command> of files into the Hadoop filesystem. HBase does
- not normally use the mapreduce daemons. These do not need to be
- started.</para>
-
-
-
- <para><emphasis>If</emphasis> you are managing your own ZooKeeper,
- start it and confirm its running else, HBase will start up ZooKeeper
- for you as part of its start process.</para>
-
+ </section>
- <para>Start HBase with the following command:</para>
- <programlisting>bin/start-hbase.sh</programlisting>
- <para>Run the above from the <varname>HBASE_HOME</varname> directory.</para>
+ <section
+ xml:id="fully_dist">
+ <title>Fully-distributed</title>
- <para>You should now have a running HBase instance. HBase logs can be
- found in the <filename>logs</filename> subdirectory. Check them out
- especially if HBase had trouble starting.</para>
+ <para>For running a fully-distributed operation on more than one host, make the following
+ configurations. In <filename>hbase-site.xml</filename>, add the property
+ <varname>hbase.cluster.distributed</varname> and set it to <varname>true</varname> and
+ point the HBase <varname>hbase.rootdir</varname> at the appropriate HDFS NameNode and
+ location in HDFS where you would like HBase to write data. For example, if you namenode
+ were running at namenode.example.org on port 8020 and you wanted to home your HBase in
+ HDFS at <filename>/hbase</filename>, make the following configuration.</para>
+ <programlisting><![CDATA[
+<configuration>
+ ...
+ <property>
+ <name>hbase.rootdir</name>
+ <value>hdfs://namenode.example.org:8020/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>
+]]>
+ </programlisting>
+ <section
+ xml:id="regionserver">
+ <title><filename>regionservers</filename></title>
- <para>HBase also puts up a UI listing vital attributes. By default its
- deployed on the Master host at port 16010 (HBase RegionServers listen
- on port 16020 by default and put up an informational http server at
- 16030). If the Master were running on a host named
- <varname>master.example.org</varname> on the default port, to see the
- Master's homepage you'd point your browser at
- <filename>http://master.example.org:16010</filename>.</para>
+ <para>In addition, a fully-distributed mode requires that you modify
+ <filename>conf/regionservers</filename>. The <xref
+ linkend="regionservers" /> file lists all hosts that you would have running
+ <application>HRegionServer</application>s, one host per line (This file in HBase is
+ like the Hadoop <filename>slaves</filename> file). All servers listed in this file will
+ be started and stopped when HBase cluster start or stop is run.</para>
+ </section>
- <para>Prior to HBase 0.98, the default ports the master ui was deployed
- on port 16010, and the HBase RegionServers would listen
- on port 16020 by default and put up an informational http server at
- 16030.
- </para>
+ <section
+ xml:id="hbase.zookeeper">
+ <title>ZooKeeper and HBase</title>
+ <para>See section <xref
+ linkend="zookeeper" /> for ZooKeeper setup for HBase.</para>
+ </section>
- <para>Once HBase has started, see the <xref linkend="shell_exercises" /> for how to
- create tables, add data, scan your insertions, and finally disable and
- drop your tables.</para>
+ <section
+ xml:id="hdfs_client_conf">
+ <title>HDFS Client Configuration</title>
+ <para>Of note, if you have made <emphasis>HDFS client configuration</emphasis> on your
+ Hadoop cluster -- i.e. configuration you want HDFS clients to use as opposed to
+ server-side configurations -- HBase will not see this configuration unless you do one of
+ the following:</para>
+ <itemizedlist>
+ <listitem>
+ <para>Add a pointer to your <varname>HADOOP_CONF_DIR</varname> to the
+ <varname>HBASE_CLASSPATH</varname> environment variable in
+ <filename>hbase-env.sh</filename>.</para>
+ </listitem>
- <para>To stop HBase after exiting the HBase shell enter
- <programlisting>$ ./bin/stop-hbase.sh
-stopping hbase...............</programlisting> 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.</para>
+ <listitem>
+ <para>Add a copy of <filename>hdfs-site.xml</filename> (or
+ <filename>hadoop-site.xml</filename>) or, better, symlinks, under
+ <filename>${HBASE_HOME}/conf</filename>, or</para>
+ </listitem>
+ <listitem>
+ <para>if only a small set of HDFS client configurations, add them to
+ <filename>hbase-site.xml</filename>.</para>
+ </listitem>
+ </itemizedlist>
+ <para>An example of such an HDFS client configuration is
+ <varname>dfs.replication</varname>. 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.</para>
+ </section>
</section>
- </section> <!-- run modes -->
-
-
-
- <section xml:id="config.files">
- <title>Configuration Files</title>
-
- <section xml:id="hbase.site">
- <title><filename>hbase-site.xml</filename> and <filename>hbase-default.xml</filename></title>
- <para>Just as in Hadoop where you add site-specific HDFS configuration
- to the <filename>hdfs-site.xml</filename> file,
- for HBase, site specific customizations go into
- the file <filename>conf/hbase-site.xml</filename>.
- For the list of configurable properties, see
- <xref linkend="hbase_default_configurations" />
- below or view the raw <filename>hbase-default.xml</filename>
- source file in the HBase source code at
- <filename>src/main/resources</filename>.
- </para>
- <para>
- Not all configuration options make it out to
- <filename>hbase-default.xml</filename>. Configuration
- that it is thought rare anyone would change can exist only
- in code; the only way to turn up such configurations is
- via a reading of the source code itself.
- </para>
- <para>
- Currently, changes here will require a cluster restart for HBase to notice the change.
- </para>
- <!--The file hbase-default.xml is generated as part of
+ </section>
+
+ <section
+ xml:id="confirm">
+ <title>Running and Confirming Your Installation</title>
+
+
+
+ <para>Make sure HDFS is running first. Start and stop the Hadoop HDFS daemons by running
+ <filename>bin/start-hdfs.sh</filename> over in the <varname>HADOOP_HOME</varname>
+ directory. You can ensure it started properly by testing the <command>put</command> and
+ <command>get</command> of files into the Hadoop filesystem. HBase does not normally use
+ the mapreduce daemons. These do not need to be started.</para>
+ <para><emphasis>If</emphasis> you are managing your own ZooKeeper, start it and confirm its
+ running else, HBase will start up ZooKeeper for you as part of its start process.</para>
+ <para>Start HBase with the following command:</para>
+ <screen>bin/start-hbase.sh</screen>
+ <para>Run the above from the <varname>HBASE_HOME</varname> directory.</para>
+ <para>You should now have a running HBase instance. HBase logs can be found in the
+ <filename>logs</filename> subdirectory. Check them out especially if HBase had trouble
+ starting.</para>
+
+ <para>HBase also puts up a UI listing vital attributes. By default its deployed on the Master
+ host at port 16010 (HBase RegionServers listen on port 16020 by default and put up an
+ informational http server at 16030). If the Master were running on a host named
+ <varname>master.example.org</varname> on the default port, to see the Master's homepage
+ you'd point your browser at <filename>http://master.example.org:16010</filename>.</para>
+
+ <para>Prior to HBase 0.98, the default ports the master ui was deployed on port 16010, and the
+ HBase RegionServers would listen on port 16020 by default and put up an informational http
+ server at 16030. </para>
+
+ <para>Once HBase has started, see the <xref
+ linkend="shell_exercises" /> for how to create tables, add data, scan your insertions, and
+ finally disable and drop your tables.</para>
+
+ <para>To stop HBase after exiting the HBase shell enter</para>
+ <screen>$ ./bin/stop-hbase.sh
+stopping hbase...............</screen>
+ <para>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.</para>
+ </section>
+ </section>
+ <!-- run modes -->
+
+
+
+ <section
+ xml:id="config.files">
+ <title>Configuration Files</title>
+
+ <section
+ xml:id="hbase.site">
+ <title><filename>hbase-site.xml</filename> and <filename>hbase-default.xml</filename></title>
+ <para>Just as in Hadoop where you add site-specific HDFS configuration to the
+ <filename>hdfs-site.xml</filename> file, for HBase, site specific customizations go into
+ the file <filename>conf/hbase-site.xml</filename>. For the list of configurable properties,
+ see <xref
+ linkend="hbase_default_configurations" /> below or view the raw
+ <filename>hbase-default.xml</filename> source file in the HBase source code at
+ <filename>src/main/resources</filename>. </para>
+ <para> Not all configuration options make it out to <filename>hbase-default.xml</filename>.
+ Configuration that it is thought rare anyone would change can exist only in code; the only
+ way to turn up such configurations is via a reading of the source code itself. </para>
+ <para> Currently, changes here will require a cluster restart for HBase to notice the change. </para>
+ <!--The file hbase-default.xml is generated as part of
the build of the hbase site. See the hbase pom.xml.
The generated file is a docbook section with a glossary
in it-->
- <!--presumes the pre-site target has put the hbase-default.xml at this location-->
- <xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="../../../target/docbkx/hbase-default.xml">
+ <!--presumes the pre-site target has put the hbase-default.xml at this location-->
+ <xi:include
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ href="../../../target/docbkx/hbase-default.xml">
<xi:fallback>
- <section xml:id="hbase_default_configurations">
- <title></title>
+ <section
+ xml:id="hbase_default_configurations">
+ <title />
<para>
- <emphasis>This file is fallback content</emphasis>. If you are seeing this, something is wrong with the build of the HBase documentation or you are doing pre-build verification.
- </para>
- <para>
- The file hbase-default.xml is generated as part of
- the build of the hbase site. See the hbase <filename>pom.xml</filename>.
- The generated file is a docbook glossary.
- </para>
+ <emphasis>This file is fallback content</emphasis>. If you are seeing this, something
+ is wrong with the build of the HBase documentation or you are doing pre-build
+ verification. </para>
+ <para> The file hbase-default.xml is generated as part of the build of the hbase site.
+ See the hbase <filename>pom.xml</filename>. The generated file is a docbook glossary. </para>
<section>
<title>IDs that are auto-generated and cause validation errors if not present</title>
- <para>
- Each of these is a reference to a configuration file parameter which will cause an error if you are using the fallback content here. This is a dirty dirty hack.
- </para>
- <section xml:id="fail.fast.expired.active.master">
+ <para> Each of these is a reference to a configuration file parameter which will cause
+ an error if you are using the fallback content here. This is a dirty dirty hack. </para>
+ <section
+ xml:id="fail.fast.expired.active.master">
<title>fail.fast.expired.active.master</title>
<para />
</section>
- <section xml:id="hbase.hregion.memstore.flush.size">
+ <section
+ xml:id="hbase.hregion.memstore.flush.size">
<title>"hbase.hregion.memstore.flush.size"</title>
<para />
</section>
- <section xml:id="hbase.hstore.bytes.per.checksum">
+ <section
+ xml:id="hbase.hstore.bytes.per.checksum">
<title>hbase.hstore.bytes.per.checksum</title>
<para />
</section>
- <section xml:id="hbase.online.schema.update.enable">
+ <section
+ xml:id="hbase.online.schema.update.enable">
<title>hbase.online.schema.update.enable</title>
<para />
</section>
- <section xml:id="hbase.regionserver.global.memstore.size">
+ <section
+ xml:id="hbase.regionserver.global.memstore.size">
<title>hbase.regionserver.global.memstore.size</title>
<para />
</section>
- <section xml:id="hbase.hregion.max.filesize">
+ <section
+ xml:id="hbase.hregion.max.filesize">
<title>hbase.hregion.max.filesize</title>
<para />
</section>
- <section xml:id="hbase.hstore.blockingStoreFiles">
+ <section
+ xml:id="hbase.hstore.blockingStoreFiles">
<title>hbase.hstore.BlockingStoreFiles</title>
<para />
</section>
- <section xml:id="hfile.block.cache.size">
+ <section
+ xml:id="hfile.block.cache.size">
<title>hfile.block.cache.size</title>
<para />
</section>
- <section xml:id="copy.table">
+ <section
+ xml:id="copy.table">
<title>copy.table</title>
<para />
</section>
- <section xml:id="hbase.hstore.checksum.algorithm">
+ <section
+ xml:id="hbase.hstore.checksum.algorithm">
<title>hbase.hstore.checksum.algorithm</title>
<para />
</section>
- <section xml:id="hbase.zookeeper.useMulti">
+ <section
+ xml:id="hbase.zookeeper.useMulti">
<title>hbase.zookeeper.useMulti</title>
<para />
</section>
- <section xml:id="hbase.hregion.memstore.block.multiplier">
+ <section
+ xml:id="hbase.hregion.memstore.block.multiplier">
<title>hbase.hregion.memstore.block.multiplier</title>
<para />
</section>
- <section xml:id="hbase.regionserver.global.memstore.size.lower.limit">
+ <section
+ xml:id="hbase.regionserver.global.memstore.size.lower.limit">
<title>hbase.regionserver.global.memstore.size.lower.limit</title>
<para />
</section>
@@ -841,52 +943,45 @@ stopping hbase...............</programlisting> Shutdown can take a moment to
</xi:include>
</section>
- <section xml:id="hbase.env.sh">
+ <section
+ xml:id="hbase.env.sh">
<title><filename>hbase-env.sh</filename></title>
- <para>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
- <filename>conf/hbase-env.sh</filename> 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.</para>
- <para>
- Changes here will require a cluster restart for HBase to notice the change.
- </para>
- </section>
+ <para>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 <filename>conf/hbase-env.sh</filename> 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.</para>
+ <para> Changes here will require a cluster restart for HBase to notice the change. </para>
+ </section>
- <section xml:id="log4j">
+ <section
+ xml:id="log4j">
<title><filename>log4j.properties</filename></title>
- <para>Edit this file to change rate at which HBase files
- are rolled and to change the level at which HBase logs messages.
- </para>
- <para>
- 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.
- </para>
- </section>
+ <para>Edit this file to change rate at which HBase files are rolled and to change the level at
+ which HBase logs messages. </para>
+ <para> 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. </para>
+ </section>
- <section xml:id="client_dependencies"><title>Client configuration and dependencies connecting to an HBase cluster</title>
- <para>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.</para>
- <para>
- Since the HBase Master may move around, clients bootstrap by looking to ZooKeeper for
- current critical locations. ZooKeeper is where all these values are kept. Thus clients
- require the location of the ZooKeeper ensemble information before they can do anything else.
- Usually this the ensemble location is kept out in the <filename>hbase-site.xml</filename> and
- is picked up by the client from the <varname>CLASSPATH</varname>.</para>
-
- <para>If you are configuring an IDE to run a HBase client, you should
- include the <filename>conf/</filename> directory on your classpath so
- <filename>hbase-site.xml</filename> settings can be found (or
- add <filename>src/test/resources</filename> to pick up the hbase-site.xml
- used by tests).
- </para>
- <para>
- Minimally, a client of HBase needs several libraries in its <varname>CLASSPATH</varname> when connecting to a cluster, including:
- <programlisting>
+ <section
+ xml:id="client_dependencies">
+ <title>Client configuration and dependencies connecting to an HBase cluster</title>
+ <para>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.</para>
+ <para> Since the HBase Master may move around, clients bootstrap by looking to ZooKeeper for
+ current critical locations. ZooKeeper is where all these values are kept.
<TRUNCATED>
[08/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/performance.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/performance.xml b/src/main/docbkx/performance.xml
index a56c522..cbe600e 100644
--- a/src/main/docbkx/performance.xml
+++ b/src/main/docbkx/performance.xml
@@ -1,13 +1,15 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="performance"
- xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ version="5.0"
+ xml:id="performance"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -28,186 +30,232 @@
-->
<title>Apache HBase Performance Tuning</title>
- <section xml:id="perf.os">
+ <section
+ xml:id="perf.os">
<title>Operating System</title>
- <section xml:id="perf.os.ram">
- <title>Memory</title>
- <para>RAM, RAM, RAM. Don't starve HBase.</para>
- </section>
- <section xml:id="perf.os.64">
- <title>64-bit</title>
- <para>Use a 64-bit platform (and 64-bit JVM).</para>
- </section>
- <section xml:id="perf.os.swap">
- <title>Swapping</title>
- <para>Watch out for swapping. Set swappiness to 0.</para>
- </section>
+ <section
+ xml:id="perf.os.ram">
+ <title>Memory</title>
+ <para>RAM, RAM, RAM. Don't starve HBase.</para>
+ </section>
+ <section
+ xml:id="perf.os.64">
+ <title>64-bit</title>
+ <para>Use a 64-bit platform (and 64-bit JVM).</para>
+ </section>
+ <section
+ xml:id="perf.os.swap">
+ <title>Swapping</title>
+ <para>Watch out for swapping. Set swappiness to 0.</para>
+ </section>
</section>
- <section xml:id="perf.network">
+ <section
+ xml:id="perf.network">
<title>Network</title>
<para> Perhaps the most important factor in avoiding network issues degrading Hadoop and HBase
performance is the switching hardware that is used, decisions made early in the scope of the
project can cause major problems when you double or triple the size of your cluster (or more). </para>
- <para>
- Important items to consider:
- <itemizedlist>
- <listitem><para>Switching capacity of the device</para></listitem>
- <listitem><para>Number of systems connected</para></listitem>
- <listitem><para>Uplink capacity</para></listitem>
- </itemizedlist>
+ <para> Important items to consider: <itemizedlist>
+ <listitem>
+ <para>Switching capacity of the device</para>
+ </listitem>
+ <listitem>
+ <para>Number of systems connected</para>
+ </listitem>
+ <listitem>
+ <para>Uplink capacity</para>
+ </listitem>
+ </itemizedlist>
</para>
- <section xml:id="perf.network.1switch">
+ <section
+ xml:id="perf.network.1switch">
<title>Single Switch</title>
- <para>The single most important factor in this configuration is that the switching capacity of the hardware is capable of
- handling the traffic which can be generated by all systems connected to the switch. Some lower priced commodity hardware
- can have a slower switching capacity than could be utilized by a full switch.
- </para>
+ <para>The single most important factor in this configuration is that the switching capacity of
+ the hardware is capable of handling the traffic which can be generated by all systems
+ connected to the switch. Some lower priced commodity hardware can have a slower switching
+ capacity than could be utilized by a full switch. </para>
</section>
- <section xml:id="perf.network.2switch">
+ <section
+ xml:id="perf.network.2switch">
<title>Multiple Switches</title>
- <para>Multiple switches are a potential pitfall in the architecture. The most common configuration of lower priced hardware is a
- simple 1Gbps uplink from one switch to another. This often overlooked pinch point can easily become a bottleneck for cluster communication.
- Especially with MapReduce jobs that are both reading and writing a lot of data the communication across this uplink could be saturated.
- </para>
- <para>Mitigation of this issue is fairly simple and can be accomplished in multiple ways:
+ <para>Multiple switches are a potential pitfall in the architecture. The most common
+ configuration of lower priced hardware is a simple 1Gbps uplink from one switch to another.
+ This often overlooked pinch point can easily become a bottleneck for cluster communication.
+ Especially with MapReduce jobs that are both reading and writing a lot of data the
+ communication across this uplink could be saturated. </para>
+ <para>Mitigation of this issue is fairly simple and can be accomplished in multiple ways: </para>
<itemizedlist>
- <listitem><para>Use appropriate hardware for the scale of the cluster which you're attempting to build.</para></listitem>
- <listitem><para>Use larger single switch configurations i.e. single 48 port as opposed to 2x 24 port</para></listitem>
- <listitem><para>Configure port trunking for uplinks to utilize multiple interfaces to increase cross switch bandwidth.</para></listitem>
+ <listitem>
+ <para>Use appropriate hardware for the scale of the cluster which you're attempting to
+ build.</para>
+ </listitem>
+ <listitem>
+ <para>Use larger single switch configurations i.e. single 48 port as opposed to 2x 24
+ port</para>
+ </listitem>
+ <listitem>
+ <para>Configure port trunking for uplinks to utilize multiple interfaces to increase cross
+ switch bandwidth.</para>
+ </listitem>
</itemizedlist>
- </para>
</section>
- <section xml:id="perf.network.multirack">
+ <section
+ xml:id="perf.network.multirack">
<title>Multiple Racks</title>
- <para>Multiple rack configurations carry the same potential issues as multiple switches, and can suffer performance degradation from two main areas:
- <itemizedlist>
- <listitem><para>Poor switch capacity performance</para></listitem>
- <listitem><para>Insufficient uplink to another rack</para></listitem>
- </itemizedlist>
- If the the switches in your rack have appropriate switching capacity to handle all the hosts at full speed, the next most likely issue will be caused by homing
- more of your cluster across racks. The easiest way to avoid issues when spanning multiple racks is to use port trunking to create a bonded uplink to other racks.
- The downside of this method however, is in the overhead of ports that could potentially be used. An example of this is, creating an 8Gbps port channel from rack
- A to rack B, using 8 of your 24 ports to communicate between racks gives you a poor ROI, using too few however can mean you're not getting the most out of your cluster.
- </para>
- <para>Using 10Gbe links between racks will greatly increase performance, and assuming your switches support a 10Gbe uplink or allow for an expansion card will allow you to
- save your ports for machines as opposed to uplinks.
- </para>
- </section>
- <section xml:id="perf.network.ints">
+ <para>Multiple rack configurations carry the same potential issues as multiple switches, and
+ can suffer performance degradation from two main areas: </para>
+ <itemizedlist>
+ <listitem>
+ <para>Poor switch capacity performance</para>
+ </listitem>
+ <listitem>
+ <para>Insufficient uplink to another rack</para>
+ </listitem>
+ </itemizedlist>
+ <para>If the the switches in your rack have appropriate switching capacity to handle all the
+ hosts at full speed, the next most likely issue will be caused by homing more of your
+ cluster across racks. The easiest way to avoid issues when spanning multiple racks is to use
+ port trunking to create a bonded uplink to other racks. The downside of this method however,
+ is in the overhead of ports that could potentially be used. An example of this is, creating
+ an 8Gbps port channel from rack A to rack B, using 8 of your 24 ports to communicate between
+ racks gives you a poor ROI, using too few however can mean you're not getting the most out
+ of your cluster. </para>
+ <para>Using 10Gbe links between racks will greatly increase performance, and assuming your
+ switches support a 10Gbe uplink or allow for an expansion card will allow you to save your
+ ports for machines as opposed to uplinks. </para>
+ </section>
+ <section
+ xml:id="perf.network.ints">
<title>Network Interfaces</title>
- <para>Are all the network interfaces functioning correctly? Are you sure? See the Troubleshooting Case Study in <xref linkend="casestudies.slownode"/>.
- </para>
+ <para>Are all the network interfaces functioning correctly? Are you sure? See the
+ Troubleshooting Case Study in <xref
+ linkend="casestudies.slownode" />. </para>
</section>
- </section> <!-- network -->
+ </section>
+ <!-- network -->
- <section xml:id="jvm">
+ <section
+ xml:id="jvm">
<title>Java</title>
- <section xml:id="gc">
+ <section
+ xml:id="gc">
<title>The Garbage Collector and Apache HBase</title>
- <section xml:id="gcpause">
+ <section
+ xml:id="gcpause">
<title>Long GC pauses</title>
- <para xml:id="mslab">In his presentation, <link
- xlink:href="http://www.slideshare.net/cloudera/hbase-hug-presentation">Avoiding
- Full GCs with MemStore-Local Allocation Buffers</link>, Todd Lipcon
- describes two cases of stop-the-world garbage collections common in
- HBase, especially during loading; CMS failure modes and old generation
- heap fragmentation brought. To address the first, start the CMS
- earlier than default by adding
- <code>-XX:CMSInitiatingOccupancyFraction</code> and setting it down
- from defaults. Start at 60 or 70 percent (The lower you bring down the
- threshold, the more GCing is done, the more CPU used). To address the
- second fragmentation issue, Todd added an experimental facility,
- <indexterm><primary>MSLAB</primary></indexterm>, that
- must be explicitly enabled in Apache HBase 0.90.x (Its defaulted to be on in
- Apache 0.92.x HBase). See <code>hbase.hregion.memstore.mslab.enabled</code>
- to true in your <classname>Configuration</classname>. See the cited
- slides for background and detail<footnote><para>The latest jvms do better
- regards fragmentation so make sure you are running a recent release.
- Read down in the message,
- <link xlink:href="http://osdir.com/ml/hotspot-gc-use/2011-11/msg00002.html">Identifying concurrent mode failures caused by fragmentation</link>.</para></footnote>.
- Be aware that when enabled, each MemStore instance will occupy at least
- an MSLAB instance of memory. If you have thousands of regions or lots
- of regions each with many column families, this allocation of MSLAB
- may be responsible for a good portion of your heap allocation and in
- an extreme case cause you to OOME. Disable MSLAB in this case, or
- lower the amount of memory it uses or float less regions per server.
- </para>
- <para>If you have a write-heavy workload, check out
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE-8163">HBASE-8163 MemStoreChunkPool: An improvement for JAVA GC when using MSLAB</link>.
- It describes configurations to lower the amount of young GC during write-heavy loadings. If you do not have HBASE-8163 installed, and you are
- trying to improve your young GC times, one trick to consider -- courtesy of our Liang Xie -- is to set the GC config <varname>-XX:PretenureSizeThreshold</varname> in <filename>hbase-env.sh</filename>
- to be just smaller than the size of <varname>hbase.hregion.memstore.mslab.chunksize</varname> so MSLAB allocations happen in the
- tenured space directly rather than first in the young gen. You'd do this because these MSLAB allocations are going to likely make it
- to the old gen anyways and rather than pay the price of a copies between s0 and s1 in eden space followed by the copy up from
- young to old gen after the MSLABs have achieved sufficient tenure, save a bit of YGC churn and allocate in the old gen directly.
- </para>
- <para>For more information about GC logs, see <xref linkend="trouble.log.gc" />.
- </para>
+ <para
+ xml:id="mslab">In his presentation, <link
+ xlink:href="http://www.slideshare.net/cloudera/hbase-hug-presentation">Avoiding Full GCs
+ with MemStore-Local Allocation Buffers</link>, Todd Lipcon describes two cases of
+ stop-the-world garbage collections common in HBase, especially during loading; CMS failure
+ modes and old generation heap fragmentation brought. To address the first, start the CMS
+ earlier than default by adding <code>-XX:CMSInitiatingOccupancyFraction</code> and setting
+ it down from defaults. Start at 60 or 70 percent (The lower you bring down the threshold,
+ the more GCing is done, the more CPU used). To address the second fragmentation issue,
+ Todd added an experimental facility, <indexterm><primary>MSLAB</primary></indexterm>, that
+ must be explicitly enabled in Apache HBase 0.90.x (Its defaulted to be on in Apache 0.92.x
+ HBase). See <code>hbase.hregion.memstore.mslab.enabled</code> to true in your
+ <classname>Configuration</classname>. See the cited slides for background and detail<footnote>
+ <para>The latest jvms do better regards fragmentation so make sure you are running a
+ recent release. Read down in the message, <link
+ xlink:href="http://osdir.com/ml/hotspot-gc-use/2011-11/msg00002.html">Identifying
+ concurrent mode failures caused by fragmentation</link>.</para>
+ </footnote>. Be aware that when enabled, each MemStore instance will occupy at least an
+ MSLAB instance of memory. If you have thousands of regions or lots of regions each with
+ many column families, this allocation of MSLAB may be responsible for a good portion of
+ your heap allocation and in an extreme case cause you to OOME. Disable MSLAB in this case,
+ or lower the amount of memory it uses or float less regions per server. </para>
+ <para>If you have a write-heavy workload, check out <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-8163">HBASE-8163
+ MemStoreChunkPool: An improvement for JAVA GC when using MSLAB</link>. It describes
+ configurations to lower the amount of young GC during write-heavy loadings. If you do not
+ have HBASE-8163 installed, and you are trying to improve your young GC times, one trick to
+ consider -- courtesy of our Liang Xie -- is to set the GC config
+ <varname>-XX:PretenureSizeThreshold</varname> in <filename>hbase-env.sh</filename> to be
+ just smaller than the size of <varname>hbase.hregion.memstore.mslab.chunksize</varname> so
+ MSLAB allocations happen in the tenured space directly rather than first in the young gen.
+ You'd do this because these MSLAB allocations are going to likely make it to the old gen
+ anyways and rather than pay the price of a copies between s0 and s1 in eden space followed
+ by the copy up from young to old gen after the MSLABs have achieved sufficient tenure,
+ save a bit of YGC churn and allocate in the old gen directly. </para>
+ <para>For more information about GC logs, see <xref
+ linkend="trouble.log.gc" />. </para>
</section>
</section>
</section>
- <section xml:id="perf.configurations">
+ <section
+ xml:id="perf.configurations">
<title>HBase Configurations</title>
- <para>See <xref linkend="recommended_configurations" />.</para>
+ <para>See <xref
+ linkend="recommended_configurations" />.</para>
- <section xml:id="perf.compactions.and.splits">
+ <section
+ xml:id="perf.compactions.and.splits">
<title>Managing Compactions</title>
<para>For larger systems, managing <link
- linkend="disable.splitting">compactions and splits</link> may be
- something you want to consider.</para>
- </section>
-
- <section xml:id="perf.handlers">
- <title><varname>hbase.regionserver.handler.count</varname></title>
- <para>See <xref linkend="hbase.regionserver.handler.count"/>.
- </para>
- </section>
- <section xml:id="perf.hfile.block.cache.size">
- <title><varname>hfile.block.cache.size</varname></title>
- <para>See <xref linkend="hfile.block.cache.size"/>.
- A memory setting for the RegionServer process.
- </para>
- </section>
- <section xml:id="perf.rs.memstore.size">
- <title><varname>hbase.regionserver.global.memstore.size</varname></title>
- <para>See <xref linkend="hbase.regionserver.global.memstore.size"/>.
- This memory setting is often adjusted for the RegionServer process depending on needs.
- </para>
- </section>
- <section xml:id="perf.rs.memstore.size.lower.limit">
- <title><varname>hbase.regionserver.global.memstore.size.lower.limit</varname></title>
- <para>See <xref linkend="hbase.regionserver.global.memstore.size.lower.limit"/>.
- This memory setting is often adjusted for the RegionServer process depending on needs.
- </para>
- </section>
- <section xml:id="perf.hstore.blockingstorefiles">
- <title><varname>hbase.hstore.blockingStoreFiles</varname></title>
- <para>See <xref linkend="hbase.hstore.blockingStoreFiles"/>.
- If there is blocking in the RegionServer logs, increasing this can help.
- </para>
- </section>
- <section xml:id="perf.hregion.memstore.block.multiplier">
- <title><varname>hbase.hregion.memstore.block.multiplier</varname></title>
- <para>See <xref linkend="hbase.hregion.memstore.block.multiplier"/>.
- If there is enough RAM, increasing this can help.
- </para>
- </section>
- <section xml:id="hbase.regionserver.checksum.verify">
- <title><varname>hbase.regionserver.checksum.verify</varname></title>
- <para>Have HBase write the checksum into the datablock and save
- having to do the checksum seek whenever you read.</para>
-
- <para>See <xref linkend="hbase.regionserver.checksum.verify"/>,
- <xref linkend="hbase.hstore.bytes.per.checksum"/> and <xref linkend="hbase.hstore.checksum.algorithm"/>
- For more information see the
- release note on <link xlink:href="https://issues.apache.org/jira/browse/HBASE-5074">HBASE-5074 support checksums in HBase block cache</link>.
- </para>
+ linkend="disable.splitting">compactions and splits</link> may be something you want to
+ consider.</para>
+ </section>
+
+ <section
+ xml:id="perf.handlers">
+ <title><varname>hbase.regionserver.handler.count</varname></title>
+ <para>See <xref
+ linkend="hbase.regionserver.handler.count" />. </para>
+ </section>
+ <section
+ xml:id="perf.hfile.block.cache.size">
+ <title><varname>hfile.block.cache.size</varname></title>
+ <para>See <xref
+ linkend="hfile.block.cache.size" />. A memory setting for the RegionServer process.
+ </para>
+ </section>
+ <section
+ xml:id="perf.rs.memstore.size">
+ <title><varname>hbase.regionserver.global.memstore.size</varname></title>
+ <para>See <xref
+ linkend="hbase.regionserver.global.memstore.size" />. This memory setting is often
+ adjusted for the RegionServer process depending on needs. </para>
+ </section>
+ <section
+ xml:id="perf.rs.memstore.size.lower.limit">
+ <title><varname>hbase.regionserver.global.memstore.size.lower.limit</varname></title>
+ <para>See <xref
+ linkend="hbase.regionserver.global.memstore.size.lower.limit" />. This memory setting is
+ often adjusted for the RegionServer process depending on needs. </para>
+ </section>
+ <section
+ xml:id="perf.hstore.blockingstorefiles">
+ <title><varname>hbase.hstore.blockingStoreFiles</varname></title>
+ <para>See <xref
+ linkend="hbase.hstore.blockingStoreFiles" />. If there is blocking in the RegionServer
+ logs, increasing this can help. </para>
+ </section>
+ <section
+ xml:id="perf.hregion.memstore.block.multiplier">
+ <title><varname>hbase.hregion.memstore.block.multiplier</varname></title>
+ <para>See <xref
+ linkend="hbase.hregion.memstore.block.multiplier" />. If there is enough RAM, increasing
+ this can help. </para>
+ </section>
+ <section
+ xml:id="hbase.regionserver.checksum.verify">
+ <title><varname>hbase.regionserver.checksum.verify</varname></title>
+ <para>Have HBase write the checksum into the datablock and save having to do the checksum seek
+ whenever you read.</para>
+
+ <para>See <xref
+ linkend="hbase.regionserver.checksum.verify" />, <xref
+ linkend="hbase.hstore.bytes.per.checksum" /> and <xref
+ linkend="hbase.hstore.checksum.algorithm" /> For more information see the release note on <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-5074">HBASE-5074 support checksums
+ in HBase block cache</link>. </para>
</section>
</section>
@@ -215,293 +263,335 @@
- <section xml:id="perf.zookeeper">
+ <section
+ xml:id="perf.zookeeper">
<title>ZooKeeper</title>
- <para>See <xref linkend="zookeeper"/> for information on configuring ZooKeeper, and see the part
- about having a dedicated disk.
- </para>
+ <para>See <xref
+ linkend="zookeeper" /> for information on configuring ZooKeeper, and see the part about
+ having a dedicated disk. </para>
</section>
- <section xml:id="perf.schema">
- <title>Schema Design</title>
+ <section
+ xml:id="perf.schema">
+ <title>Schema Design</title>
- <section xml:id="perf.number.of.cfs">
+ <section
+ xml:id="perf.number.of.cfs">
<title>Number of Column Families</title>
- <para>See <xref linkend="number.of.cfs" />.</para>
+ <para>See <xref
+ linkend="number.of.cfs" />.</para>
</section>
- <section xml:id="perf.schema.keys">
+ <section
+ xml:id="perf.schema.keys">
<title>Key and Attribute Lengths</title>
- <para>See <xref linkend="keysize" />. See also <xref linkend="perf.compression.however" /> for
- compression caveats.</para>
- </section>
- <section xml:id="schema.regionsize"><title>Table RegionSize</title>
- <para>The regionsize can be set on a per-table basis via <code>setFileSize</code> on
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HTableDescriptor.html">HTableDescriptor</link> in the
- event where certain tables require different regionsizes than the configured default regionsize.
- </para>
- <para>See <xref linkend="ops.capacity.regions"/> for more information.
- </para>
- </section>
- <section xml:id="schema.bloom">
- <title>Bloom Filters</title>
- <para>Bloom Filters can be enabled per-ColumnFamily.
- Use <code>HColumnDescriptor.setBloomFilterType(NONE | ROW |
- ROWCOL)</code> to enable blooms per Column Family. Default =
- <varname>NONE</varname> for no bloom filters. If
- <varname>ROW</varname>, the hash of the row will be added to the bloom
- on each insert. If <varname>ROWCOL</varname>, the hash of the row +
- column family name + column family qualifier will be added to the bloom on
- each key insert.</para>
- <para>See <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link> and
- <xref linkend="blooms"/> for more information or this answer up in quora,
-<link xlink:href="http://www.quora.com/How-are-bloom-filters-used-in-HBase">How are bloom filters used in HBase?</link>.
- </para>
- </section>
- <section xml:id="schema.cf.blocksize"><title>ColumnFamily BlockSize</title>
- <para>The blocksize can be configured for each ColumnFamily in a table, and this defaults to 64k. Larger cell values require larger blocksizes.
- There is an inverse relationship between blocksize and the resulting StoreFile indexes (i.e., if the blocksize is doubled then the resulting
- indexes should be roughly halved).
- </para>
- <para>See <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>
- and <xref linkend="store"/>for more information.
- </para>
- </section>
- <section xml:id="cf.in.memory">
- <title>In-Memory ColumnFamilies</title>
- <para>ColumnFamilies can optionally be defined as in-memory. Data is still persisted to disk, just like any other ColumnFamily.
- In-memory blocks have the highest priority in the <xref linkend="block.cache" />, but it is not a guarantee that the entire table
- will be in memory.
- </para>
- <para>See <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link> for more information.
- </para>
- </section>
- <section xml:id="perf.compression">
+ <para>See <xref
+ linkend="keysize" />. See also <xref
+ linkend="perf.compression.however" /> for compression caveats.</para>
+ </section>
+ <section
+ xml:id="schema.regionsize">
+ <title>Table RegionSize</title>
+ <para>The regionsize can be set on a per-table basis via <code>setFileSize</code> on <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HTableDescriptor.html">HTableDescriptor</link>
+ in the event where certain tables require different regionsizes than the configured default
+ regionsize. </para>
+ <para>See <xref
+ linkend="ops.capacity.regions" /> for more information. </para>
+ </section>
+ <section
+ xml:id="schema.bloom">
+ <title>Bloom Filters</title>
+ <para>Bloom Filters can be enabled per-ColumnFamily. Use
+ <code>HColumnDescriptor.setBloomFilterType(NONE | ROW | ROWCOL)</code> to enable blooms
+ per Column Family. Default = <varname>NONE</varname> for no bloom filters. If
+ <varname>ROW</varname>, the hash of the row will be added to the bloom on each insert. If
+ <varname>ROWCOL</varname>, the hash of the row + column family name + column family
+ qualifier will be added to the bloom on each key insert.</para>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>
+ and <xref
+ linkend="blooms" /> for more information or this answer up in quora, <link
+ xlink:href="http://www.quora.com/How-are-bloom-filters-used-in-HBase">How are bloom
+ filters used in HBase?</link>. </para>
+ </section>
+ <section
+ xml:id="schema.cf.blocksize">
+ <title>ColumnFamily BlockSize</title>
+ <para>The blocksize can be configured for each ColumnFamily in a table, and this defaults to
+ 64k. Larger cell values require larger blocksizes. There is an inverse relationship between
+ blocksize and the resulting StoreFile indexes (i.e., if the blocksize is doubled then the
+ resulting indexes should be roughly halved). </para>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>
+ and <xref
+ linkend="store" />for more information. </para>
+ </section>
+ <section
+ xml:id="cf.in.memory">
+ <title>In-Memory ColumnFamilies</title>
+ <para>ColumnFamilies can optionally be defined as in-memory. Data is still persisted to disk,
+ just like any other ColumnFamily. In-memory blocks have the highest priority in the <xref
+ linkend="block.cache" />, but it is not a guarantee that the entire table will be in
+ memory. </para>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>
+ for more information. </para>
+ </section>
+ <section
+ xml:id="perf.compression">
<title>Compression</title>
- <para>Production systems should use compression with their ColumnFamily definitions. See <xref linkend="compression" /> for more information.
- </para>
- <section xml:id="perf.compression.however"><title>However...</title>
- <para>Compression deflates data <emphasis>on disk</emphasis>. When it's in-memory (e.g., in the
- MemStore) or on the wire (e.g., transferring between RegionServer and Client) it's inflated.
- So while using ColumnFamily compression is a best practice, but it's not going to completely eliminate
- the impact of over-sized Keys, over-sized ColumnFamily names, or over-sized Column names.
- </para>
- <para>See <xref linkend="keysize" /> on for schema design tips, and <xref linkend="keyvalue"/> for more information on HBase stores data internally.
- </para>
+ <para>Production systems should use compression with their ColumnFamily definitions. See <xref
+ linkend="compression" /> for more information. </para>
+ <section
+ xml:id="perf.compression.however">
+ <title>However...</title>
+ <para>Compression deflates data <emphasis>on disk</emphasis>. When it's in-memory (e.g., in
+ the MemStore) or on the wire (e.g., transferring between RegionServer and Client) it's
+ inflated. So while using ColumnFamily compression is a best practice, but it's not going
+ to completely eliminate the impact of over-sized Keys, over-sized ColumnFamily names, or
+ over-sized Column names. </para>
+ <para>See <xref
+ linkend="keysize" /> on for schema design tips, and <xref
+ linkend="keyvalue" /> for more information on HBase stores data internally. </para>
</section>
</section>
- </section> <!-- perf schema -->
+ </section>
+ <!-- perf schema -->
- <section xml:id="perf.general">
+ <section
+ xml:id="perf.general">
<title>HBase General Patterns</title>
- <section xml:id="perf.general.constants">
+ <section
+ xml:id="perf.general.constants">
<title>Constants</title>
- <para>When people get started with HBase they have a tendency to write code that looks like this:
-<programlisting>
+ <para>When people get started with HBase they have a tendency to write code that looks like
+ this:</para>
+ <programlisting>
Get get = new Get(rowkey);
Result r = htable.get(get);
byte[] b = r.getValue(Bytes.toBytes("cf"), Bytes.toBytes("attr")); // returns current version of value
-</programlisting>
- But especially when inside loops (and MapReduce jobs), converting the columnFamily and column-names
- to byte-arrays repeatedly is surprisingly expensive.
- It's better to use constants for the byte-arrays, like this:
-<programlisting>
+ </programlisting>
+ <para>But especially when inside loops (and MapReduce jobs), converting the columnFamily and
+ column-names to byte-arrays repeatedly is surprisingly expensive. It's better to use
+ constants for the byte-arrays, like this:</para>
+ <programlisting>
public static final byte[] CF = "cf".getBytes();
public static final byte[] ATTR = "attr".getBytes();
...
Get get = new Get(rowkey);
Result r = htable.get(get);
byte[] b = r.getValue(CF, ATTR); // returns current version of value
-</programlisting>
- </para>
+ </programlisting>
</section>
</section>
- <section xml:id="perf.writing">
+ <section
+ xml:id="perf.writing">
<title>Writing to HBase</title>
- <section xml:id="perf.batch.loading">
+ <section
+ xml:id="perf.batch.loading">
<title>Batch Loading</title>
- <para>Use the bulk load tool if you can. See
- <xref linkend="arch.bulk.load"/>.
- Otherwise, pay attention to the below.
- </para>
- </section> <!-- batch loading -->
-
- <section xml:id="precreate.regions">
- <title>
- Table Creation: Pre-Creating Regions
- </title>
-<para>
-Tables in HBase are initially created with one region by default. For bulk imports, this means that all clients will write to the same region
-until it is large enough to split and become distributed across the cluster. A useful pattern to speed up the bulk import process is to pre-create empty regions.
- Be somewhat conservative in this, because too-many regions can actually degrade performance.
-</para>
- <para>There are two different approaches to pre-creating splits. The first approach is to rely on the default <code>HBaseAdmin</code> strategy
- (which is implemented in <code>Bytes.split</code>)...
- </para>
-<programlisting>
+ <para>Use the bulk load tool if you can. See <xref
+ linkend="arch.bulk.load" />. Otherwise, pay attention to the below. </para>
+ </section>
+ <!-- batch loading -->
+
+ <section
+ xml:id="precreate.regions">
+ <title> Table Creation: Pre-Creating Regions </title>
+ <para> Tables in HBase are initially created with one region by default. For bulk imports,
+ this means that all clients will write to the same region until it is large enough to split
+ and become distributed across the cluster. A useful pattern to speed up the bulk import
+ process is to pre-create empty regions. Be somewhat conservative in this, because too-many
+ regions can actually degrade performance. </para>
+ <para>There are two different approaches to pre-creating splits. The first approach is to rely
+ on the default <code>HBaseAdmin</code> strategy (which is implemented in
+ <code>Bytes.split</code>)... </para>
+ <programlisting>
byte[] startKey = ...; // your lowest keuy
byte[] endKey = ...; // your highest key
int numberOfRegions = ...; // # of regions to create
admin.createTable(table, startKey, endKey, numberOfRegions);
-</programlisting>
- <para>And the other approach is to define the splits yourself...
- </para>
-<programlisting>
+ </programlisting>
+ <para>And the other approach is to define the splits yourself... </para>
+ <programlisting>
byte[][] splits = ...; // create your own splits
admin.createTable(table, splits);
</programlisting>
-<para>
- See <xref linkend="rowkey.regionsplits"/> for issues related to understanding your keyspace and pre-creating regions.
- </para>
- </section>
- <section xml:id="def.log.flush">
- <title>
- Table Creation: Deferred Log Flush
- </title>
-<para>
-The default behavior for Puts using the Write Ahead Log (WAL) is that <classname>HLog</classname> edits will be written immediately. If deferred log flush is used,
-WAL edits are kept in memory until the flush period. The benefit is aggregated and asynchronous <classname>HLog</classname>- writes, but the potential downside is that if
- the RegionServer goes down the yet-to-be-flushed edits are lost. This is safer, however, than not using WAL at all with Puts.
-</para>
-<para>
-Deferred log flush can be configured on tables via <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HTableDescriptor.html">HTableDescriptor</link>. The default value of <varname>hbase.regionserver.optionallogflushinterval</varname> is 1000ms.
-</para>
- </section>
-
- <section xml:id="perf.hbase.client.autoflush">
- <title>HBase Client: AutoFlush</title>
-
- <para>When performing a lot of Puts, make sure that setAutoFlush is set
- to false on your <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html">HTable</link>
- instance. Otherwise, the Puts will be sent one at a time to the
- RegionServer. Puts added via <code> htable.add(Put)</code> and <code> htable.add( <List> Put)</code>
- wind up in the same write buffer. If <code>autoFlush = false</code>,
- these messages are not sent until the write-buffer is filled. To
- explicitly flush the messages, call <methodname>flushCommits</methodname>.
- Calling <methodname>close</methodname> on the <classname>HTable</classname>
- instance will invoke <methodname>flushCommits</methodname>.</para>
- </section>
- <section xml:id="perf.hbase.client.putwal">
- <title>HBase Client: Turn off WAL on Puts</title>
- <para>A frequently discussed option for increasing throughput on <classname>Put</classname>s is to call <code>writeToWAL(false)</code>. Turning this off means
- that the RegionServer will <emphasis>not</emphasis> write the <classname>Put</classname> to the Write Ahead Log,
- only into the memstore, HOWEVER the consequence is that if there
- is a RegionServer failure <emphasis>there will be data loss</emphasis>.
- If <code>writeToWAL(false)</code> is used, do so with extreme caution. You may find in actuality that
- it makes little difference if your load is well distributed across the cluster.
- </para>
- <para>In general, it is best to use WAL for Puts, and where loading throughput
- is a concern to use <link linkend="perf.batch.loading">bulk loading</link> techniques instead.
- </para>
- </section>
- <section xml:id="perf.hbase.client.regiongroup">
+ <para> See <xref
+ linkend="rowkey.regionsplits" /> for issues related to understanding your keyspace and
+ pre-creating regions. </para>
+ </section>
+ <section
+ xml:id="def.log.flush">
+ <title> Table Creation: Deferred Log Flush </title>
+ <para> The default behavior for Puts using the Write Ahead Log (WAL) is that
+ <classname>HLog</classname> edits will be written immediately. If deferred log flush is
+ used, WAL edits are kept in memory until the flush period. The benefit is aggregated and
+ asynchronous <classname>HLog</classname>- writes, but the potential downside is that if the
+ RegionServer goes down the yet-to-be-flushed edits are lost. This is safer, however, than
+ not using WAL at all with Puts. </para>
+ <para> Deferred log flush can be configured on tables via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HTableDescriptor.html">HTableDescriptor</link>.
+ The default value of <varname>hbase.regionserver.optionallogflushinterval</varname> is
+ 1000ms. </para>
+ </section>
+
+ <section
+ xml:id="perf.hbase.client.autoflush">
+ <title>HBase Client: AutoFlush</title>
+
+ <para>When performing a lot of Puts, make sure that setAutoFlush is set to false on your <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html">HTable</link>
+ instance. Otherwise, the Puts will be sent one at a time to the RegionServer. Puts added via
+ <code> htable.add(Put)</code> and <code> htable.add( <List> Put)</code> wind up in
+ the same write buffer. If <code>autoFlush = false</code>, these messages are not sent until
+ the write-buffer is filled. To explicitly flush the messages, call
+ <methodname>flushCommits</methodname>. Calling <methodname>close</methodname> on the
+ <classname>HTable</classname> instance will invoke
+ <methodname>flushCommits</methodname>.</para>
+ </section>
+ <section
+ xml:id="perf.hbase.client.putwal">
+ <title>HBase Client: Turn off WAL on Puts</title>
+ <para>A frequently discussed option for increasing throughput on <classname>Put</classname>s
+ is to call <code>writeToWAL(false)</code>. Turning this off means that the RegionServer will
+ <emphasis>not</emphasis> write the <classname>Put</classname> to the Write Ahead Log, only
+ into the memstore, HOWEVER the consequence is that if there is a RegionServer failure
+ <emphasis>there will be data loss</emphasis>. If <code>writeToWAL(false)</code> is used,
+ do so with extreme caution. You may find in actuality that it makes little difference if
+ your load is well distributed across the cluster. </para>
+ <para>In general, it is best to use WAL for Puts, and where loading throughput is a concern to
+ use <link
+ linkend="perf.batch.loading">bulk loading</link> techniques instead. </para>
+ </section>
+ <section
+ xml:id="perf.hbase.client.regiongroup">
<title>HBase Client: Group Puts by RegionServer</title>
- <para>In addition to using the writeBuffer, grouping <classname>Put</classname>s by RegionServer can reduce the number of client RPC calls per writeBuffer flush.
- There is a utility <classname>HTableUtil</classname> currently on TRUNK that does this, but you can either copy that or implement your own version for
- those still on 0.90.x or earlier.
- </para>
- </section>
- <section xml:id="perf.hbase.write.mr.reducer">
- <title>MapReduce: Skip The Reducer</title>
+ <para>In addition to using the writeBuffer, grouping <classname>Put</classname>s by
+ RegionServer can reduce the number of client RPC calls per writeBuffer flush. There is a
+ utility <classname>HTableUtil</classname> currently on TRUNK that does this, but you can
+ either copy that or implement your own version for those still on 0.90.x or earlier. </para>
+ </section>
+ <section
+ xml:id="perf.hbase.write.mr.reducer">
+ <title>MapReduce: Skip The Reducer</title>
<para>When writing a lot of data to an HBase table from a MR job (e.g., with <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableOutputFormat.html">TableOutputFormat</link>), and specifically where Puts are being emitted
- from the Mapper, skip the Reducer step. When a Reducer step is used, all of the output (Puts) from the Mapper will get spooled to disk, then sorted/shuffled to other
- Reducers that will most likely be off-node. It's far more efficient to just write directly to HBase.
- </para>
- <para>For summary jobs where HBase is used as a source and a sink, then writes will be coming from the Reducer step (e.g., summarize values then write out result).
- This is a different processing problem than from the the above case.
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/mapreduce/TableOutputFormat.html">TableOutputFormat</link>),
+ and specifically where Puts are being emitted from the Mapper, skip the Reducer step. When a
+ Reducer step is used, all of the output (Puts) from the Mapper will get spooled to disk,
+ then sorted/shuffled to other Reducers that will most likely be off-node. It's far more
+ efficient to just write directly to HBase. </para>
+ <para>For summary jobs where HBase is used as a source and a sink, then writes will be coming
+ from the Reducer step (e.g., summarize values then write out result). This is a different
+ processing problem than from the the above case. </para>
+ </section>
+
+ <section
+ xml:id="perf.one.region">
+ <title>Anti-Pattern: One Hot Region</title>
+ <para>If all your data is being written to one region at a time, then re-read the section on
+ processing <link
+ linkend="timeseries">timeseries</link> data.</para>
+ <para>Also, if you are pre-splitting regions and all your data is <emphasis>still</emphasis>
+ winding up in a single region even though your keys aren't monotonically increasing, confirm
+ that your keyspace actually works with the split strategy. There are a variety of reasons
+ that regions may appear "well split" but won't work with your data. As the HBase client
+ communicates directly with the RegionServers, this can be obtained via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#getRegionLocation%28byte[]%29">HTable.getRegionLocation</link>. </para>
+ <para>See <xref
+ linkend="precreate.regions" />, as well as <xref
+ linkend="perf.configurations" />
</para>
</section>
- <section xml:id="perf.one.region">
- <title>Anti-Pattern: One Hot Region</title>
- <para>If all your data is being written to one region at a time, then re-read the
- section on processing <link linkend="timeseries">timeseries</link> data.</para>
- <para>Also, if you are pre-splitting regions and all your data is <emphasis>still</emphasis> winding up in a single region even though
- your keys aren't monotonically increasing, confirm that your keyspace actually works with the split strategy. There are a
- variety of reasons that regions may appear "well split" but won't work with your data. As
- the HBase client communicates directly with the RegionServers, this can be obtained via
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#getRegionLocation%28byte[]%29">HTable.getRegionLocation</link>.
- </para>
- <para>See <xref linkend="precreate.regions"/>, as well as <xref linkend="perf.configurations"/> </para>
</section>
+ <!-- writing -->
- </section> <!-- writing -->
-
- <section xml:id="perf.reading">
+ <section
+ xml:id="perf.reading">
<title>Reading from HBase</title>
- <para>The mailing list can help if you are having performance issues.
- For example, here is a good general thread on what to look at addressing
- read-time issues: <link xlink:href="http://search-hadoop.com/m/qOo2yyHtCC1">HBase Random Read latency > 100ms</link></para>
- <section xml:id="perf.hbase.client.caching">
+ <para>The mailing list can help if you are having performance issues. For example, here is a
+ good general thread on what to look at addressing read-time issues: <link
+ xlink:href="http://search-hadoop.com/m/qOo2yyHtCC1">HBase Random Read latency >
+ 100ms</link></para>
+ <section
+ xml:id="perf.hbase.client.caching">
<title>Scan Caching</title>
- <para>If HBase is used as an input source for a MapReduce job, for
- example, make sure that the input <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link>
- instance to the MapReduce job has <methodname>setCaching</methodname> set to something greater
- than the default (which is 1). Using the default value means that the
- map-task will make call back to the region-server for every record
- processed. Setting this value to 500, for example, will transfer 500
- rows at a time to the client to be processed. There is a cost/benefit to
- have the cache value be large because it costs more in memory for both
- client and RegionServer, so bigger isn't always better.</para>
- <section xml:id="perf.hbase.client.caching.mr">
+ <para>If HBase is used as an input source for a MapReduce job, for example, make sure that the
+ input <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link>
+ instance to the MapReduce job has <methodname>setCaching</methodname> set to something
+ greater than the default (which is 1). Using the default value means that the map-task will
+ make call back to the region-server for every record processed. Setting this value to 500,
+ for example, will transfer 500 rows at a time to the client to be processed. There is a
+ cost/benefit to have the cache value be large because it costs more in memory for both
+ client and RegionServer, so bigger isn't always better.</para>
+ <section
+ xml:id="perf.hbase.client.caching.mr">
<title>Scan Caching in MapReduce Jobs</title>
- <para>Scan settings in MapReduce jobs deserve special attention. Timeouts can result (e.g., UnknownScannerException)
- in Map tasks if it takes longer to process a batch of records before the client goes back to the RegionServer for the
- next set of data. This problem can occur because there is non-trivial processing occuring per row. If you process
- rows quickly, set caching higher. If you process rows more slowly (e.g., lots of transformations per row, writes),
- then set caching lower.
- </para>
- <para>Timeouts can also happen in a non-MapReduce use case (i.e., single threaded HBase client doing a Scan), but the
- processing that is often performed in MapReduce jobs tends to exacerbate this issue.
- </para>
+ <para>Scan settings in MapReduce jobs deserve special attention. Timeouts can result (e.g.,
+ UnknownScannerException) in Map tasks if it takes longer to process a batch of records
+ before the client goes back to the RegionServer for the next set of data. This problem can
+ occur because there is non-trivial processing occuring per row. If you process rows
+ quickly, set caching higher. If you process rows more slowly (e.g., lots of
+ transformations per row, writes), then set caching lower. </para>
+ <para>Timeouts can also happen in a non-MapReduce use case (i.e., single threaded HBase
+ client doing a Scan), but the processing that is often performed in MapReduce jobs tends
+ to exacerbate this issue. </para>
</section>
</section>
- <section xml:id="perf.hbase.client.selection">
+ <section
+ xml:id="perf.hbase.client.selection">
<title>Scan Attribute Selection</title>
- <para>Whenever a Scan is used to process large numbers of rows (and especially when used
- as a MapReduce source), be aware of which attributes are selected. If <code>scan.addFamily</code> is called
- then <emphasis>all</emphasis> of the attributes in the specified ColumnFamily will be returned to the client.
- If only a small number of the available attributes are to be processed, then only those attributes should be specified
- in the input scan because attribute over-selection is a non-trivial performance penalty over large datasets.
- </para>
+ <para>Whenever a Scan is used to process large numbers of rows (and especially when used as a
+ MapReduce source), be aware of which attributes are selected. If <code>scan.addFamily</code>
+ is called then <emphasis>all</emphasis> of the attributes in the specified ColumnFamily will
+ be returned to the client. If only a small number of the available attributes are to be
+ processed, then only those attributes should be specified in the input scan because
+ attribute over-selection is a non-trivial performance penalty over large datasets. </para>
</section>
- <section xml:id="perf.hbase.client.seek">
+ <section
+ xml:id="perf.hbase.client.seek">
<title>Avoid scan seeks</title>
- <para>When columns are selected explicitly with <code>scan.addColumn</code>, HBase will schedule seek operations to seek between the
- selected columns. When rows have few columns and each column has only a few versions this can be inefficient. A seek operation is generally
- slower if does not seek at least past 5-10 columns/versions or 512-1024 bytes.</para>
- <para>In order to opportunistically look ahead a few columns/versions to see if the next column/version can be found that
- way before a seek operation is scheduled, a new attribute <code>Scan.HINT_LOOKAHEAD</code> can be set the on Scan object. The following code instructs the
- RegionServer to attempt two iterations of next before a seek is scheduled:<programlisting>
+ <para>When columns are selected explicitly with <code>scan.addColumn</code>, HBase will
+ schedule seek operations to seek between the selected columns. When rows have few columns
+ and each column has only a few versions this can be inefficient. A seek operation is
+ generally slower if does not seek at least past 5-10 columns/versions or 512-1024
+ bytes.</para>
+ <para>In order to opportunistically look ahead a few columns/versions to see if the next
+ column/version can be found that way before a seek operation is scheduled, a new attribute
+ <code>Scan.HINT_LOOKAHEAD</code> can be set the on Scan object. The following code
+ instructs the RegionServer to attempt two iterations of next before a seek is
+ scheduled:</para>
+ <programlisting>
Scan scan = new Scan();
scan.addColumn(...);
scan.setAttribute(Scan.HINT_LOOKAHEAD, Bytes.toBytes(2));
table.getScanner(scan);
-</programlisting></para>
- </section>
- <section xml:id="perf.hbase.mr.input">
- <title>MapReduce - Input Splits</title>
- <para>For MapReduce jobs that use HBase tables as a source, if there a pattern where the "slow" map tasks seem to
- have the same Input Split (i.e., the RegionServer serving the data), see the
- Troubleshooting Case Study in <xref linkend="casestudies.slownode"/>.
- </para>
+ </programlisting>
+ </section>
+ <section
+ xml:id="perf.hbase.mr.input">
+ <title>MapReduce - Input Splits</title>
+ <para>For MapReduce jobs that use HBase tables as a source, if there a pattern where the
+ "slow" map tasks seem to have the same Input Split (i.e., the RegionServer serving the
+ data), see the Troubleshooting Case Study in <xref
+ linkend="casestudies.slownode" />. </para>
</section>
- <section xml:id="perf.hbase.client.scannerclose">
+ <section
+ xml:id="perf.hbase.client.scannerclose">
<title>Close ResultScanners</title>
- <para>This isn't so much about improving performance but rather
- <emphasis>avoiding</emphasis> performance problems. If you forget to
- close <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/ResultScanner.html">ResultScanners</link>
- you can cause problems on the RegionServers. Always have ResultScanner
- processing enclosed in try/catch blocks... <programlisting>
+ <para>This isn't so much about improving performance but rather <emphasis>avoiding</emphasis>
+ performance problems. If you forget to close <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/ResultScanner.html">ResultScanners</link>
+ you can cause problems on the RegionServers. Always have ResultScanner processing enclosed
+ in try/catch blocks...</para>
+ <programlisting>
Scan scan = new Scan();
// set attrs...
ResultScanner rs = htable.getScanner(scan);
@@ -511,184 +601,201 @@ try {
} finally {
rs.close(); // always close the ResultScanner!
}
-htable.close();</programlisting></para>
+htable.close();
+ </programlisting>
</section>
- <section xml:id="perf.hbase.client.blockcache">
+ <section
+ xml:id="perf.hbase.client.blockcache">
<title>Block Cache</title>
<para><link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link>
- instances can be set to use the block cache in the RegionServer via the
- <methodname>setCacheBlocks</methodname> method. For input Scans to MapReduce jobs, this should be
- <varname>false</varname>. For frequently accessed rows, it is advisable to use the block
- cache.</para>
- </section>
- <section xml:id="perf.hbase.client.rowkeyonly">
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link>
+ instances can be set to use the block cache in the RegionServer via the
+ <methodname>setCacheBlocks</methodname> method. For input Scans to MapReduce jobs, this
+ should be <varname>false</varname>. For frequently accessed rows, it is advisable to use the
+ block cache.</para>
+ </section>
+ <section
+ xml:id="perf.hbase.client.rowkeyonly">
<title>Optimal Loading of Row Keys</title>
- <para>When performing a table <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">scan</link>
- where only the row keys are needed (no families, qualifiers, values or timestamps), add a FilterList with a
- <varname>MUST_PASS_ALL</varname> operator to the scanner using <methodname>setFilter</methodname>. The filter list
- should include both a <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/FirstKeyOnlyFilter.html">FirstKeyOnlyFilter</link>
- and a <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/KeyOnlyFilter.html">KeyOnlyFilter</link>.
- Using this filter combination will result in a worst case scenario of a RegionServer reading a single value from disk
- and minimal network traffic to the client for a single row.
+ <para>When performing a table <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">scan</link>
+ where only the row keys are needed (no families, qualifiers, values or timestamps), add a
+ FilterList with a <varname>MUST_PASS_ALL</varname> operator to the scanner using
+ <methodname>setFilter</methodname>. The filter list should include both a <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/FirstKeyOnlyFilter.html">FirstKeyOnlyFilter</link>
+ and a <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/KeyOnlyFilter.html">KeyOnlyFilter</link>.
+ Using this filter combination will result in a worst case scenario of a RegionServer reading
+ a single value from disk and minimal network traffic to the client for a single row. </para>
+ </section>
+ <section
+ xml:id="perf.hbase.read.dist">
+ <title>Concurrency: Monitor Data Spread</title>
+ <para>When performing a high number of concurrent reads, monitor the data spread of the target
+ tables. If the target table(s) have too few regions then the reads could likely be served
+ from too few nodes. </para>
+ <para>See <xref
+ linkend="precreate.regions" />, as well as <xref
+ linkend="perf.configurations" />
</para>
</section>
- <section xml:id="perf.hbase.read.dist">
- <title>Concurrency: Monitor Data Spread</title>
- <para>When performing a high number of concurrent reads, monitor the data spread of the target tables. If the target table(s) have
- too few regions then the reads could likely be served from too few nodes. </para>
- <para>See <xref linkend="precreate.regions"/>, as well as <xref linkend="perf.configurations"/> </para>
- </section>
- <section xml:id="blooms">
- <title>Bloom Filters</title>
- <para>Enabling Bloom Filters can save your having to go to disk and
- can help improve read latencies.</para>
- <para><link xlink:href="http://en.wikipedia.org/wiki/Bloom_filter">Bloom filters</link> were developed over in <link
- xlink:href="https://issues.apache.org/jira/browse/HBASE-1200">HBase-1200
- Add bloomfilters</link>.<footnote>
- <para>For description of the development process -- why static blooms
- rather than dynamic -- and for an overview of the unique properties
- that pertain to blooms in HBase, as well as possible future
- directions, see the <emphasis>Development Process</emphasis> section
- of the document <link
- xlink:href="https://issues.apache.org/jira/secure/attachment/12444007/Bloom_Filters_in_HBase.pdf">BloomFilters
- in HBase</link> attached to <link
- xlink:href="https://issues.apache.org/jira/browse/HBASE-1200">HBase-1200</link>.</para>
- </footnote><footnote>
- <para>The bloom filters described here are actually version two of
- blooms in HBase. In versions up to 0.19.x, HBase had a dynamic bloom
- option based on work done by the <link
- xlink:href="http://www.one-lab.org">European Commission One-Lab
- Project 034819</link>. The core of the HBase bloom work was later
- pulled up into Hadoop to implement org.apache.hadoop.io.BloomMapFile.
- Version 1 of HBase blooms never worked that well. Version 2 is a
- rewrite from scratch though again it starts with the one-lab
- work.</para>
- </footnote></para>
- <para>See also <xref linkend="schema.bloom" />.
- </para>
-
- <section xml:id="bloom_footprint">
- <title>Bloom StoreFile footprint</title>
-
- <para>Bloom filters add an entry to the <classname>StoreFile</classname>
- general <classname>FileInfo</classname> data structure and then two
- extra entries to the <classname>StoreFile</classname> metadata
- section.</para>
-
- <section>
- <title>BloomFilter in the <classname>StoreFile</classname>
- <classname>FileInfo</classname> data structure</title>
-
- <para><classname>FileInfo</classname> has a
- <varname>BLOOM_FILTER_TYPE</varname> entry which is set to
- <varname>NONE</varname>, <varname>ROW</varname> or
- <varname>ROWCOL.</varname></para>
- </section>
+ <section
+ xml:id="blooms">
+ <title>Bloom Filters</title>
+ <para>Enabling Bloom Filters can save your having to go to disk and can help improve read
+ latencies.</para>
+ <para><link
+ xlink:href="http://en.wikipedia.org/wiki/Bloom_filter">Bloom filters</link> were developed
+ over in <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-1200">HBase-1200 Add
+ bloomfilters</link>.<footnote>
+ <para>For description of the development process -- why static blooms rather than dynamic
+ -- and for an overview of the unique properties that pertain to blooms in HBase, as well
+ as possible future directions, see the <emphasis>Development Process</emphasis> section
+ of the document <link
+ xlink:href="https://issues.apache.org/jira/secure/attachment/12444007/Bloom_Filters_in_HBase.pdf">BloomFilters
+ in HBase</link> attached to <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-1200">HBase-1200</link>.</para>
+ </footnote><footnote>
+ <para>The bloom filters described here are actually version two of blooms in HBase. In
+ versions up to 0.19.x, HBase had a dynamic bloom option based on work done by the <link
+ xlink:href="http://www.one-lab.org">European Commission One-Lab Project 034819</link>.
+ The core of the HBase bloom work was later pulled up into Hadoop to implement
+ org.apache.hadoop.io.BloomMapFile. Version 1 of HBase blooms never worked that well.
+ Version 2 is a rewrite from scratch though again it starts with the one-lab work.</para>
+ </footnote></para>
+ <para>See also <xref
+ linkend="schema.bloom" />. </para>
+
+ <section
+ xml:id="bloom_footprint">
+ <title>Bloom StoreFile footprint</title>
+
+ <para>Bloom filters add an entry to the <classname>StoreFile</classname> general
+ <classname>FileInfo</classname> data structure and then two extra entries to the
+ <classname>StoreFile</classname> metadata section.</para>
+
+ <section>
+ <title>BloomFilter in the <classname>StoreFile</classname>
+ <classname>FileInfo</classname> data structure</title>
- <section>
- <title>BloomFilter entries in <classname>StoreFile</classname>
- metadata</title>
+ <para><classname>FileInfo</classname> has a <varname>BLOOM_FILTER_TYPE</varname> entry
+ which is set to <varname>NONE</varname>, <varname>ROW</varname> or
+ <varname>ROWCOL.</varname></para>
+ </section>
+
+ <section>
+ <title>BloomFilter entries in <classname>StoreFile</classname> metadata</title>
- <para><varname>BLOOM_FILTER_META</varname> holds Bloom Size, Hash
- Function used, etc. Its small in size and is cached on
- <classname>StoreFile.Reader</classname> load</para>
- <para><varname>BLOOM_FILTER_DATA</varname> is the actual bloomfilter
- data. Obtained on-demand. Stored in the LRU cache, if it is enabled
- (Its enabled by default).</para>
+ <para><varname>BLOOM_FILTER_META</varname> holds Bloom Size, Hash Function used, etc. Its
+ small in size and is cached on <classname>StoreFile.Reader</classname> load</para>
+ <para><varname>BLOOM_FILTER_DATA</varname> is the actual bloomfilter data. Obtained
+ on-demand. Stored in the LRU cache, if it is enabled (Its enabled by default).</para>
+ </section>
</section>
- </section>
- <section xml:id="config.bloom">
- <title>Bloom Filter Configuration</title>
+ <section
+ xml:id="config.bloom">
+ <title>Bloom Filter Configuration</title>
<section>
- <title><varname>io.hfile.bloom.enabled</varname> global kill
- switch</title>
+ <title><varname>io.hfile.bloom.enabled</varname> global kill switch</title>
- <para><code>io.hfile.bloom.enabled</code> in
- <classname>Configuration</classname> serves as the kill switch in case
- something goes wrong. Default = <varname>true</varname>.</para>
+ <para><code>io.hfile.bloom.enabled</code> in <classname>Configuration</classname> serves
+ as the kill switch in case something goes wrong. Default =
+ <varname>true</varname>.</para>
</section>
<section>
- <title><varname>io.hfile.bloom.error.rate</varname></title>
+ <title><varname>io.hfile.bloom.error.rate</varname></title>
- <para><varname>io.hfile.bloom.error.rate</varname> = average false
- positive rate. Default = 1%. Decrease rate by ½ (e.g. to .5%) == +1
- bit per bloom entry.</para>
+ <para><varname>io.hfile.bloom.error.rate</varname> = average false positive rate. Default
+ = 1%. Decrease rate by ½ (e.g. to .5%) == +1 bit per bloom entry.</para>
</section>
<section>
- <title><varname>io.hfile.bloom.max.fold</varname></title>
-
- <para><varname>io.hfile.bloom.max.fold</varname> = guaranteed minimum
- fold rate. Most people should leave this alone. Default = 7, or can
- collapse to at least 1/128th of original size. See the
- <emphasis>Development Process</emphasis> section of the document <link
- xlink:href="https://issues.apache.org/jira/secure/attachment/12444007/Bloom_Filters_in_HBase.pdf">BloomFilters
- in HBase</link> for more on what this option means.</para>
- </section>
+ <title><varname>io.hfile.bloom.max.fold</varname></title>
+
+ <para><varname>io.hfile.bloom.max.fold</varname> = guaranteed minimum fold rate. Most
+ people should leave this alone. Default = 7, or can collapse to at least 1/128th of
+ original size. See the <emphasis>Development Process</emphasis> section of the document <link
+ xlink:href="https://issues.apache.org/jira/secure/attachment/12444007/Bloom_Filters_in_HBase.pdf">BloomFilters
+ in HBase</link> for more on what this option means.</para>
</section>
- </section> <!-- bloom -->
+ </section>
+ </section>
+ <!-- bloom -->
- </section> <!-- reading -->
+ </section>
+ <!-- reading -->
- <section xml:id="perf.deleting">
+ <section
+ xml:id="perf.deleting">
<title>Deleting from HBase</title>
- <section xml:id="perf.deleting.queue">
- <title>Using HBase Tables as Queues</title>
- <para>HBase tables are sometimes used as queues. In this case, special care must be taken to regularly perform major compactions on tables used in
- this manner. As is documented in <xref linkend="datamodel" />, marking rows as deleted creates additional StoreFiles which then need to be processed
- on reads. Tombstones only get cleaned up with major compactions.
- </para>
- <para>See also <xref linkend="compaction" /> and <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HBaseAdmin.html#majorCompact%28java.lang.String%29">HBaseAdmin.majorCompact</link>.
- </para>
- </section>
- <section xml:id="perf.deleting.rpc">
- <title>Delete RPC Behavior</title>
- <para>Be aware that <code>htable.delete(Delete)</code> doesn't use the writeBuffer. It will execute an RegionServer RPC with each invocation.
- For a large number of deletes, consider <code>htable.delete(List)</code>.
- </para>
- <para>See <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#delete%28org.apache.hadoop.hbase.client.Delete%29"></link>
- </para>
- </section>
- </section> <!-- deleting -->
-
- <section xml:id="perf.hdfs"><title>HDFS</title>
- <para>Because HBase runs on <xref linkend="arch.hdfs" /> it is important to understand how it works and how it affects
- HBase.
- </para>
- <section xml:id="perf.hdfs.curr"><title>Current Issues With Low-Latency Reads</title>
- <para>The original use-case for HDFS was batch processing. As such, there low-latency reads were historically not a priority.
- With the increased adoption of Apache HBase this is changing, and several improvements are already in development.
- See the
- <link xlink:href="https://issues.apache.org/jira/browse/HDFS-1599">Umbrella Jira Ticket for HDFS Improvements for HBase</link>.
+ <section
+ xml:id="perf.deleting.queue">
+ <title>Using HBase Tables as Queues</title>
+ <para>HBase tables are sometimes used as queues. In this case, special care must be taken to
+ regularly perform major compactions on tables used in this manner. As is documented in <xref
+ linkend="datamodel" />, marking rows as deleted creates additional StoreFiles which then
+ need to be processed on reads. Tombstones only get cleaned up with major compactions. </para>
+ <para>See also <xref
+ linkend="compaction" /> and <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HBaseAdmin.html#majorCompact%28java.lang.String%29">HBaseAdmin.majorCompact</link>.
</para>
</section>
- <section xml:id="perf.hdfs.configs.localread">
- <title>Leveraging local data</title>
-<para>Since Hadoop 1.0.0 (also 0.22.1, 0.23.1, CDH3u3 and HDP 1.0) via
-<link xlink:href="https://issues.apache.org/jira/browse/HDFS-2246">HDFS-2246</link>,
-it is possible for the DFSClient to take a "short circuit" and
-read directly from the disk instead of going through the DataNode when the
-data is local. What this means for HBase is that the RegionServers can
-read directly off their machine's disks instead of having to open a
-socket to talk to the DataNode, the former being generally much
-faster<footnote><para>See JD's <link xlink:href="http://files.meetup.com/1350427/hug_ebay_jdcryans.pdf">Performance Talk</link></para></footnote>.
-Also see <link xlink:href="http://search-hadoop.com/m/zV6dKrLCVh1">HBase, mail # dev - read short circuit</link> thread for
-more discussion around short circuit reads.
-</para>
-<para>To enable "short circuit" reads, it will depend on your version of Hadoop.
- The original shortcircuit read patch was much improved upon in Hadoop 2 in
- <link xlink:href="https://issues.apache.org/jira/browse/HDFS-347">HDFS-347</link>.
- See <link xlink:href="http://blog.cloudera.com/blog/2013/08/how-improved-short-circuit-local-reads-bring-better-performance-and-security-to-hadoop/"></link> for details
- on the difference between the old and new implementations. See
- <link xlink:href="http://archive.cloudera.com/cdh4/cdh/4/hadoop/hadoop-project-dist/hadoop-hdfs/ShortCircuitLocalReads.html">Hadoop shortcircuit reads configuration page</link>
- for how to enable the latter, better version of shortcircuit.
-For example, here is a minimal config. enabling short-circuit reads added to
-<filename>hbase-site.xml</filename>:
-<programlisting><![CDATA[<property>
+ <section
+ xml:id="perf.deleting.rpc">
+ <title>Delete RPC Behavior</title>
+ <para>Be aware that <code>htable.delete(Delete)</code> doesn't use the writeBuffer. It will
+ execute an RegionServer RPC with each invocation. For a large number of deletes, consider
+ <code>htable.delete(List)</code>. </para>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#delete%28org.apache.hadoop.hbase.client.Delete%29" />
+ </para>
+ </section>
+ </section>
+ <!-- deleting -->
+
+ <section
+ xml:id="perf.hdfs">
+ <title>HDFS</title>
+ <para>Because HBase runs on <xref
+ linkend="arch.hdfs" /> it is important to understand how it works and how it affects HBase. </para>
+ <section
+ xml:id="perf.hdfs.curr">
+ <title>Current Issues With Low-Latency Reads</title>
+ <para>The original use-case for HDFS was batch processing. As such, there low-latency reads
+ were historically not a priority. With the increased adoption of Apache HBase this is
+ changing, and several improvements are already in development. See the <link
+ xlink:href="https://issues.apache.org/jira/browse/HDFS-1599">Umbrella Jira Ticket for HDFS
+ Improvements for HBase</link>. </para>
+ </section>
+ <section
+ xml:id="perf.hdfs.configs.localread">
+ <title>Leveraging local data</title>
+ <para>Since Hadoop 1.0.0 (also 0.22.1, 0.23.1, CDH3u3 and HDP 1.0) via <link
+ xlink:href="https://issues.apache.org/jira/browse/HDFS-2246">HDFS-2246</link>, it is
+ possible for the DFSClient to take a "short circuit" and read directly from the disk instead
+ of going through the DataNode when the data is local. What this means for HBase is that the
+ RegionServers can read directly off their machine's disks instead of having to open a socket
+ to talk to the DataNode, the former being generally much faster<footnote>
+ <para>See JD's <link
+ xlink:href="http://files.meetup.com/1350427/hug_ebay_jdcryans.pdf">Performance
+ Talk</link></para>
+ </footnote>. Also see <link
+ xlink:href="http://search-hadoop.com/m/zV6dKrLCVh1">HBase, mail # dev - read short
+ circuit</link> thread for more discussion around short circuit reads. </para>
+ <para>To enable "short circuit" reads, it will depend on your version of Hadoop. The original
+ shortcircuit read patch was much improved upon in Hadoop 2 in <link
+ xlink:href="https://issues.apache.org/jira/browse/HDFS-347">HDFS-347</link>. See <link
+ xlink:href="http://blog.cloudera.com/blog/2013/08/how-improved-short-circuit-local-reads-bring-better-performance-and-security-to-hadoop/" />
+ for details on the difference between the old and new implementations. See <link
+ xlink:href="http://archive.cloudera.com/cdh4/cdh/4/hadoop/hadoop-project-dist/hadoop-hdfs/ShortCircuitLocalReads.html">Hadoop
+ shortcircuit reads configuration page</link> for how to enable the latter, better version
+ of shortcircuit. For example, here is a minimal config. enabling short-circuit reads added
+ to <filename>hbase-site.xml</filename>: </para>
+ <programlisting><![CDATA[<property>
<name>dfs.client.read.shortcircuit</name>
<value>true</value>
<description>
@@ -705,74 +812,85 @@ For example, here is a minimal config. enabling short-circuit reads added to
TCP port of the DataNode.
</description>
</property>]]></programlisting>
-Be careful about permissions for the directory that hosts the shared domain
-socket; dfsclient will complain if open to other than the hbase user.
-<footnote><para>If you are running on an old Hadoop, one that is without
- <link xlink:href="https://issues.apache.org/jira/browse/HDFS-347">HDFS-347</link> but that
- has
-<link xlink:href="https://issues.apache.org/jira/browse/HDFS-2246">HDFS-2246</link>,
-you must set two configurations.
-First, the hdfs-site.xml needs to be amended. Set
-the property <varname>dfs.block.local-path-access.user</varname>
-to be the <emphasis>only</emphasis> user that can use the shortcut.
-This has to be the user that started HBase. Then in hbase-site.xml,
-set <varname>dfs.client.read.shortcircuit</varname> to be <varname>true</varname>
-</para></footnote>
-</para>
-<para>
-Services -- at least the HBase RegionServers -- will need to be restarted in order to pick up the new
-configurations.
-</para>
-<note xml:id="dfs.client.read.shortcircuit.buffer.size">
- <title>dfs.client.read.shortcircuit.buffer.size</title>
- <para>The default for this value is too high when running on a highly trafficed HBase.
- In HBase, if this value has not been set, we set it down from the default of 1M to 128k
- (Since HBase 0.98.0 and 0.96.1). See <link xlink:href="https://issues.apache.org/jira/browse/HBASE-8143">HBASE-8143 HBase on Hadoop 2 with local short circuit reads (ssr) causes OOM</link>).
- The Hadoop DFSClient in HBase will allocate a direct byte buffer of this size for <emphasis>each</emphasis>
- block it has open; given HBase keeps its HDFS files open all the time, this can add up quickly.</para>
-</note>
- </section>
-
- <section xml:id="perf.hdfs.comp"><title>Performance Comparisons of HBase vs. HDFS</title>
- <para>A fairly common question on the dist-list is why HBase isn't as performant as HDFS files in a batch context (e.g., as
- a MapReduce source or sink). The short answer is that HBase is doing a lot more than HDFS (e.g., reading the KeyValues,
- returning the most current row or specified timestamps, etc.), and as such HBase is 4-5 times slower than HDFS in this
- processing context. There is room for improvement and this gap will, over time, be reduced, but HDFS
- will always be faster in this use-case.
- </para>
+ <para>Be careful about permissions for the directory that hosts the shared domain socket;
+ dfsclient will complain if open to other than the hbase user. <footnote>
+ <para>If you are running on an old Hadoop, one that is without <link
+ xlink:href="https://issues.apache.org/jira/browse/HDFS-347">HDFS-347</link> but that
+ has <link
+ xlink:href="https://issues.apache.org/jira/browse/HDFS-2246">HDFS-2246</link>, you
+ must set two configurations. First, the hdfs-site.xml needs to be amended. Set the
+ property <varname>dfs.block.local-path-access.user</varname> to be the
+ <emphasis>only</emphasis> user that can use the shortcut. This has to be the user that
+ started HBase. Then in hbase-site.xml, set
+ <varname>dfs.client.read.shortcircuit</varname> to be <varname>true</varname>
+ </para>
+ </footnote>
+ </para>
+ <para> Services -- at least the HBase RegionServers -- will need to be restarted in order to
+ pick up the new configurations. </para>
+ <note
+ xml:id="dfs.client.read.shortcircuit.buffer.size">
+ <title>dfs.client.read.shortcircuit.buffer.size</title>
+ <para>The default for this value is too high when running on a highly trafficed HBase. In
+ HBase, if this value has not been set, we set it down from the default of 1M to 128k
+ (Since HBase 0.98.0 and 0.96.1). See <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-8143">HBASE-8143 HBase on Hadoop
+ 2 with local short circuit reads (ssr) causes OOM</link>). The Hadoop DFSClient in HBase
+ will allocate a direct byte buffer of this size for <emphasis>each</emphasis> block it has
+ open; given HBase keeps its HDFS files open all the time, this can add up quickly.</para>
+ </note>
+ </section>
+
+ <section
+ xml:id="perf.hdfs.comp">
+ <title>Performance Comparisons of HBase vs. HDFS</title>
+ <para>A fairly common question on the dist-list is why HBase isn't as performant as HDFS files
+ in a batch context (e.g., as a MapReduce source or sink). The short answer is that HBase is
+ doing a lot more than HDFS (e.g., reading the KeyValues, returning the most current row or
+ specified timestamps, etc.), and as such HBase is 4-5 times slower than HDFS in this
+ processing context. There is room for improvement and this gap will, over time, be reduced,
+ but HDFS will always be faster in this use-case. </para>
</section>
</section>
- <section xml:id="perf.ec2"><title>Amazon EC2</title>
- <para>Performance questions are common on Amazon EC2 environments because it is a shared environment. You will
- not see the same throughput as a dedicated server. In terms of running tests on EC2, run them several times for the same
- reason (i.e., it's a shared environment and you don't know what else is happening on the server).
- </para>
- <para>If you are running on EC2 and post performance questions on the dist-list, please state this fact up-front that
- because EC2 issues are practically a separate class of performance issues.
- </para>
+ <section
+ xml:id="perf.ec2">
+ <title>Amazon EC2</title>
+ <para>Performance questions are common on Amazon EC2 environments because it is a shared
+ environment. You will not see the same throughput as a dedicated server. In terms of running
+ tests on EC2, run them several times for the same reason (i.e., it's a shared environment and
+ you don't know what else is happening on the server). </para>
+ <para>If you are running on EC2 and post performance questions on the dist-list, please state
+ this fact up-front that because EC2 issues are practically a separate class of performance
+ issues. </para>
</section>
- <section xml:id="perf.hbase.mr.cluster"><title>Collocating HBase and MapReduce</title>
- <para>It is often recommended to have different clusters for HBase and MapReduce. A better qualification of this is:
- don't collocate a HBase that serves live requests with a heavy MR workload. OLTP and OLAP-optimized systems have
- conflicting requirements and one will lose to the other, usually the former. For example, short latency-sensitive
- disk reads will have to wait in line behind longer reads that are trying to squeeze out as much throughput as
- possible. MR jobs that write to HBase will also generate flushes and compactions, which will in turn invalidate
- blocks in the <xref linkend="block.cache"/>.
- </para>
- <para>If you need to process the data from your live HBase cluster in MR, you can ship the deltas with <xref linkend="copy.table"/>
- or use replication to get the new data in real time on the OLAP cluster. In the worst case, if you really need to
- collocate both, set MR to use less Map and Reduce slots than you'd normally configure, possibly just one.
- </para>
- <para>When HBase is used for OLAP operations, it's preferable to set it up in a hardened way like configuring the ZooKeeper session
- timeout higher and giving more memory to the MemStores (the argument being that the Block Cache won't be used much
- since the workloads are usually long scans).
- </para>
+ <section
+ xml:id="perf.hbase.mr.cluster">
+ <title>Collocating HBase and MapReduce</title>
+ <para>It is often recommended to have different clusters for HBase and MapReduce. A better
+ qualification of this is: don't collocate a HBase that serves live requests with a heavy MR
+ workload. OLTP and OLAP-optimized systems have conflicting requirements and one will lose to
+ the other, usually the former. For example, short latency-sensitive disk reads will have to
+ wait in line behind longer reads that are trying to squeeze out as much throughput as
+ possible. MR jobs that write to HBase will also generate flushes and compactions, which will
+ in turn invalidate blocks in the <xref
+ linkend="block.cache" />. </para>
+ <para>If you need to process the data from your live HBase cluster in MR, you can ship the
+ deltas with <xref
+ linkend="copy.table" /> or use replication to get the new data in real time on the OLAP
+ cluster. In the worst case, if you really need to collocate both, set MR to use less Map and
+ Reduce slots than you'd normally configure, possibly just one. </para>
+ <para>When HBase is used for OLAP operations, it's preferable to set it up in a hardened way
+ like configuring the ZooKeeper session timeout higher and giving more memory to the MemStores
+ (the argument being that the Block Cache won't be used much since the workloads are usually
+ long scans). </para>
</section>
- <section xml:id="perf.casestudy"><title>Case Studies</title>
- <para>For Performance and Troubleshooting Case Studies, see <xref linkend="casestudies"/>.
- </para>
+ <section
+ xml:id="perf.casestudy">
+ <title>Case Studies</title>
+ <para>For Performance and Troubleshooting Case Studies, see <xref
+ linkend="casestudies" />. </para>
</section>
</chapter>
[04/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/shell.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/shell.xml b/src/main/docbkx/shell.xml
index aaddc8d..deca139 100644
--- a/src/main/docbkx/shell.xml
+++ b/src/main/docbkx/shell.xml
@@ -1,13 +1,15 @@
<?xml version="1.0"?>
- <chapter xml:id="shell"
- version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ xml:id="shell"
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -28,54 +30,46 @@
-->
<title>The Apache HBase Shell</title>
- <para>
- The Apache HBase Shell is <link xlink:href="http://jruby.org">(J)Ruby</link>'s
- IRB with some HBase particular commands added. Anything you can do in
- IRB, you should be able to do in the HBase Shell.</para>
- <para>To run the HBase shell,
- do as follows:
- <programlisting>$ ./bin/hbase shell</programlisting>
- </para>
- <para>Type <command>help</command> and then <command><RETURN></command>
- to see a listing of shell
- commands and options. Browse at least the paragraphs at the end of
- the help emission for the gist of how variables and command
- arguments are entered into the
- HBase shell; in particular note how table names, rows, and
- columns, etc., must be quoted.</para>
- <para>See <xref linkend="shell_exercises" />
- for example basic shell operation.
- </para>
- <para>Here is a nicely formatted listing of <link xlink:href="http://learnhbase.wordpress.com/2013/03/02/hbase-shell-commands/">all shell commands</link> by Rajeshbabu Chintaguntla.
- </para>
-
- <section xml:id="scripting"><title>Scripting</title>
- <para>For examples scripting Apache HBase, look in the
- HBase <filename>bin</filename> directory. Look at the files
- that end in <filename>*.rb</filename>. To run one of these
- files, do as follows:
- <programlisting>$ ./bin/hbase org.jruby.Main PATH_TO_SCRIPT</programlisting>
- </para>
+ <para> The Apache HBase Shell is <link
+ xlink:href="http://jruby.org">(J)Ruby</link>'s IRB with some HBase particular commands
+ added. Anything you can do in IRB, you should be able to do in the HBase Shell.</para>
+ <para>To run the HBase shell, do as follows:</para>
+ <programlisting>$ ./bin/hbase shell</programlisting>
+ <para>Type <command>help</command> and then <command><RETURN></command> to see a listing
+ of shell commands and options. Browse at least the paragraphs at the end of the help
+ emission for the gist of how variables and command arguments are entered into the HBase
+ shell; in particular note how table names, rows, and columns, etc., must be quoted.</para>
+ <para>See <xref
+ linkend="shell_exercises" /> for example basic shell operation. </para>
+ <para>Here is a nicely formatted listing of <link
+ xlink:href="http://learnhbase.wordpress.com/2013/03/02/hbase-shell-commands/">all shell
+ commands</link> by Rajeshbabu Chintaguntla. </para>
+
+ <section
+ xml:id="scripting">
+ <title>Scripting</title>
+ <para>For examples scripting Apache HBase, look in the HBase <filename>bin</filename>
+ directory. Look at the files that end in <filename>*.rb</filename>. To run one of these
+ files, do as follows:</para>
+ <programlisting>$ ./bin/hbase org.jruby.Main PATH_TO_SCRIPT</programlisting>
</section>
- <section xml:id="shell_tricks"><title>Shell Tricks</title>
- <section xml:id="table_variables"><title>Table variables</title>
-
- <para>
- HBase 0.95 adds shell commands that provide a jruby-style
- object-oriented references for tables. Previously all of
- the shell commands that act upon a table have a procedural
- style that always took the name of the table as an
- argument. HBase 0.95 introduces the ability to assign a
- table to a jruby variable. The table reference can be used
- to perform data read write operations such as puts, scans,
- and gets well as admin functionality such as disabling,
- dropping, describing tables.
- </para>
-
- <para>
- For example, previously you would always specify a table name:
- <programlisting>
+ <section
+ xml:id="shell_tricks">
+ <title>Shell Tricks</title>
+ <section
+ xml:id="table_variables">
+ <title>Table variables</title>
+
+ <para> HBase 0.95 adds shell commands that provide a jruby-style object-oriented
+ references for tables. Previously all of the shell commands that act upon a table
+ have a procedural style that always took the name of the table as an argument. HBase
+ 0.95 introduces the ability to assign a table to a jruby variable. The table
+ reference can be used to perform data read write operations such as puts, scans, and
+ gets well as admin functionality such as disabling, dropping, describing tables. </para>
+
+ <para> For example, previously you would always specify a table name:</para>
+ <screen>
hbase(main):000:0> create ‘t’, ‘f’
0 row(s) in 1.0970 seconds
hbase(main):001:0> put 't', 'rold', 'f', 'v'
@@ -101,12 +95,11 @@ hbase(main):005:0> drop 't'
0 row(s) in 23.1670 seconds
hbase(main):006:0>
- </programlisting>
- </para>
-
- <para>
- Now you can assign the table to a variable and use the results in jruby shell code.
- <programlisting>
+ </screen>
+
+ <para> Now you can assign the table to a variable and use the results in jruby shell
+ code.</para>
+ <screen>
hbase(main):007 > t = create 't', 'f'
0 row(s) in 1.0970 seconds
@@ -128,13 +121,11 @@ hbase(main):038:0> t.disable
0 row(s) in 6.2350 seconds
hbase(main):039:0> t.drop
0 row(s) in 0.2340 seconds
- </programlisting>
- </para>
+ </screen>
- <para>
- If the table has already been created, you can assign a
- Table to a variable by using the get_table method:
- <programlisting>
+ <para> If the table has already been created, you can assign a Table to a variable by
+ using the get_table method:</para>
+ <screen>
hbase(main):011 > create 't','f'
0 row(s) in 1.2500 seconds
@@ -150,15 +141,12 @@ ROW COLUMN+CELL
r1 column=f:, timestamp=1378473876949, value=v
1 row(s) in 0.0240 seconds
hbase(main):015:0>
- </programlisting>
- </para>
-
- <para>
- The list functionality has also been extended so that it
- returns a list of table names as strings. You can then use
- jruby to script table operations based on these names. The
- list_snapshots command also acts similarly.
- <programlisting>
+ </screen>
+
+ <para> The list functionality has also been extended so that it returns a list of table
+ names as strings. You can then use jruby to script table operations based on these
+ names. The list_snapshots command also acts similarly.</para>
+ <screen>
hbase(main):016 > tables = list(‘t.*’)
TABLE
t
@@ -170,66 +158,66 @@ hbase(main):017:0> tables.map { |t| disable t ; drop t}
=> [nil]
hbase(main):018:0>
- </programlisting>
- </para>
+ </screen>
</section>
- <section><title><filename>irbrc</filename></title>
- <para>Create an <filename>.irbrc</filename> file for yourself in your home
- directory. Add customizations. A useful one is command history so commands are save
- across Shell invocations:
- <programlisting>
- $ more .irbrc
- require 'irb/ext/save-history'
- IRB.conf[:SAVE_HISTORY] = 100
- IRB.conf[:HISTORY_FILE] = "#{ENV['HOME']}/.irb-save-history"</programlisting>
- See the <application>ruby</application> documentation of <filename>.irbrc</filename>
- to learn about other possible configurations. </para>
- </section>
- <section><title>LOG data to timestamp</title>
- <para>
- To convert the date '08/08/16 20:56:29' from an hbase log into a timestamp, do:
- <programlisting>
- hbase(main):021:0> import java.text.SimpleDateFormat
- hbase(main):022:0> import java.text.ParsePosition
- hbase(main):023:0> SimpleDateFormat.new("yy/MM/dd HH:mm:ss").parse("08/08/16 20:56:29", ParsePosition.new(0)).getTime() => 1218920189000</programlisting>
- </para>
- <para>
- To go the other direction:
- <programlisting>
- hbase(main):021:0> import java.util.Date
- hbase(main):022:0> Date.new(1218920189000).toString() => "Sat Aug 16 20:56:29 UTC 2008"</programlisting>
+ <section>
+ <title><filename>irbrc</filename></title>
+ <para>Create an <filename>.irbrc</filename> file for yourself in your home directory.
+ Add customizations. A useful one is command history so commands are save across
+ Shell invocations:</para>
+ <screen>
+$ more .irbrc
+require 'irb/ext/save-history'
+IRB.conf[:SAVE_HISTORY] = 100
+IRB.conf[:HISTORY_FILE] = "#{ENV['HOME']}/.irb-save-history"</screen>
+ <para>See the <application>ruby</application> documentation of
+ <filename>.irbrc</filename> to learn about other possible configurations.
</para>
- <para>
- To output in a format that is exactly like that of the HBase log format will take a little messing with
- <link xlink:href="http://download.oracle.com/javase/6/docs/api/java/text/SimpleDateFormat.html">SimpleDateFormat</link>.
+ </section>
+ <section>
+ <title>LOG data to timestamp</title>
+ <para> To convert the date '08/08/16 20:56:29' from an hbase log into a timestamp,
+ do:</para>
+ <screen>
+hbase(main):021:0> import java.text.SimpleDateFormat
+hbase(main):022:0> import java.text.ParsePosition
+hbase(main):023:0> SimpleDateFormat.new("yy/MM/dd HH:mm:ss").parse("08/08/16 20:56:29", ParsePosition.new(0)).getTime() => 1218920189000</screen>
+ <para> To go the other direction:</para>
+ <screen>
+hbase(main):021:0> import java.util.Date
+hbase(main):022:0> Date.new(1218920189000).toString() => "Sat Aug 16 20:56:29 UTC 2008"</screen>
+ <para> To output in a format that is exactly like that of the HBase log format will take
+ a little messing with <link
+ xlink:href="http://download.oracle.com/javase/6/docs/api/java/text/SimpleDateFormat.html">SimpleDateFormat</link>.
</para>
</section>
- <section><title>Debug</title>
- <section><title>Shell debug switch</title>
- <para>You can set a debug switch in the shell to see more output
- -- e.g. more of the stack trace on exception --
- when you run a command:
- <programlisting>hbase> debug <RETURN></programlisting>
- </para>
+ <section>
+ <title>Debug</title>
+ <section>
+ <title>Shell debug switch</title>
+ <para>You can set a debug switch in the shell to see more output -- e.g. more of the
+ stack trace on exception -- when you run a command:</para>
+ <programlisting>hbase> debug <RETURN></programlisting>
</section>
- <section><title>DEBUG log level</title>
- <para>To enable DEBUG level logging in the shell,
- launch it with the <command>-d</command> option.
- <programlisting>$ ./bin/hbase shell -d</programlisting>
- </para>
+ <section>
+ <title>DEBUG log level</title>
+ <para>To enable DEBUG level logging in the shell, launch it with the
+ <command>-d</command> option.</para>
+ <programlisting>$ ./bin/hbase shell -d</programlisting>
</section>
- </section>
- <section><title>Commands</title>
- <section><title>count</title>
- <para>Count command returns the number of rows in a table.
- It's quite fast when configured with the right CACHE
- <programlisting>hbase> count '<tablename>', CACHE => 1000</programlisting>
- The above count fetches 1000 rows at a time. Set CACHE lower if your rows are big.
- Default is to fetch one row at a time.
- </para>
+ </section>
+ <section>
+ <title>Commands</title>
+ <section>
+ <title>count</title>
+ <para>Count command returns the number of rows in a table. It's quite fast when
+ configured with the right CACHE
+ <programlisting>hbase> count '<tablename>', CACHE => 1000</programlisting>
+ The above count fetches 1000 rows at a time. Set CACHE lower if your rows are
+ big. Default is to fetch one row at a time. </para>
</section>
- </section>
+ </section>
</section>
- </chapter>
+</chapter>
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/tracing.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/tracing.xml b/src/main/docbkx/tracing.xml
index cdece20..220cc79 100644
--- a/src/main/docbkx/tracing.xml
+++ b/src/main/docbkx/tracing.xml
@@ -1,12 +1,14 @@
<?xml version="1.0" encoding="UTF-8"?>
-<appendix xml:id="tracing"
- version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
+<appendix
+ xml:id="tracing"
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
<!--/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -28,193 +30,158 @@
<title>Enabling Dapper-like Tracing in HBase</title>
<para>
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE-6449">HBASE-6449</link>
- added support for tracing requests through HBase, using the open source tracing library,
- <link xlink:href="http://github.com/cloudera/htrace">HTrace</link>.
- Setting up tracing is quite simple,
- however it currently requires some very minor changes to your client code
- (it would not be very difficult to remove this requirement).
- </para>
+ <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-6449">HBASE-6449</link> added support
+ for tracing requests through HBase, using the open source tracing library, <link
+ xlink:href="http://github.com/cloudera/htrace">HTrace</link>. Setting up tracing is quite
+ simple, however it currently requires some very minor changes to your client code (it would not
+ be very difficult to remove this requirement). </para>
- <section xml:id="tracing.spanreceivers">
+ <section
+ xml:id="tracing.spanreceivers">
<title>SpanReceivers</title>
- <para>
- The tracing system works by collecting information in structs called 'Spans'.
- It is up to you to choose how you want to receive this information
- by implementing the <classname>SpanReceiver</classname> interface,
- which defines one method:
-<programlisting><![CDATA[
- public void receiveSpan(Span span);
+ <para> The tracing system works by collecting information in structs called 'Spans'. It is up to
+ you to choose how you want to receive this information by implementing the
+ <classname>SpanReceiver</classname> interface, which defines one method: </para>
+ <programlisting><![CDATA[
+public void receiveSpan(Span span);
]]></programlisting>
- This method serves as a callback whenever a span is completed.
- HTrace allows you to use as many SpanReceivers as you want
- so you can easily send trace information to multiple destinations.
- </para>
+ <para>This method serves as a callback whenever a span is completed. HTrace allows you to use as
+ many SpanReceivers as you want so you can easily send trace information to multiple
+ destinations. </para>
- <para>
- Configure what SpanReceivers you'd like to us
- by putting a comma separated list of the
- fully-qualified class name of classes implementing
- <classname>SpanReceiver</classname> in <filename>hbase-site.xml</filename>
- property: <varname>hbase.trace.spanreceiver.classes</varname>.
- </para>
+ <para> Configure what SpanReceivers you'd like to us by putting a comma separated list of the
+ fully-qualified class name of classes implementing <classname>SpanReceiver</classname> in
+ <filename>hbase-site.xml</filename> property:
+ <varname>hbase.trace.spanreceiver.classes</varname>. </para>
- <para>
- HTrace includes a <classname>LocalFileSpanReceiver</classname>
- that writes all span information to local files in a JSON-based format.
- The <classname>LocalFileSpanReceiver</classname>
- looks in <filename>hbase-site.xml</filename>
- for a <varname>hbase.local-file-span-receiver.path</varname>
- property with a value describing the name of the file
- to which nodes should write their span information.
-<programlisting><![CDATA[
- <property>
- <name>hbase.trace.spanreceiver.classes</name>
- <value>org.htrace.impl.LocalFileSpanReceiver</value>
- </property>
- <property>
- <name>hbase.local-file-span-receiver.path</name>
- <value>/var/log/hbase/htrace.out</value>
- </property>
+ <para> HTrace includes a <classname>LocalFileSpanReceiver</classname> that writes all span
+ information to local files in a JSON-based format. The
+ <classname>LocalFileSpanReceiver</classname> looks in <filename>hbase-site.xml</filename>
+ for a <varname>hbase.local-file-span-receiver.path</varname> property with a value describing
+ the name of the file to which nodes should write their span information. </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.trace.spanreceiver.classes</name>
+ <value>org.htrace.impl.LocalFileSpanReceiver</value>
+</property>
+<property>
+ <name>hbase.local-file-span-receiver.path</name>
+ <value>/var/log/hbase/htrace.out</value>
+</property>
]]></programlisting>
- </para>
+ <para> HTrace also provides <classname>ZipkinSpanReceiver</classname> which converts spans to <link
+ xlink:href="http://github.com/twitter/zipkin">Zipkin</link> span format and send them to
+ Zipkin server. In order to use this span receiver, you need to install the jar of
+ htrace-zipkin to your HBase's classpath on all of the nodes in your cluster. </para>
<para>
- HTrace also provides <classname>ZipkinSpanReceiver</classname>
- which converts spans to
- <link xlink:href="http://github.com/twitter/zipkin">Zipkin</link>
- span format and send them to Zipkin server.
- In order to use this span receiver,
- you need to install the jar of htrace-zipkin to your HBase's classpath
- on all of the nodes in your cluster.
- </para>
- <para>
- <filename>htrace-zipkin</filename> is published to the maven central repository.
- You could get the latest version from there or just build it locally and then
- copy it out to all nodes, change your config to use zipkin receiver, distribute
- the new configuration and then (rolling) restart.
- </para>
- <para>
- Here is the example of manual setup procedure.
-<programlisting><![CDATA[
- $ git clone https://github.com/cloudera/htrace
- $ cd htrace/htrace-zipkin
- $ mvn compile assembly:single
- $ cp target/htrace-zipkin-*-jar-with-dependencies.jar $HBASE_HOME/lib/
- # copy jar to all nodes...
-]]></programlisting>
- The <classname>ZipkinSpanReceiver</classname>
- looks in <filename>hbase-site.xml</filename>
- for a <varname>hbase.zipkin.collector-hostname</varname>
- and <varname>hbase.zipkin.collector-port</varname>
- property with a value describing the Zipkin collector server
- to which span information are sent.
-<programlisting><![CDATA[
- <property>
- <name>hbase.trace.spanreceiver.classes</name>
- <value>org.htrace.impl.ZipkinSpanReceiver</value>
- </property>
- <property>
- <name>hbase.zipkin.collector-hostname</name>
- <value>localhost</value>
- </property>
- <property>
- <name>hbase.zipkin.collector-port</name>
- <value>9410</value>
- </property>
+ <filename>htrace-zipkin</filename> is published to the maven central repository. You could get
+ the latest version from there or just build it locally and then copy it out to all nodes,
+ change your config to use zipkin receiver, distribute the new configuration and then (rolling)
+ restart. </para>
+ <para> Here is the example of manual setup procedure. </para>
+ <screen><![CDATA[
+$ git clone https://github.com/cloudera/htrace
+$ cd htrace/htrace-zipkin
+$ mvn compile assembly:single
+$ cp target/htrace-zipkin-*-jar-with-dependencies.jar $HBASE_HOME/lib/
+ # copy jar to all nodes...
+]]></screen>
+ <para>The <classname>ZipkinSpanReceiver</classname> looks in <filename>hbase-site.xml</filename>
+ for a <varname>hbase.zipkin.collector-hostname</varname> and
+ <varname>hbase.zipkin.collector-port</varname> property with a value describing the Zipkin
+ collector server to which span information are sent. </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.trace.spanreceiver.classes</name>
+ <value>org.htrace.impl.ZipkinSpanReceiver</value>
+</property>
+<property>
+ <name>hbase.zipkin.collector-hostname</name>
+ <value>localhost</value>
+</property>
+<property>
+ <name>hbase.zipkin.collector-port</name>
+ <value>9410</value>
+</property>
]]></programlisting>
- </para>
- <para>
- If you do not want to use the included span receivers,
- you are encouraged to write your own receiver
- (take a look at <classname>LocalFileSpanReceiver</classname> for an example).
- If you think others would benefit from your receiver,
- file a JIRA or send a pull request to
- <link xlink:href="http://github.com/cloudera/htrace">HTrace</link>.
- </para>
+ <para> If you do not want to use the included span receivers, you are encouraged to write your
+ own receiver (take a look at <classname>LocalFileSpanReceiver</classname> for an example). If
+ you think others would benefit from your receiver, file a JIRA or send a pull request to <link
+ xlink:href="http://github.com/cloudera/htrace">HTrace</link>. </para>
</section>
- <section xml:id="tracing.client.modifications">
+ <section
+ xml:id="tracing.client.modifications">
<title>Client Modifications</title>
- <para>
- In order to turn on tracing in your client code,
- you must initialize the module sending spans to receiver
- once per client process.
-<programlisting><![CDATA[
- private SpanReceiverHost spanReceiverHost;
-
- ...
-
- Configuration conf = HBaseConfiguration.create();
- SpanReceiverHost spanReceiverHost = SpanReceiverHost.getInstance(conf);
+ <para> In order to turn on tracing in your client code, you must initialize the module sending
+ spans to receiver once per client process. </para>
+ <programlisting><![CDATA[
+private SpanReceiverHost spanReceiverHost;
+
+...
+
+ Configuration conf = HBaseConfiguration.create();
+ SpanReceiverHost spanReceiverHost = SpanReceiverHost.getInstance(conf);
+]]></programlisting>
+ <para>Then you simply start tracing span before requests you think are interesting, and close it
+ when the request is done. For example, if you wanted to trace all of your get operations, you
+ change this: </para>
+ <programlisting><![CDATA[
+HTable table = new HTable(conf, "t1");
+Get get = new Get(Bytes.toBytes("r1"));
+Result res = table.get(get);
]]></programlisting>
- Then you simply start tracing span before requests you think are interesting,
- and close it when the request is done.
- For example, if you wanted to trace all of your get operations,
- you change this:
-<programlisting><![CDATA[
+ <para>into: </para>
+ <programlisting><![CDATA[
+TraceScope ts = Trace.startSpan("Gets", Sampler.ALWAYS);
+try {
HTable table = new HTable(conf, "t1");
Get get = new Get(Bytes.toBytes("r1"));
Result res = table.get(get);
+} finally {
+ ts.close();
+}
]]></programlisting>
- into:
-<programlisting><![CDATA[
- TraceScope ts = Trace.startSpan("Gets", Sampler.ALWAYS);
- try {
- HTable table = new HTable(conf, "t1");
- Get get = new Get(Bytes.toBytes("r1"));
- Result res = table.get(get);
- } finally {
- ts.close();
- }
+ <para>If you wanted to trace half of your 'get' operations, you would pass in: </para>
+ <programlisting><![CDATA[
+new ProbabilitySampler(0.5)
]]></programlisting>
- If you wanted to trace half of your 'get' operations, you would pass in:
-<programlisting><![CDATA[
- new ProbabilitySampler(0.5)
-]]></programlisting>
- in lieu of <varname>Sampler.ALWAYS</varname>
- to <classname>Trace.startSpan()</classname>.
- See the HTrace <filename>README</filename> for more information on Samplers.
- </para>
+ <para>in lieu of <varname>Sampler.ALWAYS</varname> to <classname>Trace.startSpan()</classname>.
+ See the HTrace <filename>README</filename> for more information on Samplers. </para>
</section>
- <section xml:id="tracing.client.shell">
+ <section
+ xml:id="tracing.client.shell">
<title>Tracing from HBase Shell</title>
- <para>
- You can use <command>trace</command> command
- for tracing requests from HBase Shell.
- <command>trace 'start'</command> command turns on tracing and
- <command>trace 'stop'</command> command turns off tracing.
-<programlisting><![CDATA[
- hbase(main):001:0> trace 'start'
- hbase(main):002:0> put 'test', 'row1', 'f:', 'val1' # traced commands
- hbase(main):003:0> trace 'stop'
+ <para> You can use <command>trace</command> command for tracing requests from HBase Shell.
+ <command>trace 'start'</command> command turns on tracing and <command>trace
+ 'stop'</command> command turns off tracing. </para>
+ <programlisting><![CDATA[
+hbase(main):001:0> trace 'start'
+hbase(main):002:0> put 'test', 'row1', 'f:', 'val1' # traced commands
+hbase(main):003:0> trace 'stop'
]]></programlisting>
- </para>
<para>
- <command>trace 'start'</command> and
- <command>trace 'stop'</command> always
- returns boolean value representing
- if or not there is ongoing tracing.
- As a result, <command>trace 'stop'</command>
- returns false on suceess.
- <command>trace 'status'</command>
- just returns if or not tracing is turned on.
-<programlisting><![CDATA[
- hbase(main):001:0> trace 'start'
- => true
-
- hbase(main):002:0> trace 'status'
- => true
-
- hbase(main):003:0> trace 'stop'
- => false
-
- hbase(main):004:0> trace 'status'
- => false
+ <command>trace 'start'</command> and <command>trace 'stop'</command> always returns boolean
+ value representing if or not there is ongoing tracing. As a result, <command>trace
+ 'stop'</command> returns false on suceess. <command>trace 'status'</command> just returns if
+ or not tracing is turned on. </para>
+ <programlisting><![CDATA[
+hbase(main):001:0> trace 'start'
+=> true
+
+hbase(main):002:0> trace 'status'
+=> true
+
+hbase(main):003:0> trace 'stop'
+=> false
+
+hbase(main):004:0> trace 'status'
+=> false
]]></programlisting>
- </para>
</section>
</appendix>
[06/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/schema_design.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/schema_design.xml b/src/main/docbkx/schema_design.xml
index a79f175..2fdeb00 100644
--- a/src/main/docbkx/schema_design.xml
+++ b/src/main/docbkx/schema_design.xml
@@ -1,13 +1,15 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="schema"
- xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ version="5.0"
+ xml:id="schema"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
*
* Licensed to the Apache Software Foundation (ASF) under one
@@ -28,21 +30,21 @@
*/
-->
<title>HBase and Schema Design</title>
- <para>A good general introduction on the strength and weaknesses modelling on
- the various non-rdbms datastores is Ian Varley's Master thesis,
- <link xlink:href="http://ianvarley.com/UT/MR/Varley_MastersReport_Full_2009-08-07.pdf">No Relation: The Mixed Blessings of Non-Relational Databases</link>.
- Recommended. Also, read <xref linkend="keyvalue"/> for how HBase stores data internally, and the section on
- <xref linkend="schema.casestudies"/>.
- </para>
- <section xml:id="schema.creation">
- <title>
- Schema Creation
- </title>
- <para>HBase schemas can be created or updated with <xref linkend="shell" />
- or by using <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HBaseAdmin.html">HBaseAdmin</link> in the Java API.
- </para>
- <para>Tables must be disabled when making ColumnFamily modifications, for example:</para>
- <programlisting>
+ <para>A good general introduction on the strength and weaknesses modelling on the various
+ non-rdbms datastores is Ian Varley's Master thesis, <link
+ xlink:href="http://ianvarley.com/UT/MR/Varley_MastersReport_Full_2009-08-07.pdf">No Relation:
+ The Mixed Blessings of Non-Relational Databases</link>. Recommended. Also, read <xref
+ linkend="keyvalue" /> for how HBase stores data internally, and the section on <xref
+ linkend="schema.casestudies" />. </para>
+ <section
+ xml:id="schema.creation">
+ <title> Schema Creation </title>
+ <para>HBase schemas can be created or updated with <xref
+ linkend="shell" /> or by using <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HBaseAdmin.html">HBaseAdmin</link>
+ in the Java API. </para>
+ <para>Tables must be disabled when making ColumnFamily modifications, for example:</para>
+ <programlisting>
Configuration config = HBaseConfiguration.create();
HBaseAdmin admin = new HBaseAdmin(conf);
String table = "myTable";
@@ -55,110 +57,134 @@ HColumnDescriptor cf2 = ...;
admin.modifyColumn(table, cf2); // modifying existing ColumnFamily
admin.enableTable(table);
- </programlisting>
- <para>See <xref linkend="client_dependencies"/> for more information about configuring client connections.</para>
- <para>Note: online schema changes are supported in the 0.92.x codebase, but the 0.90.x codebase requires the table
- to be disabled.
- </para>
- <section xml:id="schema.updates"><title>Schema Updates</title>
- <para>When changes are made to either Tables or ColumnFamilies (e.g., region size, block size), these changes
- take effect the next time there is a major compaction and the StoreFiles get re-written.
- </para>
- <para>See <xref linkend="store"/> for more information on StoreFiles.
- </para>
+ </programlisting>
+ <para>See <xref
+ linkend="client_dependencies" /> for more information about configuring client
+ connections.</para>
+ <para>Note: online schema changes are supported in the 0.92.x codebase, but the 0.90.x codebase
+ requires the table to be disabled. </para>
+ <section
+ xml:id="schema.updates">
+ <title>Schema Updates</title>
+ <para>When changes are made to either Tables or ColumnFamilies (e.g., region size, block
+ size), these changes take effect the next time there is a major compaction and the
+ StoreFiles get re-written. </para>
+ <para>See <xref
+ linkend="store" /> for more information on StoreFiles. </para>
</section>
</section>
- <section xml:id="number.of.cfs">
- <title>
- On the number of column families
- </title>
- <para>
- HBase currently does not do well with anything above two or three column families so keep the number
- of column families in your schema low. Currently, flushing and compactions are done on a per Region basis so
- if one column family is carrying the bulk of the data bringing on flushes, the adjacent families
- will also be flushed though the amount of data they carry is small. When many column families the
- flushing and compaction interaction can make for a bunch of needless i/o loading (To be addressed by
- changing flushing and compaction to work on a per column family basis). For more information
- on compactions, see <xref linkend="compaction"/>.
- </para>
- <para>Try to make do with one column family if you can in your schemas. Only introduce a
- second and third column family in the case where data access is usually column scoped;
- i.e. you query one column family or the other but usually not both at the one time.
- </para>
- <section xml:id="number.of.cfs.card"><title>Cardinality of ColumnFamilies</title>
- <para>Where multiple ColumnFamilies exist in a single table, be aware of the cardinality (i.e., number of rows).
- If ColumnFamilyA has 1 million rows and ColumnFamilyB has 1 billion rows, ColumnFamilyA's data will likely be spread
- across many, many regions (and RegionServers). This makes mass scans for ColumnFamilyA less efficient.
- </para>
+ <section
+ xml:id="number.of.cfs">
+ <title> On the number of column families </title>
+ <para> HBase currently does not do well with anything above two or three column families so keep
+ the number of column families in your schema low. Currently, flushing and compactions are done
+ on a per Region basis so if one column family is carrying the bulk of the data bringing on
+ flushes, the adjacent families will also be flushed though the amount of data they carry is
+ small. When many column families the flushing and compaction interaction can make for a bunch
+ of needless i/o loading (To be addressed by changing flushing and compaction to work on a per
+ column family basis). For more information on compactions, see <xref
+ linkend="compaction" />. </para>
+ <para>Try to make do with one column family if you can in your schemas. Only introduce a second
+ and third column family in the case where data access is usually column scoped; i.e. you query
+ one column family or the other but usually not both at the one time. </para>
+ <section
+ xml:id="number.of.cfs.card">
+ <title>Cardinality of ColumnFamilies</title>
+ <para>Where multiple ColumnFamilies exist in a single table, be aware of the cardinality
+ (i.e., number of rows). If ColumnFamilyA has 1 million rows and ColumnFamilyB has 1 billion
+ rows, ColumnFamilyA's data will likely be spread across many, many regions (and
+ RegionServers). This makes mass scans for ColumnFamilyA less efficient. </para>
</section>
</section>
- <section xml:id="rowkey.design"><title>Rowkey Design</title>
- <section xml:id="timeseries">
- <title>
- Monotonically Increasing Row Keys/Timeseries Data
- </title>
- <para>
- In the HBase chapter of Tom White's book <link xlink:href="http://oreilly.com/catalog/9780596521981">Hadoop: The Definitive Guide</link> (O'Reilly) there is a an optimization note on watching out for a phenomenon where an import process walks in lock-step with all clients in concert pounding one of the table's regions (and thus, a single node), then moving onto the next region, etc. With monotonically increasing row-keys (i.e., using a timestamp), this will happen. See this comic by IKai Lan on why monotonically increasing row keys are problematic in BigTable-like datastores:
- <link xlink:href="http://ikaisays.com/2011/01/25/app-engine-datastore-tip-monotonically-increasing-values-are-bad/">monotonically increasing values are bad</link>. The pile-up on a single region brought on
- by monotonically increasing keys can be mitigated by randomizing the input records to not be in sorted order, but in general it's best to avoid using a timestamp or a sequence (e.g. 1, 2, 3) as the row-key.
- </para>
- <para>If you do need to upload time series data into HBase, you should
- study <link xlink:href="http://opentsdb.net/">OpenTSDB</link> as a
- successful example. It has a page describing the <link xlink:href=" http://opentsdb.net/schema.html">schema</link> it uses in
- HBase. The key format in OpenTSDB is effectively [metric_type][event_timestamp], which would appear at first glance to contradict the previous advice about not using a timestamp as the key. However, the difference is that the timestamp is not in the <emphasis>lead</emphasis> position of the key, and the design assumption is that there are dozens or hundreds (or more) of different metric types. Thus, even with a continual stream of input data with a mix of metric types, the Puts are distributed across various points of regions in the table.
- </para>
- <para>See <xref linkend="schema.casestudies"/> for some rowkey design examples.
- </para>
- </section>
- <section xml:id="keysize">
+ <section
+ xml:id="rowkey.design">
+ <title>Rowkey Design</title>
+ <section
+ xml:id="timeseries">
+ <title> Monotonically Increasing Row Keys/Timeseries Data </title>
+ <para> In the HBase chapter of Tom White's book <link
+ xlink:href="http://oreilly.com/catalog/9780596521981">Hadoop: The Definitive Guide</link>
+ (O'Reilly) there is a an optimization note on watching out for a phenomenon where an import
+ process walks in lock-step with all clients in concert pounding one of the table's regions
+ (and thus, a single node), then moving onto the next region, etc. With monotonically
+ increasing row-keys (i.e., using a timestamp), this will happen. See this comic by IKai Lan
+ on why monotonically increasing row keys are problematic in BigTable-like datastores: <link
+ xlink:href="http://ikaisays.com/2011/01/25/app-engine-datastore-tip-monotonically-increasing-values-are-bad/">monotonically
+ increasing values are bad</link>. The pile-up on a single region brought on by
+ monotonically increasing keys can be mitigated by randomizing the input records to not be in
+ sorted order, but in general it's best to avoid using a timestamp or a sequence (e.g. 1, 2,
+ 3) as the row-key. </para>
+ <para>If you do need to upload time series data into HBase, you should study <link
+ xlink:href="http://opentsdb.net/">OpenTSDB</link> as a successful example. It has a page
+ describing the <link
+ xlink:href=" http://opentsdb.net/schema.html">schema</link> it uses in HBase. The key
+ format in OpenTSDB is effectively [metric_type][event_timestamp], which would appear at
+ first glance to contradict the previous advice about not using a timestamp as the key.
+ However, the difference is that the timestamp is not in the <emphasis>lead</emphasis>
+ position of the key, and the design assumption is that there are dozens or hundreds (or
+ more) of different metric types. Thus, even with a continual stream of input data with a mix
+ of metric types, the Puts are distributed across various points of regions in the table. </para>
+ <para>See <xref
+ linkend="schema.casestudies" /> for some rowkey design examples. </para>
+ </section>
+ <section
+ xml:id="keysize">
<title>Try to minimize row and column sizes</title>
<subtitle>Or why are my StoreFile indices large?</subtitle>
- <para>In HBase, values are always freighted with their coordinates; as a
- cell value passes through the system, it'll be accompanied by its
- row, column name, and timestamp - always. If your rows and column names
- are large, especially compared to the size of the cell value, then
- you may run up against some interesting scenarios. One such is
- the case described by Marc Limotte at the tail of
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE-3551?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13005272#comment-13005272">HBASE-3551</link>
- (recommended!).
- Therein, the indices that are kept on HBase storefiles (<xref linkend="hfile" />)
- to facilitate random access may end up occupyng large chunks of the HBase
- allotted RAM because the cell value coordinates are large.
- Mark in the above cited comment suggests upping the block size so
- entries in the store file index happen at a larger interval or
- modify the table schema so it makes for smaller rows and column
- names.
- Compression will also make for larger indices. See
- the thread <link xlink:href="http://search-hadoop.com/m/hemBv1LiN4Q1/a+question+storefileIndexSize&subj=a+question+storefileIndexSize">a question storefileIndexSize</link>
- up on the user mailing list.
- </para>
- <para>Most of the time small inefficiencies don't matter all that much. Unfortunately,
- this is a case where they do. Whatever patterns are selected for ColumnFamilies, attributes, and rowkeys they could be repeated
- several billion times in your data. </para>
- <para>See <xref linkend="keyvalue"/> for more information on HBase stores data internally to see why this is important.</para>
- <section xml:id="keysize.cf"><title>Column Families</title>
- <para>Try to keep the ColumnFamily names as small as possible, preferably one character (e.g. "d" for data/default).
- </para>
- <para>See <xref linkend="keyvalue"/> for more information on HBase stores data internally to see why this is important.</para>
- </section>
- <section xml:id="keysize.attributes"><title>Attributes</title>
- <para>Although verbose attribute names (e.g., "myVeryImportantAttribute") are easier to read, prefer shorter attribute names (e.g., "via")
- to store in HBase.
- </para>
- <para>See <xref linkend="keyvalue"/> for more information on HBase stores data internally to see why this is important.</para>
- </section>
- <section xml:id="keysize.row"><title>Rowkey Length</title>
- <para>Keep them as short as is reasonable such that they can still be useful for required data access (e.g., Get vs. Scan).
- A short key that is useless for data access is not better than a longer key with better get/scan properties. Expect tradeoffs
- when designing rowkeys.
- </para>
- </section>
- <section xml:id="keysize.patterns"><title>Byte Patterns</title>
- <para>A long is 8 bytes. You can store an unsigned number up to 18,446,744,073,709,551,615 in those eight bytes.
- If you stored this number as a String -- presuming a byte per character -- you need nearly 3x the bytes.
- </para>
- <para>Not convinced? Below is some sample code that you can run on your own.
-<programlisting>
+ <para>In HBase, values are always freighted with their coordinates; as a cell value passes
+ through the system, it'll be accompanied by its row, column name, and timestamp - always. If
+ your rows and column names are large, especially compared to the size of the cell value,
+ then you may run up against some interesting scenarios. One such is the case described by
+ Marc Limotte at the tail of <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-3551?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13005272#comment-13005272">HBASE-3551</link>
+ (recommended!). Therein, the indices that are kept on HBase storefiles (<xref
+ linkend="hfile" />) to facilitate random access may end up occupyng large chunks of the
+ HBase allotted RAM because the cell value coordinates are large. Mark in the above cited
+ comment suggests upping the block size so entries in the store file index happen at a larger
+ interval or modify the table schema so it makes for smaller rows and column names.
+ Compression will also make for larger indices. See the thread <link
+ xlink:href="http://search-hadoop.com/m/hemBv1LiN4Q1/a+question+storefileIndexSize&subj=a+question+storefileIndexSize">a
+ question storefileIndexSize</link> up on the user mailing list. </para>
+ <para>Most of the time small inefficiencies don't matter all that much. Unfortunately, this is
+ a case where they do. Whatever patterns are selected for ColumnFamilies, attributes, and
+ rowkeys they could be repeated several billion times in your data. </para>
+ <para>See <xref
+ linkend="keyvalue" /> for more information on HBase stores data internally to see why this
+ is important.</para>
+ <section
+ xml:id="keysize.cf">
+ <title>Column Families</title>
+ <para>Try to keep the ColumnFamily names as small as possible, preferably one character
+ (e.g. "d" for data/default). </para>
+ <para>See <xref
+ linkend="keyvalue" /> for more information on HBase stores data internally to see why
+ this is important.</para>
+ </section>
+ <section
+ xml:id="keysize.attributes">
+ <title>Attributes</title>
+ <para>Although verbose attribute names (e.g., "myVeryImportantAttribute") are easier to
+ read, prefer shorter attribute names (e.g., "via") to store in HBase. </para>
+ <para>See <xref
+ linkend="keyvalue" /> for more information on HBase stores data internally to see why
+ this is important.</para>
+ </section>
+ <section
+ xml:id="keysize.row">
+ <title>Rowkey Length</title>
+ <para>Keep them as short as is reasonable such that they can still be useful for required
+ data access (e.g., Get vs. Scan). A short key that is useless for data access is not
+ better than a longer key with better get/scan properties. Expect tradeoffs when designing
+ rowkeys. </para>
+ </section>
+ <section
+ xml:id="keysize.patterns">
+ <title>Byte Patterns</title>
+ <para>A long is 8 bytes. You can store an unsigned number up to 18,446,744,073,709,551,615
+ in those eight bytes. If you stored this number as a String -- presuming a byte per
+ character -- you need nearly 3x the bytes. </para>
+ <para>Not convinced? Below is some sample code that you can run on your own.</para>
+ <programlisting>
// long
//
long l = 1234567890L;
@@ -178,11 +204,11 @@ System.out.println("md5 digest bytes length: " + digest.length); // returns 1
String sDigest = new String(digest);
byte[] sbDigest = Bytes.toBytes(sDigest);
System.out.println("md5 digest as string length: " + sbDigest.length); // returns 26
-</programlisting>
- </para>
- <para>Unfortunately, using a binary representation of a type will make your data harder to read outside of your code. For example,
- this is what you will see in the shell when you increment a value:
-<programlisting>
+ </programlisting>
+ <para>Unfortunately, using a binary representation of a type will make your data harder to
+ read outside of your code. For example, this is what you will see in the shell when you
+ increment a value:</para>
+ <programlisting>
hbase(main):001:0> incr 't', 'r', 'f:q', 1
COUNTER VALUE = 1
@@ -190,53 +216,67 @@ hbase(main):002:0> get 't', 'r'
COLUMN CELL
f:q timestamp=1369163040570, value=\x00\x00\x00\x00\x00\x00\x00\x01
1 row(s) in 0.0310 seconds
-</programlisting>
- The shell makes a best effort to print a string, and it this case it decided to just print the hex. The same will
- happen to your row keys inside the region names. It can be okay if you know what's being stored, but it might also
- be unreadable if arbitrary data can be put in the same cells. This is the main trade-off.
- </para>
- </section>
+ </programlisting>
+ <para>The shell makes a best effort to print a string, and it this case it decided to just
+ print the hex. The same will happen to your row keys inside the region names. It can be
+ okay if you know what's being stored, but it might also be unreadable if arbitrary data
+ can be put in the same cells. This is the main trade-off. </para>
+ </section>
</section>
- <section xml:id="reverse.timestamp"><title>Reverse Timestamps</title>
- <note>
- <title>Reverse Scan API</title>
- <para>
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE-4811">HBASE-4811</link> implements an API to scan a table or a range within a table in reverse, reducing the need to optimize your schema for forward or reverse scanning. This feature is available in HBase 0.98 and later. See <link xlink:href="https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html#setReversed%28boolean" /> for more information.
- </para>
- </note>
+ <section
+ xml:id="reverse.timestamp">
+ <title>Reverse Timestamps</title>
+ <note>
+ <title>Reverse Scan API</title>
+ <para>
+ <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-4811">HBASE-4811</link>
+ implements an API to scan a table or a range within a table in reverse, reducing the need
+ to optimize your schema for forward or reverse scanning. This feature is available in
+ HBase 0.98 and later. See <link
+ xlink:href="https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html#setReversed%28boolean" />
+ for more information. </para>
+ </note>
- <para>A common problem in database processing is quickly finding the most recent version of a value. A technique using reverse timestamps
- as a part of the key can help greatly with a special case of this problem. Also found in the HBase chapter of Tom White's book Hadoop: The Definitive Guide (O'Reilly),
- the technique involves appending (<code>Long.MAX_VALUE - timestamp</code>) to the end of any key, e.g., [key][reverse_timestamp].
- </para>
- <para>The most recent value for [key] in a table can be found by performing a Scan for [key] and obtaining the first record. Since HBase keys
- are in sorted order, this key sorts before any older row-keys for [key] and thus is first.
- </para>
- <para>This technique would be used instead of using <xref linkend="schema.versions"/> where the intent is to hold onto all versions
- "forever" (or a very long time) and at the same time quickly obtain access to any other version by using the same Scan technique.
- </para>
+ <para>A common problem in database processing is quickly finding the most recent version of a
+ value. A technique using reverse timestamps as a part of the key can help greatly with a
+ special case of this problem. Also found in the HBase chapter of Tom White's book Hadoop:
+ The Definitive Guide (O'Reilly), the technique involves appending (<code>Long.MAX_VALUE -
+ timestamp</code>) to the end of any key, e.g., [key][reverse_timestamp]. </para>
+ <para>The most recent value for [key] in a table can be found by performing a Scan for [key]
+ and obtaining the first record. Since HBase keys are in sorted order, this key sorts before
+ any older row-keys for [key] and thus is first. </para>
+ <para>This technique would be used instead of using <xref
+ linkend="schema.versions" /> where the intent is to hold onto all versions "forever" (or a
+ very long time) and at the same time quickly obtain access to any other version by using the
+ same Scan technique. </para>
</section>
- <section xml:id="rowkey.scope">
- <title>Rowkeys and ColumnFamilies</title>
- <para>Rowkeys are scoped to ColumnFamilies. Thus, the same rowkey could exist in each ColumnFamily that exists in a table without collision.
- </para>
+ <section
+ xml:id="rowkey.scope">
+ <title>Rowkeys and ColumnFamilies</title>
+ <para>Rowkeys are scoped to ColumnFamilies. Thus, the same rowkey could exist in each
+ ColumnFamily that exists in a table without collision. </para>
</section>
- <section xml:id="changing.rowkeys"><title>Immutability of Rowkeys</title>
- <para>Rowkeys cannot be changed. The only way they can be "changed" in a table is if the row is deleted and then re-inserted.
- This is a fairly common question on the HBase dist-list so it pays to get the rowkeys right the first time (and/or before you've
- inserted a lot of data).
- </para>
+ <section
+ xml:id="changing.rowkeys">
+ <title>Immutability of Rowkeys</title>
+ <para>Rowkeys cannot be changed. The only way they can be "changed" in a table is if the row
+ is deleted and then re-inserted. This is a fairly common question on the HBase dist-list so
+ it pays to get the rowkeys right the first time (and/or before you've inserted a lot of
+ data). </para>
</section>
- <section xml:id="rowkey.regionsplits"><title>Relationship Between RowKeys and Region Splits</title>
- <para>If you pre-split your table, it is <emphasis>critical</emphasis> to understand how your rowkey will be distributed across
- the region boundaries. As an example of why this is important, consider the example of using displayable hex characters as the
- lead position of the key (e.g., "0000000000000000" to "ffffffffffffffff"). Running those key ranges through <code>Bytes.split</code>
- (which is the split strategy used when creating regions in <code>HBaseAdmin.createTable(byte[] startKey, byte[] endKey, numRegions)</code>
- for 10 regions will generate the following splits...
- </para>
- <para>
- <programlisting>
+ <section
+ xml:id="rowkey.regionsplits">
+ <title>Relationship Between RowKeys and Region Splits</title>
+ <para>If you pre-split your table, it is <emphasis>critical</emphasis> to understand how your
+ rowkey will be distributed across the region boundaries. As an example of why this is
+ important, consider the example of using displayable hex characters as the lead position of
+ the key (e.g., "0000000000000000" to "ffffffffffffffff"). Running those
+ key ranges through <code>Bytes.split</code> (which is the split strategy used when creating
+ regions in <code>HBaseAdmin.createTable(byte[] startKey, byte[] endKey, numRegions)</code>
+ for 10 regions will generate the following splits... </para>
+ <screen>
48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 48 // 0
54 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 -10 // 6
61 -67 -67 -67 -67 -67 -67 -67 -67 -67 -67 -67 -67 -67 -67 -68 // =
@@ -246,27 +286,28 @@ COLUMN CELL
88 -40 -40 -40 -40 -40 -40 -40 -40 -40 -40 -40 -40 -40 -40 -44 // X
95 -97 -97 -97 -97 -97 -97 -97 -97 -97 -97 -97 -97 -97 -97 -102 // _
102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 102 // f
- </programlisting>
- ... (note: the lead byte is listed to the right as a comment.) Given that the first split is a '0' and the last split is an 'f',
- everything is great, right? Not so fast.
- </para>
- <para>The problem is that all the data is going to pile up in the first 2 regions and the last region thus creating a "lumpy" (and
- possibly "hot") region problem. To understand why, refer to an <link xlink:href="http://www.asciitable.com">ASCII Table</link>.
- '0' is byte 48, and 'f' is byte 102, but there is a huge gap in byte values (bytes 58 to 96) that will <emphasis>never appear in this
- keyspace</emphasis> because the only values are [0-9] and [a-f]. Thus, the middle regions regions will
- never be used. To make pre-spliting work with this example keyspace, a custom definition of splits (i.e., and not relying on the
- built-in split method) is required.
- </para>
- <para>Lesson #1: Pre-splitting tables is generally a best practice, but you need to pre-split them in such a way that all the
- regions are accessible in the keyspace. While this example demonstrated the problem with a hex-key keyspace, the same problem can happen
- with <emphasis>any</emphasis> keyspace. Know your data.
- </para>
- <para>Lesson #2: While generally not advisable, using hex-keys (and more generally, displayable data) can still work with pre-split
- tables as long as all the created regions are accessible in the keyspace.
- </para>
- <para>To conclude this example, the following is an example of how appropriate splits can be pre-created for hex-keys:.
- </para>
-<programlisting>public static boolean createTable(HBaseAdmin admin, HTableDescriptor table, byte[][] splits)
+ </screen>
+ <para>... (note: the lead byte is listed to the right as a comment.) Given that the first
+ split is a '0' and the last split is an 'f', everything is great, right? Not so fast. </para>
+ <para>The problem is that all the data is going to pile up in the first 2 regions and the last
+ region thus creating a "lumpy" (and possibly "hot") region problem. To understand why, refer
+ to an <link
+ xlink:href="http://www.asciitable.com">ASCII Table</link>. '0' is byte 48, and 'f' is byte
+ 102, but there is a huge gap in byte values (bytes 58 to 96) that will <emphasis>never
+ appear in this keyspace</emphasis> because the only values are [0-9] and [a-f]. Thus, the
+ middle regions regions will never be used. To make pre-spliting work with this example
+ keyspace, a custom definition of splits (i.e., and not relying on the built-in split method)
+ is required. </para>
+ <para>Lesson #1: Pre-splitting tables is generally a best practice, but you need to pre-split
+ them in such a way that all the regions are accessible in the keyspace. While this example
+ demonstrated the problem with a hex-key keyspace, the same problem can happen with
+ <emphasis>any</emphasis> keyspace. Know your data. </para>
+ <para>Lesson #2: While generally not advisable, using hex-keys (and more generally,
+ displayable data) can still work with pre-split tables as long as all the created regions
+ are accessible in the keyspace. </para>
+ <para>To conclude this example, the following is an example of how appropriate splits can be
+ pre-created for hex-keys:. </para>
+ <programlisting><![CDATA[public static boolean createTable(HBaseAdmin admin, HTableDescriptor table, byte[][] splits)
throws IOException {
try {
admin.createTable( table, splits );
@@ -285,655 +326,807 @@ public static byte[][] getHexSplits(String startKey, String endKey, int numRegio
BigInteger range = highestKey.subtract(lowestKey);
BigInteger regionIncrement = range.divide(BigInteger.valueOf(numRegions));
lowestKey = lowestKey.add(regionIncrement);
- for(int i=0; i < numRegions-1;i++) {
+ for(int i=0; i < numRegions-1;i++) {
BigInteger key = lowestKey.add(regionIncrement.multiply(BigInteger.valueOf(i)));
byte[] b = String.format("%016x", key).getBytes();
splits[i] = b;
}
return splits;
-}</programlisting>
+}]]></programlisting>
</section>
- </section> <!-- rowkey design -->
- <section xml:id="schema.versions">
- <title>
- Number of Versions
- </title>
- <section xml:id="schema.versions.max"><title>Maximum Number of Versions</title>
- <para>The maximum number of row versions to store is configured per column
- family via <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>.
- The default for max versions is 1.
- This is an important parameter because as described in <xref linkend="datamodel" />
- section HBase does <emphasis>not</emphasis> overwrite row values, but rather
- stores different values per row by time (and qualifier). Excess versions are removed during major
- compactions. The number of max versions may need to be increased or decreased depending on application needs.
- </para>
- <para>It is not recommended setting the number of max versions to an exceedingly high level (e.g., hundreds or more) unless those old values are
- very dear to you because this will greatly increase StoreFile size.
- </para>
- </section>
- <section xml:id="schema.minversions">
- <title>
- Minimum Number of Versions
- </title>
- <para>Like maximum number of row versions, the minimum number of row versions to keep is configured per column
- family via <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>.
- The default for min versions is 0, which means the feature is disabled.
- The minimum number of row versions parameter is used together with the time-to-live parameter and can be combined with the
- number of row versions parameter to allow configurations such as
- "keep the last T minutes worth of data, at most N versions, <emphasis>but keep at least M versions around</emphasis>"
- (where M is the value for minimum number of row versions, M<N).
- This parameter should only be set when time-to-live is enabled for a column family and must be less than the
- number of row versions.
- </para>
+ </section>
+ <!-- rowkey design -->
+ <section
+ xml:id="schema.versions">
+ <title> Number of Versions </title>
+ <section
+ xml:id="schema.versions.max">
+ <title>Maximum Number of Versions</title>
+ <para>The maximum number of row versions to store is configured per column family via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>.
+ The default for max versions is 1. This is an important parameter because as described in <xref
+ linkend="datamodel" /> section HBase does <emphasis>not</emphasis> overwrite row values,
+ but rather stores different values per row by time (and qualifier). Excess versions are
+ removed during major compactions. The number of max versions may need to be increased or
+ decreased depending on application needs. </para>
+ <para>It is not recommended setting the number of max versions to an exceedingly high level
+ (e.g., hundreds or more) unless those old values are very dear to you because this will
+ greatly increase StoreFile size. </para>
+ </section>
+ <section
+ xml:id="schema.minversions">
+ <title> Minimum Number of Versions </title>
+ <para>Like maximum number of row versions, the minimum number of row versions to keep is
+ configured per column family via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>.
+ The default for min versions is 0, which means the feature is disabled. The minimum number
+ of row versions parameter is used together with the time-to-live parameter and can be
+ combined with the number of row versions parameter to allow configurations such as "keep the
+ last T minutes worth of data, at most N versions, <emphasis>but keep at least M versions
+ around</emphasis>" (where M is the value for minimum number of row versions, M<N). This
+ parameter should only be set when time-to-live is enabled for a column family and must be
+ less than the number of row versions. </para>
</section>
</section>
- <section xml:id="supported.datatypes">
- <title>
- Supported Datatypes
- </title>
- <para>HBase supports a "bytes-in/bytes-out" interface via <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Put.html">Put</link> and
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Result.html">Result</link>, so anything that can be
- converted to an array of bytes can be stored as a value. Input could be strings, numbers, complex objects, or even images as long as they can rendered as bytes.
- </para>
- <para>There are practical limits to the size of values (e.g., storing 10-50MB objects in HBase would probably be too much to ask);
- search the mailling list for conversations on this topic. All rows in HBase conform to the <xref linkend="datamodel"/>, and
- that includes versioning. Take that into consideration when making your design, as well as block size for the ColumnFamily.
- </para>
+ <section
+ xml:id="supported.datatypes">
+ <title> Supported Datatypes </title>
+ <para>HBase supports a "bytes-in/bytes-out" interface via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Put.html">Put</link>
+ and <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Result.html">Result</link>,
+ so anything that can be converted to an array of bytes can be stored as a value. Input could
+ be strings, numbers, complex objects, or even images as long as they can rendered as bytes. </para>
+ <para>There are practical limits to the size of values (e.g., storing 10-50MB objects in HBase
+ would probably be too much to ask); search the mailling list for conversations on this topic.
+ All rows in HBase conform to the <xref
+ linkend="datamodel" />, and that includes versioning. Take that into consideration when
+ making your design, as well as block size for the ColumnFamily. </para>
- <section xml:id="counters">
+ <section
+ xml:id="counters">
<title>Counters</title>
- <para>
- One supported datatype that deserves special mention are "counters" (i.e., the ability to do atomic increments of numbers). See
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#increment%28org.apache.hadoop.hbase.client.Increment%29">Increment</link> in HTable.
- </para>
- <para>Synchronization on counters are done on the RegionServer, not in the client.
- </para>
+ <para> One supported datatype that deserves special mention are "counters" (i.e., the ability
+ to do atomic increments of numbers). See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#increment%28org.apache.hadoop.hbase.client.Increment%29">Increment</link>
+ in HTable. </para>
+ <para>Synchronization on counters are done on the RegionServer, not in the client. </para>
</section>
</section>
- <section xml:id="schema.joins"><title>Joins</title>
- <para>If you have multiple tables, don't forget to factor in the potential for <xref linkend="joins"/> into the schema design.
- </para>
+ <section
+ xml:id="schema.joins">
+ <title>Joins</title>
+ <para>If you have multiple tables, don't forget to factor in the potential for <xref
+ linkend="joins" /> into the schema design. </para>
</section>
- <section xml:id="ttl">
- <title>Time To Live (TTL)</title>
- <para>ColumnFamilies can set a TTL length in seconds, and HBase will automatically delete rows once the expiration time is reached.
- This applies to <emphasis>all</emphasis> versions of a row - even the current one. The TTL time encoded in the HBase for the row is specified in UTC.
- </para>
- <para>See <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link> for more information.
- </para>
+ <section
+ xml:id="ttl">
+ <title>Time To Live (TTL)</title>
+ <para>ColumnFamilies can set a TTL length in seconds, and HBase will automatically delete rows
+ once the expiration time is reached. This applies to <emphasis>all</emphasis> versions of a
+ row - even the current one. The TTL time encoded in the HBase for the row is specified in UTC. </para>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>
+ for more information. </para>
</section>
- <section xml:id="cf.keep.deleted">
- <title>
- Keeping Deleted Cells
- </title>
- <para>ColumnFamilies can optionally keep deleted cells. That means deleted cells can still be retrieved with
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html">Get</link> or
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link> operations,
- as long these operations have a time range specified that ends before the timestamp of any delete that would affect the cells.
- This allows for point in time queries even in the presence of deletes.
- </para>
- <para>
- Deleted cells are still subject to TTL and there will never be more than "maximum number of versions" deleted cells.
- A new "raw" scan options returns all deleted rows and the delete markers.
- </para>
- <para>See <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link> for more information.
- </para>
+ <section
+ xml:id="cf.keep.deleted">
+ <title> Keeping Deleted Cells </title>
+ <para>ColumnFamilies can optionally keep deleted cells. That means deleted cells can still be
+ retrieved with <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html">Get</link>
+ or <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link>
+ operations, as long these operations have a time range specified that ends before the
+ timestamp of any delete that would affect the cells. This allows for point in time queries
+ even in the presence of deletes. </para>
+ <para> Deleted cells are still subject to TTL and there will never be more than "maximum number
+ of versions" deleted cells. A new "raw" scan options returns all deleted rows and the delete
+ markers. </para>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/HColumnDescriptor.html">HColumnDescriptor</link>
+ for more information. </para>
</section>
- <section xml:id="secondary.indexes">
- <title>
- Secondary Indexes and Alternate Query Paths
- </title>
- <para>This section could also be titled "what if my table rowkey looks like <emphasis>this</emphasis> but I also want to query my table like <emphasis>that</emphasis>."
- A common example on the dist-list is where a row-key is of the format "user-timestamp" but there are reporting requirements on activity across users for certain
- time ranges. Thus, selecting by user is easy because it is in the lead position of the key, but time is not.
- </para>
- <para>There is no single answer on the best way to handle this because it depends on...
- <itemizedlist>
- <listitem><para>Number of users</para></listitem>
- <listitem><para>Data size and data arrival rate</para></listitem>
- <listitem><para>Flexibility of reporting requirements (e.g., completely ad-hoc date selection vs. pre-configured ranges) </para></listitem>
- <listitem><para>Desired execution speed of query (e.g., 90 seconds may be reasonable to some for an ad-hoc report, whereas it may be too long for others) </para></listitem>
- </itemizedlist>
- ... and solutions are also influenced by the size of the cluster and how much processing power you have to throw at the solution.
- Common techniques are in sub-sections below. This is a comprehensive, but not exhaustive, list of approaches.
- </para>
- <para>It should not be a surprise that secondary indexes require additional cluster space and
+ <section
+ xml:id="secondary.indexes">
+ <title> Secondary Indexes and Alternate Query Paths </title>
+ <para>This section could also be titled "what if my table rowkey looks like
+ <emphasis>this</emphasis> but I also want to query my table like <emphasis>that</emphasis>."
+ A common example on the dist-list is where a row-key is of the format "user-timestamp" but
+ there are reporting requirements on activity across users for certain time ranges. Thus,
+ selecting by user is easy because it is in the lead position of the key, but time is not. </para>
+ <para>There is no single answer on the best way to handle this because it depends on... </para>
+ <itemizedlist>
+ <listitem>
+ <para>Number of users</para>
+ </listitem>
+ <listitem>
+ <para>Data size and data arrival rate</para>
+ </listitem>
+ <listitem>
+ <para>Flexibility of reporting requirements (e.g., completely ad-hoc date selection vs.
+ pre-configured ranges) </para>
+ </listitem>
+ <listitem>
+ <para>Desired execution speed of query (e.g., 90 seconds may be reasonable to some for an
+ ad-hoc report, whereas it may be too long for others) </para>
+ </listitem>
+ </itemizedlist>
+ <para>... and solutions are also influenced by the size of the cluster and how much processing
+ power you have to throw at the solution. Common techniques are in sub-sections below. This is
+ a comprehensive, but not exhaustive, list of approaches. </para>
+ <para>It should not be a surprise that secondary indexes require additional cluster space and
processing. This is precisely what happens in an RDBMS because the act of creating an
alternate index requires both space and processing cycles to update. RDBMS products are more
advanced in this regard to handle alternative index management out of the box. However, HBase
scales better at larger data volumes, so this is a feature trade-off. </para>
- <para>Pay attention to <xref linkend="performance"/> when implementing any of these approaches.</para>
- <para>Additionally, see the David Butler response in this dist-list thread <link xlink:href="http://search-hadoop.com/m/nvbiBp2TDP/Stargate%252Bhbase&subj=Stargate+hbase">HBase, mail # user - Stargate+hbase</link>
- </para>
- <section xml:id="secondary.indexes.filter">
- <title>
- Filter Query
- </title>
- <para>Depending on the case, it may be appropriate to use <xref linkend="client.filter"/>. In this case, no secondary index is created.
- However, don't try a full-scan on a large table like this from an application (i.e., single-threaded client).
- </para>
+ <para>Pay attention to <xref
+ linkend="performance" /> when implementing any of these approaches.</para>
+ <para>Additionally, see the David Butler response in this dist-list thread <link
+ xlink:href="http://search-hadoop.com/m/nvbiBp2TDP/Stargate%252Bhbase&subj=Stargate+hbase">HBase,
+ mail # user - Stargate+hbase</link>
+ </para>
+ <section
+ xml:id="secondary.indexes.filter">
+ <title> Filter Query </title>
+ <para>Depending on the case, it may be appropriate to use <xref
+ linkend="client.filter" />. In this case, no secondary index is created. However, don't
+ try a full-scan on a large table like this from an application (i.e., single-threaded
+ client). </para>
</section>
- <section xml:id="secondary.indexes.periodic">
- <title>
- Periodic-Update Secondary Index
- </title>
- <para>A secondary index could be created in an other table which is periodically updated via a MapReduce job. The job could be executed intra-day, but depending on
- load-strategy it could still potentially be out of sync with the main data table.</para>
- <para>See <xref linkend="mapreduce.example.readwrite"/> for more information.</para>
+ <section
+ xml:id="secondary.indexes.periodic">
+ <title> Periodic-Update Secondary Index </title>
+ <para>A secondary index could be created in an other table which is periodically updated via a
+ MapReduce job. The job could be executed intra-day, but depending on load-strategy it could
+ still potentially be out of sync with the main data table.</para>
+ <para>See <xref
+ linkend="mapreduce.example.readwrite" /> for more information.</para>
</section>
- <section xml:id="secondary.indexes.dualwrite">
- <title>
- Dual-Write Secondary Index
- </title>
- <para>Another strategy is to build the secondary index while publishing data to the cluster (e.g., write to data table, write to index table).
- If this is approach is taken after a data table already exists, then bootstrapping will be needed for the secondary index with a MapReduce job (see <xref linkend="secondary.indexes.periodic"/>).</para>
+ <section
+ xml:id="secondary.indexes.dualwrite">
+ <title> Dual-Write Secondary Index </title>
+ <para>Another strategy is to build the secondary index while publishing data to the cluster
+ (e.g., write to data table, write to index table). If this is approach is taken after a data
+ table already exists, then bootstrapping will be needed for the secondary index with a
+ MapReduce job (see <xref
+ linkend="secondary.indexes.periodic" />).</para>
</section>
- <section xml:id="secondary.indexes.summary">
- <title>
- Summary Tables
- </title>
- <para>Where time-ranges are very wide (e.g., year-long report) and where the data is voluminous, summary tables are a common approach.
- These would be generated with MapReduce jobs into another table.</para>
- <para>See <xref linkend="mapreduce.example.summary"/> for more information.</para>
+ <section
+ xml:id="secondary.indexes.summary">
+ <title> Summary Tables </title>
+ <para>Where time-ranges are very wide (e.g., year-long report) and where the data is
+ voluminous, summary tables are a common approach. These would be generated with MapReduce
+ jobs into another table.</para>
+ <para>See <xref
+ linkend="mapreduce.example.summary" /> for more information.</para>
</section>
- <section xml:id="secondary.indexes.coproc">
- <title>
- Coprocessor Secondary Index
- </title>
- <para>Coprocessors act like RDBMS triggers. These were added in 0.92. For more information, see <xref linkend="coprocessors"/>
+ <section
+ xml:id="secondary.indexes.coproc">
+ <title> Coprocessor Secondary Index </title>
+ <para>Coprocessors act like RDBMS triggers. These were added in 0.92. For more information,
+ see <xref
+ linkend="coprocessors" />
</para>
</section>
</section>
- <section xml:id="constraints"><title>Constraints</title>
- <para>HBase currently supports 'constraints' in traditional (SQL) database parlance. The advised usage for Constraints is in enforcing business rules for attributes in the table (eg. make sure values are in the range 1-10).
- Constraints could also be used to enforce referential integrity, but this is strongly discouraged as it will dramatically decrease the write throughput of the tables where integrity checking is enabled.
- Extensive documentation on using Constraints can be found at: <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/constraint">Constraint</link> since version 0.94.
- </para>
+ <section
+ xml:id="constraints">
+ <title>Constraints</title>
+ <para>HBase currently supports 'constraints' in traditional (SQL) database parlance. The advised
+ usage for Constraints is in enforcing business rules for attributes in the table (eg. make
+ sure values are in the range 1-10). Constraints could also be used to enforce referential
+ integrity, but this is strongly discouraged as it will dramatically decrease the write
+ throughput of the tables where integrity checking is enabled. Extensive documentation on using
+ Constraints can be found at: <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/constraint">Constraint</link>
+ since version 0.94. </para>
</section>
- <section xml:id="schema.casestudies"><title>Schema Design Case Studies</title>
- <para>The following will describe some typical data ingestion use-cases with HBase, and how the rowkey design and construction
- can be approached. Note: this is just an illustration of potential approaches, not an exhaustive list.
- Know your data, and know your processing requirements.
- </para>
- <para>It is highly recommended that you read the rest of the <xref linkend="schema"/> first, before reading
- these case studies.
- </para>
- <para>Thee following case studies are described:
- <itemizedlist>
- <listitem><para>Log Data / Timeseries Data</para></listitem>
- <listitem><para>Log Data / Timeseries on Steroids</para></listitem>
- <listitem><para>Customer/Order</para></listitem>
- <listitem><para>Tall/Wide/Middle Schema Design</para></listitem>
- <listitem><para>List Data</para></listitem>
- </itemizedlist>
- </para>
- <section xml:id="schema.casestudies.log-timeseries">
+ <section
+ xml:id="schema.casestudies">
+ <title>Schema Design Case Studies</title>
+ <para>The following will describe some typical data ingestion use-cases with HBase, and how the
+ rowkey design and construction can be approached. Note: this is just an illustration of
+ potential approaches, not an exhaustive list. Know your data, and know your processing
+ requirements. </para>
+ <para>It is highly recommended that you read the rest of the <xref
+ linkend="schema" /> first, before reading these case studies. </para>
+ <para>The following case studies are described: </para>
+ <itemizedlist>
+ <listitem>
+ <para>Log Data / Timeseries Data</para>
+ </listitem>
+ <listitem>
+ <para>Log Data / Timeseries on Steroids</para>
+ </listitem>
+ <listitem>
+ <para>Customer/Order</para>
+ </listitem>
+ <listitem>
+ <para>Tall/Wide/Middle Schema Design</para>
+ </listitem>
+ <listitem>
+ <para>List Data</para>
+ </listitem>
+ </itemizedlist>
+ <section
+ xml:id="schema.casestudies.log-timeseries">
<title>Case Study - Log Data and Timeseries Data</title>
- <para>Assume that the following data elements are being collected.
- <itemizedlist>
- <listitem><para>Hostname</para></listitem>
- <listitem><para>Timestamp</para></listitem>
- <listitem><para>Log event</para></listitem>
- <listitem><para>Value/message</para></listitem>
- </itemizedlist>
- We can store them in an HBase table called LOG_DATA, but what will the rowkey be?
- From these attributes the rowkey will be some combination of hostname, timestamp, and log-event - but what specifically?
- </para>
- <section xml:id="schema.casestudies.log-timeseries.tslead">
+ <para>Assume that the following data elements are being collected. </para>
+ <itemizedlist>
+ <listitem>
+ <para>Hostname</para>
+ </listitem>
+ <listitem>
+ <para>Timestamp</para>
+ </listitem>
+ <listitem>
+ <para>Log event</para>
+ </listitem>
+ <listitem>
+ <para>Value/message</para>
+ </listitem>
+ </itemizedlist>
+ <para>We can store them in an HBase table called LOG_DATA, but what will the rowkey be? From
+ these attributes the rowkey will be some combination of hostname, timestamp, and log-event -
+ but what specifically? </para>
+ <section
+ xml:id="schema.casestudies.log-timeseries.tslead">
<title>Timestamp In The Rowkey Lead Position</title>
- <para>The rowkey <code>[timestamp][hostname][log-event]</code> suffers from the monotonically increasing rowkey problem
- described in <xref linkend="timeseries"/>.
- </para>
- <para>There is another pattern frequently mentioned in the dist-lists about “bucketing” timestamps, by performing a mod operation
- on the timestamp. If time-oriented scans are important, this could be a useful approach. Attention must be paid to the number
- of buckets, because this will require the same number of scans to return results.
-<programlisting>
+ <para>The rowkey <code>[timestamp][hostname][log-event]</code> suffers from the
+ monotonically increasing rowkey problem described in <xref
+ linkend="timeseries" />. </para>
+ <para>There is another pattern frequently mentioned in the dist-lists about “bucketing”
+ timestamps, by performing a mod operation on the timestamp. If time-oriented scans are
+ important, this could be a useful approach. Attention must be paid to the number of
+ buckets, because this will require the same number of scans to return results.</para>
+ <programlisting>
long bucket = timestamp % numBuckets;
-</programlisting>
- … to construct:
-<programlisting>
+ </programlisting>
+ <para>… to construct:</para>
+ <programlisting>
[bucket][timestamp][hostname][log-event]
-</programlisting>
- As stated above, to select data for a particular timerange, a Scan will need to be performed for each bucket. 100 buckets,
- for example, will provide a wide distribution in the keyspace but it will require 100 Scans to obtain data for a single
- timestamp, so there are trade-offs.
- </para>
- </section> <!-- ts lead -->
- <section xml:id="schema.casestudies.log-timeseries.hostlead">
+ </programlisting>
+ <para>As stated above, to select data for a particular timerange, a Scan will need to be
+ performed for each bucket. 100 buckets, for example, will provide a wide distribution in
+ the keyspace but it will require 100 Scans to obtain data for a single timestamp, so there
+ are trade-offs. </para>
+ </section>
+ <!-- ts lead -->
+ <section
+ xml:id="schema.casestudies.log-timeseries.hostlead">
<title>Host In The Rowkey Lead Position</title>
- <para>The rowkey <code>[hostname][log-event][timestamp]</code> is a candidate if there is a large-ish number of hosts to spread
- the writes and reads across the keyspace. This approach would be useful if scanning by hostname was a priority.
- </para>
- </section> <!-- host lead -->
- <section xml:id="schema.casestudies.log-timeseries.revts">
+ <para>The rowkey <code>[hostname][log-event][timestamp]</code> is a candidate if there is a
+ large-ish number of hosts to spread the writes and reads across the keyspace. This
+ approach would be useful if scanning by hostname was a priority. </para>
+ </section>
+ <!-- host lead -->
+ <section
+ xml:id="schema.casestudies.log-timeseries.revts">
<title>Timestamp, or Reverse Timestamp?</title>
- <para>If the most important access path is to pull most recent events, then storing the timestamps as reverse-timestamps
- (e.g., <code>timestamp = Long.MAX_VALUE – timestamp</code>) will create the property of being able to do a Scan on
- <code>[hostname][log-event]</code> to obtain the quickly obtain the most recently captured events.
- </para>
- <para>Neither approach is wrong, it just depends on what is most appropriate for the situation.
- </para>
- <note>
- <title>Reverse Scan API</title>
- <para>
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE-4811">HBASE-4811</link> implements an API to scan a table or a range within a table in reverse, reducing the need to optimize your schema for forward or reverse scanning. This feature is available in HBase 0.98 and later. See <link xlink:href="https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html#setReversed%28boolean" /> for more information.
- </para>
- </note>
- </section> <!-- revts -->
- <section xml:id="schema.casestudies.log-timeseries.varkeys">
+ <para>If the most important access path is to pull most recent events, then storing the
+ timestamps as reverse-timestamps (e.g., <code>timestamp = Long.MAX_VALUE –
+ timestamp</code>) will create the property of being able to do a Scan on
+ <code>[hostname][log-event]</code> to obtain the quickly obtain the most recently
+ captured events. </para>
+ <para>Neither approach is wrong, it just depends on what is most appropriate for the
+ situation. </para>
+ <note>
+ <title>Reverse Scan API</title>
+ <para>
+ <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-4811">HBASE-4811</link>
+ implements an API to scan a table or a range within a table in reverse, reducing the
+ need to optimize your schema for forward or reverse scanning. This feature is available
+ in HBase 0.98 and later. See <link
+ xlink:href="https://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html#setReversed%28boolean" />
+ for more information. </para>
+ </note>
+ </section>
+ <!-- revts -->
+ <section
+ xml:id="schema.casestudies.log-timeseries.varkeys">
<title>Variangle Length or Fixed Length Rowkeys?</title>
- <para>It is critical to remember that rowkeys are stamped on every column in HBase. If the hostname is “a” and the event type
- is “e1” then the resulting rowkey would be quite small. However, what if the ingested hostname is
- “myserver1.mycompany.com” and the event type is “com.package1.subpackage2.subsubpackage3.ImportantService”?
- </para>
- <para>It might make sense to use some substitution in the rowkey. There are at least two approaches: hashed and numeric.
- In the Hostname In The Rowkey Lead Position example, it might look like this:
- </para>
- <para>Composite Rowkey With Hashes:
- <itemizedlist>
- <listitem><para>[MD5 hash of hostname] = 16 bytes</para></listitem>
- <listitem><para>[MD5 hash of event-type] = 16 bytes</para></listitem>
- <listitem><para>[timestamp] = 8 bytes</para></listitem>
- </itemizedlist>
- </para>
- <para>Composite Rowkey With Numeric Substitution:
- </para>
- <para>For this approach another lookup table would be needed in addition to LOG_DATA, called LOG_TYPES.
- The rowkey of LOG_TYPES would be:
- <itemizedlist>
- <listitem><para>[type] (e.g., byte indicating hostname vs. event-type)</para></listitem>
- <listitem><para>[bytes] variable length bytes for raw hostname or event-type.</para></listitem>
- </itemizedlist>
- A column for this rowkey could be a long with an assigned number, which could be obtained by using an
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#incrementColumnValue%28byte[],%20byte[],%20byte[],%20long%29">HBase counter</link>.
- </para>
- <para>So the resulting composite rowkey would be:
- <itemizedlist>
- <listitem><para>[substituted long for hostname] = 8 bytes</para></listitem>
- <listitem><para>[substituted long for event type] = 8 bytes</para></listitem>
- <listitem><para>[timestamp] = 8 bytes</para></listitem>
- </itemizedlist>
- In either the Hash or Numeric substitution approach, the raw values for hostname and event-type can be stored as columns.
- </para>
- </section> <!-- varkeys -->
- </section> <!-- log data and timeseries -->
- <section xml:id="schema.casestudies.log-steroids">
+ <para>It is critical to remember that rowkeys are stamped on every column in HBase. If the
+ hostname is “a” and the event type is “e1” then the resulting rowkey would be quite small.
+ However, what if the ingested hostname is “myserver1.mycompany.com” and the event type is
+ “com.package1.subpackage2.subsubpackage3.ImportantService”? </para>
+ <para>It might make sense to use some substitution in the rowkey. There are at least two
+ approaches: hashed and numeric. In the Hostname In The Rowkey Lead Position example, it
+ might look like this: </para>
+ <para>Composite Rowkey With Hashes:</para>
+ <itemizedlist>
+ <listitem>
+ <para>[MD5 hash of hostname] = 16 bytes</para>
+ </listitem>
+ <listitem>
+ <para>[MD5 hash of event-type] = 16 bytes</para>
+ </listitem>
+ <listitem>
+ <para>[timestamp] = 8 bytes</para>
+ </listitem>
+ </itemizedlist>
+ <para>Composite Rowkey With Numeric Substitution: </para>
+ <para>For this approach another lookup table would be needed in addition to LOG_DATA, called
+ LOG_TYPES. The rowkey of LOG_TYPES would be: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[type] (e.g., byte indicating hostname vs. event-type)</para>
+ </listitem>
+ <listitem>
+ <para>[bytes] variable length bytes for raw hostname or event-type.</para>
+ </listitem>
+ </itemizedlist>
+ <para>A column for this rowkey could be a long with an assigned number, which could be
+ obtained by using an <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#incrementColumnValue%28byte[],%20byte[],%20byte[],%20long%29">HBase
+ counter</link>. </para>
+ <para>So the resulting composite rowkey would be: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[substituted long for hostname] = 8 bytes</para>
+ </listitem>
+ <listitem>
+ <para>[substituted long for event type] = 8 bytes</para>
+ </listitem>
+ <listitem>
+ <para>[timestamp] = 8 bytes</para>
+ </listitem>
+ </itemizedlist>
+ <para>In either the Hash or Numeric substitution approach, the raw values for hostname and
+ event-type can be stored as columns. </para>
+ </section>
+ <!-- varkeys -->
+ </section>
+ <!-- log data and timeseries -->
+ <section
+ xml:id="schema.casestudies.log-steroids">
<title>Case Study - Log Data and Timeseries Data on Steroids</title>
- <para>This effectively is the OpenTSDB approach. What OpenTSDB does is re-write data and pack rows into columns for
- certain time-periods. For a detailed explanation, see: <link xlink:href="http://opentsdb.net/schema.html">http://opentsdb.net/schema.html</link>,
- and <link xlink:href="http://www.cloudera.com/content/cloudera/en/resources/library/hbasecon/video-hbasecon-2012-lessons-learned-from-opentsdb.html">Lessons Learned from OpenTSDB</link>
- from HBaseCon2012.
- </para>
- <para>But this is how the general concept works: data is ingested, for example, in this manner…
-<programlisting>
+ <para>This effectively is the OpenTSDB approach. What OpenTSDB does is re-write data and pack
+ rows into columns for certain time-periods. For a detailed explanation, see: <link
+ xlink:href="http://opentsdb.net/schema.html">http://opentsdb.net/schema.html</link>, and <link
+ xlink:href="http://www.cloudera.com/content/cloudera/en/resources/library/hbasecon/video-hbasecon-2012-lessons-learned-from-opentsdb.html">Lessons
+ Learned from OpenTSDB</link> from HBaseCon2012. </para>
+ <para>But this is how the general concept works: data is ingested, for example, in this
+ manner…</para>
+ <screen>
[hostname][log-event][timestamp1]
[hostname][log-event][timestamp2]
[hostname][log-event][timestamp3]
-</programlisting>
- … with separate rowkeys for each detailed event, but is re-written like this…
- </para>
- <para><code>[hostname][log-event][timerange]</code>
- </para>
- <para>… and each of the above events are converted into columns stored with a time-offset relative to the beginning timerange
- (e.g., every 5 minutes). This is obviously a very advanced processing technique, but HBase makes this possible.
- </para>
- </section> <!-- log data timeseries steroids -->
-
- <section xml:id="schema.casestudies.custorder">
+ </screen>
+ <para>… with separate rowkeys for each detailed event, but is re-written like this… </para>
+ <screen>[hostname][log-event][timerange]</screen>
+ <para>… and each of the above events are converted into columns stored with a time-offset
+ relative to the beginning timerange (e.g., every 5 minutes). This is obviously a very
+ advanced processing technique, but HBase makes this possible. </para>
+ </section>
+ <!-- log data timeseries steroids -->
+
+ <section
+ xml:id="schema.casestudies.custorder">
<title>Case Study - Customer/Order</title>
- <para>Assume that HBase is used to store customer and order information. There are two core record-types being ingested:
- a Customer record type, and Order record type.
- </para>
- <para>The Customer record type would include all the things that you’d typically expect:
- <itemizedlist>
- <listitem><para>Customer number</para></listitem>
- <listitem><para>Customer name</para></listitem>
- <listitem><para>Address (e.g., city, state, zip)</para></listitem>
- <listitem><para>Phone numbers, etc.</para></listitem>
- </itemizedlist>
- </para>
- <para>The Order record type would include things like:
- <itemizedlist>
- <listitem><para>Customer number</para></listitem>
- <listitem><para>Order number</para></listitem>
- <listitem><para>Sales date</para></listitem>
- <listitem><para>A series of nested objects for shipping locations and line-items (see <xref linkend="schema.casestudies.custorder.obj"/>
- for details)</para></listitem>
- </itemizedlist>
- </para>
- <para>Assuming that the combination of customer number and sales order uniquely identify an order, these two attributes will compose
- the rowkey, and specifically a composite key such as:
- </para>
- <para><code>[customer number][order number]</code>
- </para>
- <para>… for a ORDER table. However, there are more design decisions to make: are the <emphasis>raw</emphasis> values the best choices for rowkeys?
- </para>
- <para>The same design questions in the Log Data use-case confront us here. What is the keyspace of the customer number, and what is the
-format (e.g., numeric? alphanumeric?) As it is advantageous to use fixed-length keys in HBase, as well as keys that can support a
-reasonable spread in the keyspace, similar options appear:
- </para>
- <para>Composite Rowkey With Hashes:
+ <para>Assume that HBase is used to store customer and order information. There are two core
+ record-types being ingested: a Customer record type, and Order record type. </para>
+ <para>The Customer record type would include all the things that you’d typically expect: </para>
<itemizedlist>
- <listitem><para>[MD5 of customer number] = 16 bytes</para></listitem>
- <listitem><para>[MD5 of order number] = 16 bytes</para></listitem>
+ <listitem>
+ <para>Customer number</para>
+ </listitem>
+ <listitem>
+ <para>Customer name</para>
+ </listitem>
+ <listitem>
+ <para>Address (e.g., city, state, zip)</para>
+ </listitem>
+ <listitem>
+ <para>Phone numbers, etc.</para>
+ </listitem>
</itemizedlist>
- </para>
- <para>Composite Numeric/Hash Combo Rowkey:
+ <para>The Order record type would include things like: </para>
+ <itemizedlist>
+ <listitem>
+ <para>Customer number</para>
+ </listitem>
+ <listitem>
+ <para>Order number</para>
+ </listitem>
+ <listitem>
+ <para>Sales date</para>
+ </listitem>
+ <listitem>
+ <para>A series of nested objects for shipping locations and line-items (see <xref
+ linkend="schema.casestudies.custorder.obj" /> for details)</para>
+ </listitem>
+ </itemizedlist>
+ <para>Assuming that the combination of customer number and sales order uniquely identify an
+ order, these two attributes will compose the rowkey, and specifically a composite key such
+ as: </para>
+ <screen>[customer number][order number]</screen>
+ <para>… for a ORDER table. However, there are more design decisions to make: are the
+ <emphasis>raw</emphasis> values the best choices for rowkeys? </para>
+ <para>The same design questions in the Log Data use-case confront us here. What is the
+ keyspace of the customer number, and what is the format (e.g., numeric? alphanumeric?) As it
+ is advantageous to use fixed-length keys in HBase, as well as keys that can support a
+ reasonable spread in the keyspace, similar options appear: </para>
+ <para>Composite Rowkey With Hashes: </para>
<itemizedlist>
- <listitem><para>[substituted long for customer number] = 8 bytes</para></listitem>
- <listitem><para>[MD5 of order number] = 16 bytes</para></listitem>
+ <listitem>
+ <para>[MD5 of customer number] = 16 bytes</para>
+ </listitem>
+ <listitem>
+ <para>[MD5 of order number] = 16 bytes</para>
+ </listitem>
</itemizedlist>
- </para>
- <section xml:id="schema.casestudies.custorder.tables">
- <title>Single Table? Multiple Tables?</title>
- <para>A traditional design approach would have separate tables for CUSTOMER and SALES. Another option is to pack multiple
- record types into a single table (e.g., CUSTOMER++).
- </para>
- <para>Customer Record Type Rowkey:
- <itemizedlist>
- <listitem><para>[customer-id]</para></listitem>
- <listitem><para>[type] = type indicating ‘1’ for customer record type</para></listitem>
- </itemizedlist>
- </para>
- <para>Order Record Type Rowkey:
- <itemizedlist>
- <listitem><para>[customer-id]</para></listitem>
- <listitem><para>[type] = type indicating ‘2’ for order record type</para></listitem>
- <listitem><para>[order]</para></listitem>
- </itemizedlist>
- </para>
- <para>The advantage of this particular CUSTOMER++ approach is that organizes many different record-types by customer-id
- (e.g., a single scan could get you everything about that customer). The disadvantage is that it’s not as easy to scan for
- a particular record-type.
- </para>
+ <para>Composite Numeric/Hash Combo Rowkey: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[substituted long for customer number] = 8 bytes</para>
+ </listitem>
+ <listitem>
+ <para>[MD5 of order number] = 16 bytes</para>
+ </listitem>
+ </itemizedlist>
+ <section
+ xml:id="schema.casestudies.custorder.tables">
+ <title>Single Table? Multiple Tables?</title>
+ <para>A traditional design approach would have separate tables for CUSTOMER and SALES.
+ Another option is to pack multiple record types into a single table (e.g., CUSTOMER++). </para>
+ <para>Customer Record Type Rowkey: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[customer-id]</para>
+ </listitem>
+ <listitem>
+ <para>[type] = type indicating ‘1’ for customer record type</para>
+ </listitem>
+ </itemizedlist>
+ <para>Order Record Type Rowkey: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[customer-id]</para>
+ </listitem>
+ <listitem>
+ <para>[type] = type indicating ‘2’ for order record type</para>
+ </listitem>
+ <listitem>
+ <para>[order]</para>
+ </listitem>
+ </itemizedlist>
+ <para>The advantage of this particular CUSTOMER++ approach is that organizes many different
+ record-types by customer-id (e.g., a single scan could get you everything about that
+ customer). The disadvantage is that it’s not as easy to scan for a particular record-type.
+ </para>
+ </section>
+ <section
+ xml:id="schema.casestudies.custorder.obj">
+ <title>Order Object Design</title>
+ <para>Now we need to address how to model the Order object. Assume that the class structure
+ is as follows:</para>
+ <variablelist>
+ <varlistentry>
+ <term>Order</term>
+ <listitem>
+ <para>(an Order can have multiple ShippingLocations</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>LineItem</term>
+ <listitem>
+ <para>(a ShippingLocation can have multiple LineItems</para>
+ </listitem>
+ </varlistentry>
+ </variablelist>
+ <para>... there are multiple options on storing this data. </para>
+ <section
+ xml:id="schema.casestudies.custorder.obj.norm">
+ <title>Completely Normalized</title>
+ <para>With this approach, there would be separate tables for ORDER, SHIPPING_LOCATION, and
+ LINE_ITEM. </para>
+ <para>The ORDER table's rowkey was described above: <xref
+ linkend="schema.casestudies.custorder" />
+ </para>
+ <para>The SHIPPING_LOCATION's composite rowkey would be something like this: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[order-rowkey]</para>
+ </listitem>
+ <listitem>
+ <para>[shipping location number] (e.g., 1st location, 2nd, etc.)</para>
+ </listitem>
+ </itemizedlist>
+ <para>The LINE_ITEM table's composite rowkey would be something like this: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[order-rowkey]</para>
+ </listitem>
+ <listitem>
+ <para>[shipping location number] (e.g., 1st location, 2nd, etc.)</para>
+ </listitem>
+ <listitem>
+ <para>[line item number] (e.g., 1st lineitem, 2nd, etc.)</para>
+ </listitem>
+ </itemizedlist>
+ <para>Such a normalized model is likely to be the approach with an RDBMS, but that's not
+ your only option with HBase. The cons of such an approach is that to retrieve
+ information about any Order, you will need: </para>
+ <itemizedlist>
+ <listitem>
+ <para>Get on the ORDER table for the Order</para>
+ </listitem>
+ <listitem>
+ <para>Scan on the SHIPPING_LOCATION table for that order to get the ShippingLocation
+ instances</para>
+ </listitem>
+ <listitem>
+ <para>Scan on the LINE_ITEM for each ShippingLocation</para>
+ </listitem>
+ </itemizedlist>
+ <para>... granted, this is what an RDBMS would do under the covers anyway, but since there
+ are no joins in HBase you're just more aware of this fact. </para>
+ </section>
+ <section
+ xml:id="schema.casestudies.custorder.obj.rectype">
+ <title>Single Table With Record Types</title>
+ <para>With this approach, there would exist a single table ORDER that would contain </para>
+ <para>The Order rowkey was described above: <xref
+ linkend="schema.casestudies.custorder" /></para>
+ <itemizedlist>
+ <listitem>
+ <para>[order-rowkey]</para>
+ </listitem>
+ <listitem>
+ <para>[ORDER record type]</para>
+ </listitem>
+ </itemizedlist>
+ <para>The ShippingLocation composite rowkey would be something like this: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[order-rowkey]</para>
+ </listitem>
+ <listitem>
+ <para>[SHIPPING record type]</para>
+ </listitem>
+ <listitem>
+ <para>[shipping location number] (e.g., 1st location, 2nd, etc.)</para>
+ </listitem>
+ </itemizedlist>
+ <para>The LineItem composite rowkey would be something like this: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[order-rowkey]</para>
+ </listitem>
+ <listitem>
+ <para>[LINE record type]</para>
+ </listitem>
+ <listitem>
+ <para>[shipping location number] (e.g., 1st location, 2nd, etc.)</para>
+ </listitem>
+ <listitem>
+ <para>[line item number] (e.g., 1st lineitem, 2nd, etc.)</para>
+ </listitem>
+ </itemizedlist>
+ </section>
+ <section
+ xml:id="schema.casestudies.custorder.obj.denorm">
+ <title>Denormalized</title>
+ <para>A variant of the Single Table With Record Types approach is to denormalize and
+ flatten some of the object hierarchy, such as collapsing the ShippingLocation attributes
+ onto each LineItem instance. </para>
+ <para>The LineItem composite rowkey would be something like this: </para>
+ <itemizedlist>
+ <listitem>
+ <para>[order-rowkey]</para>
+ </listitem>
+ <listitem>
+ <para>[LINE record type]</para>
+ </listitem>
+ <listitem>
+ <para>[line item number] (e.g., 1st lineitem, 2nd, etc. - care must be taken that
+ there are unique across the entire order)</para>
+ </listitem>
+ </itemizedlist>
+ <para>... and the LineItem columns would be something like this: </para>
+ <itemizedlist>
+ <listitem>
+ <para>itemNumber</para>
+ </listitem>
+ <listitem>
+ <para>quantity</para>
+ </listitem>
+ <listitem>
+ <para>price</para>
+ </listitem>
+ <listitem>
+ <para>shipToLine1 (denormalized from ShippingLocation)</para>
+ </listitem>
+ <listitem>
+ <para>shipToLine2 (denormalized from ShippingLocation)</para>
+ </listitem>
+ <listitem>
+ <para>shipToCity (denormalized from ShippingLocation)</para>
+ </listitem>
+ <listitem>
+ <para>shipToState (denormalized from ShippingLocation)</para>
+ </listitem>
+ <listitem>
+ <para>shipToZip (denormalized from ShippingLocation)</para>
+ </listitem>
+ </itemizedlist>
+ <para>The pros of this approach include a less complex object heirarchy, but one of the
+ cons is that updating gets more complicated in case any of this information changes.
+ </para>
</section>
- <section xml:id="schema.casestudies.custorder.obj">
- <title>Order Object Design</title>
- <para>Now we need to address how to model the Order object. Assume that the class structure is as follows:
-<programlisting>
-<filename>Order</filename>
- <filename>ShippingLocation</filename> (an Order can have multiple ShippingLocations)
- <filename>LineItem</filename> (a ShippingLocation can have multiple LineItems)
-</programlisting>
- ... there are multiple options on storing this data.
- </para>
- <section xml:id="schema.casestudies.custorder.obj.norm">
- <title>Completely Normalized</title>
- <para>With this approach, there would be separate tables for ORDER, SHIPPING_LOCATION, and LINE_ITEM.
- </para>
- <para>The ORDER table's rowkey was described above: <xref linkend="schema.casestudies.custorder"/>
- </para>
- <para>The SHIPPING_LOCATION's composite rowkey would be something like this:
- <itemizedlist>
- <listitem><para>[order-rowkey]</para></listitem>
- <listitem><para>[shipping location number] (e.g., 1st location, 2nd, etc.)</para></listitem>
- </itemizedlist>
- </para>
- <para>The LINE_ITEM table's composite rowkey would be something like this:
- <itemizedlist>
- <listitem><para>[order-rowkey]</para></listitem>
- <listitem><para>[shipping location number] (e.g., 1st location, 2nd, etc.)</para></listitem>
- <listitem><para>[line item number] (e.g., 1st lineitem, 2nd, etc.)</para></listitem>
- </itemizedlist>
- </para>
- <para>Such a normalized model is likely to be the approach with an RDBMS, but that's not your only option with HBase.
- The cons of such an approach is that to retrieve information about any Order, you will need:
- <itemizedlist>
- <listitem><para>Get on the ORDER table for the Order</para></listitem>
- <listitem><para>Scan on the SHIPPING_LOCATION table for that order to get the ShippingLocation instances</para></listitem>
- <listitem><para>Scan on the LINE_ITEM for each ShippingLocation</para></listitem>
- </itemizedlist>
- ... granted, this is what an RDBMS would do under the covers anyway, but since there are no joins in HBase
- you're just more aware of this fact.
- </para>
- </section>
- <section xml:id="schema.casestudies.custorder.obj.rectype">
- <title>Single Table With Record Types</title>
- <para>With this approach, there would exist a single table ORDER that would contain
- </para>
- <para>The Order rowkey was described above: <xref linkend="schema.casestudies.custorder"/>
- <itemizedlist>
- <listitem><para>[order-rowkey]</para></listitem>
- <listitem><para>[ORDER record type]</para></listitem>
- </itemizedlist>
- </para>
- <para>The ShippingLocation composite rowkey would be something like this:
- <itemizedlist>
- <listitem><para>[order-rowkey]</para></listitem>
- <listitem><para>[SHIPPING record type]</para></listitem>
- <listitem><para>[shipping location number] (e.g.,
<TRUNCATED>
[07/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/preface.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/preface.xml b/src/main/docbkx/preface.xml
index 7d05abe..ff8efb9 100644
--- a/src/main/docbkx/preface.xml
+++ b/src/main/docbkx/preface.xml
@@ -1,12 +1,15 @@
<?xml version="1.0" encoding="UTF-8"?>
-<preface version="5.0" xml:id="preface" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<preface
+ version="5.0"
+ xml:id="preface"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -25,47 +28,42 @@
* limitations under the License.
*/
-->
- <title>Preface</title>
+ <title>Preface</title>
- <para>This is the official reference guide for the <link
- xlink:href="http://hbase.apache.org/">HBase</link> version it ships with.
- Herein you will find either the definitive documentation on an HBase topic
- as of its standing when the referenced HBase version shipped, or it
- will point to the location in <link
- xlink:href="http://hbase.apache.org/apidocs/index.html">javadoc</link>,
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE">JIRA</link>
- or <link xlink:href="http://wiki.apache.org/hadoop/Hbase">wiki</link> where
- the pertinent information can be found.</para>
+ <para>This is the official reference guide for the <link
+ xlink:href="http://hbase.apache.org/">HBase</link> version it ships with. Herein you
+ will find either the definitive documentation on an HBase topic as of its standing when the
+ referenced HBase version shipped, or it will point to the location in <link
+ xlink:href="http://hbase.apache.org/apidocs/index.html">javadoc</link>, <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE">JIRA</link> or <link
+ xlink:href="http://wiki.apache.org/hadoop/Hbase">wiki</link> where the pertinent
+ information can be found.</para>
- <para>This reference guide is a work in progress. The source for this guide can
- be found at <filename>src/main/docbkx</filename> in a checkout of the hbase
- project. This reference guide is marked up using
- <link xlink:href="http://www.docbook.com/">DocBook</link> from which the
- the finished guide is generated as part of the 'site' build target. Run
- <programlisting>mvn site</programlisting> to generate this documentation.
- Amendments and improvements to the documentation are welcomed. Add a
- patch to an issue up in the HBase <link
- xlink:href="https://issues.apache.org/jira/browse/HBASE">JIRA</link>.</para>
+ <para>This reference guide is a work in progress. The source for this guide can be found at
+ <filename>src/main/docbkx</filename> in a checkout of the hbase project. This reference
+ guide is marked up using <link
+ xlink:href="http://www.docbook.com/">DocBook</link> from which the the finished guide is
+ generated as part of the 'site' build target. Run <programlisting>mvn site</programlisting>
+ to generate this documentation. Amendments and improvements to the documentation are
+ welcomed. Add a patch to an issue up in the HBase <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE">JIRA</link>.</para>
- <note xml:id="headsup">
- <title>Heads-up if this is your first foray into the world of distributed computing...</title>
- <para>
- 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' operation can hiccup because of any
- of a myriad set of reasons from bugs in HBase itself through misconfigurations
- -- misconfiguration of HBase but also operating system misconfigurations --
- through to hardware problems whether it be a bug in your network card
- drivers or an underprovisioned RAM bus (to mention two recent
- examples of hardware issues that manifested as "HBase is slow").
- You will also need to do a recalibration if up to this your
- computing has been bound to a single box. Here is one good
- starting point:
- <link xlink:href="http://en.wikipedia.org/wiki/Fallacies_of_Distributed_Computing">Fallacies of Distributed Computing</link>.
- That said, you are welcome. Its a fun place to be. Yours, the HBase Community.
- </para>
- </note>
+ <note
+ xml:id="headsup">
+ <title>Heads-up if this is your first foray into the world of distributed
+ computing...</title>
+ <para> 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' operation can hiccup because of any of a myriad
+ set of reasons from bugs in HBase itself through misconfigurations -- misconfiguration
+ of HBase but also operating system misconfigurations -- through to hardware problems
+ whether it be a bug in your network card drivers or an underprovisioned RAM bus (to
+ mention two recent examples of hardware issues that manifested as "HBase is slow"). You
+ will also need to do a recalibration if up to this your computing has been bound to a
+ single box. Here is one good starting point: <link
+ xlink:href="http://en.wikipedia.org/wiki/Fallacies_of_Distributed_Computing">Fallacies
+ of Distributed Computing</link>. That said, you are welcome. Its a fun place to be.
+ Yours, the HBase Community. </para>
+ </note>
</preface>
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/rpc.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/rpc.xml b/src/main/docbkx/rpc.xml
index cbc59b7..5745a33 100644
--- a/src/main/docbkx/rpc.xml
+++ b/src/main/docbkx/rpc.xml
@@ -1,13 +1,15 @@
<?xml version="1.0" encoding="UTF-8"?>
-<appendix xml:id="hbase.rpc"
- version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
- <!--/**
+<appendix
+ xml:id="hbase.rpc"
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
@@ -26,211 +28,273 @@
*/
-->
- <title>0.95 RPC Specification</title>
- <para>In 0.95, all client/server communication is done with
- <link xlink:href="https://code.google.com/p/protobuf/">protobuf’ed</link> Messages rather than with
- <link xlink:href="http://hadoop.apache.org/docs/current/api/org/apache/hadoop/io/Writable.html">Hadoop Writables</link>.
- Our RPC wire format therefore changes.
- This document describes the client/server request/response protocol and our new RPC wire-format.</para>
- <para/>
- <para>For what RPC is like in 0.94 and previous,
- see Benoît/Tsuna’s <link xlink:href="https://github.com/OpenTSDB/asynchbase/blob/master/src/HBaseRpc.java#L164">Unofficial Hadoop / HBase RPC protocol documentation</link>.
- For more background on how we arrived at this spec., see
- <link xlink:href="https://docs.google.com/document/d/1WCKwgaLDqBw2vpux0jPsAu2WPTRISob7HGCO8YhfDTA/edit#">HBase RPC: WIP</link></para>
- <para/>
- <section><title>Goals</title>
- <para>
- <orderedlist>
- <listitem>
- <para>A wire-format we can evolve</para>
- </listitem>
- <listitem>
- <para>A format that does not require our rewriting server core or
- radically changing its current architecture (for later).</para>
- </listitem>
- </orderedlist>
- </para>
- </section>
- <section><title>TODO</title>
- <para>
- <orderedlist>
- <listitem>
- <para>List of problems with currently specified format and where
- we would like to go in a version2, etc. For example, what would we
- have to change if anything to move server async or to support
- streaming/chunking?</para>
- </listitem>
- <listitem>
- <para>Diagram on how it works</para>
- </listitem>
- <listitem>
- <para>A grammar that succinctly describes the wire-format. Currently
- we have these words and the content of the rpc protobuf idl but
- a grammar for the back and forth would help with groking rpc. Also,
- a little state machine on client/server interactions would help
- with understanding (and ensuring correct implementation).</para>
- </listitem>
- </orderedlist>
- </para>
- </section>
- <section><title>RPC</title>
- <para>The client will send setup information on connection establish.
- Thereafter, the client invokes methods against the remote server sending a protobuf Message and receiving a protobuf Message in response.
- Communication is synchronous. All back and forth is preceded by an int that has the total length of the request/response.
- Optionally, Cells(KeyValues) can be passed outside of protobufs in follow-behind Cell blocks (because
- <link xlink:href="https://docs.google.com/document/d/1WEtrq-JTIUhlnlnvA0oYRLp0F8MKpEBeBSCFcQiacdw/edit#">we can’t protobuf megabytes of KeyValues</link> or Cells).
- These CellBlocks are encoded and optionally compressed.</para>
- <para/>
- <para>For more detail on the protobufs involved, see the
- <link xlink:href="http://svn.apache.org/viewvc/hbase/trunk/hbase-protocol/src/main/protobuf/RPC.proto?view=markup">RPC.proto</link> file in trunk.</para>
+ <title>0.95 RPC Specification</title>
+ <para>In 0.95, all client/server communication is done with <link
+ xlink:href="https://code.google.com/p/protobuf/">protobuf’ed</link> Messages rather than
+ with <link
+ xlink:href="http://hadoop.apache.org/docs/current/api/org/apache/hadoop/io/Writable.html">Hadoop
+ Writables</link>. Our RPC wire format therefore changes. This document describes the
+ client/server request/response protocol and our new RPC wire-format.</para>
+ <para />
+ <para>For what RPC is like in 0.94 and previous, see Benoît/Tsuna’s <link
+ xlink:href="https://github.com/OpenTSDB/asynchbase/blob/master/src/HBaseRpc.java#L164">Unofficial
+ Hadoop / HBase RPC protocol documentation</link>. For more background on how we arrived
+ at this spec., see <link
+ xlink:href="https://docs.google.com/document/d/1WCKwgaLDqBw2vpux0jPsAu2WPTRISob7HGCO8YhfDTA/edit#">HBase
+ RPC: WIP</link></para>
+ <para />
+ <section>
+ <title>Goals</title>
+ <para>
+ <orderedlist>
+ <listitem>
+ <para>A wire-format we can evolve</para>
+ </listitem>
+ <listitem>
+ <para>A format that does not require our rewriting server core or radically
+ changing its current architecture (for later).</para>
+ </listitem>
+ </orderedlist>
+ </para>
+ </section>
+ <section>
+ <title>TODO</title>
+ <para>
+ <orderedlist>
+ <listitem>
+ <para>List of problems with currently specified format and where we would like
+ to go in a version2, etc. For example, what would we have to change if
+ anything to move server async or to support streaming/chunking?</para>
+ </listitem>
+ <listitem>
+ <para>Diagram on how it works</para>
+ </listitem>
+ <listitem>
+ <para>A grammar that succinctly describes the wire-format. Currently we have
+ these words and the content of the rpc protobuf idl but a grammar for the
+ back and forth would help with groking rpc. Also, a little state machine on
+ client/server interactions would help with understanding (and ensuring
+ correct implementation).</para>
+ </listitem>
+ </orderedlist>
+ </para>
+ </section>
+ <section>
+ <title>RPC</title>
+ <para>The client will send setup information on connection establish. Thereafter, the client
+ invokes methods against the remote server sending a protobuf Message and receiving a
+ protobuf Message in response. Communication is synchronous. All back and forth is
+ preceded by an int that has the total length of the request/response. Optionally,
+ Cells(KeyValues) can be passed outside of protobufs in follow-behind Cell blocks
+ (because <link
+ xlink:href="https://docs.google.com/document/d/1WEtrq-JTIUhlnlnvA0oYRLp0F8MKpEBeBSCFcQiacdw/edit#">we
+ can’t protobuf megabytes of KeyValues</link> or Cells). These CellBlocks are encoded
+ and optionally compressed.</para>
+ <para />
+ <para>For more detail on the protobufs involved, see the <link
+ xlink:href="http://svn.apache.org/viewvc/hbase/trunk/hbase-protocol/src/main/protobuf/RPC.proto?view=markup">RPC.proto</link>
+ file in trunk.</para>
- <section>
- <title>Connection Setup</title>
- <para>Client initiates connection.</para>
- <section><title>Client</title>
- <para>On connection setup, client sends a preamble followed by a connection header.
- </para>
+ <section>
+ <title>Connection Setup</title>
+ <para>Client initiates connection.</para>
+ <section>
+ <title>Client</title>
+ <para>On connection setup, client sends a preamble followed by a connection header. </para>
- <section>
- <title><preamble></title>
- <para><programlisting><MAGIC 4 byte integer> <1 byte RPC Format Version> <1 byte auth type><footnote><para> We need the auth method spec. here so the connection header is encoded if auth enabled.</para></footnote></programlisting></para>
- <para>E.g.: HBas0x000x50 -- 4 bytes of MAGIC -- ‘HBas’ -- plus one-byte of version, 0 in this case, and one byte, 0x50 (SIMPLE). of an auth type.</para>
- </section>
+ <section>
+ <title><preamble></title>
+ <para><programlisting><MAGIC 4 byte integer> <1 byte RPC Format Version> <1 byte auth type><footnote><para> We need the auth method spec. here so the connection header is encoded if auth enabled.</para></footnote></programlisting></para>
+ <para>E.g.: HBas0x000x50 -- 4 bytes of MAGIC -- ‘HBas’ -- plus one-byte of
+ version, 0 in this case, and one byte, 0x50 (SIMPLE). of an auth
+ type.</para>
+ </section>
- <section>
- <title><Protobuf ConnectionHeader Message></title>
- <para>Has user info, and “protocol”, as well as the encoders and compression the client will use sending CellBlocks.
- CellBlock encoders and compressors are for the life of the connection.
- CellBlock encoders implement org.apache.hadoop.hbase.codec.Codec.
- CellBlocks may then also be compressed.
- Compressors implement org.apache.hadoop.io.compress.CompressionCodec.
- This protobuf is written using writeDelimited so is prefaced by a pb varint
- with its serialized length</para>
- </section>
- </section><!--Client-->
+ <section>
+ <title><Protobuf ConnectionHeader Message></title>
+ <para>Has user info, and “protocol”, as well as the encoders and compression the
+ client will use sending CellBlocks. CellBlock encoders and compressors are
+ for the life of the connection. CellBlock encoders implement
+ org.apache.hadoop.hbase.codec.Codec. CellBlocks may then also be compressed.
+ Compressors implement org.apache.hadoop.io.compress.CompressionCodec. This
+ protobuf is written using writeDelimited so is prefaced by a pb varint with
+ its serialized length</para>
+ </section>
+ </section>
+ <!--Client-->
- <section><title>Server</title>
- <para>After client sends preamble and connection header,
- server does NOT respond if successful connection setup.
- No response means server is READY to accept requests and to give out response.
- If the version or authentication in the preamble is not agreeable or the server has trouble parsing the preamble,
- it will throw a org.apache.hadoop.hbase.ipc.FatalConnectionException explaining the error and will then disconnect.
- If the client in the connection header -- i.e. the protobuf’d Message that comes after the connection preamble -- asks for for a
- Service the server does not support or a codec the server does not have, again we throw a FatalConnectionException with explanation.</para>
- </section>
- </section>
+ <section>
+ <title>Server</title>
+ <para>After client sends preamble and connection header, server does NOT respond if
+ successful connection setup. No response means server is READY to accept
+ requests and to give out response. If the version or authentication in the
+ preamble is not agreeable or the server has trouble parsing the preamble, it
+ will throw a org.apache.hadoop.hbase.ipc.FatalConnectionException explaining the
+ error and will then disconnect. If the client in the connection header -- i.e.
+ the protobuf’d Message that comes after the connection preamble -- asks for for
+ a Service the server does not support or a codec the server does not have, again
+ we throw a FatalConnectionException with explanation.</para>
+ </section>
+ </section>
- <section><title>Request</title>
- <para>After a Connection has been set up, client makes requests. Server responds.</para>
- <para>A request is made up of a protobuf RequestHeader followed by a protobuf Message parameter.
- The header includes the method name and optionally, metadata on the optional CellBlock that may be following.
- The parameter type suits the method being invoked: i.e. if we are doing a getRegionInfo request,
- the protobuf Message param will be an instance of GetRegionInfoRequest.
- The response will be a GetRegionInfoResponse.
- The CellBlock is optionally used ferrying the bulk of the RPC data: i.e Cells/KeyValues.</para>
- <para/>
- <section><title>Request Parts</title>
- <section><title><Total Length></title>
- <para>The request is prefaced by an int that holds the total length of what follows.</para>
- </section>
- <section><title><Protobuf RequestHeader Message></title>
- <para>Will have call.id, trace.id, and method name, etc. including optional Metadata on the Cell block IFF one is following.
- Data is protobuf’d inline in this pb Message or optionally comes in the following CellBlock</para>
- </section>
- <section><title><Protobuf Param Message></title>
- <para>If the method being invoked is getRegionInfo, if you study the Service descriptor for the client to regionserver protocol,
- you will find that the request sends a GetRegionInfoRequest protobuf Message param in this position.</para>
- </section>
- <section><title><CellBlock></title>
- <para>An encoded and optionally compressed Cell block.</para>
- </section>
- </section><!--Request parts-->
- </section><!--Request-->
+ <section>
+ <title>Request</title>
+ <para>After a Connection has been set up, client makes requests. Server responds.</para>
+ <para>A request is made up of a protobuf RequestHeader followed by a protobuf Message
+ parameter. The header includes the method name and optionally, metadata on the
+ optional CellBlock that may be following. The parameter type suits the method being
+ invoked: i.e. if we are doing a getRegionInfo request, the protobuf Message param
+ will be an instance of GetRegionInfoRequest. The response will be a
+ GetRegionInfoResponse. The CellBlock is optionally used ferrying the bulk of the RPC
+ data: i.e Cells/KeyValues.</para>
+ <section>
+ <title>Request Parts</title>
+ <section>
+ <title><Total Length></title>
+ <para>The request is prefaced by an int that holds the total length of what
+ follows.</para>
+ </section>
+ <section>
+ <title><Protobuf RequestHeader Message></title>
+ <para>Will have call.id, trace.id, and method name, etc. including optional
+ Metadata on the Cell block IFF one is following. Data is protobuf’d inline
+ in this pb Message or optionally comes in the following CellBlock</para>
+ </section>
+ <section>
+ <title><Protobuf Param Message></title>
+ <para>If the method being invoked is getRegionInfo, if you study the Service
+ descriptor for the client to regionserver protocol, you will find that the
+ request sends a GetRegionInfoRequest protobuf Message param in this
+ position.</para>
+ </section>
+ <section>
+ <title><CellBlock></title>
+ <para>An encoded and optionally compressed Cell block.</para>
+ </section>
+ </section>
+ <!--Request parts-->
+ </section>
+ <!--Request-->
- <section><title>Response</title>
- <para>Same as Request, it is a protobuf ResponseHeader followed by a protobuf Message response where the Message response type suits the method invoked.
- Bulk of the data may come in a following CellBlock.</para>
- <section><title>Response Parts</title>
- <section><title><Total Length></title>
- <para>The response is prefaced by an int that holds the total length of what follows.</para>
- </section>
- <section><title><Protobuf ResponseHeader Message></title>
- <para>Will have call.id, etc. Will include exception if failed processing. Optionally includes metadata on optional, IFF there is a CellBlock following.</para>
- </section>
+ <section>
+ <title>Response</title>
+ <para>Same as Request, it is a protobuf ResponseHeader followed by a protobuf Message
+ response where the Message response type suits the method invoked. Bulk of the data
+ may come in a following CellBlock.</para>
+ <section>
+ <title>Response Parts</title>
+ <section>
+ <title><Total Length></title>
+ <para>The response is prefaced by an int that holds the total length of what
+ follows.</para>
+ </section>
+ <section>
+ <title><Protobuf ResponseHeader Message></title>
+ <para>Will have call.id, etc. Will include exception if failed processing.
+ Optionally includes metadata on optional, IFF there is a CellBlock
+ following.</para>
+ </section>
- <section><title><Protobuf Response Message></title>
- <para>Return or may be nothing if exception. If the method being invoked is getRegionInfo, if you study the Service descriptor for the client to regionserver protocol,
- you will find that the response sends a GetRegionInfoResponse protobuf Message param in this position.</para>
- </section>
- <section><title><CellBlock></title>
- <para>An encoded and optionally compressed Cell block.</para>
- </section>
- </section><!--Parts-->
- </section><!--Response-->
+ <section>
+ <title><Protobuf Response Message></title>
+ <para>Return or may be nothing if exception. If the method being invoked is
+ getRegionInfo, if you study the Service descriptor for the client to
+ regionserver protocol, you will find that the response sends a
+ GetRegionInfoResponse protobuf Message param in this position.</para>
+ </section>
+ <section>
+ <title><CellBlock></title>
+ <para>An encoded and optionally compressed Cell block.</para>
+ </section>
+ </section>
+ <!--Parts-->
+ </section>
+ <!--Response-->
- <section><title>Exceptions</title>
- <para>There are two distinct types.
- There is the request failed which is encapsulated inside the response header for the response.
- The connection stays open to receive new requests.
- The second type, the FatalConnectionException, kills the connection.</para>
- <para>Exceptions can carry extra information.
- See the ExceptionResponse protobuf type.
- It has a flag to indicate do-no-retry as well as other miscellaneous payload to help improve client responsiveness.</para>
- </section>
- <section><title>CellBlocks</title>
- <para>These are not versioned.
- Server can do the codec or it cannot.
- If new version of a codec with say, tighter encoding, then give it a new class name.
- Codecs will live on the server for all time so old clients can connect.</para>
- </section>
- </section>
+ <section>
+ <title>Exceptions</title>
+ <para>There are two distinct types. There is the request failed which is encapsulated
+ inside the response header for the response. The connection stays open to receive
+ new requests. The second type, the FatalConnectionException, kills the
+ connection.</para>
+ <para>Exceptions can carry extra information. See the ExceptionResponse protobuf type.
+ It has a flag to indicate do-no-retry as well as other miscellaneous payload to help
+ improve client responsiveness.</para>
+ </section>
+ <section>
+ <title>CellBlocks</title>
+ <para>These are not versioned. Server can do the codec or it cannot. If new version of a
+ codec with say, tighter encoding, then give it a new class name. Codecs will live on
+ the server for all time so old clients can connect.</para>
+ </section>
+ </section>
- <section><title>Notes</title>
- <section><title>Constraints</title>
- <para>In some part, current wire-format -- i.e. all requests and responses preceeded by a length -- has been dictated by current server non-async architecture.</para>
- </section>
- <section><title>One fat pb request or header+param</title>
- <para>We went with pb header followed by pb param making a request and a pb header followed by pb response for now.
- Doing header+param rather than a single protobuf Message with both header and param content:</para>
- <para>
- <orderedlist>
- <listitem>
- <para>Is closer to what we currently have</para>
- </listitem>
- <listitem>
- <para>Having a single fat pb requires extra copying putting the already pb’d param into the body of the fat request pb (and same making result)</para>
- </listitem>
- <listitem>
- <para>We can decide whether to accept the request or not before we read the param; for example, the request might be low priority. As is, we read header+param in one go as server is currently implemented so this is a TODO.</para>
- </listitem>
- </orderedlist>
- </para>
- <para>The advantages are minor. If later, fat request has clear advantage, can roll out a v2 later.</para>
- </section>
- <section xml:id="rpc.configs"><title>RPC Configurations</title>
- <section><title>CellBlock Codecs</title>
- <para>To enable a codec other than the default <classname>KeyValueCodec</classname>,
- set <varname>hbase.client.rpc.codec</varname>
- to the name of the Codec class to use. Codec must implement hbase's <classname>Codec</classname> Interface. After connection setup,
- all passed cellblocks will be sent with this codec. The server will return cellblocks using this same codec as long
- as the codec is on the servers' CLASSPATH (else you will get <classname>UnsupportedCellCodecException</classname>).</para>
- <para>To change the default codec, set <varname>hbase.client.default.rpc.codec</varname>.
- </para>
- <para>To disable cellblocks completely and to go pure protobuf, set the default to the
- empty String and do not specify a codec in your Configuration. So, set <varname>hbase.client.default.rpc.codec</varname>
- to the empty string and do not set <varname>hbase.client.rpc.codec</varname>.
- This will cause the client to connect to the server with no codec specified.
- If a server sees no codec, it will return all responses in pure protobuf.
- Running pure protobuf all the time will be slower than running with cellblocks.
- </para>
- </section>
- <section><title>Compression</title>
- <para>Uses hadoops compression codecs. To enable compressing of passed CellBlocks, set <varname>hbase.client.rpc.compressor</varname>
- to the name of the Compressor to use. Compressor must implement Hadoops' CompressionCodec Interface. After connection setup,
- all passed cellblocks will be sent compressed. The server will return cellblocks compressed using this same compressor as long
- as the compressor is on its CLASSPATH (else you will get <classname>UnsupportedCompressionCodecException</classname>).</para>
- </section>
- </section>
- </section>
+ <section>
+ <title>Notes</title>
+ <section>
+ <title>Constraints</title>
+ <para>In some part, current wire-format -- i.e. all requests and responses preceeded by
+ a length -- has been dictated by current server non-async architecture.</para>
+ </section>
+ <section>
+ <title>One fat pb request or header+param</title>
+ <para>We went with pb header followed by pb param making a request and a pb header
+ followed by pb response for now. Doing header+param rather than a single protobuf
+ Message with both header and param content:</para>
+ <para>
+ <orderedlist>
+ <listitem>
+ <para>Is closer to what we currently have</para>
+ </listitem>
+ <listitem>
+ <para>Having a single fat pb requires extra copying putting the already pb’d
+ param into the body of the fat request pb (and same making
+ result)</para>
+ </listitem>
+ <listitem>
+ <para>We can decide whether to accept the request or not before we read the
+ param; for example, the request might be low priority. As is, we read
+ header+param in one go as server is currently implemented so this is a
+ TODO.</para>
+ </listitem>
+ </orderedlist>
+ </para>
+ <para>The advantages are minor. If later, fat request has clear advantage, can roll out
+ a v2 later.</para>
+ </section>
+ <section
+ xml:id="rpc.configs">
+ <title>RPC Configurations</title>
+ <section>
+ <title>CellBlock Codecs</title>
+ <para>To enable a codec other than the default <classname>KeyValueCodec</classname>,
+ set <varname>hbase.client.rpc.codec</varname> to the name of the Codec class to
+ use. Codec must implement hbase's <classname>Codec</classname> Interface. After
+ connection setup, all passed cellblocks will be sent with this codec. The server
+ will return cellblocks using this same codec as long as the codec is on the
+ servers' CLASSPATH (else you will get
+ <classname>UnsupportedCellCodecException</classname>).</para>
+ <para>To change the default codec, set
+ <varname>hbase.client.default.rpc.codec</varname>. </para>
+ <para>To disable cellblocks completely and to go pure protobuf, set the default to
+ the empty String and do not specify a codec in your Configuration. So, set
+ <varname>hbase.client.default.rpc.codec</varname> to the empty string and do
+ not set <varname>hbase.client.rpc.codec</varname>. This will cause the client to
+ connect to the server with no codec specified. If a server sees no codec, it
+ will return all responses in pure protobuf. Running pure protobuf all the time
+ will be slower than running with cellblocks. </para>
+ </section>
+ <section>
+ <title>Compression</title>
+ <para>Uses hadoops compression codecs. To enable compressing of passed CellBlocks,
+ set <varname>hbase.client.rpc.compressor</varname> to the name of the Compressor
+ to use. Compressor must implement Hadoops' CompressionCodec Interface. After
+ connection setup, all passed cellblocks will be sent compressed. The server will
+ return cellblocks compressed using this same compressor as long as the
+ compressor is on its CLASSPATH (else you will get
+ <classname>UnsupportedCompressionCodecException</classname>).</para>
+ </section>
+ </section>
+ </section>
</appendix>
[14/14] git commit: HBASE-11199 One-time effort to pretty-print the
Docbook XML, to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
HBASE-11199 One-time effort to pretty-print the Docbook XML, to make further patch review easier (Misty Stanley-Jones)
Project: http://git-wip-us.apache.org/repos/asf/hbase/repo
Commit: http://git-wip-us.apache.org/repos/asf/hbase/commit/63e8304e
Tree: http://git-wip-us.apache.org/repos/asf/hbase/tree/63e8304e
Diff: http://git-wip-us.apache.org/repos/asf/hbase/diff/63e8304e
Branch: refs/heads/master
Commit: 63e8304e96c06463e3385afc075e90d18a5bdf1e
Parents: ab896f0
Author: Michael Stack <st...@duboce.net>
Authored: Wed May 28 07:58:50 2014 -0700
Committer: Michael Stack <st...@duboce.net>
Committed: Wed May 28 07:58:50 2014 -0700
----------------------------------------------------------------------
src/main/docbkx/book.xml | 1387 ++++++++++++-------
src/main/docbkx/case_studies.xml | 262 ++--
src/main/docbkx/community.xml | 265 ++--
src/main/docbkx/configuration.xml | 2220 ++++++++++++++++--------------
src/main/docbkx/cp.xml | 26 +-
src/main/docbkx/developer.xml | 842 ++++++-----
src/main/docbkx/external_apis.xml | 20 +-
src/main/docbkx/getting_started.xml | 330 ++---
src/main/docbkx/ops_mgt.xml | 789 ++++++-----
src/main/docbkx/performance.xml | 1314 ++++++++++--------
src/main/docbkx/preface.xml | 94 +-
src/main/docbkx/rpc.xml | 476 ++++---
src/main/docbkx/schema_design.xml | 1761 +++++++++++++-----------
src/main/docbkx/security.xml | 1896 +++++++++++++------------
src/main/docbkx/shell.xml | 246 ++--
src/main/docbkx/tracing.xml | 307 ++---
src/main/docbkx/troubleshooting.xml | 1449 ++++++++++---------
src/main/docbkx/upgrading.xml | 779 ++++++-----
src/main/docbkx/zookeeper.xml | 904 ++++++------
19 files changed, 8307 insertions(+), 7060 deletions(-)
----------------------------------------------------------------------
[13/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/book.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/book.xml b/src/main/docbkx/book.xml
index 1fca2be..2ac9de3 100644
--- a/src/main/docbkx/book.xml
+++ b/src/main/docbkx/book.xml
@@ -19,38 +19,45 @@
* limitations under the License.
*/
-->
-<book version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook" xml:id="book">
+<book
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook"
+ xml:id="book">
<info>
- <title><link xlink:href="http://www.hbase.org">
- The Apache HBase™ Reference Guide
- </link></title>
- <subtitle><link xlink:href="http://www.hbase.org">
- <inlinemediaobject>
- <imageobject>
- <imagedata align="center" valign="middle" fileref="hbase_logo.png" />
- </imageobject>
- </inlinemediaobject>
- </link>
+ <title><link
+ xlink:href="http://www.hbase.org"> The Apache HBase™ Reference Guide </link></title>
+ <subtitle><link
+ xlink:href="http://www.hbase.org">
+ <inlinemediaobject>
+ <imageobject>
+ <imagedata
+ align="center"
+ valign="middle"
+ fileref="hbase_logo.png" />
+ </imageobject>
+ </inlinemediaobject>
+ </link>
</subtitle>
- <copyright><year>2014</year><holder>Apache Software Foundation.
- All Rights Reserved. Apache Hadoop, Hadoop, MapReduce, HDFS, Zookeeper, HBase, and the HBase project logo are trademarks of the Apache Software Foundation.
- </holder>
+ <copyright>
+ <year>2014</year>
+ <holder>Apache Software Foundation. All Rights Reserved. Apache Hadoop, Hadoop, MapReduce,
+ HDFS, Zookeeper, HBase, and the HBase project logo are trademarks of the Apache Software
+ Foundation. </holder>
</copyright>
- <abstract>
- <para>This is the official reference guide of
- <link xlink:href="http://www.hbase.org">Apache HBase™</link>,
- a distributed, versioned, big data store built on top of
- <link xlink:href="http://hadoop.apache.org/">Apache Hadoop™</link> and
- <link xlink:href="http://zookeeper.apache.org/">Apache ZooKeeper™</link>.
- </para>
- </abstract>
+ <abstract>
+ <para>This is the official reference guide of <link
+ xlink:href="http://www.hbase.org">Apache HBase™</link>, a distributed, versioned, big
+ data store built on top of <link
+ xlink:href="http://hadoop.apache.org/">Apache Hadoop™</link> and <link
+ xlink:href="http://zookeeper.apache.org/">Apache ZooKeeper™</link>. </para>
+ </abstract>
<revhistory>
<revision>
@@ -65,151 +72,241 @@
</info>
<!--XInclude some chapters-->
- <xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="preface.xml" />
- <xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="getting_started.xml" />
- <xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="configuration.xml" />
- <xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="upgrading.xml"/>
- <xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="shell.xml"/>
+ <xi:include
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ href="preface.xml" />
+ <xi:include
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ href="getting_started.xml" />
+ <xi:include
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ href="configuration.xml" />
+ <xi:include
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ href="upgrading.xml" />
+ <xi:include
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ href="shell.xml" />
- <chapter xml:id="datamodel">
+ <chapter
+ xml:id="datamodel">
<title>Data Model</title>
- <para>In short, applications store data into an HBase table.
- Tables are made of rows and columns.
- All columns in HBase belong to a particular column family.
- Table cells -- the intersection of row and column
- coordinates -- are versioned.
- A cell’s content is an uninterpreted array of bytes.
- </para>
- <para>Table row keys are also byte arrays so almost anything can
- serve as a row key from strings to binary representations of longs or
- even serialized data structures. Rows in HBase tables
- are sorted by row key. The sort is byte-ordered. All table accesses are
- via the table row key -- its primary key.
-</para>
+ <para>In short, applications store data into an HBase table. Tables are made of rows and
+ columns. All columns in HBase belong to a particular column family. Table cells -- the
+ intersection of row and column coordinates -- are versioned. A cell’s content is an
+ uninterpreted array of bytes. </para>
+ <para>Table row keys are also byte arrays so almost anything can serve as a row key from strings
+ to binary representations of longs or even serialized data structures. Rows in HBase tables
+ are sorted by row key. The sort is byte-ordered. All table accesses are via the table row key
+ -- its primary key. </para>
- <section xml:id="conceptual.view"><title>Conceptual View</title>
- <para>
- The following example is a slightly modified form of the one on page
- 2 of the <link xlink:href="http://research.google.com/archive/bigtable.html">BigTable</link> paper.
- There is a table called <varname>webtable</varname> that contains two column families named
- <varname>contents</varname> and <varname>anchor</varname>.
- In this example, <varname>anchor</varname> contains two
- columns (<varname>anchor:cssnsi.com</varname>, <varname>anchor:my.look.ca</varname>)
- and <varname>contents</varname> contains one column (<varname>contents:html</varname>).
- <note>
- <title>Column Names</title>
- <para>
- By convention, a column name is made of its column family prefix and a
- <emphasis>qualifier</emphasis>. For example, the
- column
- <emphasis>contents:html</emphasis> is made up of the column family <varname>contents</varname>
- and <varname>html</varname> qualifier.
- The colon character (<literal>:</literal>) delimits the column family from the
- column family <emphasis>qualifier</emphasis>.
- </para>
- </note>
- <table frame='all'><title>Table <varname>webtable</varname></title>
- <tgroup cols='4' align='left' colsep='1' rowsep='1'>
- <colspec colname='c1'/>
- <colspec colname='c2'/>
- <colspec colname='c3'/>
- <colspec colname='c4'/>
- <thead>
- <row><entry>Row Key</entry><entry>Time Stamp</entry><entry>ColumnFamily <varname>contents</varname></entry><entry>ColumnFamily <varname>anchor</varname></entry></row>
- </thead>
- <tbody>
- <row><entry>"com.cnn.www"</entry><entry>t9</entry><entry></entry><entry><varname>anchor:cnnsi.com</varname> = "CNN"</entry></row>
- <row><entry>"com.cnn.www"</entry><entry>t8</entry><entry></entry><entry><varname>anchor:my.look.ca</varname> = "CNN.com"</entry></row>
- <row><entry>"com.cnn.www"</entry><entry>t6</entry><entry><varname>contents:html</varname> = "<html>..."</entry><entry></entry></row>
- <row><entry>"com.cnn.www"</entry><entry>t5</entry><entry><varname>contents:html</varname> = "<html>..."</entry><entry></entry></row>
- <row><entry>"com.cnn.www"</entry><entry>t3</entry><entry><varname>contents:html</varname> = "<html>..."</entry><entry></entry></row>
- </tbody>
- </tgroup>
- </table>
- </para>
- </section>
- <section xml:id="physical.view"><title>Physical View</title>
- <para>
- Although at a conceptual level tables may be viewed as a sparse set of rows.
- Physically they are stored on a per-column family basis. New columns
- (i.e., <varname>columnfamily:column</varname>) can be added to any
- column family without pre-announcing them.
- <table frame='all'><title>ColumnFamily <varname>anchor</varname></title>
- <tgroup cols='3' align='left' colsep='1' rowsep='1'>
- <colspec colname='c1'/>
- <colspec colname='c2'/>
- <colspec colname='c3'/>
- <thead>
- <row><entry>Row Key</entry><entry>Time Stamp</entry><entry>Column Family <varname>anchor</varname></entry></row>
- </thead>
- <tbody>
- <row><entry>"com.cnn.www"</entry><entry>t9</entry><entry><varname>anchor:cnnsi.com</varname> = "CNN"</entry></row>
- <row><entry>"com.cnn.www"</entry><entry>t8</entry><entry><varname>anchor:my.look.ca</varname> = "CNN.com"</entry></row>
- </tbody>
- </tgroup>
- </table>
- <table frame='all'><title>ColumnFamily <varname>contents</varname></title>
- <tgroup cols='3' align='left' colsep='1' rowsep='1'>
- <colspec colname='c1'/>
- <colspec colname='c2'/>
- <colspec colname='c3'/>
- <thead>
- <row><entry>Row Key</entry><entry>Time Stamp</entry><entry>ColumnFamily "contents:"</entry></row>
- </thead>
- <tbody>
- <row><entry>"com.cnn.www"</entry><entry>t6</entry><entry><varname>contents:html</varname> = "<html>..."</entry></row>
- <row><entry>"com.cnn.www"</entry><entry>t5</entry><entry><varname>contents:html</varname> = "<html>..."</entry></row>
- <row><entry>"com.cnn.www"</entry><entry>t3</entry><entry><varname>contents:html</varname> = "<html>..."</entry></row>
- </tbody>
- </tgroup>
- </table>
- It is important to note in the diagram above that the empty cells shown in the
- conceptual view are not stored since they need not be in a column-oriented
- storage format. Thus a request for the value of the <varname>contents:html</varname>
- column at time stamp <literal>t8</literal> would return no value. Similarly, a
- request for an <varname>anchor:my.look.ca</varname> value at time stamp
- <literal>t9</literal> would return no value. However, if no timestamp is
- supplied, the most recent value for a particular column would be returned
- and would also be the first one found since timestamps are stored in
- descending order. Thus a request for the values of all columns in the row
- <varname>com.cnn.www</varname> if no timestamp is specified would be:
- the value of <varname>contents:html</varname> from time stamp
- <literal>t6</literal>, the value of <varname>anchor:cnnsi.com</varname>
- from time stamp <literal>t9</literal>, the value of
- <varname>anchor:my.look.ca</varname> from time stamp <literal>t8</literal>.
- </para>
- <para>For more information about the internals of how Apache HBase stores data, see <xref linkend="regions.arch" />.
- </para>
- </section>
+ <section
+ xml:id="conceptual.view">
+ <title>Conceptual View</title>
+ <para> The following example is a slightly modified form of the one on page 2 of the <link
+ xlink:href="http://research.google.com/archive/bigtable.html">BigTable</link> paper. There
+ is a table called <varname>webtable</varname> that contains two column families named
+ <varname>contents</varname> and <varname>anchor</varname>. In this example,
+ <varname>anchor</varname> contains two columns (<varname>anchor:cssnsi.com</varname>,
+ <varname>anchor:my.look.ca</varname>) and <varname>contents</varname> contains one column
+ (<varname>contents:html</varname>). <note>
+ <title>Column Names</title>
+ <para> By convention, a column name is made of its column family prefix and a
+ <emphasis>qualifier</emphasis>. For example, the column
+ <emphasis>contents:html</emphasis> is made up of the column family
+ <varname>contents</varname> and <varname>html</varname> qualifier. The colon character
+ (<literal>:</literal>) delimits the column family from the column family
+ <emphasis>qualifier</emphasis>. </para>
+ </note>
+ <table
+ frame="all">
+ <title>Table <varname>webtable</varname></title>
+ <tgroup
+ cols="4"
+ align="left"
+ colsep="1"
+ rowsep="1">
+ <colspec
+ colname="c1" />
+ <colspec
+ colname="c2" />
+ <colspec
+ colname="c3" />
+ <colspec
+ colname="c4" />
+ <thead>
+ <row>
+ <entry>Row Key</entry>
+ <entry>Time Stamp</entry>
+ <entry>ColumnFamily <varname>contents</varname></entry>
+ <entry>ColumnFamily <varname>anchor</varname></entry>
+ </row>
+ </thead>
+ <tbody>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t9</entry>
+ <entry />
+ <entry><varname>anchor:cnnsi.com</varname> = "CNN"</entry>
+ </row>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t8</entry>
+ <entry />
+ <entry><varname>anchor:my.look.ca</varname> = "CNN.com"</entry>
+ </row>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t6</entry>
+ <entry><varname>contents:html</varname> = "<html>..."</entry>
+ <entry />
+ </row>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t5</entry>
+ <entry><varname>contents:html</varname> = "<html>..."</entry>
+ <entry />
+ </row>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t3</entry>
+ <entry><varname>contents:html</varname> = "<html>..."</entry>
+ <entry />
+ </row>
+ </tbody>
+ </tgroup>
+ </table>
+ </para>
+ </section>
+ <section
+ xml:id="physical.view">
+ <title>Physical View</title>
+ <para> Although at a conceptual level tables may be viewed as a sparse set of rows. Physically
+ they are stored on a per-column family basis. New columns (i.e.,
+ <varname>columnfamily:column</varname>) can be added to any column family without
+ pre-announcing them. <table
+ frame="all">
+ <title>ColumnFamily <varname>anchor</varname></title>
+ <tgroup
+ cols="3"
+ align="left"
+ colsep="1"
+ rowsep="1">
+ <colspec
+ colname="c1" />
+ <colspec
+ colname="c2" />
+ <colspec
+ colname="c3" />
+ <thead>
+ <row>
+ <entry>Row Key</entry>
+ <entry>Time Stamp</entry>
+ <entry>Column Family <varname>anchor</varname></entry>
+ </row>
+ </thead>
+ <tbody>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t9</entry>
+ <entry><varname>anchor:cnnsi.com</varname> = "CNN"</entry>
+ </row>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t8</entry>
+ <entry><varname>anchor:my.look.ca</varname> = "CNN.com"</entry>
+ </row>
+ </tbody>
+ </tgroup>
+ </table>
+ <table
+ frame="all">
+ <title>ColumnFamily <varname>contents</varname></title>
+ <tgroup
+ cols="3"
+ align="left"
+ colsep="1"
+ rowsep="1">
+ <colspec
+ colname="c1" />
+ <colspec
+ colname="c2" />
+ <colspec
+ colname="c3" />
+ <thead>
+ <row>
+ <entry>Row Key</entry>
+ <entry>Time Stamp</entry>
+ <entry>ColumnFamily "contents:"</entry>
+ </row>
+ </thead>
+ <tbody>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t6</entry>
+ <entry><varname>contents:html</varname> = "<html>..."</entry>
+ </row>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t5</entry>
+ <entry><varname>contents:html</varname> = "<html>..."</entry>
+ </row>
+ <row>
+ <entry>"com.cnn.www"</entry>
+ <entry>t3</entry>
+ <entry><varname>contents:html</varname> = "<html>..."</entry>
+ </row>
+ </tbody>
+ </tgroup>
+ </table> It is important to note in the diagram above that the empty cells shown in the
+ conceptual view are not stored since they need not be in a column-oriented storage format.
+ Thus a request for the value of the <varname>contents:html</varname> column at time stamp
+ <literal>t8</literal> would return no value. Similarly, a request for an
+ <varname>anchor:my.look.ca</varname> value at time stamp <literal>t9</literal> would
+ return no value. However, if no timestamp is supplied, the most recent value for a
+ particular column would be returned and would also be the first one found since timestamps
+ are stored in descending order. Thus a request for the values of all columns in the row
+ <varname>com.cnn.www</varname> if no timestamp is specified would be: the value of
+ <varname>contents:html</varname> from time stamp <literal>t6</literal>, the value of
+ <varname>anchor:cnnsi.com</varname> from time stamp <literal>t9</literal>, the value of
+ <varname>anchor:my.look.ca</varname> from time stamp <literal>t8</literal>. </para>
+ <para>For more information about the internals of how Apache HBase stores data, see <xref
+ linkend="regions.arch" />. </para>
+ </section>
- <section xml:id="namespace">
+ <section
+ xml:id="namespace">
<title>Namespace</title>
- <para>
- A namespace is a logical grouping of tables analogous to a database in relation database
- systems. This abstraction lays the groundwork for upcoming multi-tenancy related features:
- <itemizedlist>
- <listitem><para>Quota Management (HBASE-8410) - Restrict the amount of resources (ie
- regions, tables) a namespace can consume.</para></listitem>
- <listitem><para>Namespace Security Administration (HBASE-9206) - provide another
- level of security administration for tenants.</para></listitem>
- <listitem><para>Region server groups (HBASE-6721) - A namespace/table can be
- pinned onto a subset of regionservers thus guaranteeing a course level of
- isolation.</para></listitem>
+ <para> A namespace is a logical grouping of tables analogous to a database in relation
+ database systems. This abstraction lays the groundwork for upcoming multi-tenancy related
+ features: <itemizedlist>
+ <listitem>
+ <para>Quota Management (HBASE-8410) - Restrict the amount of resources (ie regions,
+ tables) a namespace can consume.</para>
+ </listitem>
+ <listitem>
+ <para>Namespace Security Administration (HBASE-9206) - provide another level of security
+ administration for tenants.</para>
+ </listitem>
+ <listitem>
+ <para>Region server groups (HBASE-6721) - A namespace/table can be pinned onto a subset
+ of regionservers thus guaranteeing a course level of isolation.</para>
+ </listitem>
</itemizedlist>
</para>
- <section xml:id="namespace_creation">
+ <section
+ xml:id="namespace_creation">
<title>Namespace management</title>
- <para>
- A namespace can be created, removed or altered. Namespace membership is determined during
- table creation by specifying a fully-qualified table name of the form:</para>
-
- <programlisting><table namespace>:<table qualifier></programlisting>
-
+ <para> A namespace can be created, removed or altered. Namespace membership is determined
+ during table creation by specifying a fully-qualified table name of the form:</para>
+
+ <programlisting><![CDATA[<table namespace>:<table qualifier>]]></programlisting>
+
<example>
<title>Examples</title>
- <programlisting>
+ <programlisting>
#Create a namespace
create_namespace 'my_ns'
</programlisting>
@@ -227,20 +324,23 @@ alter_namespace 'my_ns', {METHOD => 'set', 'PROPERTY_NAME' => 'PROPERTY_VALUE'}
</programlisting>
</example>
</section>
- <section xml:id="namespace_special">
+ <section
+ xml:id="namespace_special">
<title>Predefined namespaces</title>
- <para>
- There are two predefined special namespaces:
- <itemizedlist>
- <listitem><para>hbase - system namespace, used to contain hbase internal tables</para></listitem>
- <listitem><para>default - tables with no explicit specified namespace will automatically
- fall into this namespace.</para></listitem>
- </itemizedlist>
- </para>
-<example>
- <title>Examples</title>
+ <para> There are two predefined special namespaces: </para>
+ <itemizedlist>
+ <listitem>
+ <para>hbase - system namespace, used to contain hbase internal tables</para>
+ </listitem>
+ <listitem>
+ <para>default - tables with no explicit specified namespace will automatically fall into
+ this namespace.</para>
+ </listitem>
+ </itemizedlist>
+ <example>
+ <title>Examples</title>
-<programlisting>
+ <programlisting>
#namespace=foo and table qualifier=bar
create 'foo:bar', 'fam'
@@ -251,85 +351,85 @@ create 'bar', 'fam'
</section>
</section>
- <section xml:id="table">
+ <section
+ xml:id="table">
<title>Table</title>
- <para>
- Tables are declared up front at schema definition time.
- </para>
+ <para> Tables are declared up front at schema definition time. </para>
</section>
- <section xml:id="row">
+ <section
+ xml:id="row">
<title>Row</title>
- <para>Row keys are uninterrpreted bytes. Rows are
- lexicographically sorted with the lowest order appearing first
- in a table. The empty byte array is used to denote both the
- start and end of a tables' namespace.</para>
+ <para>Row keys are uninterrpreted bytes. Rows are lexicographically sorted with the lowest
+ order appearing first in a table. The empty byte array is used to denote both the start and
+ end of a tables' namespace.</para>
</section>
- <section xml:id="columnfamily">
+ <section
+ xml:id="columnfamily">
<title>Column Family<indexterm><primary>Column Family</primary></indexterm></title>
- <para>
- Columns in Apache HBase are grouped into <emphasis>column families</emphasis>.
- All column members of a column family have the same prefix. For example, the
- columns <emphasis>courses:history</emphasis> and
- <emphasis>courses:math</emphasis> are both members of the
- <emphasis>courses</emphasis> column family.
- The colon character (<literal
- >:</literal>) delimits the column family from the
- <indexterm><primary>column family qualifier</primary><secondary>Column Family Qualifier</secondary></indexterm>.
- The column family prefix must be composed of
- <emphasis>printable</emphasis> characters. The qualifying tail, the
- column family <emphasis>qualifier</emphasis>, can be made of any
- arbitrary bytes. Column families must be declared up front
- at schema definition time whereas columns do not need to be
- defined at schema time but can be conjured on the fly while
- the table is up an running.</para>
- <para>Physically, all column family members are stored together on the
- filesystem. Because tunings and
- storage specifications are done at the column family level, it is
- advised that all column family members have the same general access
- pattern and size characteristics.</para>
-
- <para></para>
+ <para> Columns in Apache HBase are grouped into <emphasis>column families</emphasis>. All
+ column members of a column family have the same prefix. For example, the columns
+ <emphasis>courses:history</emphasis> and <emphasis>courses:math</emphasis> are both
+ members of the <emphasis>courses</emphasis> column family. The colon character
+ (<literal>:</literal>) delimits the column family from the <indexterm><primary>column
+ family qualifier</primary><secondary>Column Family Qualifier</secondary></indexterm>.
+ The column family prefix must be composed of <emphasis>printable</emphasis> characters. The
+ qualifying tail, the column family <emphasis>qualifier</emphasis>, can be made of any
+ arbitrary bytes. Column families must be declared up front at schema definition time whereas
+ columns do not need to be defined at schema time but can be conjured on the fly while the
+ table is up an running.</para>
+ <para>Physically, all column family members are stored together on the filesystem. Because
+ tunings and storage specifications are done at the column family level, it is advised that
+ all column family members have the same general access pattern and size
+ characteristics.</para>
+
</section>
- <section xml:id="cells">
+ <section
+ xml:id="cells">
<title>Cells<indexterm><primary>Cells</primary></indexterm></title>
- <para>A <emphasis>{row, column, version} </emphasis>tuple exactly
- specifies a <literal>cell</literal> in HBase.
- Cell content is uninterrpreted bytes</para>
+ <para>A <emphasis>{row, column, version} </emphasis>tuple exactly specifies a
+ <literal>cell</literal> in HBase. Cell content is uninterrpreted bytes</para>
</section>
- <section xml:id="data_model_operations">
- <title>Data Model Operations</title>
- <para>The four primary data model operations are Get, Put, Scan, and Delete. Operations are applied via
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html">HTable</link> instances.
- </para>
- <section xml:id="get">
+ <section
+ xml:id="data_model_operations">
+ <title>Data Model Operations</title>
+ <para>The four primary data model operations are Get, Put, Scan, and Delete. Operations are
+ applied via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html">HTable</link>
+ instances. </para>
+ <section
+ xml:id="get">
<title>Get</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html">Get</link> returns
- attributes for a specified row. Gets are executed via
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#get%28org.apache.hadoop.hbase.client.Get%29">
- HTable.get</link>.
- </para>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html">Get</link>
+ returns attributes for a specified row. Gets are executed via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#get%28org.apache.hadoop.hbase.client.Get%29">
+ HTable.get</link>. </para>
</section>
- <section xml:id="put">
+ <section
+ xml:id="put">
<title>Put</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Put.html">Put</link> either
- adds new rows to a table (if the key is new) or can update existing rows (if the key already exists). Puts are executed via
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#put%28org.apache.hadoop.hbase.client.Put%29">
- HTable.put</link> (writeBuffer) or <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#batch%28java.util.List%29">
- HTable.batch</link> (non-writeBuffer).
- </para>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Put.html">Put</link>
+ either adds new rows to a table (if the key is new) or can update existing rows (if the
+ key already exists). Puts are executed via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#put%28org.apache.hadoop.hbase.client.Put%29">
+ HTable.put</link> (writeBuffer) or <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#batch%28java.util.List%29">
+ HTable.batch</link> (non-writeBuffer). </para>
</section>
- <section xml:id="scan">
- <title>Scans</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link> allow
- iteration over multiple rows for specified attributes.
- </para>
- <para>The following is an example of a
- on an HTable table instance. Assume that a table is populated with rows with keys "row1", "row2", "row3",
- and then another set of rows with the keys "abc1", "abc2", and "abc3". The following example shows how startRow and stopRow
- can be applied to a Scan instance to return the rows beginning with "row".
-<programlisting>
+ <section
+ xml:id="scan">
+ <title>Scans</title>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scan</link>
+ allow iteration over multiple rows for specified attributes. </para>
+ <para>The following is an example of a on an HTable table instance. Assume that a table is
+ populated with rows with keys "row1", "row2", "row3", and then another set of rows with
+ the keys "abc1", "abc2", and "abc3". The following example shows how startRow and stopRow
+ can be applied to a Scan instance to return the rows beginning with "row".</para>
+ <programlisting>
public static final byte[] CF = "cf".getBytes();
public static final byte[] ATTR = "attr".getBytes();
...
@@ -348,122 +448,121 @@ try {
rs.close(); // always close the ResultScanner!
}
</programlisting>
- </para>
- <para>Note that generally the easiest way to specify a specific stop point for a scan is by using the <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/InclusiveStopFilter.html">InclusiveStopFilter</link> class.
- </para>
- </section>
- <section xml:id="delete">
+ <para>Note that generally the easiest way to specify a specific stop point for a scan is by
+ using the <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/InclusiveStopFilter.html">InclusiveStopFilter</link>
+ class. </para>
+ </section>
+ <section
+ xml:id="delete">
<title>Delete</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Delete.html">Delete</link> removes
- a row from a table. Deletes are executed via
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#delete%28org.apache.hadoop.hbase.client.Delete%29">
- HTable.delete</link>.
- </para>
- <para>HBase does not modify data in place, and so deletes are handled by creating new markers called <emphasis>tombstones</emphasis>.
- These tombstones, along with the dead values, are cleaned up on major compactions.
- </para>
- <para>See <xref linkend="version.delete"/> for more information on deleting versions of columns, and see
- <xref linkend="compaction"/> for more information on compactions.
- </para>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Delete.html">Delete</link>
+ removes a row from a table. Deletes are executed via <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/HTable.html#delete%28org.apache.hadoop.hbase.client.Delete%29">
+ HTable.delete</link>. </para>
+ <para>HBase does not modify data in place, and so deletes are handled by creating new
+ markers called <emphasis>tombstones</emphasis>. These tombstones, along with the dead
+ values, are cleaned up on major compactions. </para>
+ <para>See <xref
+ linkend="version.delete" /> for more information on deleting versions of columns, and
+ see <xref
+ linkend="compaction" /> for more information on compactions. </para>
</section>
</section>
- <section xml:id="versions">
+ <section
+ xml:id="versions">
<title>Versions<indexterm><primary>Versions</primary></indexterm></title>
- <para>A <emphasis>{row, column, version} </emphasis>tuple exactly
- specifies a <literal>cell</literal> in HBase. It's possible to have an
- unbounded number of cells where the row and column are the same but the
- cell address differs only in its version dimension.</para>
-
- <para>While rows and column keys are expressed as bytes, the version is
- specified using a long integer. Typically this long contains time
- instances such as those returned by
- <code>java.util.Date.getTime()</code> or
- <code>System.currentTimeMillis()</code>, that is: <quote>the difference,
- measured in milliseconds, between the current time and midnight, January
- 1, 1970 UTC</quote>.</para>
-
- <para>The HBase version dimension is stored in decreasing order, so that
- when reading from a store file, the most recent values are found
- first.</para>
-
- <para>There is a lot of confusion over the semantics of
- <literal>cell</literal> versions, in HBase. In particular, a couple
- questions that often come up are:<itemizedlist>
- <listitem>
- <para>If multiple writes to a cell have the same version, are all
- versions maintained or just the last?<footnote>
- <para>Currently, only the last written is fetchable.</para>
- </footnote></para>
- </listitem>
-
- <listitem>
- <para>Is it OK to write cells in a non-increasing version
- order?<footnote>
- <para>Yes</para>
- </footnote></para>
- </listitem>
- </itemizedlist></para>
-
- <para>Below we describe how the version dimension in HBase currently
- works<footnote>
+ <para>A <emphasis>{row, column, version} </emphasis>tuple exactly specifies a
+ <literal>cell</literal> in HBase. It's possible to have an unbounded number of cells where
+ the row and column are the same but the cell address differs only in its version
+ dimension.</para>
+
+ <para>While rows and column keys are expressed as bytes, the version is specified using a long
+ integer. Typically this long contains time instances such as those returned by
+ <code>java.util.Date.getTime()</code> or <code>System.currentTimeMillis()</code>, that is:
+ <quote>the difference, measured in milliseconds, between the current time and midnight,
+ January 1, 1970 UTC</quote>.</para>
+
+ <para>The HBase version dimension is stored in decreasing order, so that when reading from a
+ store file, the most recent values are found first.</para>
+
+ <para>There is a lot of confusion over the semantics of <literal>cell</literal> versions, in
+ HBase. In particular, a couple questions that often come up are:</para>
+ <itemizedlist>
+ <listitem>
+ <para>If multiple writes to a cell have the same version, are all versions maintained or
+ just the last?<footnote>
+ <para>Currently, only the last written is fetchable.</para>
+ </footnote></para>
+ </listitem>
+
+ <listitem>
+ <para>Is it OK to write cells in a non-increasing version order?<footnote>
+ <para>Yes</para>
+ </footnote></para>
+ </listitem>
+ </itemizedlist>
+
+ <para>Below we describe how the version dimension in HBase currently works<footnote>
<para>See <link
- xlink:href="https://issues.apache.org/jira/browse/HBASE-2406">HBASE-2406</link>
- for discussion of HBase versions. <link
- xlink:href="http://outerthought.org/blog/417-ot.html">Bending time
- in HBase</link> makes for a good read on the version, or time,
- dimension in HBase. It has more detail on versioning than is
- provided here. As of this writing, the limiitation
- <emphasis>Overwriting values at existing timestamps</emphasis>
- mentioned in the article no longer holds in HBase. This section is
- basically a synopsis of this article by Bruno Dumon.</para>
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-2406">HBASE-2406</link> for
+ discussion of HBase versions. <link
+ xlink:href="http://outerthought.org/blog/417-ot.html">Bending time in HBase</link>
+ makes for a good read on the version, or time, dimension in HBase. It has more detail on
+ versioning than is provided here. As of this writing, the limiitation
+ <emphasis>Overwriting values at existing timestamps</emphasis> mentioned in the
+ article no longer holds in HBase. This section is basically a synopsis of this article
+ by Bruno Dumon.</para>
</footnote>.</para>
- <section xml:id="versions.ops">
+ <section
+ xml:id="versions.ops">
<title>Versions and HBase Operations</title>
- <para>In this section we look at the behavior of the version dimension
- for each of the core HBase operations.</para>
+ <para>In this section we look at the behavior of the version dimension for each of the core
+ HBase operations.</para>
<section>
<title>Get/Scan</title>
- <para>Gets are implemented on top of Scans. The below discussion of
- <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html">Get</link> applies equally to <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scans</link>.</para>
+ <para>Gets are implemented on top of Scans. The below discussion of <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html">Get</link>
+ applies equally to <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Scan.html">Scans</link>.</para>
- <para>By default, i.e. if you specify no explicit version, when
- doing a <literal>get</literal>, the cell whose version has the
- largest value is returned (which may or may not be the latest one
- written, see later). The default behavior can be modified in the
- following ways:</para>
+ <para>By default, i.e. if you specify no explicit version, when doing a
+ <literal>get</literal>, the cell whose version has the largest value is returned
+ (which may or may not be the latest one written, see later). The default behavior can be
+ modified in the following ways:</para>
<itemizedlist>
<listitem>
<para>to return more than one version, see <link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html#setMaxVersions()">Get.setMaxVersions()</link></para>
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/client/Get.html#setMaxVersions()">Get.setMaxVersions()</link></para>
</listitem>
<listitem>
<para>to return versions other than the latest, see <link
- xlink:href="???">Get.setTimeRange()</link></para>
+ xlink:href="???">Get.setTimeRange()</link></para>
- <para>To retrieve the latest version that is less than or equal
- to a given value, thus giving the 'latest' state of the record
- at a certain point in time, just use a range from 0 to the
- desired version and set the max versions to 1.</para>
+ <para>To retrieve the latest version that is less than or equal to a given value, thus
+ giving the 'latest' state of the record at a certain point in time, just use a range
+ from 0 to the desired version and set the max versions to 1.</para>
</listitem>
</itemizedlist>
</section>
- <section xml:id="default_get_example">
- <title>Default Get Example</title>
- <para>The following Get will only retrieve the current version of the row
-<programlisting>
+ <section
+ xml:id="default_get_example">
+ <title>Default Get Example</title>
+ <para>The following Get will only retrieve the current version of the row</para>
+ <programlisting>
public static final byte[] CF = "cf".getBytes();
public static final byte[] ATTR = "attr".getBytes();
...
@@ -471,12 +570,12 @@ Get get = new Get(Bytes.toBytes("row1"));
Result r = htable.get(get);
byte[] b = r.getValue(CF, ATTR); // returns current version of value
</programlisting>
- </para>
</section>
- <section xml:id="versioned_get_example">
- <title>Versioned Get Example</title>
- <para>The following Get will return the last 3 versions of the row.
-<programlisting>
+ <section
+ xml:id="versioned_get_example">
+ <title>Versioned Get Example</title>
+ <para>The following Get will return the last 3 versions of the row.</para>
+ <programlisting>
public static final byte[] CF = "cf".getBytes();
public static final byte[] ATTR = "attr".getBytes();
...
@@ -486,26 +585,25 @@ Result r = htable.get(get);
byte[] b = r.getValue(CF, ATTR); // returns current version of value
List<KeyValue> kv = r.getColumn(CF, ATTR); // returns all versions of this column
</programlisting>
- </para>
</section>
<section>
<title>Put</title>
- <para>Doing a put always creates a new version of a
- <literal>cell</literal>, at a certain timestamp. By default the
- system uses the server's <literal>currentTimeMillis</literal>, but
- you can specify the version (= the long integer) yourself, on a
- per-column level. This means you could assign a time in the past or
- the future, or use the long value for non-time purposes.</para>
-
- <para>To overwrite an existing value, do a put at exactly the same
- row, column, and version as that of the cell you would
- overshadow.</para>
- <section xml:id="implicit_version_example">
- <title>Implicit Version Example</title>
- <para>The following Put will be implicitly versioned by HBase with the current time.
-<programlisting>
+ <para>Doing a put always creates a new version of a <literal>cell</literal>, at a certain
+ timestamp. By default the system uses the server's <literal>currentTimeMillis</literal>,
+ but you can specify the version (= the long integer) yourself, on a per-column level.
+ This means you could assign a time in the past or the future, or use the long value for
+ non-time purposes.</para>
+
+ <para>To overwrite an existing value, do a put at exactly the same row, column, and
+ version as that of the cell you would overshadow.</para>
+ <section
+ xml:id="implicit_version_example">
+ <title>Implicit Version Example</title>
+ <para>The following Put will be implicitly versioned by HBase with the current
+ time.</para>
+ <programlisting>
public static final byte[] CF = "cf".getBytes();
public static final byte[] ATTR = "attr".getBytes();
...
@@ -513,12 +611,12 @@ Put put = new Put(Bytes.toBytes(row));
put.add(CF, ATTR, Bytes.toBytes( data));
htable.put(put);
</programlisting>
- </para>
</section>
- <section xml:id="explicit_version_example">
- <title>Explicit Version Example</title>
- <para>The following Put has the version timestamp explicitly set.
-<programlisting>
+ <section
+ xml:id="explicit_version_example">
+ <title>Explicit Version Example</title>
+ <para>The following Put has the version timestamp explicitly set.</para>
+ <programlisting>
public static final byte[] CF = "cf".getBytes();
public static final byte[] ATTR = "attr".getBytes();
...
@@ -527,62 +625,63 @@ long explicitTimeInMs = 555; // just an example
put.add(CF, ATTR, explicitTimeInMs, Bytes.toBytes(data));
htable.put(put);
</programlisting>
- Caution: the version timestamp is internally by HBase for things like time-to-live calculations.
- It's usually best to avoid setting this timestamp yourself. Prefer using a separate
- timestamp attribute of the row, or have the timestamp a part of the rowkey, or both.
- </para>
+ <para>Caution: the version timestamp is internally by HBase for things like time-to-live
+ calculations. It's usually best to avoid setting this timestamp yourself. Prefer using
+ a separate timestamp attribute of the row, or have the timestamp a part of the rowkey,
+ or both. </para>
</section>
</section>
- <section xml:id="version.delete">
+ <section
+ xml:id="version.delete">
<title>Delete</title>
- <para>There are three different types of internal delete markers
- <footnote><para>See Lars Hofhansl's blog for discussion of his attempt
- adding another, <link xlink:href="http://hadoop-hbase.blogspot.com/2012/01/scanning-in-hbase.html">Scanning in HBase: Prefix Delete Marker</link></para></footnote>:
- <itemizedlist>
- <listitem><para>Delete: for a specific version of a column.</para>
+ <para>There are three different types of internal delete markers <footnote>
+ <para>See Lars Hofhansl's blog for discussion of his attempt adding another, <link
+ xlink:href="http://hadoop-hbase.blogspot.com/2012/01/scanning-in-hbase.html">Scanning
+ in HBase: Prefix Delete Marker</link></para>
+ </footnote>: </para>
+ <itemizedlist>
+ <listitem>
+ <para>Delete: for a specific version of a column.</para>
</listitem>
- <listitem><para>Delete column: for all versions of a column.</para>
+ <listitem>
+ <para>Delete column: for all versions of a column.</para>
</listitem>
- <listitem><para>Delete family: for all columns of a particular ColumnFamily</para>
+ <listitem>
+ <para>Delete family: for all columns of a particular ColumnFamily</para>
</listitem>
</itemizedlist>
- When deleting an entire row, HBase will internally create a tombstone for each ColumnFamily (i.e., not each individual column).
- </para>
- <para>Deletes work by creating <emphasis>tombstone</emphasis>
- markers. For example, let's suppose we want to delete a row. For
- this you can specify a version, or else by default the
- <literal>currentTimeMillis</literal> is used. What this means is
- <quote>delete all cells where the version is less than or equal to
- this version</quote>. HBase never modifies data in place, so for
- example a delete will not immediately delete (or mark as deleted)
- the entries in the storage file that correspond to the delete
- condition. Rather, a so-called <emphasis>tombstone</emphasis> is
- written, which will mask the deleted values<footnote>
- <para>When HBase does a major compaction, the tombstones are
- processed to actually remove the dead values, together with the
- tombstones themselves.</para>
- </footnote>. If the version you specified when deleting a row is
- larger than the version of any value in the row, then you can
- consider the complete row to be deleted.</para>
- <para>For an informative discussion on how deletes and versioning interact, see
- the thread <link xlink:href="http://comments.gmane.org/gmane.comp.java.hadoop.hbase.user/28421">Put w/ timestamp -> Deleteall -> Put w/ timestamp fails</link>
- up on the user mailing list.</para>
- <para>Also see <xref linkend="keyvalue"/> for more information on the internal KeyValue format.
- </para>
- <para>Delete markers are purged during the major compaction of store,
- unless the KEEP_DELETED_CELLS is set in the column family. In some
- scenarios, users want to keep the deletes for a time and you can set the
- delete TTL: hbase.hstore.time.to.purge.deletes in the configuration.
- If this delete TTL is not set, or set to 0, all delete markers including those
- with future timestamp are purged during the later major compaction.
- Otherwise, a delete marker is kept until the major compaction after
- marker's timestamp + delete TTL.
- </para>
+ <para>When deleting an entire row, HBase will internally create a tombstone for each
+ ColumnFamily (i.e., not each individual column). </para>
+ <para>Deletes work by creating <emphasis>tombstone</emphasis> markers. For example, let's
+ suppose we want to delete a row. For this you can specify a version, or else by default
+ the <literal>currentTimeMillis</literal> is used. What this means is <quote>delete all
+ cells where the version is less than or equal to this version</quote>. HBase never
+ modifies data in place, so for example a delete will not immediately delete (or mark as
+ deleted) the entries in the storage file that correspond to the delete condition.
+ Rather, a so-called <emphasis>tombstone</emphasis> is written, which will mask the
+ deleted values<footnote>
+ <para>When HBase does a major compaction, the tombstones are processed to actually
+ remove the dead values, together with the tombstones themselves.</para>
+ </footnote>. If the version you specified when deleting a row is larger than the version
+ of any value in the row, then you can consider the complete row to be deleted.</para>
+ <para>For an informative discussion on how deletes and versioning interact, see the thread <link
+ xlink:href="http://comments.gmane.org/gmane.comp.java.hadoop.hbase.user/28421">Put w/
+ timestamp -> Deleteall -> Put w/ timestamp fails</link> up on the user mailing
+ list.</para>
+ <para>Also see <xref
+ linkend="keyvalue" /> for more information on the internal KeyValue format. </para>
+ <para>Delete markers are purged during the major compaction of store, unless the
+ KEEP_DELETED_CELLS is set in the column family. In some scenarios, users want to keep
+ the deletes for a time and you can set the delete TTL:
+ hbase.hstore.time.to.purge.deletes in the configuration. If this delete TTL is not set,
+ or set to 0, all delete markers including those with future timestamp are purged during
+ the later major compaction. Otherwise, a delete marker is kept until the major
+ compaction after marker's timestamp + delete TTL. </para>
</section>
- </section>
+ </section>
<section>
<title>Current Limitations</title>
@@ -608,18 +707,18 @@ htable.put(put);
within the same millisecond.</para>
</section>
- <section>
+ <section
+ xml:id="major.compactions.change.query.results">
<title>Major compactions change query results</title>
-
- <para><quote>...create three cell versions at t1, t2 and t3, with a
- maximum-versions setting of 2. So when getting all versions, only
- the values at t2 and t3 will be returned. But if you delete the
- version at t2 or t3, the one at t1 will appear again. Obviously,
- once a major compaction has run, such behavior will not be the case
- anymore...<footnote>
+
+ <para><quote>...create three cell versions at t1, t2 and t3, with a maximum-versions
+ setting of 2. So when getting all versions, only the values at t2 and t3 will be
+ returned. But if you delete the version at t2 or t3, the one at t1 will appear again.
+ Obviously, once a major compaction has run, such behavior will not be the case anymore...<footnote>
<para>See <emphasis>Garbage Collection</emphasis> in <link
- xlink:href="http://outerthought.org/blog/417-ot.html">Bending
- time in HBase</link> </para>
+ xlink:href="http://outerthought.org/blog/417-ot.html">Bending time in
+ HBase</link>
+ </para>
</footnote></quote></para>
</section>
</section>
@@ -1452,7 +1551,7 @@ connection.close();</programlisting>
<para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/FilterList.html">FilterList</link>
represents a list of Filters with a relationship of <code>FilterList.Operator.MUST_PASS_ALL</code> or
<code>FilterList.Operator.MUST_PASS_ONE</code> between the Filters. The following example shows an 'or' between two
- Filters (checking for either 'my value' or 'my other value' on the same attribute).
+ Filters (checking for either 'my value' or 'my other value' on the same attribute).</para>
<programlisting>
FilterList list = new FilterList(FilterList.Operator.MUST_PASS_ONE);
SingleColumnValueFilter filter1 = new SingleColumnValueFilter(
@@ -1471,21 +1570,22 @@ SingleColumnValueFilter filter2 = new SingleColumnValueFilter(
list.add(filter2);
scan.setFilter(list);
</programlisting>
- </para>
</section>
</section>
- <section xml:id="client.filter.cv"><title>Column Value</title>
- <section xml:id="client.filter.cv.scvf"><title>SingleColumnValueFilter</title>
+ <section
+ xml:id="client.filter.cv">
+ <title>Column Value</title>
+ <section
+ xml:id="client.filter.cv.scvf">
+ <title>SingleColumnValueFilter</title>
<para><link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/SingleColumnValueFilter.html"
- >SingleColumnValueFilter</link> can be used to test column values for equivalence
- (<code><link
- xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/CompareFilter.CompareOp.html"
- >CompareOp.EQUAL</link>
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/SingleColumnValueFilter.html">SingleColumnValueFilter</link>
+ can be used to test column values for equivalence (<code><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/CompareFilter.CompareOp.html">CompareOp.EQUAL</link>
</code>), inequality (<code>CompareOp.NOT_EQUAL</code>), or ranges (e.g.,
<code>CompareOp.GREATER</code>). The following is example of testing equivalence a
- column to a String value "my value"...
- <programlisting>
+ column to a String value "my value"...</para>
+ <programlisting>
SingleColumnValueFilter filter = new SingleColumnValueFilter(
cf,
column,
@@ -1494,17 +1594,21 @@ SingleColumnValueFilter filter = new SingleColumnValueFilter(
);
scan.setFilter(filter);
</programlisting>
- </para>
</section>
</section>
- <section xml:id="client.filter.cvp"><title>Column Value Comparators</title>
- <para>There are several Comparator classes in the Filter package that deserve special mention.
- These Comparators are used in concert with other Filters, such as <xref linkend="client.filter.cv.scvf" />.
- </para>
- <section xml:id="client.filter.cvp.rcs"><title>RegexStringComparator</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/RegexStringComparator.html">RegexStringComparator</link>
- supports regular expressions for value comparisons.
-<programlisting>
+ <section
+ xml:id="client.filter.cvp">
+ <title>Column Value Comparators</title>
+ <para>There are several Comparator classes in the Filter package that deserve special
+ mention. These Comparators are used in concert with other Filters, such as <xref
+ linkend="client.filter.cv.scvf" />. </para>
+ <section
+ xml:id="client.filter.cvp.rcs">
+ <title>RegexStringComparator</title>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/RegexStringComparator.html">RegexStringComparator</link>
+ supports regular expressions for value comparisons.</para>
+ <programlisting>
RegexStringComparator comp = new RegexStringComparator("my."); // any value that starts with 'my'
SingleColumnValueFilter filter = new SingleColumnValueFilter(
cf,
@@ -1514,14 +1618,18 @@ SingleColumnValueFilter filter = new SingleColumnValueFilter(
);
scan.setFilter(filter);
</programlisting>
- See the Oracle JavaDoc for <link xlink:href="http://download.oracle.com/javase/6/docs/api/java/util/regex/Pattern.html">supported RegEx patterns in Java</link>.
- </para>
+ <para>See the Oracle JavaDoc for <link
+ xlink:href="http://download.oracle.com/javase/6/docs/api/java/util/regex/Pattern.html">supported
+ RegEx patterns in Java</link>. </para>
</section>
- <section xml:id="client.filter.cvp.SubStringComparator"><title>SubstringComparator</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/SubstringComparator.html">SubstringComparator</link>
- can be used to determine if a given substring exists in a value. The comparison is case-insensitive.
- </para>
-<programlisting>
+ <section
+ xml:id="client.filter.cvp.SubStringComparator">
+ <title>SubstringComparator</title>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/SubstringComparator.html">SubstringComparator</link>
+ can be used to determine if a given substring exists in a value. The comparison is
+ case-insensitive. </para>
+ <programlisting>
SubstringComparator comp = new SubstringComparator("y val"); // looking for 'my value'
SingleColumnValueFilter filter = new SingleColumnValueFilter(
cf,
@@ -1532,37 +1640,53 @@ SingleColumnValueFilter filter = new SingleColumnValueFilter(
scan.setFilter(filter);
</programlisting>
</section>
- <section xml:id="client.filter.cvp.bfp"><title>BinaryPrefixComparator</title>
- <para>See <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/BinaryPrefixComparator.html">BinaryPrefixComparator</link>.</para>
+ <section
+ xml:id="client.filter.cvp.bfp">
+ <title>BinaryPrefixComparator</title>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/BinaryPrefixComparator.html">BinaryPrefixComparator</link>.</para>
</section>
- <section xml:id="client.filter.cvp.bc"><title>BinaryComparator</title>
- <para>See <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/BinaryComparator.html">BinaryComparator</link>.</para>
+ <section
+ xml:id="client.filter.cvp.bc">
+ <title>BinaryComparator</title>
+ <para>See <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/BinaryComparator.html">BinaryComparator</link>.</para>
</section>
</section>
- <section xml:id="client.filter.kvm"><title>KeyValue Metadata</title>
- <para>As HBase stores data internally as KeyValue pairs, KeyValue Metadata Filters evaluate the existence of keys (i.e., ColumnFamily:Column qualifiers)
- for a row, as opposed to values the previous section.
- </para>
- <section xml:id="client.filter.kvm.ff"><title>FamilyFilter</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/FamilyFilter.html">FamilyFilter</link> can be used
- to filter on the ColumnFamily. It is generally a better idea to select ColumnFamilies in the Scan than to do it with a Filter.</para>
+ <section
+ xml:id="client.filter.kvm">
+ <title>KeyValue Metadata</title>
+ <para>As HBase stores data internally as KeyValue pairs, KeyValue Metadata Filters evaluate
+ the existence of keys (i.e., ColumnFamily:Column qualifiers) for a row, as opposed to
+ values the previous section. </para>
+ <section
+ xml:id="client.filter.kvm.ff">
+ <title>FamilyFilter</title>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/FamilyFilter.html">FamilyFilter</link>
+ can be used to filter on the ColumnFamily. It is generally a better idea to select
+ ColumnFamilies in the Scan than to do it with a Filter.</para>
</section>
- <section xml:id="client.filter.kvm.qf"><title>QualifierFilter</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/QualifierFilter.html">QualifierFilter</link> can be used
- to filter based on Column (aka Qualifier) name.
- </para>
+ <section
+ xml:id="client.filter.kvm.qf">
+ <title>QualifierFilter</title>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/QualifierFilter.html">QualifierFilter</link>
+ can be used to filter based on Column (aka Qualifier) name. </para>
</section>
- <section xml:id="client.filter.kvm.cpf"><title>ColumnPrefixFilter</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/ColumnPrefixFilter.html">ColumnPrefixFilter</link> can be used
- to filter based on the lead portion of Column (aka Qualifier) names.
- </para>
- <para>A ColumnPrefixFilter seeks ahead to the first column matching the prefix in each row and for each involved column family. It can be used to efficiently
- get a subset of the columns in very wide rows.
- </para>
- <para>Note: The same column qualifier can be used in different column families. This filter returns all matching columns.
- </para>
- <para>Example: Find all columns in a row and family that start with "abc"
-<programlisting>
+ <section
+ xml:id="client.filter.kvm.cpf">
+ <title>ColumnPrefixFilter</title>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/ColumnPrefixFilter.html">ColumnPrefixFilter</link>
+ can be used to filter based on the lead portion of Column (aka Qualifier) names. </para>
+ <para>A ColumnPrefixFilter seeks ahead to the first column matching the prefix in each row
+ and for each involved column family. It can be used to efficiently get a subset of the
+ columns in very wide rows. </para>
+ <para>Note: The same column qualifier can be used in different column families. This
+ filter returns all matching columns. </para>
+ <para>Example: Find all columns in a row and family that start with "abc"</para>
+ <programlisting>
HTableInterface t = ...;
byte[] row = ...;
byte[] family = ...;
@@ -1580,17 +1704,19 @@ for (Result r = rs.next(); r != null; r = rs.next()) {
}
rs.close();
</programlisting>
-</para>
</section>
- <section xml:id="client.filter.kvm.mcpf"><title>MultipleColumnPrefixFilter</title>
- <para><link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/MultipleColumnPrefixFilter.html">MultipleColumnPrefixFilter</link> behaves like ColumnPrefixFilter
- but allows specifying multiple prefixes.
- </para>
- <para>Like ColumnPrefixFilter, MultipleColumnPrefixFilter efficiently seeks ahead to the first column matching the lowest prefix and also seeks past ranges of columns between prefixes.
- It can be used to efficiently get discontinuous sets of columns from very wide rows.
- </para>
- <para>Example: Find all columns in a row and family that start with "abc" or "xyz"
-<programlisting>
+ <section
+ xml:id="client.filter.kvm.mcpf">
+ <title>MultipleColumnPrefixFilter</title>
+ <para><link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/MultipleColumnPrefixFilter.html">MultipleColumnPrefixFilter</link>
+ behaves like ColumnPrefixFilter but allows specifying multiple prefixes. </para>
+ <para>Like ColumnPrefixFilter, MultipleColumnPrefixFilter efficiently seeks ahead to the
+ first column matching the lowest prefix and also seeks past ranges of columns between
+ prefixes. It can be used to efficiently get discontinuous sets of columns from very wide
+ rows. </para>
+ <para>Example: Find all columns in a row and family that start with "abc" or "xyz"</para>
+ <programlisting>
HTableInterface t = ...;
byte[] row = ...;
byte[] family = ...;
@@ -1608,19 +1734,22 @@ for (Result r = rs.next(); r != null; r = rs.next()) {
}
rs.close();
</programlisting>
-</para>
</section>
- <section xml:id="client.filter.kvm.crf "><title>ColumnRangeFilter</title>
- <para>A <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/ColumnRangeFilter.html">ColumnRangeFilter</link> allows efficient intra row scanning.
- </para>
- <para>A ColumnRangeFilter can seek ahead to the first matching column for each involved column family. It can be used to efficiently
- get a 'slice' of the columns of a very wide row.
- i.e. you have a million columns in a row but you only want to look at columns bbbb-bbdd.
- </para>
- <para>Note: The same column qualifier can be used in different column families. This filter returns all matching columns.
- </para>
- <para>Example: Find all columns in a row and family between "bbbb" (inclusive) and "bbdd" (inclusive)
-<programlisting>
+ <section
+ xml:id="client.filter.kvm.crf ">
+ <title>ColumnRangeFilter</title>
+ <para>A <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/filter/ColumnRangeFilter.html">ColumnRangeFilter</link>
+ allows efficient intra row scanning. </para>
+ <para>A ColumnRangeFilter can seek ahead to the first matching column for each involved
+ column family. It can be used to efficiently get a 'slice' of the columns of a very wide
+ row. i.e. you have a million columns in a row but you only want to look at columns
+ bbbb-bbdd. </para>
+ <para>Note: The same column qualifier can be used in different column families. This
+ filter returns all matching columns. </para>
+ <para>Example: Find all columns in a row and family between "bbbb" (inclusive) and "bbdd"
+ (inclusive)</para>
+ <programlisting>
HTableInterface t = ...;
byte[] row = ...;
byte[] family = ...;
@@ -1639,7 +1768,6 @@ for (Result r = rs.next(); r != null; r = rs.next()) {
}
rs.close();
</programlisting>
-</para>
<para>Note: Introduced in HBase 0.92</para>
</section>
</section>
@@ -2279,18 +2407,297 @@ myHtd.setValue(HTableDescriptor.SPLIT_POLICY, MyCustomSplitPolicy.class.getName(
</section>
</section>
- <section xml:id="compaction">
- <title>Compaction</title>
- <para>There are two types of compactions: minor and major. Minor compactions will usually pick up a couple of the smaller adjacent
- StoreFiles and rewrite them as one. Minors do not drop deletes or expired cells, only major compactions do this. Sometimes a minor compaction
- will pick up all the StoreFiles in the Store and in this case it actually promotes itself to being a major compaction.
- </para>
- <para>After a major compaction runs there will be a single StoreFile per Store, and this will help performance usually. Caution: major compactions rewrite all of the Stores data and on a loaded system, this may not be tenable;
- major compactions will usually have to be done manually on large systems. See <xref linkend="managed.compactions" />.
- </para>
- <para>Compactions will <emphasis>not</emphasis> perform region merges. See <xref linkend="ops.regionmgt.merge"/> for more information on region merging.
- </para>
- <section xml:id="compaction.file.selection">
+ <section
+ xml:id="compaction">
+ <title>Compaction</title>
+ <para><firstterm>Compaction</firstterm> is an operation which reduces the number of
+ StoreFiles, by merging them together, in order to increase performance on read
+ operations. Compactions can be resource-intensive to perform, and can either help or
+ hinder performance depending on many factors. </para>
+ <para>Compactions fall into two categories: minor and major.</para>
+ <para><firstterm>Minor compactions</firstterm> usually pick up a small number of small,
+ adjacent <systemitem>StoreFiles</systemitem> and rewrite them as a single
+ <systemitem>StoreFile</systemitem>. Minor compactions do not drop deletes or expired
+ cells. If a minor compaction picks up all the <systemitem>StoreFiles</systemitem> in a
+ <systemitem>Store</systemitem>, it promotes itself from a minor to a major compaction.
+ If there are a lot of small files to be compacted, the algorithm tends to favor minor
+ compactions to "clean up" those small files.</para>
+ <para>The goal of a <firstterm>major compaction</firstterm> is to end up with a single
+ StoreFile per store. Major compactions also process delete markers and max versions.
+ Attempting to process these during a minor compaction could cause side effects. </para>
+
+ <formalpara>
+ <title>Compaction and Deletions</title>
+ <para> When an explicit deletion occurs in HBase, the data is not actually deleted.
+ Instead, a <firstterm>tombstone</firstterm> marker is written. The tombstone marker
+ prevents the data from being returned with queries. During a major compaction, the
+ data is actually deleted, and the tombstone marker is removed from the StoreFile. If
+ the deletion happens because of an expired TTL, no tombstone is created. Instead, the
+ expired data is filtered out and is not written back to the compacted StoreFile.</para>
+ </formalpara>
+
+ <formalpara>
+ <title>Compaction and Versions</title>
+ <para> When you create a column family, you can specify the maximum number of versions
+ to keep, by specifying <varname>HColumnDescriptor.setMaxVersions(int
+ versions)</varname>. The default value is <literal>3</literal>. If more versions
+ than the specified maximum exist, the excess versions are filtered out and not written
+ back to the compacted StoreFile.</para>
+ </formalpara>
+
+ <note>
+ <title>Major Compactions Can Impact Query Results</title>
+ <para> In some situations, older versions can be inadvertently
+ resurrected if a newer version is explicitly deleted. See <xref
+ linkend="major.compactions.change.query.results" /> for a more in-depth explanation. This
+ situation is only possible before the compaction finishes.
+ </para>
+ </note>
+
+ <para>In theory, major compactions improve performance. However, on a highly loaded
+ system, major compactions can require an inappropriate number of resources and adversely
+ affect performance. In a default configuration, major compactions are scheduled
+ automatically to run once in a 7-day period. This is usually inappropriate for systems
+ in production. You can manage major compactions manually. See <xref
+ linkend="managed.compactions" />. </para>
+ <para>Compactions do not perform region merges. See <xref
+ linkend="ops.regionmgt.merge" /> for more information on region merging. </para>
+ <section
+ xml:id="compaction.file.selection">
+ <title>Algorithm for Compaction File Selection - HBase 0.96.x and newer</title>
+ <para>The compaction algorithms used by HBase have evolved over time. HBase 0.96
+ introduced new algorithms for compaction file selection. To find out about the old
+ algorithms, see <xref
+ linkend="compaction" />. The rest of this section describes the new algorithm. File
+ selection happens in several phases and is controlled by several configurable
+ parameters. These parameters will be explained in context, and then will be given in a
+ table which shows their descriptions, defaults, and implications of changing
+ them.</para>
+
+ <formalpara>
+ <title>The<link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-7842">Exploring Compaction Policy</link></title>
+ <para><link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-7842">HBASE-7842</link>
+ was introduced in HBase 0.96 and represents a major change in the algorithms for
+ file selection for compactions. Its goal is to do the most impactful compaction with
+ the lowest cost, in situations where a lot of files need compaction. In such a
+ situation, the list of all eligible files is "explored", and files are grouped by
+ size before any ratio-based algorithms are run. This favors clean-up of large
+ numbers of small files before larger files are considered. For more details, refer
+ to the link to the JIRA. Most of the code for this change can be reviewed in
+ <filename>hbase-server/src/main/java/org/apache/hadoop/hbase/regionserver/compactions/ExploringCompactionPolicy.java</filename>.</para>
+ </formalpara>
+
+ <variablelist>
+ <title>Algorithms for Determining File List and Compaction Type</title>
+ <varlistentry>
+ <term>Create a list of all files which can possibly be compacted, ordered by
+ sequence ID.</term>
+ <listitem>
+ <para>The first phase is to create a list of all candidates for compaction. A list
+ is created of all StoreFiles not already in the compaction queue, and all files
+ newer than the newest file that is currently being compacted. This list of files
+ is ordered by the sequence ID. The sequence ID is generated when a Put is
+ appended to the write-ahead log (WAL), and is stored in the metadata of the
+ StoreFile.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>Check to see if major compaction is required because there are too many
+ StoreFiles and the memstore is too large.</term>
+ <listitem>
+ <para>A store can only <varname>have hbase.hstore.blockingStoreFiles</varname>. If
+ the store has too many files, you cannot flush data. In addition, you cannot
+ perform an insert if the memstore is over
+ <varname>hbase.hregion.memstore.flush.size</varname>. Normally, minor
+ compactions will alleviate this situation. However, if the normal compaction
+ algorithm do not find any normally-eligible StoreFiles, a major compaction is
+ the only way to get out of this situation, and is forced. This is also called a
+ size-based or size-triggered major compaction.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>If this compaction was user-requested, do a major compaction.</term>
+ <listitem>
+ <para>Compactions can run on a schedule or can be initiated manually. If a
+ compaction is requested manually, it is always a major compaction. If the
+ compaction is user-requested, the major compaction still happens even if the are
+ more than <varname>hbase.hstore.compaction.max</varname> files that need
+ compaction.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>Exclude files which are too large.</term>
+ <listitem>
+ <para>The purpose of compaction is to merge small files together, and it is
+ counterproductive to compact files which are too large. Files larger than
+ <varname>hbase.hstore.compaction.max.size</varname> are excluded from
+ consideration.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>If configured, exclude bulk-loaded files.</term>
+ <listitem>
+ <para>You may decide to exclude bulk-loaded files from compaction, in the bulk
+ load operation, by specifying the
+ <varname>hbase.mapreduce.hfileoutputformat.compaction.exclude
+ parameter.</varname> If a bulk-loaded file was excluded, it is removed from
+ consideration at this point.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>If there are too many files to compact, do a minor compaction.</term>
+ <listitem>
+ <para>The maximum number of files allowed in a major compaction is controlled by
+ the <varname>hbase.hstore.compaction.max</varname> parameter. If the list
+ contains more than this number of files, a compaction that would otherwise be a
+ major compaction is downgraded to a minor compaction. However, a user-requested
+ major compaction still occurs even if there are more than
+ <varname>hbase.hstore.compaction.max</varname> files to compact.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>Only run the compaction if enough files need to be compacted.</term>
+ <listitem>
+ <para>If the list contains fewer than
+ <varname>hbase.hstore.compaction.min</varname> files to compact, compaction is
+ aborted.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>If this is a minor compaction, determine which files are eligible, based upon
+ the <varname>hbase.store.compaction.ratio</varname>.</term>
+ <listitem>
+ <para>The value of the <varname>hbase.store.compaction.ratio</varname> parameter
+ is multiplied by the sum of files smaller than a given file, to determine
+ whether that file is selected for compaction during a minor compaction. For
+ instance, if hbase.store.compaction.ratio is 1.2, FileX is 5 mb, FileY is 2 mb,
+ and FileZ is 3 mb:</para>
+ <screen>5 <= 1.2 x (2 + 3) or 5 <= 6</screen>
+ <para>In this scenario, FileX is eligible for minor compaction. If FileX were 7
+ mb, it would not be eligible for minor compaction. This ratio favors smaller
+ files. You can configure a different ratio for use in off-peak hours, using the
+ parameter <varname>hbase.hstore.compaction.ratio.offpeak</varname>, if you also
+ configure <varname>hbase.offpeak.start.hour</varname> and
+ <varname>hbase.offpeak.end.hour</varname>.</para>
+ </listitem>
+ </varlistentry>
+ <varlistentry>
+ <term>If major compactions are not managed manually, and it has been too long since
+ the last major compaction, run a major compaction anyway.</term>
+ <listitem>
+ <para>If the last major compaction was too long ago and there is more than one
+ file to be compacted, a major compaction is run, even if it would otherwise have
+ been minor. By default, the maximum time between major compactions is 7 days,
+ plus or minus a 4.8 hour period, and determined randomly within those
+ parameters. Prior to HBase 0.96, the major compaction period was 24 hours. This
+ is also referred to as a time-based or time-triggered major compaction. See
+ <varname>hbase.hregion.majorcompaction</varname> in the table below to tune or
+ disable time-based major compactions.</para>
+ </listitem>
+ </varlistentry>
+ </variablelist>
+ <table>
+ <title>Parameters Used by Compaction Algorithm</title>
+ <textobject>
+ <para>This table contains the main configuration parameters for compaction. This
+ list is not exhaustive. To tune these parameters from the defaults, edit the
+ <filename>hbase-default.xml</filename> file. For a full list of all
+ configuration parameters available, see <xref
+ linkend="config.files" />.</para>
+ </textobject>
+ <tgroup
+ cols="3">
+ <thead>
+ <row>
+ <entry>Parameter</entry>
+ <entry>Description</entry>
+ <entry>Default</entry>
+ </row>
+ </thead>
+ <tbody>
+ <row>
+ <entry>hbase.hstore.compaction.min</entry>
+ <entry>The minimum number of files which must be eligible for compaction before
+ compaction can run.</entry>
+ <entry>3</entry>
+ </row>
+ <row>
+ <entry>hbase.hstore.compaction.max</entry>
+ <entry>The maximum number of files which will be selected for a single minor
+ compaction, regardless of the number of eligible files.</entry>
+ <entry>10</entry>
+ </row>
+ <row>
+ <entry>hbase.hstore.compaction.min.size</entry>
+ <entry>A StoreFile smaller than this size (in bytes) will always be eligible for
+ minor compaction.</entry>
+ <entry>10</entry>
+ </row>
+ <row>
+ <entry>hbase.hstore.compaction.max.size</entry>
+ <entry>A StoreFile larger than this size (in bytes) will be excluded from minor
+ compaction.</entry>
+ <entry>1000</entry>
+ </row>
+ <row>
+ <entry>hbase.store.compaction.ratio</entry>
+ <entry>For minor compaction, this ratio is used to determine whether a given
+ file is eligible for compaction. Its effect is to limit compaction of large
+ files. Expressed as a floating-point decimal.</entry>
+ <entry>1.2F</entry>
+ </row>
+ <row>
+ <entry>hbase.hstore.compaction.ratio.offpeak</entry>
+ <entry>The compaction ratio used during off-peak compactions, if off-peak is
+ enabled. Expressed as a floating-point decimal. This allows for more
+ aggressive compaction, because in theory, the cluster is under less load.
+ Ignored if off-peak is disabled (default).</entry>
+ <entry>5.0F</entry>
+ </row>
+ <row>
+ <entry>hbase.offpeak.start.hour</entry>
+ <entry>The start of off-peak hours, expressed as an integer between 0 and 23,
+ inclusive. Set to <literal>-1</literal> to disable off-peak.</entry>
+ <entry>-1 (disabled)</entry>
+ </row>
+ <row>
+ <entry>hbase.offpeak.end.hour</entry>
+ <entry>The end of off-peak hours, expressed as an integer between 0 and 23,
+ inclusive. Set to <literal>-1</literal> to disable off-peak.</entry>
+ <entry>-1 (disabled)</entry>
+ </row>
+ <row>
+ <entry>hbase.regionserver.thread.compaction.throttle</entry>
+ <entry>Throttles compaction if too much of a backlog of compaction work
+ exists.</entry>
+ <entry>2 x hbase.hstore.compaction.max x hbase.hregion.memstore.flush.size
+ (which defaults to 128)</entry>
+ </row>
+ <row>
+ <entry>hbase.hregion.majorcompaction</entry>
+ <entry>Time between major compactions, expressed in milliseconds. Set to 0 to
+ disable time-based automatic major compactions. User-requested and size-based
<TRUNCATED>
[10/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/cp.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/cp.xml b/src/main/docbkx/cp.xml
index 71f0c75..0dac7b7 100644
--- a/src/main/docbkx/cp.xml
+++ b/src/main/docbkx/cp.xml
@@ -1,12 +1,15 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="cp" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ version="5.0"
+ xml:id="cp"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -26,8 +29,9 @@
*/
-->
<title>Apache HBase Coprocessors</title>
- <para>The idea of HBase coprocessors was inspired by Google's BigTable coprocessors. The <link xlink:href="https://blogs.apache.org/hbase/entry/coprocessor_introduction">Apache HBase Blog on Coprocessor</link> is a very good documentation on that. It has detailed information about the coprocessor framework, terminology, management, and so on.
- </para>
+ <para>The idea of HBase coprocessors was inspired by Google's BigTable coprocessors. The <link
+ xlink:href="https://blogs.apache.org/hbase/entry/coprocessor_introduction">Apache HBase Blog
+ on Coprocessor</link> is a very good documentation on that. It has detailed information about
+ the coprocessor framework, terminology, management, and so on. </para>
</chapter>
-
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/developer.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/developer.xml b/src/main/docbkx/developer.xml
index 92eadb5..73d7cac 100644
--- a/src/main/docbkx/developer.xml
+++ b/src/main/docbkx/developer.xml
@@ -1,13 +1,15 @@
<?xml version="1.0"?>
- <chapter xml:id="developer"
- version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ xml:id="developer"
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -502,7 +504,7 @@ HBase have a character not usually seen in other projects.</para>
integration with corresponding JUnit <link xlink:href="http://www.junit.org/node/581">categories</link>:
<classname>SmallTests</classname>, <classname>MediumTests</classname>,
<classname>LargeTests</classname>, <classname>IntegrationTests</classname>.
-JUnit categories are denoted using java annotations and look like this in your unit test code.
+JUnit categories are denoted using java annotations and look like this in your unit test code.</para>
<programlisting>...
@Category(SmallTests.class)
public class TestHRegionInfo {
@@ -511,360 +513,447 @@ public class TestHRegionInfo {
// ...
}
}</programlisting>
-The above example shows how to mark a unit test as belonging to the small category.
-All unit tests in HBase have a categorization.
-</para>
-<para>
-The first three categories, small, medium, and large are for tests run when
-you type <code>$ mvn test</code>; i.e. these three categorizations are for
-HBase unit tests. The integration category is for not for unit tests but for integration
-tests. These are run when you invoke <code>$ mvn verify</code>. Integration tests
-are described in <xref linkend="integration.tests"/> and will not be discussed further
-in this section on HBase unit tests.</para>
-<para>
-Apache HBase uses a patched maven surefire plugin and maven profiles to implement
-its unit test characterizations.
-</para>
-<para>Read the below to figure which annotation of the set small, medium, and large to
-put on your new HBase unit test.
-</para>
-
-<section xml:id="hbase.unittests.small">
-<title>Small Tests<indexterm><primary>SmallTests</primary></indexterm></title>
-<para>
-<emphasis>Small</emphasis> tests are executed in a shared JVM. We put in this category all the tests that can
-be executed quickly in a shared JVM. The maximum execution time for a small test is 15 seconds,
-and small tests should not use a (mini)cluster.</para>
-</section>
+ <para>The above example shows how to mark a unit test as belonging to the small category.
+ All unit tests in HBase have a categorization. </para>
+ <para> The first three categories, small, medium, and large are for tests run when you
+ type <code>$ mvn test</code>; i.e. these three categorizations are for HBase unit
+ tests. The integration category is for not for unit tests but for integration tests.
+ These are run when you invoke <code>$ mvn verify</code>. Integration tests are
+ described in <xref
+ linkend="integration.tests" /> and will not be discussed further in this section
+ on HBase unit tests.</para>
+ <para> Apache HBase uses a patched maven surefire plugin and maven profiles to implement
+ its unit test characterizations. </para>
+ <para>Read the below to figure which annotation of the set small, medium, and large to
+ put on your new HBase unit test. </para>
+
+ <section
+ xml:id="hbase.unittests.small">
+ <title>Small Tests<indexterm><primary>SmallTests</primary></indexterm></title>
+ <para>
+ <emphasis>Small</emphasis> tests are executed in a shared JVM. We put in this
+ category all the tests that can be executed quickly in a shared JVM. The maximum
+ execution time for a small test is 15 seconds, and small tests should not use a
+ (mini)cluster.</para>
+ </section>
-<section xml:id="hbase.unittests.medium">
-<title>Medium Tests<indexterm><primary>MediumTests</primary></indexterm></title>
-<para><emphasis>Medium</emphasis> tests represent tests that must be executed
-before proposing a patch. They are designed to run in less than 30 minutes altogether,
-and are quite stable in their results. They are designed to last less than 50 seconds
-individually. They can use a cluster, and each of them is executed in a separate JVM.
-</para>
-</section>
+ <section
+ xml:id="hbase.unittests.medium">
+ <title>Medium Tests<indexterm><primary>MediumTests</primary></indexterm></title>
+ <para><emphasis>Medium</emphasis> tests represent tests that must be executed before
+ proposing a patch. They are designed to run in less than 30 minutes altogether,
+ and are quite stable in their results. They are designed to last less than 50
+ seconds individually. They can use a cluster, and each of them is executed in a
+ separate JVM. </para>
+ </section>
-<section xml:id="hbase.unittests.large">
-<title>Large Tests<indexterm><primary>LargeTests</primary></indexterm></title>
-<para><emphasis>Large</emphasis> tests are everything else. They are typically large-scale
-tests, regression tests for specific bugs, timeout tests, performance tests.
-They are executed before a commit on the pre-integration machines. They can be run on
-the developer machine as well.
-</para>
-</section>
-<section xml:id="hbase.unittests.integration">
-<title>Integration Tests<indexterm><primary>IntegrationTests</primary></indexterm></title>
-<para><emphasis>Integration</emphasis> tests are system level tests. See
-<xref linkend="integration.tests"/> for more info.
-</para>
-</section>
-</section>
+ <section
+ xml:id="hbase.unittests.large">
+ <title>Large Tests<indexterm><primary>LargeTests</primary></indexterm></title>
+ <para><emphasis>Large</emphasis> tests are everything else. They are typically
+ large-scale tests, regression tests for specific bugs, timeout tests,
+ performance tests. They are executed before a commit on the pre-integration
+ machines. They can be run on the developer machine as well. </para>
+ </section>
+ <section
+ xml:id="hbase.unittests.integration">
+ <title>Integration
+ Tests<indexterm><primary>IntegrationTests</primary></indexterm></title>
+ <para><emphasis>Integration</emphasis> tests are system level tests. See <xref
+ linkend="integration.tests" /> for more info. </para>
+ </section>
+ </section>
-<section xml:id="hbase.unittests.cmds">
-<title>Running tests</title>
-<para>Below we describe how to run the Apache HBase junit categories.</para>
-
-<section xml:id="hbase.unittests.cmds.test">
-<title>Default: small and medium category tests
-</title>
-<para>Running <programlisting>mvn test</programlisting> will execute all small tests in a single JVM
-(no fork) and then medium tests in a separate JVM for each test instance.
-Medium tests are NOT executed if there is an error in a small test.
-Large tests are NOT executed. There is one report for small tests, and one report for
-medium tests if they are executed.
-</para>
-</section>
+ <section
+ xml:id="hbase.unittests.cmds">
+ <title>Running tests</title>
+ <para>Below we describe how to run the Apache HBase junit categories.</para>
+
+ <section
+ xml:id="hbase.unittests.cmds.test">
+ <title>Default: small and medium category tests </title>
+ <para>Running <programlisting>mvn test</programlisting> will execute all small tests
+ in a single JVM (no fork) and then medium tests in a separate JVM for each test
+ instance. Medium tests are NOT executed if there is an error in a small test.
+ Large tests are NOT executed. There is one report for small tests, and one
+ report for medium tests if they are executed. </para>
+ </section>
-<section xml:id="hbase.unittests.cmds.test.runAllTests">
-<title>Running all tests</title>
-<para>Running <programlisting>mvn test -P runAllTests</programlisting>
-will execute small tests in a single JVM then medium and large tests in a separate JVM for each test.
-Medium and large tests are NOT executed if there is an error in a small test.
-Large tests are NOT executed if there is an error in a small or medium test.
-There is one report for small tests, and one report for medium and large tests if they are executed.
-</para>
-</section>
+ <section
+ xml:id="hbase.unittests.cmds.test.runAllTests">
+ <title>Running all tests</title>
+ <para>Running <programlisting>mvn test -P runAllTests</programlisting> will execute
+ small tests in a single JVM then medium and large tests in a separate JVM for
+ each test. Medium and large tests are NOT executed if there is an error in a
+ small test. Large tests are NOT executed if there is an error in a small or
+ medium test. There is one report for small tests, and one report for medium and
+ large tests if they are executed. </para>
+ </section>
-<section xml:id="hbase.unittests.cmds.test.localtests.mytest">
-<title>Running a single test or all tests in a package</title>
-<para>To run an individual test, e.g. <classname>MyTest</classname>, do
-<programlisting>mvn test -Dtest=MyTest</programlisting> You can also
-pass multiple, individual tests as a comma-delimited list:
-<programlisting>mvn test -Dtest=MyTest1,MyTest2,MyTest3</programlisting>
-You can also pass a package, which will run all tests under the package:
-<programlisting>mvn test '-Dtest=org.apache.hadoop.hbase.client.*'</programlisting>
-</para>
+ <section
+ xml:id="hbase.unittests.cmds.test.localtests.mytest">
+ <title>Running a single test or all tests in a package</title>
+ <para>To run an individual test, e.g. <classname>MyTest</classname>, do
+ <programlisting>mvn test -Dtest=MyTest</programlisting> You can also pass
+ multiple, individual tests as a comma-delimited list:
+ <programlisting>mvn test -Dtest=MyTest1,MyTest2,MyTest3</programlisting> You can
+ also pass a package, which will run all tests under the package:
+ <programlisting>mvn test '-Dtest=org.apache.hadoop.hbase.client.*'</programlisting>
+ </para>
-<para>
-When <code>-Dtest</code> is specified, <code>localTests</code> profile will be used. It will use the official release
-of maven surefire, rather than our custom surefire plugin, and the old connector (The HBase build uses a patched
-version of the maven surefire plugin). Each junit tests is executed in a separate JVM (A fork per test class).
-There is no parallelization when tests are running in this mode. You will see a new message at the end of the
--report: "[INFO] Tests are skipped". It's harmless. While you need to make sure the sum of <code>Tests run:</code> in
-the <code>Results :</code> section of test reports matching the number of tests you specified because no
-error will be reported when a non-existent test case is specified.
-</para>
-</section>
+ <para> When <code>-Dtest</code> is specified, <code>localTests</code> profile will
+ be used. It will use the official release of maven surefire, rather than our
+ custom surefire plugin, and the old connector (The HBase build uses a patched
+ version of the maven surefire plugin). Each junit tests is executed in a
+ separate JVM (A fork per test class). There is no parallelization when tests are
+ running in this mode. You will see a new message at the end of the -report:
+ "[INFO] Tests are skipped". It's harmless. While you need to make sure the sum
+ of <code>Tests run:</code> in the <code>Results :</code> section of test reports
+ matching the number of tests you specified because no error will be reported
+ when a non-existent test case is specified. </para>
+ </section>
-<section xml:id="hbase.unittests.cmds.test.profiles">
-<title>Other test invocation permutations</title>
-<para>Running <programlisting>mvn test -P runSmallTests</programlisting> will execute "small" tests only, using a single JVM.
-</para>
-<para>Running <programlisting>mvn test -P runMediumTests</programlisting> will execute "medium" tests only, launching a new JVM for each test-class.
-</para>
-<para>Running <programlisting>mvn test -P runLargeTests</programlisting> will execute "large" tests only, launching a new JVM for each test-class.
-</para>
-<para>For convenience, you can run <programlisting>mvn test -P runDevTests</programlisting> to execute both small and medium tests, using a single JVM.
-</para>
-</section>
+ <section
+ xml:id="hbase.unittests.cmds.test.profiles">
+ <title>Other test invocation permutations</title>
+ <para>Running <command>mvn test -P runSmallTests</command> will execute "small"
+ tests only, using a single JVM. </para>
+ <para>Running <command>mvn test -P runMediumTests</command> will execute "medium"
+ tests only, launching a new JVM for each test-class. </para>
+ <para>Running <command>mvn test -P runLargeTests</command> will execute "large"
+ tests only, launching a new JVM for each test-class. </para>
+ <para>For convenience, you can run <command>mvn test -P runDevTests</command> to
+ execute both small and medium tests, using a single JVM. </para>
+ </section>
-<section xml:id="hbase.unittests.test.faster">
-<title>Running tests faster</title>
-<para> By default, <code>$ mvn test -P runAllTests</code> runs 5 tests in parallel. It can be
- increased on a developer's machine. Allowing that you can have 2 tests in
- parallel per core, and you need about 2Gb of memory per test (at the extreme),
- if you have an 8 core, 24Gb box, you can have 16 tests in parallel. but the
- memory available limits it to 12 (24/2), To run all tests with 12 tests in
- parallel, do this: <command>mvn test -P runAllTests
+ <section
+ xml:id="hbase.unittests.test.faster">
+ <title>Running tests faster</title>
+ <para> By default, <code>$ mvn test -P runAllTests</code> runs 5 tests in parallel.
+ It can be increased on a developer's machine. Allowing that you can have 2 tests
+ in parallel per core, and you need about 2Gb of memory per test (at the
+ extreme), if you have an 8 core, 24Gb box, you can have 16 tests in parallel.
+ but the memory available limits it to 12 (24/2), To run all tests with 12 tests
+ in parallel, do this: <command>mvn test -P runAllTests
-Dsurefire.secondPartThreadCount=12</command>. To increase the speed, you
can as well use a ramdisk. You will need 2Gb of memory to run all tests. You
will also need to delete the files between two test run. The typical way to
- configure a ramdisk on Linux is:
- <programlisting>$ sudo mkdir /ram2G
-sudo mount -t tmpfs -o size=2048M tmpfs /ram2G</programlisting>
- You can then use it to run all HBase tests with the command: <command>mvn test
+ configure a ramdisk on Linux is:</para>
+ <screen>$ sudo mkdir /ram2G
+sudo mount -t tmpfs -o size=2048M tmpfs /ram2G</screen>
+ <para>You can then use it to run all HBase tests with the command: </para>
+ <screen>mvn test
-P runAllTests -Dsurefire.secondPartThreadCount=12
- -Dtest.build.data.basedirectory=/ram2G</command>
- </para>
-</section>
-
-<section xml:id="hbase.unittests.cmds.test.hbasetests">
-<title><command>hbasetests.sh</command></title>
-<para>It's also possible to use the script <command>hbasetests.sh</command>. This script runs the medium and
-large tests in parallel with two maven instances, and provides a single report. This script does not use
-the hbase version of surefire so no parallelization is being done other than the two maven instances the
-script sets up.
-It must be executed from the directory which contains the <filename>pom.xml</filename>.</para>
-<para>For example running
-<programlisting>./dev-support/hbasetests.sh</programlisting> will execute small and medium tests.
-Running <programlisting>./dev-support/hbasetests.sh runAllTests</programlisting> will execute all tests.
-Running <programlisting>./dev-support/hbasetests.sh replayFailed</programlisting> will rerun the failed tests a
-second time, in a separate jvm and without parallelisation.
-</para>
-</section>
-<section xml:id="hbase.unittests.resource.checker">
-<title>Test Resource Checker<indexterm><primary>Test Resource Checker</primary></indexterm></title>
-<para>
-A custom Maven SureFire plugin listener checks a number of resources before
-and after each HBase unit test runs and logs its findings at the end of the test
-output files which can be found in <filename>target/surefire-reports</filename>
-per Maven module (Tests write test reports named for the test class into this directory.
-Check the <filename>*-out.txt</filename> files). The resources counted are the number
-of threads, the number of file descriptors, etc. If the number has increased, it adds
-a <emphasis>LEAK?</emphasis> comment in the logs. As you can have an HBase instance
-running in the background, some threads can be deleted/created without any specific
-action in the test. However, if the test does not work as expected, or if the test
-should not impact these resources, it's worth checking these log lines
-<computeroutput>...hbase.ResourceChecker(157): before...</computeroutput> and
-<computeroutput>...hbase.ResourceChecker(157): after...</computeroutput>. For example:
-<computeroutput>
-2012-09-26 09:22:15,315 INFO [pool-1-thread-1] hbase.ResourceChecker(157): after: regionserver.TestColumnSeeking#testReseeking Thread=65 (was 65), OpenFileDescriptor=107 (was 107), MaxFileDescriptor=10240 (was 10240), ConnectionCount=1 (was 1)
-</computeroutput>
-</para>
-</section>
-</section>
-
-<section xml:id="hbase.tests.writing">
-<title>Writing Tests</title>
-<section xml:id="hbase.tests.rules">
-<title>General rules</title>
-<itemizedlist>
-<listitem>
-<para>As much as possible, tests should be written as category small tests.</para>
-</listitem>
-<listitem>
-<para>All tests must be written to support parallel execution on the same machine, hence they should not use shared resources as fixed ports or fixed file names.</para>
-</listitem>
-<listitem>
-<para>Tests should not overlog. More than 100 lines/second makes the logs complex to read and use i/o that are hence not available for the other tests.</para>
-</listitem>
-<listitem>
-<para>Tests can be written with <classname>HBaseTestingUtility</classname>.
-This class offers helper functions to create a temp directory and do the cleanup, or to start a cluster.</para>
-</listitem>
-</itemizedlist>
-</section>
-<section xml:id="hbase.tests.categories">
-<title>Categories and execution time</title>
-<itemizedlist>
-<listitem>
-<para>All tests must be categorized, if not they could be skipped.</para>
-</listitem>
-<listitem>
-<para>All tests should be written to be as fast as possible.</para>
-</listitem>
-<listitem>
-<para>Small category tests should last less than 15 seconds, and must not have any side effect.</para>
-</listitem>
-<listitem>
-<para>Medium category tests should last less than 50 seconds.</para>
-</listitem>
-<listitem>
-<para>Large category tests should last less than 3 minutes. This should ensure a good parallelization for people using it, and ease the analysis when the test fails.</para>
-</listitem>
-</itemizedlist>
-</section>
-<section xml:id="hbase.tests.sleeps">
-<title>Sleeps in tests</title>
-<para>Whenever possible, tests should not use <methodname>Thread.sleep</methodname>, but rather waiting for the real event they need. This is faster and clearer for the reader.
-Tests should not do a <methodname>Thread.sleep</methodname> without testing an ending condition. This allows understanding what the test is waiting for. Moreover, the test will work whatever the machine performance is.
-Sleep should be minimal to be as fast as possible. Waiting for a variable should be done in a 40ms sleep loop. Waiting for a socket operation should be done in a 200 ms sleep loop.
-</para>
-</section>
-
-<section xml:id="hbase.tests.cluster">
-<title>Tests using a cluster
-</title>
-
-<para>Tests using a HRegion do not have to start a cluster: A region can use the local file system.
-Start/stopping a cluster cost around 10 seconds. They should not be started per test method but per test class.
-Started cluster must be shutdown using <methodname>HBaseTestingUtility#shutdownMiniCluster</methodname>, which cleans the directories.
-As most as possible, tests should use the default settings for the cluster. When they don't, they should document it. This will allow to share the cluster later.
-</para>
-</section>
-</section>
+ -Dtest.build.data.basedirectory=/ram2G</screen>
+ </section>
-<section xml:id="integration.tests">
-<title>Integration Tests</title>
-<para>HBase integration/system tests are tests that are beyond HBase unit tests. They
-are generally long-lasting, sizeable (the test can be asked to 1M rows or 1B rows),
-targetable (they can take configuration that will point them at the ready-made cluster
-they are to run against; integration tests do not include cluster start/stop code),
-and verifying success, integration tests rely on public APIs only; they do not
-attempt to examine server internals asserting success/fail. Integration tests
-are what you would run when you need to more elaborate proofing of a release candidate
-beyond what unit tests can do. They are not generally run on the Apache Continuous Integration
-build server, however, some sites opt to run integration tests as a part of their
-continuous testing on an actual cluster.
-</para>
-<para>
-Integration tests currently live under the <filename>src/test</filename> directory
-in the hbase-it submodule and will match the regex: <filename>**/IntegrationTest*.java</filename>.
-All integration tests are also annotated with <code>@Category(IntegrationTests.class)</code>.
-</para>
+ <section
+ xml:id="hbase.unittests.cmds.test.hbasetests">
+ <title><command>hbasetests.sh</command></title>
+ <para>It's also possible to use the script <command>hbasetests.sh</command>. This
+ script runs the medium and large tests in parallel with two maven instances, and
+ provides a single report. This script does not use the hbase version of surefire
+ so no parallelization is being done other than the two maven instances the
+ script sets up. It must be executed from the directory which contains the
+ <filename>pom.xml</filename>.</para>
+ <para>For example running <command>./dev-support/hbasetests.sh</command> will
+ execute small and medium tests. Running <command>./dev-support/hbasetests.sh
+ runAllTests</command> will execute all tests. Running
+ <command>./dev-support/hbasetests.sh replayFailed</command> will rerun the
+ failed tests a second time, in a separate jvm and without parallelisation.
+ </para>
+ </section>
+ <section
+ xml:id="hbase.unittests.resource.checker">
+ <title>Test Resource Checker<indexterm><primary>Test Resource
+ Checker</primary></indexterm></title>
+ <para> A custom Maven SureFire plugin listener checks a number of resources before
+ and after each HBase unit test runs and logs its findings at the end of the test
+ output files which can be found in <filename>target/surefire-reports</filename>
+ per Maven module (Tests write test reports named for the test class into this
+ directory. Check the <filename>*-out.txt</filename> files). The resources
+ counted are the number of threads, the number of file descriptors, etc. If the
+ number has increased, it adds a <emphasis>LEAK?</emphasis> comment in the logs.
+ As you can have an HBase instance running in the background, some threads can be
+ deleted/created without any specific action in the test. However, if the test
+ does not work as expected, or if the test should not impact these resources,
+ it's worth checking these log lines
+ <computeroutput>...hbase.ResourceChecker(157): before...</computeroutput>
+ and <computeroutput>...hbase.ResourceChecker(157): after...</computeroutput>.
+ For example: </para>
+ <screen>2012-09-26 09:22:15,315 INFO [pool-1-thread-1]
+hbase.ResourceChecker(157): after:
+regionserver.TestColumnSeeking#testReseeking Thread=65 (was 65),
+OpenFileDescriptor=107 (was 107), MaxFileDescriptor=10240 (was 10240),
+ConnectionCount=1 (was 1) </screen>
+ </section>
+ </section>
-<para>
-Integration tests can be run in two modes: using a mini cluster, or against an actual distributed cluster.
-Maven failsafe is used to run the tests using the mini cluster. IntegrationTestsDriver class is used for
-executing the tests against a distributed cluster. Integration tests SHOULD NOT assume that they are running against a
-mini cluster, and SHOULD NOT use private API's to access cluster state. To interact with the distributed or mini
-cluster uniformly, <code>IntegrationTestingUtility</code>, and <code>HBaseCluster</code> classes,
-and public client API's can be used.
-</para>
+ <section
+ xml:id="hbase.tests.writing">
+ <title>Writing Tests</title>
+ <section
+ xml:id="hbase.tests.rules">
+ <title>General rules</title>
+ <itemizedlist>
+ <listitem>
+ <para>As much as possible, tests should be written as category small
+ tests.</para>
+ </listitem>
+ <listitem>
+ <para>All tests must be written to support parallel execution on the same
+ machine, hence they should not use shared resources as fixed ports or
+ fixed file names.</para>
+ </listitem>
+ <listitem>
+ <para>Tests should not overlog. More than 100 lines/second makes the logs
+ complex to read and use i/o that are hence not available for the other
+ tests.</para>
+ </listitem>
+ <listitem>
+ <para>Tests can be written with <classname>HBaseTestingUtility</classname>.
+ This class offers helper functions to create a temp directory and do the
+ cleanup, or to start a cluster.</para>
+ </listitem>
+ </itemizedlist>
+ </section>
+ <section
+ xml:id="hbase.tests.categories">
+ <title>Categories and execution time</title>
+ <itemizedlist>
+ <listitem>
+ <para>All tests must be categorized, if not they could be skipped.</para>
+ </listitem>
+ <listitem>
+ <para>All tests should be written to be as fast as possible.</para>
+ </listitem>
+ <listitem>
+ <para>Small category tests should last less than 15 seconds, and must not
+ have any side effect.</para>
+ </listitem>
+ <listitem>
+ <para>Medium category tests should last less than 50 seconds.</para>
+ </listitem>
+ <listitem>
+ <para>Large category tests should last less than 3 minutes. This should
+ ensure a good parallelization for people using it, and ease the analysis
+ when the test fails.</para>
+ </listitem>
+ </itemizedlist>
+ </section>
+ <section
+ xml:id="hbase.tests.sleeps">
+ <title>Sleeps in tests</title>
+ <para>Whenever possible, tests should not use <methodname>Thread.sleep</methodname>,
+ but rather waiting for the real event they need. This is faster and clearer for
+ the reader. Tests should not do a <methodname>Thread.sleep</methodname> without
+ testing an ending condition. This allows understanding what the test is waiting
+ for. Moreover, the test will work whatever the machine performance is. Sleep
+ should be minimal to be as fast as possible. Waiting for a variable should be
+ done in a 40ms sleep loop. Waiting for a socket operation should be done in a
+ 200 ms sleep loop. </para>
+ </section>
-<para>
-On a distributed cluster, integration tests that use ChaosMonkey or otherwise manipulate services thru cluster manager (e.g. restart regionservers) use SSH to do it.
-To run these, test process should be able to run commands on remote end, so ssh should be configured accordingly (for example, if HBase runs under hbase
-user in your cluster, you can set up passwordless ssh for that user and run the test also under it). To facilitate that, <code>hbase.it.clustermanager.ssh.user</code>,
-<code>hbase.it.clustermanager.ssh.opts</code> and <code>hbase.it.clustermanager.ssh.cmd</code> configuration settings can be used. "User" is the remote user that cluster manager should use to perform ssh commands.
-"Opts" contains additional options that are passed to SSH (for example, "-i /tmp/my-key").
-Finally, if you have some custom environment setup, "cmd" is the override format for the entire tunnel (ssh) command. The default string is {<code>/usr/bin/ssh %1$s %2$s%3$s%4$s "%5$s"</code>} and is a good starting point. This is a standard Java format string with 5 arguments that is used to execute the remote command. The argument 1 (%1$s) is SSH options set the via opts setting or via environment variable, 2 is SSH user name, 3 is "@" if username is set or "" otherwise, 4 is the target host name, and 5 is the logical command to execute (that may include single quotes, so don't use them). For example, if you run the tests under non-hbase user and want to ssh as that user and change to hbase on remote machine, you can use {<code>/usr/bin/ssh %1$s %2$s%3$s%4$s "su hbase - -c \"%5$s\""</code>}. That way, to kill RS (for example) integration tests may run {<code>/usr/bin/ssh some-hostname "su hbase - -c \"ps aux | ... | kill ...\""</code>}.
-The command is logged in the test logs, so you can verify it is correct for your environment.
-</para>
+ <section
+ xml:id="hbase.tests.cluster">
+ <title>Tests using a cluster </title>
+
+ <para>Tests using a HRegion do not have to start a cluster: A region can use the
+ local file system. Start/stopping a cluster cost around 10 seconds. They should
+ not be started per test method but per test class. Started cluster must be
+ shutdown using <methodname>HBaseTestingUtility#shutdownMiniCluster</methodname>,
+ which cleans the directories. As most as possible, tests should use the default
+ settings for the cluster. When they don't, they should document it. This will
+ allow to share the cluster later. </para>
+ </section>
+ </section>
-<section xml:id="maven.build.commands.integration.tests.mini">
-<title>Running integration tests against mini cluster</title>
-<para>HBase 0.92 added a <varname>verify</varname> maven target.
-Invoking it, for example by doing <code>mvn verify</code>, will
-run all the phases up to and including the verify phase via the
-maven <link xlink:href="http://maven.apache.org/plugins/maven-failsafe-plugin/">failsafe plugin</link>,
-running all the above mentioned HBase unit tests as well as tests that are in the HBase integration test group.
-After you have completed
- <programlisting>mvn install -DskipTests</programlisting>
-You can run just the integration tests by invoking:
- <programlisting>
+ <section
+ xml:id="integration.tests">
+ <title>Integration Tests</title>
+ <para>HBase integration/system tests are tests that are beyond HBase unit tests. They
+ are generally long-lasting, sizeable (the test can be asked to 1M rows or 1B rows),
+ targetable (they can take configuration that will point them at the ready-made
+ cluster they are to run against; integration tests do not include cluster start/stop
+ code), and verifying success, integration tests rely on public APIs only; they do
+ not attempt to examine server internals asserting success/fail. Integration tests
+ are what you would run when you need to more elaborate proofing of a release
+ candidate beyond what unit tests can do. They are not generally run on the Apache
+ Continuous Integration build server, however, some sites opt to run integration
+ tests as a part of their continuous testing on an actual cluster. </para>
+ <para> Integration tests currently live under the <filename>src/test</filename>
+ directory in the hbase-it submodule and will match the regex:
+ <filename>**/IntegrationTest*.java</filename>. All integration tests are also
+ annotated with <code>@Category(IntegrationTests.class)</code>. </para>
+
+ <para> Integration tests can be run in two modes: using a mini cluster, or against an
+ actual distributed cluster. Maven failsafe is used to run the tests using the mini
+ cluster. IntegrationTestsDriver class is used for executing the tests against a
+ distributed cluster. Integration tests SHOULD NOT assume that they are running
+ against a mini cluster, and SHOULD NOT use private API's to access cluster state. To
+ interact with the distributed or mini cluster uniformly,
+ <code>IntegrationTestingUtility</code>, and <code>HBaseCluster</code> classes,
+ and public client API's can be used. </para>
+
+ <para> On a distributed cluster, integration tests that use ChaosMonkey or otherwise
+ manipulate services thru cluster manager (e.g. restart regionservers) use SSH to do
+ it. To run these, test process should be able to run commands on remote end, so ssh
+ should be configured accordingly (for example, if HBase runs under hbase user in
+ your cluster, you can set up passwordless ssh for that user and run the test also
+ under it). To facilitate that, <code>hbase.it.clustermanager.ssh.user</code>,
+ <code>hbase.it.clustermanager.ssh.opts</code> and
+ <code>hbase.it.clustermanager.ssh.cmd</code> configuration settings can be used.
+ "User" is the remote user that cluster manager should use to perform ssh commands.
+ "Opts" contains additional options that are passed to SSH (for example, "-i
+ /tmp/my-key"). Finally, if you have some custom environment setup, "cmd" is the
+ override format for the entire tunnel (ssh) command. The default string is
+ {<code>/usr/bin/ssh %1$s %2$s%3$s%4$s "%5$s"</code>} and is a good starting
+ point. This is a standard Java format string with 5 arguments that is used to
+ execute the remote command. The argument 1 (%1$s) is SSH options set the via opts
+ setting or via environment variable, 2 is SSH user name, 3 is "@" if username is set
+ or "" otherwise, 4 is the target host name, and 5 is the logical command to execute
+ (that may include single quotes, so don't use them). For example, if you run the
+ tests under non-hbase user and want to ssh as that user and change to hbase on
+ remote machine, you can use {<code>/usr/bin/ssh %1$s %2$s%3$s%4$s "su hbase - -c
+ \"%5$s\""</code>}. That way, to kill RS (for example) integration tests may run
+ {<code>/usr/bin/ssh some-hostname "su hbase - -c \"ps aux | ... | kill
+ ...\""</code>}. The command is logged in the test logs, so you can verify it is
+ correct for your environment. </para>
+
+ <section
+ xml:id="maven.build.commands.integration.tests.mini">
+ <title>Running integration tests against mini cluster</title>
+ <para>HBase 0.92 added a <varname>verify</varname> maven target. Invoking it, for
+ example by doing <code>mvn verify</code>, will run all the phases up to and
+ including the verify phase via the maven <link
+ xlink:href="http://maven.apache.org/plugins/maven-failsafe-plugin/">failsafe
+ plugin</link>, running all the above mentioned HBase unit tests as well as
+ tests that are in the HBase integration test group. After you have completed
+ <command>mvn install -DskipTests</command> You can run just the integration
+ tests by invoking:</para>
+ <programlisting>
cd hbase-it
mvn verify</programlisting>
+ <para>If you just want to run the integration tests in top-level, you need to run
+ two commands. First: <command>mvn failsafe:integration-test</command> This
+ actually runs ALL the integration tests. </para>
+ <note>
+ <para>This command will always output <code>BUILD SUCCESS</code> even if there
+ are test failures. </para>
+ </note>
+ <para>At this point, you could grep the output by hand looking for failed tests.
+ However, maven will do this for us; just use: <command>mvn
+ failsafe:verify</command> The above command basically looks at all the test
+ results (so don't remove the 'target' directory) for test failures and reports
+ the results.</para>
+
+ <section
+ xml:id="maven.build.commands.integration.tests2">
+ <title>Running a subset of Integration tests</title>
+ <para>This is very similar to how you specify running a subset of unit tests
+ (see above), but use the property <code>it.test</code> instead of
+ <code>test</code>. To just run
+ <classname>IntegrationTestClassXYZ.java</classname>, use: <command>mvn
+ failsafe:integration-test -Dit.test=IntegrationTestClassXYZ</command>
+ The next thing you might want to do is run groups of integration tests, say
+ all integration tests that are named IntegrationTestClassX*.java:
+ <command>mvn failsafe:integration-test -Dit.test=*ClassX*</command> This
+ runs everything that is an integration test that matches *ClassX*. This
+ means anything matching: "**/IntegrationTest*ClassX*". You can also run
+ multiple groups of integration tests using comma-delimited lists (similar to
+ unit tests). Using a list of matches still supports full regex matching for
+ each of the groups.This would look something like: <command>mvn
+ failsafe:integration-test -Dit.test=*ClassX*, *ClassY</command>
+ </para>
+ </section>
+ </section>
+ <section
+ xml:id="maven.build.commands.integration.tests.distributed">
+ <title>Running integration tests against distributed cluster</title>
+ <para> If you have an already-setup HBase cluster, you can launch the integration
+ tests by invoking the class <code>IntegrationTestsDriver</code>. You may have to
+ run test-compile first. The configuration will be picked by the bin/hbase
+ script. <programlisting>mvn test-compile</programlisting> Then launch the tests
+ with:</para>
+ <programlisting>bin/hbase [--config config_dir] org.apache.hadoop.hbase.IntegrationTestsDriver</programlisting>
+ <para>Pass <code>-h</code> to get usage on this sweet tool. Running the
+ IntegrationTestsDriver without any argument will launch tests found under
+ <code>hbase-it/src/test</code>, having
+ <code>@Category(IntegrationTests.class)</code> annotation, and a name
+ starting with <code>IntegrationTests</code>. See the usage, by passing -h, to
+ see how to filter test classes. You can pass a regex which is checked against
+ the full class name; so, part of class name can be used. IntegrationTestsDriver
+ uses Junit to run the tests. Currently there is no support for running
+ integration tests against a distributed cluster using maven (see <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-6201">HBASE-6201</link>). </para>
+
+ <para> The tests interact with the distributed cluster by using the methods in the
+ <code>DistributedHBaseCluster</code> (implementing
+ <code>HBaseCluster</code>) class, which in turn uses a pluggable
+ <code>ClusterManager</code>. Concrete implementations provide actual
+ functionality for carrying out deployment-specific and environment-dependent
+ tasks (SSH, etc). The default <code>ClusterManager</code> is
+ <code>HBaseClusterManager</code>, which uses SSH to remotely execute
+ start/stop/kill/signal commands, and assumes some posix commands (ps, etc). Also
+ assumes the user running the test has enough "power" to start/stop servers on
+ the remote machines. By default, it picks up <code>HBASE_SSH_OPTS, HBASE_HOME,
+ HBASE_CONF_DIR</code> from the env, and uses
+ <code>bin/hbase-daemon.sh</code> to carry out the actions. Currently tarball
+ deployments, deployments which uses hbase-daemons.sh, and <link
+ xlink:href="http://incubator.apache.org/ambari/">Apache Ambari</link>
+ deployments are supported. /etc/init.d/ scripts are not supported for now, but
+ it can be easily added. For other deployment options, a ClusterManager can be
+ implemented and plugged in. </para>
+ </section>
-If you just want to run the integration tests in top-level, you need to run two commands. First:
- <programlisting>mvn failsafe:integration-test</programlisting>
-This actually runs ALL the integration tests.
- <note><para>This command will always output <code>BUILD SUCCESS</code> even if there are test failures.
- </para></note>
- At this point, you could grep the output by hand looking for failed tests. However, maven will do this for us; just use:
- <programlisting>mvn failsafe:verify</programlisting>
- The above command basically looks at all the test results (so don't remove the 'target' directory) for test failures and reports the results.</para>
-
- <section xml:id="maven.build.commands.integration.tests2">
- <title>Running a subset of Integration tests</title>
- <para>This is very similar to how you specify running a subset of unit tests (see above), but use the property
- <code>it.test</code> instead of <code>test</code>.
-To just run <classname>IntegrationTestClassXYZ.java</classname>, use:
- <programlisting>mvn failsafe:integration-test -Dit.test=IntegrationTestClassXYZ</programlisting>
- The next thing you might want to do is run groups of integration tests, say all integration tests that are named IntegrationTestClassX*.java:
- <programlisting>mvn failsafe:integration-test -Dit.test=*ClassX*</programlisting>
- This runs everything that is an integration test that matches *ClassX*. This means anything matching: "**/IntegrationTest*ClassX*".
- You can also run multiple groups of integration tests using comma-delimited lists (similar to unit tests). Using a list of matches still supports full regex matching for each of the groups.This would look something like:
- <programlisting>mvn failsafe:integration-test -Dit.test=*ClassX*, *ClassY</programlisting>
- </para>
- </section>
-</section>
-<section xml:id="maven.build.commands.integration.tests.distributed">
-<title>Running integration tests against distributed cluster</title>
-<para>
-If you have an already-setup HBase cluster, you can launch the integration tests by invoking the class <code>IntegrationTestsDriver</code>. You may have to
-run test-compile first. The configuration will be picked by the bin/hbase script.
-<programlisting>mvn test-compile</programlisting>
-Then launch the tests with:
-<programlisting>bin/hbase [--config config_dir] org.apache.hadoop.hbase.IntegrationTestsDriver</programlisting>
-Pass <code>-h</code> to get usage on this sweet tool. Running the IntegrationTestsDriver without any argument will launch tests found under <code>hbase-it/src/test</code>, having <code>@Category(IntegrationTests.class)</code> annotation,
-and a name starting with <code>IntegrationTests</code>. See the usage, by passing -h, to see how to filter test classes.
-You can pass a regex which is checked against the full class name; so, part of class name can be used.
-IntegrationTestsDriver uses Junit to run the tests. Currently there is no support for running integration tests against a distributed cluster using maven (see <link xlink:href="https://issues.apache.org/jira/browse/HBASE-6201">HBASE-6201</link>).
-</para>
-
-<para>
-The tests interact with the distributed cluster by using the methods in the <code>DistributedHBaseCluster</code> (implementing <code>HBaseCluster</code>) class, which in turn uses a pluggable <code>ClusterManager</code>. Concrete implementations provide actual functionality for carrying out deployment-specific and environment-dependent tasks (SSH, etc). The default <code>ClusterManager</code> is <code>HBaseClusterManager</code>, which uses SSH to remotely execute start/stop/kill/signal commands, and assumes some posix commands (ps, etc). Also assumes the user running the test has enough "power" to start/stop servers on the remote machines. By default, it picks up <code>HBASE_SSH_OPTS, HBASE_HOME, HBASE_CONF_DIR</code> from the env, and uses <code>bin/hbase-daemon.sh</code> to carry out the actions. Currently tarball deployments, deployments which uses hbase-daemons.sh, and <link xlink:href="http://incubator.apache.org/ambari/">Apache Ambari</link> deployments are supported. /etc/ini
t.d/ scripts are not supported for now, but it can be easily added. For other deployment options, a ClusterManager can be implemented and plugged in.
-</para>
-</section>
-
-<section xml:id="maven.build.commands.integration.tests.destructive">
-<title>Destructive integration / system tests</title>
-<para>
- In 0.96, a tool named <code>ChaosMonkey</code> has been introduced. It is modeled after the <link xlink:href="http://techblog.netflix.com/2012/07/chaos-monkey-released-into-wild.html">same-named tool by Netflix</link>.
-Some of the tests use ChaosMonkey to simulate faults in the running cluster in the way of killing random servers,
-disconnecting servers, etc. ChaosMonkey can also be used as a stand-alone tool to run a (misbehaving) policy while you
-are running other tests.
-</para>
-
-<para>
-ChaosMonkey defines Action's and Policy's. Actions are sequences of events. We have at least the following actions:</para>
-<itemizedlist>
-<listitem><para>Restart active master (sleep 5 sec)</para></listitem>
-<listitem><para>Restart random regionserver (sleep 5 sec)</para></listitem>
-<listitem><para>Restart random regionserver (sleep 60 sec)</para></listitem>
-<listitem><para>Restart META regionserver (sleep 5 sec)</para></listitem>
-<listitem><para>Restart ROOT regionserver (sleep 5 sec)</para></listitem>
-<listitem><para>Batch restart of 50% of regionservers (sleep 5 sec)</para></listitem>
-<listitem><para>Rolling restart of 100% of regionservers (sleep 5 sec)</para></listitem>
-</itemizedlist>
-<para>
-Policies on the other hand are responsible for executing the actions based on a strategy.
-The default policy is to execute a random action every minute based on predefined action
-weights. ChaosMonkey executes predefined named policies until it is stopped. More than one
-policy can be active at any time.
-</para>
-
-<para>
- To run ChaosMonkey as a standalone tool deploy your HBase cluster as usual. ChaosMonkey uses the configuration
-from the bin/hbase script, thus no extra configuration needs to be done. You can invoke the ChaosMonkey by running:</para>
-<programlisting>bin/hbase org.apache.hadoop.hbase.util.ChaosMonkey</programlisting>
-<para>
-This will output smt like:
-</para>
-<screen>
+ <section
+ xml:id="maven.build.commands.integration.tests.destructive">
+ <title>Destructive integration / system tests</title>
+ <para> In 0.96, a tool named <code>ChaosMonkey</code> has been introduced. It is
+ modeled after the <link
+ xlink:href="http://techblog.netflix.com/2012/07/chaos-monkey-released-into-wild.html">same-named
+ tool by Netflix</link>. Some of the tests use ChaosMonkey to simulate faults
+ in the running cluster in the way of killing random servers, disconnecting
+ servers, etc. ChaosMonkey can also be used as a stand-alone tool to run a
+ (misbehaving) policy while you are running other tests. </para>
+
+ <para> ChaosMonkey defines Action's and Policy's. Actions are sequences of events.
+ We have at least the following actions:</para>
+ <itemizedlist>
+ <listitem>
+ <para>Restart active master (sleep 5 sec)</para>
+ </listitem>
+ <listitem>
+ <para>Restart random regionserver (sleep 5 sec)</para>
+ </listitem>
+ <listitem>
+ <para>Restart random regionserver (sleep 60 sec)</para>
+ </listitem>
+ <listitem>
+ <para>Restart META regionserver (sleep 5 sec)</para>
+ </listitem>
+ <listitem>
+ <para>Restart ROOT regionserver (sleep 5 sec)</para>
+ </listitem>
+ <listitem>
+ <para>Batch restart of 50% of regionservers (sleep 5 sec)</para>
+ </listitem>
+ <listitem>
+ <para>Rolling restart of 100% of regionservers (sleep 5 sec)</para>
+ </listitem>
+ </itemizedlist>
+ <para> Policies on the other hand are responsible for executing the actions based on
+ a strategy. The default policy is to execute a random action every minute based
+ on predefined action weights. ChaosMonkey executes predefined named policies
+ until it is stopped. More than one policy can be active at any time. </para>
+
+ <para> To run ChaosMonkey as a standalone tool deploy your HBase cluster as usual.
+ ChaosMonkey uses the configuration from the bin/hbase script, thus no extra
+ configuration needs to be done. You can invoke the ChaosMonkey by
+ running:</para>
+ <programlisting>bin/hbase org.apache.hadoop.hbase.util.ChaosMonkey</programlisting>
+ <para> This will output smt like: </para>
+ <screen>
12/11/19 23:21:57 INFO util.ChaosMonkey: Using ChaosMonkey Policy: class org.apache.hadoop.hbase.util.ChaosMonkey$PeriodicRandomActionPolicy, period:60000
12/11/19 23:21:57 INFO util.ChaosMonkey: Sleeping for 26953 to add jitter
12/11/19 23:22:24 INFO util.ChaosMonkey: Performing action: Restart active master
@@ -1293,7 +1382,8 @@ Bar bar = foo.getBar(); <--- imagine there's an extra space(s) after the
<section xml:id="common.patch.feedback.javadoc.defaults">
<title>Javadoc - Useless Defaults</title>
- <para>Don't just leave the @param arguments the way your IDE generated them. Don't do this...
+ <para>Don't just leave the @param arguments the way your IDE generated them. Don't do
+ this...</para>
<programlisting>
/**
*
@@ -1302,31 +1392,32 @@ Bar bar = foo.getBar(); <--- imagine there's an extra space(s) after the
*/
public Foo getFoo(Bar bar);
</programlisting>
- ... either add something descriptive to the @param and @return lines, or just remove them.
- But the preference is to add something descriptive and useful.
- </para>
- </section>
- <section xml:id="common.patch.feedback.onething">
- <title>One Thing At A Time, Folks</title>
- <para>If you submit a patch for one thing, don't do auto-reformatting or unrelated reformatting of code on a completely
- different area of code.
- </para>
- <para>Likewise, don't add unrelated cleanup or refactorings outside the scope of your Jira.
- </para>
- </section>
- <section xml:id="common.patch.feedback.tests">
- <title>Ambigious Unit Tests</title>
- <para>Make sure that you're clear about what you are testing in your unit tests and why.
- </para>
- </section>
+ <para>... either add something descriptive to the @param and @return lines, or just
+ remove them. But the preference is to add something descriptive and
+ useful.</para>
+ </section>
+ <section
+ xml:id="common.patch.feedback.onething">
+ <title>One Thing At A Time, Folks</title>
+ <para>If you submit a patch for one thing, don't do auto-reformatting or unrelated
+ reformatting of code on a completely different area of code. </para>
+ <para>Likewise, don't add unrelated cleanup or refactorings outside the scope of
+ your Jira. </para>
+ </section>
+ <section
+ xml:id="common.patch.feedback.tests">
+ <title>Ambigious Unit Tests</title>
+ <para>Make sure that you're clear about what you are testing in your unit tests and
+ why. </para>
+ </section>
- </section> <!-- patch feedback -->
+ </section>
+ <!-- patch feedback -->
<section>
<title>Submitting a patch again</title>
- <para>
- Sometimes committers ask for changes for a patch. After incorporating the suggested/requested changes, follow the following process to submit the patch again.
- </para>
+ <para> Sometimes committers ask for changes for a patch. After incorporating the
+ suggested/requested changes, follow the following process to submit the patch again. </para>
<itemizedlist>
<listitem>
<para>Do not delete the old patch file</para>
@@ -1341,20 +1432,22 @@ Bar bar = foo.getBar(); <--- imagine there's an extra space(s) after the
<para>'Cancel Patch' on JIRA.. bug status will change back to Open</para>
</listitem>
<listitem>
- <para>Attach new patch file (e.g. HBASE_XXXX-v2.patch) using 'Files --> Attach'</para>
+ <para>Attach new patch file (e.g. HBASE_XXXX-v2.patch) using 'Files -->
+ Attach'</para>
</listitem>
<listitem>
- <para>Click on 'Submit Patch'. Now the bug status will say 'Patch Available'.</para>
+ <para>Click on 'Submit Patch'. Now the bug status will say 'Patch
+ Available'.</para>
</listitem>
</itemizedlist>
- <para>Committers will review the patch. Rinse and repeat as many times as needed :-)</para>
+ <para>Committers will review the patch. Rinse and repeat as many times as needed
+ :-)</para>
</section>
<section>
<title>Submitting incremental patches</title>
- <para>
- At times you may want to break a big change into mulitple patches. Here is a sample work-flow using git
- <itemizedlist>
+ <para> At times you may want to break a big change into mulitple patches. Here is a
+ sample work-flow using git <itemizedlist>
<listitem>
<para>patch 1:</para>
<itemizedlist>
@@ -1374,7 +1467,8 @@ Bar bar = foo.getBar(); <--- imagine there's an extra space(s) after the
<para>save your work</para>
<screen>$ git add file1 file2 </screen>
<screen>$ git commit -am 'saved after HBASE_XXXX-1.patch'</screen>
- <para>now you have your own branch, that is different from remote master branch</para>
+ <para>now you have your own branch, that is different from remote
+ master branch</para>
</listitem>
<listitem>
<para>make more changes...</para>
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/external_apis.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/external_apis.xml b/src/main/docbkx/external_apis.xml
index 81b823b..69f5365 100644
--- a/src/main/docbkx/external_apis.xml
+++ b/src/main/docbkx/external_apis.xml
@@ -1,13 +1,15 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="external_apis"
- xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ version="5.0"
+ xml:id="external_apis"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/getting_started.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/getting_started.xml b/src/main/docbkx/getting_started.xml
index c99adf8..54ba4af 100644
--- a/src/main/docbkx/getting_started.xml
+++ b/src/main/docbkx/getting_started.xml
@@ -1,5 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="getting_started"
+<chapter
+ version="5.0"
+ xml:id="getting_started"
xmlns="http://docbook.org/ns/docbook"
xmlns:xlink="http://www.w3.org/1999/xlink"
xmlns:xi="http://www.w3.org/2001/XInclude"
@@ -27,210 +29,214 @@
*/
-->
<title>Getting Started</title>
-
+
<section>
<title>Introduction</title>
-
- <para><xref linkend="quickstart" /> will get you up and
- running on a single-node, standalone instance of HBase.
- </para>
+
+ <para><xref
+ linkend="quickstart" /> will get you up and running on a single-node, standalone instance of
+ HBase. </para>
</section>
-
- <section xml:id="quickstart">
+
+ <section
+ xml:id="quickstart">
<title>Quick Start</title>
-
- <para>This guide describes setup of a standalone HBase instance. It will
- run against the local filesystem. In later sections we will take you through
- how to run HBase on Apache Hadoop's HDFS, a distributed filesystem. This section
- shows you how to create a table in HBase, inserting
- rows into your new HBase table via the HBase <command>shell</command>, and then cleaning
- up and shutting down your standalone, local filesystem-based HBase instance. The below exercise
- should take no more than ten minutes (not including download time).
- </para>
- <note xml:id="local.fs.durability"><title>Local Filesystem and Durability</title>
- <para>Using HBase with a LocalFileSystem does not currently guarantee durability.
- The HDFS local filesystem implementation will lose edits if files are not properly
- closed -- which is very likely to happen when experimenting with a new download.
- You need to run HBase on HDFS to ensure all writes are preserved. Running
- against the local filesystem though will get you off the ground quickly and get you
- familiar with how the general system works so lets run with it for now. See
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE-3696"/> and its associated issues for more details.</para></note>
- <note xml:id="loopback.ip.getting.started">
+
+ <para>This guide describes setup of a standalone HBase instance. It will run against the local
+ filesystem. In later sections we will take you through how to run HBase on Apache Hadoop's
+ HDFS, a distributed filesystem. This section shows you how to create a table in HBase,
+ inserting rows into your new HBase table via the HBase <command>shell</command>, and then
+ cleaning up and shutting down your standalone, local filesystem-based HBase instance. The
+ below exercise should take no more than ten minutes (not including download time). </para>
+ <note
+ xml:id="local.fs.durability">
+ <title>Local Filesystem and Durability</title>
+ <para>Using HBase with a LocalFileSystem does not currently guarantee durability. The HDFS
+ local filesystem implementation will lose edits if files are not properly closed -- which is
+ very likely to happen when experimenting with a new download. You need to run HBase on HDFS
+ to ensure all writes are preserved. Running against the local filesystem though will get you
+ off the ground quickly and get you familiar with how the general system works so lets run
+ with it for now. See <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-3696" /> and its associated issues
+ for more details.</para>
+ </note>
+ <note
+ xml:id="loopback.ip.getting.started">
<title>Loopback IP</title>
- <para><emphasis>The below advice is for hbase-0.94.x and older versions only. We believe this fixed in hbase-0.96.0 and beyond
- (let us know if we have it wrong).</emphasis> There should be no need of the below modification to <filename>/etc/hosts</filename> in
- later versions of HBase.</para>
-
- <para>HBase expects the loopback IP address to be 127.0.0.1. Ubuntu and some other distributions,
- for example, will default to 127.0.1.1 and this will cause problems for you
- <footnote><para>See <link xlink:href="http://blog.devving.com/why-does-hbase-care-about-etchosts/">Why does HBase care about /etc/hosts?</link> for detail.</para></footnote>.
- </para>
- <para><filename>/etc/hosts</filename> should look something like this:
- <programlisting>
- 127.0.0.1 localhost
- 127.0.0.1 ubuntu.ubuntu-domain ubuntu
-</programlisting>
- </para>
+ <para><emphasis>The below advice is for hbase-0.94.x and older versions only. We believe this
+ fixed in hbase-0.96.0 and beyond (let us know if we have it wrong).</emphasis> There
+ should be no need of the below modification to <filename>/etc/hosts</filename> in later
+ versions of HBase.</para>
+
+ <para>HBase expects the loopback IP address to be 127.0.0.1. Ubuntu and some other
+ distributions, for example, will default to 127.0.1.1 and this will cause problems for you <footnote>
+ <para>See <link
+ xlink:href="http://blog.devving.com/why-does-hbase-care-about-etchosts/">Why does
+ HBase care about /etc/hosts?</link> for detail.</para>
+ </footnote>. </para>
+ <para><filename>/etc/hosts</filename> should look something like this:</para>
+ <screen>
+127.0.0.1 localhost
+127.0.0.1 ubuntu.ubuntu-domain ubuntu
+ </screen>
+
</note>
-
-
+
+
<section>
<title>Download and unpack the latest stable release.</title>
-
+
<para>Choose a download site from this list of <link
- xlink:href="http://www.apache.org/dyn/closer.cgi/hbase/">Apache Download
- Mirrors</link>. Click on the suggested top link. This will take you to a
- mirror of <emphasis>HBase Releases</emphasis>. Click on the folder named
- <filename>stable</filename> and then download the file that ends in
- <filename>.tar.gz</filename> to your local filesystem; e.g.
- <filename>hbase-0.94.2.tar.gz</filename>.</para>
-
- <para>Decompress and untar your download and then change into the
- unpacked directory.</para>
-
- <para><programlisting>$ tar xfz hbase-<?eval ${project.version}?>.tar.gz
-$ cd hbase-<?eval ${project.version}?>
-</programlisting></para>
-
- <para>At this point, you are ready to start HBase. But before starting
- it, edit <filename>conf/hbase-site.xml</filename>, the file you write
- your site-specific configurations into. Set
- <varname>hbase.rootdir</varname>, the directory HBase writes data to,
- and <varname>hbase.zookeeper.property.dataDir</varname>, the directory
- ZooKeeper writes its data too:
- <programlisting><?xml version="1.0"?>
-<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
-<configuration>
- <property>
- <name>hbase.rootdir</name>
- <value>file:///DIRECTORY/hbase</value>
- </property>
- <property>
- <name>hbase.zookeeper.property.dataDir</name>
- <value>/DIRECTORY/zookeeper</value>
- </property>
-</configuration></programlisting> Replace <varname>DIRECTORY</varname> in the above with the
- path to the directory you would have HBase and ZooKeeper write their data. By default,
- <varname>hbase.rootdir</varname> is set to <filename>/tmp/hbase-${user.name}</filename>
- and similarly so for the default ZooKeeper data location which means you'll lose all
- your data whenever your server reboots unless you change it (Most operating systems clear
- <filename>/tmp</filename> on restart).</para>
+ xlink:href="http://www.apache.org/dyn/closer.cgi/hbase/">Apache Download Mirrors</link>.
+ Click on the suggested top link. This will take you to a mirror of <emphasis>HBase
+ Releases</emphasis>. Click on the folder named <filename>stable</filename> and then
+ download the file that ends in <filename>.tar.gz</filename> to your local filesystem; e.g.
+ <filename>hbase-0.94.2.tar.gz</filename>.</para>
+
+ <para>Decompress and untar your download and then change into the unpacked directory.</para>
+
+ <screen><![CDATA[$ tar xfz hbase-<?eval ${project.version}?>.tar.gz
+$ cd hbase-<?eval ${project.version}?>]]>
+ </screen>
+
+ <para>At this point, you are ready to start HBase. But before starting it, edit
+ <filename>conf/hbase-site.xml</filename>, the file you write your site-specific
+ configurations into. Set <varname>hbase.rootdir</varname>, the directory HBase writes data
+ to, and <varname>hbase.zookeeper.property.dataDir</varname>, the directory ZooKeeper writes
+ its data too:</para>
+ <programlisting><![CDATA[<?xml version="1.0"?>
+<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
+<configuration>
+ <property>
+ <name>hbase.rootdir</name>
+ <value>file:///DIRECTORY/hbase</value>
+ </property>
+ <property>
+ <name>hbase.zookeeper.property.dataDir</name>
+ <value>/DIRECTORY/zookeeper</value>
+ </property>
+</configuration>]]></programlisting>
+ <para> Replace <varname>DIRECTORY</varname> in the above with the path to the directory you
+ would have HBase and ZooKeeper write their data. By default,
+ <varname>hbase.rootdir</varname> is set to <filename>/tmp/hbase-${user.name}</filename>
+ and similarly so for the default ZooKeeper data location which means you'll lose all your
+ data whenever your server reboots unless you change it (Most operating systems clear
+ <filename>/tmp</filename> on restart).</para>
</section>
-
- <section xml:id="start_hbase">
+
+ <section
+ xml:id="start_hbase">
<title>Start HBase</title>
-
- <para>Now start HBase:<programlisting>$ ./bin/start-hbase.sh
-starting Master, logging to logs/hbase-user-master-example.org.out</programlisting></para>
-
- <para>You should now have a running standalone HBase instance. In
- standalone mode, HBase runs all daemons in the the one JVM; i.e. both
- the HBase and ZooKeeper daemons. HBase logs can be found in the
- <filename>logs</filename> subdirectory. Check them out especially if
- it seems HBase had trouble starting.</para>
-
+
+ <para>Now start HBase:</para>
+ <screen>$ ./bin/start-hbase.sh
+starting Master, logging to logs/hbase-user-master-example.org.out</screen>
+
+ <para>You should now have a running standalone HBase instance. In standalone mode, HBase runs
+ all daemons in the the one JVM; i.e. both the HBase and ZooKeeper daemons. HBase logs can be
+ found in the <filename>logs</filename> subdirectory. Check them out especially if it seems
+ HBase had trouble starting.</para>
+
<note>
<title>Is <application>java</application> installed?</title>
-
- <para>All of the above presumes a 1.6 version of Oracle
- <application>java</application> is installed on your machine and
- available on your path (See <xref linkend="java" />); i.e. when you type
- <application>java</application>, you see output that describes the
- options the java program takes (HBase requires java 6). If this is not
- the case, HBase will not start. Install java, edit
- <filename>conf/hbase-env.sh</filename>, uncommenting the
- <envar>JAVA_HOME</envar> line pointing it to your java install, then,
+
+ <para>All of the above presumes a 1.6 version of Oracle <application>java</application> is
+ installed on your machine and available on your path (See <xref
+ linkend="java" />); i.e. when you type <application>java</application>, you see output
+ that describes the options the java program takes (HBase requires java 6). If this is not
+ the case, HBase will not start. Install java, edit <filename>conf/hbase-env.sh</filename>,
+ uncommenting the <envar>JAVA_HOME</envar> line pointing it to your java install, then,
retry the steps above.</para>
</note>
</section>
-
- <section xml:id="shell_exercises">
+
+ <section
+ xml:id="shell_exercises">
<title>Shell Exercises</title>
-
+
<para>Connect to your running HBase via the <command>shell</command>.</para>
-
- <para><programlisting>$ ./bin/hbase shell
-HBase Shell; enter 'help<RETURN>' for list of supported commands.
-Type "exit<RETURN>" to leave the HBase Shell
+
+ <screen><![CDATA[$ ./bin/hbase shell
+HBase Shell; enter 'help<RETURN>' for list of supported commands.
+Type "exit<RETURN>" to leave the HBase Shell
Version: 0.90.0, r1001068, Fri Sep 24 13:55:42 PDT 2010
-hbase(main):001:0> </programlisting></para>
-
- <para>Type <command>help</command> and then
- <command><RETURN></command> to see a listing of shell commands and
- options. Browse at least the paragraphs at the end of the help emission
- for the gist of how variables and command arguments are entered into the
- HBase shell; in particular note how table names, rows, and columns,
- etc., must be quoted.</para>
-
- <para>Create a table named <varname>test</varname> with a single column family named <varname>cf</varname>.
- Verify its creation by listing all tables and then insert some
+hbase(main):001:0>]]> </screen>
+
+ <para>Type <command>help</command> and then <command><RETURN></command> to see a listing
+ of shell commands and options. Browse at least the paragraphs at the end of the help
+ emission for the gist of how variables and command arguments are entered into the HBase
+ shell; in particular note how table names, rows, and columns, etc., must be quoted.</para>
+
+ <para>Create a table named <varname>test</varname> with a single column family named
+ <varname>cf</varname>. Verify its creation by listing all tables and then insert some
values.</para>
-
- <para><programlisting>hbase(main):003:0> create 'test', 'cf'
+
+ <screen><![CDATA[hbase(main):003:0> create 'test', 'cf'
0 row(s) in 1.2200 seconds
-hbase(main):003:0> list 'test'
+hbase(main):003:0> list 'test'
..
1 row(s) in 0.0550 seconds
-hbase(main):004:0> put 'test', 'row1', 'cf:a', 'value1'
+hbase(main):004:0> put 'test', 'row1', 'cf:a', 'value1'
0 row(s) in 0.0560 seconds
-hbase(main):005:0> put 'test', 'row2', 'cf:b', 'value2'
+hbase(main):005:0> put 'test', 'row2', 'cf:b', 'value2'
0 row(s) in 0.0370 seconds
-hbase(main):006:0> put 'test', 'row3', 'cf:c', 'value3'
-0 row(s) in 0.0450 seconds</programlisting></para>
-
+hbase(main):006:0> put 'test', 'row3', 'cf:c', 'value3'
+0 row(s) in 0.0450 seconds]]></screen>
+
<para>Above we inserted 3 values, one at a time. The first insert is at
- <varname>row1</varname>, column <varname>cf:a</varname> with a value of
- <varname>value1</varname>. Columns in HBase are comprised of a column family prefix --
- <varname>cf</varname> in this example -- followed by a colon and then a
- column qualifier suffix (<varname>a</varname> in this case).</para>
-
+ <varname>row1</varname>, column <varname>cf:a</varname> with a value of
+ <varname>value1</varname>. Columns in HBase are comprised of a column family prefix --
+ <varname>cf</varname> in this example -- followed by a colon and then a column qualifier
+ suffix (<varname>a</varname> in this case).</para>
+
<para>Verify the data insert by running a scan of the table as follows</para>
-
- <para><programlisting>hbase(main):007:0> scan 'test'
+
+ <screen><![CDATA[hbase(main):007:0> scan 'test'
ROW COLUMN+CELL
row1 column=cf:a, timestamp=1288380727188, value=value1
row2 column=cf:b, timestamp=1288380738440, value=value2
row3 column=cf:c, timestamp=1288380747365, value=value3
-3 row(s) in 0.0590 seconds</programlisting></para>
-
+3 row(s) in 0.0590 seconds]]></screen>
+
<para>Get a single row</para>
-
- <para><programlisting>hbase(main):008:0> get 'test', 'row1'
+
+ <screen><![CDATA[hbase(main):008:0> get 'test', 'row1'
COLUMN CELL
cf:a timestamp=1288380727188, value=value1
-1 row(s) in 0.0400 seconds</programlisting></para>
-
- <para>Now, disable and drop your table. This will clean up all done
- above.</para>
-
- <para><programlisting>hbase(main):012:0> disable 'test'
+1 row(s) in 0.0400 seconds]]></screen>
+
+ <para>Now, disable and drop your table. This will clean up all done above.</para>
+
+ <screen>h<![CDATA[base(main):012:0> disable 'test'
0 row(s) in 1.0930 seconds
-hbase(main):013:0> drop 'test'
-0 row(s) in 0.0770 seconds </programlisting></para>
-
+hbase(main):013:0> drop 'test'
+0 row(s) in 0.0770 seconds ]]></screen>
+
<para>Exit the shell by typing exit.</para>
-
- <para><programlisting>hbase(main):014:0> exit</programlisting></para>
+
+ <programlisting><![CDATA[hbase(main):014:0> exit]]></programlisting>
</section>
-
- <section xml:id="stopping">
+
+ <section
+ xml:id="stopping">
<title>Stopping HBase</title>
-
+
<para>Stop your hbase instance by running the stop script.</para>
-
- <para><programlisting>$ ./bin/stop-hbase.sh
-stopping hbase...............</programlisting></para>
+
+ <screen>$ ./bin/stop-hbase.sh
+stopping hbase...............</screen>
</section>
-
+
<section>
<title>Where to go next</title>
-
- <para>The above described standalone setup is good for testing and
- experiments only. In the next chapter, <xref linkend="configuration" />,
- we'll go into depth on the different HBase run modes, system requirements
- running HBase, and critical configurations setting up a distributed HBase deploy.</para>
+
+ <para>The above described standalone setup is good for testing and experiments only. In the
+ next chapter, <xref
+ linkend="configuration" />, we'll go into depth on the different HBase run modes, system
+ requirements running HBase, and critical configurations setting up a distributed HBase
+ deploy.</para>
</section>
</section>
-
+
</chapter>
[02/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/upgrading.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/upgrading.xml b/src/main/docbkx/upgrading.xml
index 758d6d4..33b68d8 100644
--- a/src/main/docbkx/upgrading.xml
+++ b/src/main/docbkx/upgrading.xml
@@ -1,13 +1,15 @@
<?xml version="1.0"?>
- <chapter xml:id="upgrading"
- version="5.0" xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ xml:id="upgrading"
+ version="5.0"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -29,206 +31,221 @@
<title>Upgrading</title>
<para>You cannot skip major versions upgrading. If you are upgrading from version 0.90.x to
0.94.x, you must first go from 0.90.x to 0.92.x and then go from 0.92.x to 0.94.x.</para>
- <note><para>It may be possible to skip across versions -- for example go from
- 0.92.2 straight to 0.98.0 just following the 0.96.x upgrade instructions --
- but we have not tried it so cannot say whether it works or not.</para>
+ <note>
+ <para>It may be possible to skip across versions -- for example go from 0.92.2 straight to
+ 0.98.0 just following the 0.96.x upgrade instructions -- but we have not tried it so
+ cannot say whether it works or not.</para>
</note>
- <para>
- Review <xref linkend="configuration" />, in particular the section on Hadoop version.
- </para>
- <section xml:id="hbase.versioning">
+ <para> Review <xref
+ linkend="configuration" />, in particular the section on Hadoop version. </para>
+ <section
+ xml:id="hbase.versioning">
<title>HBase version numbers</title>
- <para>HBase has not walked a straight line where version numbers are concerned.
- Since we came up out of hadoop itself, we originally tracked hadoop versioning.
- Later we left hadoop versioning behind because we were moving at a different rate
- to that of our parent. If you are into the arcane, checkout our old wiki page
- on <link xlink:href="http://wiki.apache.org/hadoop/Hbase/HBaseVersions">HBase Versioning</link>
- which tries to connect the HBase version dots.</para>
- <section xml:id="hbase.development.series"><title>Odd/Even Versioning or "Development"" Series Releases</title>
+ <para>HBase has not walked a straight line where version numbers are concerned. Since we
+ came up out of hadoop itself, we originally tracked hadoop versioning. Later we left
+ hadoop versioning behind because we were moving at a different rate to that of our
+ parent. If you are into the arcane, checkout our old wiki page on <link
+ xlink:href="http://wiki.apache.org/hadoop/Hbase/HBaseVersions">HBase
+ Versioning</link> which tries to connect the HBase version dots.</para>
+ <section
+ xml:id="hbase.development.series">
+ <title>Odd/Even Versioning or "Development"" Series Releases</title>
<para>Ahead of big releases, we have been putting up preview versions to start the
- feedback cycle turning-over earlier. These "Development" Series releases,
- always odd-numbered, come with no guarantees, not even regards being able
- to upgrade between two sequential releases (we reserve the right to break compatibility across
- "Development" Series releases). Needless to say, these releases are not for
- production deploys. They are a preview of what is coming in the hope that
- interested parties will take the release for a test drive and flag us early if we
- there are issues we've missed ahead of our rolling a production-worthy release.
- </para>
- <para>Our first "Development" Series was the 0.89 set that came out ahead of
- HBase 0.90.0. HBase 0.95 is another "Development" Series that portends
- HBase 0.96.0.
+ feedback cycle turning-over earlier. These "Development" Series releases, always
+ odd-numbered, come with no guarantees, not even regards being able to upgrade
+ between two sequential releases (we reserve the right to break compatibility across
+ "Development" Series releases). Needless to say, these releases are not for
+ production deploys. They are a preview of what is coming in the hope that interested
+ parties will take the release for a test drive and flag us early if we there are
+ issues we've missed ahead of our rolling a production-worthy release. </para>
+ <para>Our first "Development" Series was the 0.89 set that came out ahead of HBase
+ 0.90.0. HBase 0.95 is another "Development" Series that portends HBase 0.96.0.
</para>
</section>
- <section xml:id="hbase.binary.compatibility">
+ <section
+ xml:id="hbase.binary.compatibility">
<title>Binary Compatibility</title>
- <para>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 binary compatible.
- You can safely do rolling upgrades between binary compatible versions; i.e.
- across point versions: e.g. from 0.94.5 to 0.94.6<footnote><para>See
- <link xlink:href="http://search-hadoop.com/m/bOOvwHGW981/Does+compatibility+between+versions+also+mean+binary+compatibility%253F&subj=Re+Does+compatibility+between+versions+also+mean+binary+compatibility+">Does compatibility between versions also mean binary compatibility?</link>
- discussion on the hbaes dev mailing list.
- </para></footnote>.
- </para>
+ <para>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
+ binary compatible. You can safely do rolling upgrades between binary compatible
+ versions; i.e. across point versions: e.g. from 0.94.5 to 0.94.6<footnote>
+ <para>See <link
+ xlink:href="http://search-hadoop.com/m/bOOvwHGW981/Does+compatibility+between+versions+also+mean+binary+compatibility%253F&subj=Re+Does+compatibility+between+versions+also+mean+binary+compatibility+">Does
+ compatibility between versions also mean binary compatibility?</link>
+ discussion on the hbaes dev mailing list. </para>
+ </footnote>. </para>
</section>
- <section xml:id="hbase.rolling.restart">
+ <section
+ xml:id="hbase.rolling.restart">
<title>Rolling Upgrade between versions/Binary compatibility</title>
- <para>Unless otherwise specified, HBase point versions are binary compatible.
- you can do a rolling upgrade between hbase point versions;
- for example, you can go to 0.94.6 from 0.94.5 by doing a rolling upgrade across the cluster
- replacing the 0.94.5 binary with a 0.94.6 binary.
- </para>
+ <para>Unless otherwise specified, HBase point versions are binary compatible. you can do
+ a rolling upgrade between hbase point versions; for example, you can go to 0.94.6
+ from 0.94.5 by doing a rolling upgrade across the cluster replacing the 0.94.5
+ binary with a 0.94.6 binary. </para>
</section>
-</section>
+ </section>
- <section xml:id="upgrade0.98">
- <title>Upgrading from 0.96.x to 0.98.x</title>
- <para>A rolling upgrade from 0.96.x to 0.98.x works. The two versions are not binary compatible.</para>
- <para>Additional steps are required to take advantage of some of the new features of 0.98.x, including cell visibility
- labels, cell ACLs, and transparent server side encryption. See the
- <xref linkend="security" /> chapter of this guide for more information. Significant performance improvements include a change to the write
- ahead log threading model that provides higher transaction throughput under
- high load, reverse scanners, MapReduce over snapshot files, and striped
- compaction.</para>
- <para>Clients and servers can run with 0.98.x and 0.96.x versions. However, applications may need to be recompiled due to changes in the Java API.</para>
+ <section
+ xml:id="upgrade0.98">
+ <title>Upgrading from 0.96.x to 0.98.x</title>
+ <para>A rolling upgrade from 0.96.x to 0.98.x works. The two versions are not binary
+ compatible.</para>
+ <para>Additional steps are required to take advantage of some of the new features of 0.98.x,
+ including cell visibility labels, cell ACLs, and transparent server side encryption. See
+ the <xref
+ linkend="security" /> chapter of this guide for more information. Significant
+ performance improvements include a change to the write ahead log threading model that
+ provides higher transaction throughput under high load, reverse scanners, MapReduce over
+ snapshot files, and striped compaction.</para>
+ <para>Clients and servers can run with 0.98.x and 0.96.x versions. However, applications may
+ need to be recompiled due to changes in the Java API.</para>
</section>
<section>
<title>Upgrading from 0.94.x to 0.98.x</title>
- <para>
- A rolling upgrade from 0.94.x directly to 0.98.x does not work. The upgrade path follows the same procedures as <xref linkend="upgrade0.96" />. Additional steps are required to use some of the new features of 0.98.x. See <xref linkend="upgrade0.98" /> for an abbreviated list of these features.
- </para>
+ <para> A rolling upgrade from 0.94.x directly to 0.98.x does not work. The upgrade path
+ follows the same procedures as <xref
+ linkend="upgrade0.96" />. Additional steps are required to use some of the new
+ features of 0.98.x. See <xref
+ linkend="upgrade0.98" /> for an abbreviated list of these features. </para>
</section>
- <section xml:id="upgrade0.96">
- <title>Upgrading from 0.94.x to 0.96.x</title>
- <subtitle>The Singularity</subtitle>
- <para>You will have to stop your old 0.94.x cluster completely to upgrade. If you are replicating
- between clusters, both clusters will have to go down to upgrade. Make sure it is a clean shutdown.
- The less WAL files around, the faster the upgrade will run (the upgrade will split any log files it
- finds in the filesystem as part of the upgrade process). All clients must be upgraded to 0.96 too.
- </para>
- <para>The API has changed. You will need to recompile your code against 0.96 and you may need to
- adjust applications to go against new APIs (TODO: List of changes).
- </para>
- <section>
- <title>Executing the 0.96 Upgrade</title>
- <note>
- <para>HDFS and ZooKeeper should be up and running during the upgrade process.</para>
- </note>
- <para>hbase-0.96.0 comes with an upgrade script. Run
- <programlisting>$ bin/hbase upgrade</programlisting> to see its usage.
- The script has two main modes: -check, and -execute.
- </para>
- <section><title>check</title>
- <para>The <emphasis>check</emphasis> step is run against a running 0.94 cluster.
- Run it from a downloaded 0.96.x binary. The <emphasis>check</emphasis> step
- is looking for the presence of <filename>HFileV1</filename> files. These are
- unsupported in hbase-0.96.0. To purge them -- have them rewritten as HFileV2 --
- you must run a compaction.
- </para>
- <para>The <emphasis>check</emphasis> step prints stats at the end of its run
- (grep for “Result:” in the log) printing absolute path of the tables it scanned,
- any HFileV1 files found, the regions containing said files (the regions we
- need to major compact to purge the HFileV1s), and any corrupted files if
- any found. A corrupt file is unreadable, and so is undefined (neither HFileV1 nor HFileV2).
- </para>
- <para>To run the check step, run <programlisting>$ bin/hbase upgrade -check</programlisting>.
- Here is sample output:
-<programlisting>
- Tables Processed:
- hdfs://localhost:41020/myHBase/.META.
- hdfs://localhost:41020/myHBase/usertable
- hdfs://localhost:41020/myHBase/TestTable
- hdfs://localhost:41020/myHBase/t
+ <section
+ xml:id="upgrade0.96">
+ <title>Upgrading from 0.94.x to 0.96.x</title>
+ <subtitle>The Singularity</subtitle>
+ <para>You will have to stop your old 0.94.x cluster completely to upgrade. If you are
+ replicating between clusters, both clusters will have to go down to upgrade. Make sure
+ it is a clean shutdown. The less WAL files around, the faster the upgrade will run (the
+ upgrade will split any log files it finds in the filesystem as part of the upgrade
+ process). All clients must be upgraded to 0.96 too. </para>
+ <para>The API has changed. You will need to recompile your code against 0.96 and you may
+ need to adjust applications to go against new APIs (TODO: List of changes). </para>
+ <section>
+ <title>Executing the 0.96 Upgrade</title>
+ <note>
+ <para>HDFS and ZooKeeper should be up and running during the upgrade process.</para>
+ </note>
+ <para>hbase-0.96.0 comes with an upgrade script. Run
+ <programlisting>$ bin/hbase upgrade</programlisting> to see its usage. The script
+ has two main modes: -check, and -execute. </para>
+ <section>
+ <title>check</title>
+ <para>The <emphasis>check</emphasis> step is run against a running 0.94 cluster. Run
+ it from a downloaded 0.96.x binary. The <emphasis>check</emphasis> step is
+ looking for the presence of <filename>HFileV1</filename> files. These are
+ unsupported in hbase-0.96.0. To purge them -- have them rewritten as HFileV2 --
+ you must run a compaction. </para>
+ <para>The <emphasis>check</emphasis> step prints stats at the end of its run (grep
+ for “Result:” in the log) printing absolute path of the tables it scanned, any
+ HFileV1 files found, the regions containing said files (the regions we need to
+ major compact to purge the HFileV1s), and any corrupted files if any found. A
+ corrupt file is unreadable, and so is undefined (neither HFileV1 nor HFileV2). </para>
+ <para>To run the check step, run <command>$ bin/hbase upgrade -check</command>. Here
+ is sample output:</para>
+ <screen>
+Tables Processed:
+hdfs://localhost:41020/myHBase/.META.
+hdfs://localhost:41020/myHBase/usertable
+hdfs://localhost:41020/myHBase/TestTable
+hdfs://localhost:41020/myHBase/t
- Count of HFileV1: 2
- HFileV1:
- hdfs://localhost:41020/myHBase/usertable /fa02dac1f38d03577bd0f7e666f12812/family/249450144068442524
- hdfs://localhost:41020/myHBase/usertable /ecdd3eaee2d2fcf8184ac025555bb2af/family/249450144068442512
+Count of HFileV1: 2
+HFileV1:
+hdfs://localhost:41020/myHBase/usertable /fa02dac1f38d03577bd0f7e666f12812/family/249450144068442524
+hdfs://localhost:41020/myHBase/usertable /ecdd3eaee2d2fcf8184ac025555bb2af/family/249450144068442512
- Count of corrupted files: 1
- Corrupted Files:
- hdfs://localhost:41020/myHBase/usertable/fa02dac1f38d03577bd0f7e666f12812/family/1
- Count of Regions with HFileV1: 2
- Regions to Major Compact:
- hdfs://localhost:41020/myHBase/usertable/fa02dac1f38d03577bd0f7e666f12812
- hdfs://localhost:41020/myHBase/usertable/ecdd3eaee2d2fcf8184ac025555bb2af
+Count of corrupted files: 1
+Corrupted Files:
+hdfs://localhost:41020/myHBase/usertable/fa02dac1f38d03577bd0f7e666f12812/family/1
+Count of Regions with HFileV1: 2
+Regions to Major Compact:
+hdfs://localhost:41020/myHBase/usertable/fa02dac1f38d03577bd0f7e666f12812
+hdfs://localhost:41020/myHBase/usertable/ecdd3eaee2d2fcf8184ac025555bb2af
- There are some HFileV1, or corrupt files (files with incorrect major version)
-</programlisting>
- In the above sample output, there are two HFileV1 in two regions, and one corrupt file.
- Corrupt files should probably be removed. The regions that have HFileV1s need to be major
- compacted. To major compact, start up the hbase shell and review how to compact an individual
- region. After the major compaction is done, rerun the check step and the HFileV1s shoudl be
- gone, replaced by HFileV2 instances.
- </para>
- <para>By default, the check step scans the hbase root directory (defined as hbase.rootdir in the configuration).
- To scan a specific directory only, pass the <emphasis>-dir</emphasis> option.
- <programlisting>$ bin/hbase upgrade -check -dir /myHBase/testTable</programlisting>
- The above command would detect HFileV1s in the /myHBase/testTable directory.
- </para>
- <para>
- Once the check step reports all the HFileV1 files have been rewritten, it is safe to proceed with the
- upgrade.
- </para>
- </section>
- <section><title>execute</title>
- <para>After the check step shows the cluster is free of HFileV1, it is safe to proceed with the upgrade.
- Next is the <emphasis>execute</emphasis> step. You must <emphasis>SHUTDOWN YOUR 0.94.x CLUSTER</emphasis>
- before you can run the <emphasis>execute</emphasis> step. The execute step will not run if it
- detects running HBase masters or regionservers.
- <note>
- <para>HDFS and ZooKeeper should be up and running during the upgrade process.
- If zookeeper is managed by HBase, then you can start zookeeper so it is available to the upgrade
- by running <programlisting>$ ./hbase/bin/hbase-daemon.sh start zookeeper</programlisting>
- </para></note>
- </para>
- <para>
- The <emphasis>execute</emphasis> upgrade step is made of three substeps.
+There are some HFileV1, or corrupt files (files with incorrect major version)
+ </screen>
+ <para>In the above sample output, there are two HFileV1 in two regions, and one
+ corrupt file. Corrupt files should probably be removed. The regions that have
+ HFileV1s need to be major compacted. To major compact, start up the hbase shell
+ and review how to compact an individual region. After the major compaction is
+ done, rerun the check step and the HFileV1s shoudl be gone, replaced by HFileV2
+ instances. </para>
+ <para>By default, the check step scans the hbase root directory (defined as
+ hbase.rootdir in the configuration). To scan a specific directory only, pass the
+ <emphasis>-dir</emphasis> option.</para>
+ <screen>$ bin/hbase upgrade -check -dir /myHBase/testTable</screen>
+ <para>The above command would detect HFileV1s in the /myHBase/testTable directory. </para>
+ <para> Once the check step reports all the HFileV1 files have been rewritten, it is
+ safe to proceed with the upgrade. </para>
+ </section>
+ <section>
+ <title>execute</title>
+ <para>After the check step shows the cluster is free of HFileV1, it is safe to
+ proceed with the upgrade. Next is the <emphasis>execute</emphasis> step. You
+ must <emphasis>SHUTDOWN YOUR 0.94.x CLUSTER</emphasis> before you can run the
+ <emphasis>execute</emphasis> step. The execute step will not run if it
+ detects running HBase masters or regionservers. <note>
+ <para>HDFS and ZooKeeper should be up and running during the upgrade
+ process. If zookeeper is managed by HBase, then you can start zookeeper
+ so it is available to the upgrade by running <command>$
+ ./hbase/bin/hbase-daemon.sh start zookeeper</command>
+ </para>
+ </note>
+ </para>
+ <para> The <emphasis>execute</emphasis> upgrade step is made of three substeps. </para>
+ <itemizedlist>
+ <listitem>
+ <para>Namespaces: HBase 0.96.0 has support for namespaces. The upgrade needs
+ to reorder directories in the filesystem for namespaces to work.</para>
+ </listitem>
+ <listitem>
+ <para>ZNodes: All znodes are purged so that new ones can be written in their
+ place using a new protobuf'ed format and a few are migrated in place:
+ e.g. replication and table state znodes</para>
+ </listitem>
+ <listitem>
+ <para>WAL Log Splitting: If the 0.94.x cluster shutdown was not clean, we'll
+ split WAL logs as part of migration before we startup on 0.96.0. This
+ WAL splitting runs slower than the native distributed WAL splitting
+ because it is all inside the single upgrade process (so try and get a
+ clean shutdown of the 0.94.0 cluster if you can). </para>
+ </listitem>
+ </itemizedlist>
+ <para> To run the <emphasis>execute</emphasis> step, make sure that first you have
+ copied hbase-0.96.0 binaries everywhere under servers and under clients. Make
+ sure the 0.94.0 cluster is down. Then do as follows:</para>
+ <screen>$ bin/hbase upgrade -execute</screen>
+ <para>Here is some sample output.</para>
+ <programlisting>
+Starting Namespace upgrade
+Created version file at hdfs://localhost:41020/myHBase with version=7
+Migrating table testTable to hdfs://localhost:41020/myHBase/.data/default/testTable
+…..
+Created version file at hdfs://localhost:41020/myHBase with version=8
+Successfully completed NameSpace upgrade.
+Starting Znode upgrade
+….
+Successfully completed Znode upgrade
- <itemizedlist>
- <listitem> <para>Namespaces: HBase 0.96.0 has support for namespaces. The upgrade needs to reorder directories in the filesystem for namespaces to work.</para> </listitem>
- <listitem> <para>ZNodes: All znodes are purged so that new ones can be written in their place using a new protobuf'ed format and a few are migrated in place: e.g. replication and table state znodes</para> </listitem>
- <listitem> <para>WAL Log Splitting: If the 0.94.x cluster shutdown was not clean, we'll split WAL logs as part of migration before
- we startup on 0.96.0. This WAL splitting runs slower than the native distributed WAL splitting because it is all inside the
- single upgrade process (so try and get a clean shutdown of the 0.94.0 cluster if you can).
- </para> </listitem>
- </itemizedlist>
- </para>
- <para>
- To run the <emphasis>execute</emphasis> step, make sure that first you have copied hbase-0.96.0
- binaries everywhere under servers and under clients. Make sure the 0.94.0 cluster is down.
- Then do as follows:
- <programlisting>$ bin/hbase upgrade -execute</programlisting>
- Here is some sample output
- <programlisting>
- Starting Namespace upgrade
- Created version file at hdfs://localhost:41020/myHBase with version=7
- Migrating table testTable to hdfs://localhost:41020/myHBase/.data/default/testTable
- …..
- Created version file at hdfs://localhost:41020/myHBase with version=8
- Successfully completed NameSpace upgrade.
- Starting Znode upgrade
- ….
- Successfully completed Znode upgrade
-
- Starting Log splitting
- …
- Successfully completed Log splitting
+Starting Log splitting
+…
+Successfully completed Log splitting
</programlisting>
- </para>
- <para>
- If the output from the execute step looks good, stop the zookeeper instance you started
- to do the upgrade: <programlisting>$ ./hbase/bin/hbase-daemon.sh stop zookeeper</programlisting>
- Now start up hbase-0.96.0.
- </para>
- </section>
- <section xml:id="s096.migration.troubleshooting"><title>Troubleshooting</title>
- <section xml:id="s096.migration.troubleshooting.old.client"><title>Old Client connecting to 0.96 cluster</title>
- <para>It will fail with an exception like the below. Upgrade.
- <programlisting>17:22:15 Exception in thread "main" java.lang.IllegalArgumentException: Not a host:port pair: PBUF
+ <para> If the output from the execute step looks good, stop the zookeeper instance
+ you started to do the upgrade:
+ <programlisting>$ ./hbase/bin/hbase-daemon.sh stop zookeeper</programlisting>
+ Now start up hbase-0.96.0. </para>
+ </section>
+ <section
+ xml:id="s096.migration.troubleshooting">
+ <title>Troubleshooting</title>
+ <section
+ xml:id="s096.migration.troubleshooting.old.client">
+ <title>Old Client connecting to 0.96 cluster</title>
+ <para>It will fail with an exception like the below. Upgrade.</para>
+ <screen>17:22:15 Exception in thread "main" java.lang.IllegalArgumentException: Not a host:port pair: PBUF
17:22:15 *
17:22:15 api-compat-8.ent.cloudera.com �� ���(
17:22:15 at org.apache.hadoop.hbase.util.Addressing.parseHostname(Addressing.java:60)
@@ -239,192 +256,232 @@
17:22:15 at org.apache.hadoop.hbase.client.HConnectionManager$HConnectionImplementation.getMaster(HConnectionManager.java:703)
17:22:15 at org.apache.hadoop.hbase.client.HBaseAdmin.&init>(HBaseAdmin.java:126)
17:22:15 at Client_4_3_0.setup(Client_4_3_0.java:716)
-17:22:15 at Client_4_3_0.main(Client_4_3_0.java:63)</programlisting>
- </para>
- </section>
- </section>
- </section>
+17:22:15 at Client_4_3_0.main(Client_4_3_0.java:63)</screen>
+ </section>
+ </section>
+ </section>
</section>
- <section xml:id="upgrade0.94">
- <title>Upgrading from 0.92.x to 0.94.x</title>
- <para>We used to think that 0.92 and 0.94 were interface compatible and that you can do a
- rolling upgrade between these versions but then we figured that
- <link xlink:href="https://issues.apache.org/jira/browse/HBASE-5357">HBASE-5357 Use builder pattern in HColumnDescriptor</link>
- changed method signatures so rather than return void they instead return HColumnDescriptor. This
- will throw <programlisting>java.lang.NoSuchMethodError: org.apache.hadoop.hbase.HColumnDescriptor.setMaxVersions(I)V</programlisting>
- .... so 0.92 and 0.94 are NOT compatible. You cannot do a rolling upgrade between them.
- </para>
- </section>
- <section xml:id="upgrade0.92">
- <title>Upgrading from 0.90.x to 0.92.x</title>
- <subtitle>Upgrade Guide</subtitle>
-<para>You will find that 0.92.0 runs a little differently to 0.90.x releases. Here are a few things to watch out for upgrading from 0.90.x to 0.92.0.
-<note><title>tl;dr</title>
-<para>
-If you've not patience, here are the important things to know upgrading.
-<orderedlist>
-<listitem><para>Once you upgrade, you can’t go back.</para>
-</listitem>
-<listitem><para>
-MSLAB is on by default. Watch that heap usage if you have a lot of regions.</para>
-</listitem>
-<listitem><para>
-Distributed splitting is on by defaul. It should make region server failover faster.
-</para></listitem>
-<listitem><para>
-There’s a separate tarball for security.
-</para></listitem>
-<listitem><para>
-If -XX:MaxDirectMemorySize is set in your hbase-env.sh, it’s going to enable the experimental off-heap cache (You may not want this).
-</para></listitem>
-</orderedlist>
-</para>
-</note>
-</para>
+ <section
+ xml:id="upgrade0.94">
+ <title>Upgrading from 0.92.x to 0.94.x</title>
+ <para>We used to think that 0.92 and 0.94 were interface compatible and that you can do a
+ rolling upgrade between these versions but then we figured that <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-5357">HBASE-5357 Use builder
+ pattern in HColumnDescriptor</link> changed method signatures so rather than return
+ void they instead return HColumnDescriptor. This will throw</para>
+ <screen>java.lang.NoSuchMethodError: org.apache.hadoop.hbase.HColumnDescriptor.setMaxVersions(I)V</screen>
+ <para>.... so 0.92 and 0.94 are NOT compatible. You cannot do a rolling upgrade between them.</para> </section>
+ <section
+ xml:id="upgrade0.92">
+ <title>Upgrading from 0.90.x to 0.92.x</title>
+ <subtitle>Upgrade Guide</subtitle>
+ <para>You will find that 0.92.0 runs a little differently to 0.90.x releases. Here are a few
+ things to watch out for upgrading from 0.90.x to 0.92.0. </para>
+ <note>
+ <title>tl;dr</title>
+ <para> If you've not patience, here are the important things to know upgrading. <orderedlist>
+ <listitem>
+ <para>Once you upgrade, you can’t go back.</para>
+ </listitem>
+ <listitem>
+ <para> MSLAB is on by default. Watch that heap usage if you have a lot of
+ regions.</para>
+ </listitem>
+ <listitem>
+ <para> Distributed splitting is on by defaul. It should make region server
+ failover faster. </para>
+ </listitem>
+ <listitem>
+ <para> There’s a separate tarball for security. </para>
+ </listitem>
+ <listitem>
+ <para> If -XX:MaxDirectMemorySize is set in your hbase-env.sh, it’s going to
+ enable the experimental off-heap cache (You may not want this). </para>
+ </listitem>
+ </orderedlist>
+ </para>
+ </note>
-<section>
-<title>You can’t go back!
-</title>
-<para>To move to 0.92.0, all you need to do is shutdown your cluster, replace your hbase 0.90.x with hbase 0.92.0 binaries (be sure you clear out all 0.90.x instances) and restart (You cannot do a rolling restart from 0.90.x to 0.92.x -- you must restart).
-On startup, the <varname>.META.</varname> table content is rewritten removing the table schema from the <varname>info:regioninfo</varname> column.
-Also, any flushes done post first startup will write out data in the new 0.92.0 file format, <link xlink:href="http://hbase.apache.org/book.html#hfilev2">HFile V2</link>.
-This means you cannot go back to 0.90.x once you’ve started HBase 0.92.0 over your HBase data directory.
-</para>
-</section>
+ <section>
+ <title>You can’t go back! </title>
+ <para>To move to 0.92.0, all you need to do is shutdown your cluster, replace your hbase
+ 0.90.x with hbase 0.92.0 binaries (be sure you clear out all 0.90.x instances) and
+ restart (You cannot do a rolling restart from 0.90.x to 0.92.x -- you must restart).
+ On startup, the <varname>.META.</varname> table content is rewritten removing the
+ table schema from the <varname>info:regioninfo</varname> column. Also, any flushes
+ done post first startup will write out data in the new 0.92.0 file format, <link
+ xlink:href="http://hbase.apache.org/book.html#hfilev2">HFile V2</link>. This
+ means you cannot go back to 0.90.x once you’ve started HBase 0.92.0 over your HBase
+ data directory. </para>
+ </section>
-<section>
-<title>MSLAB is ON by default
-</title>
-<para>In 0.92.0, the <link xlink:href="http://hbase.apache.org/book.html#hbase.hregion.memstore.mslab.enabled">hbase.hregion.memstore.mslab.enabled</link> flag is set to true
-(See <xref linkend="mslab" />). In 0.90.x it was <constant>false</constant>. When it is enabled, memstores will step allocate memory in MSLAB 2MB chunks even if the
-memstore has zero or just a few small elements. This is fine usually but if you had lots of regions per regionserver in a 0.90.x cluster (and MSLAB was off),
-you may find yourself OOME'ing on upgrade because the <code>thousands of regions * number of column families * 2MB MSLAB (at a minimum)</code>
-puts your heap over the top. Set <varname>hbase.hregion.memstore.mslab.enabled</varname> to
-<constant>false</constant> or set the MSLAB size down from 2MB by setting <varname>hbase.hregion.memstore.mslab.chunksize</varname> to something less.
-</para>
-</section>
+ <section>
+ <title>MSLAB is ON by default </title>
+ <para>In 0.92.0, the <link
+ xlink:href="http://hbase.apache.org/book.html#hbase.hregion.memstore.mslab.enabled">hbase.hregion.memstore.mslab.enabled</link>
+ flag is set to true (See <xref
+ linkend="mslab" />). In 0.90.x it was <constant>false</constant>. When it is
+ enabled, memstores will step allocate memory in MSLAB 2MB chunks even if the
+ memstore has zero or just a few small elements. This is fine usually but if you had
+ lots of regions per regionserver in a 0.90.x cluster (and MSLAB was off), you may
+ find yourself OOME'ing on upgrade because the <code>thousands of regions * number of
+ column families * 2MB MSLAB (at a minimum)</code> puts your heap over the top.
+ Set <varname>hbase.hregion.memstore.mslab.enabled</varname> to
+ <constant>false</constant> or set the MSLAB size down from 2MB by setting
+ <varname>hbase.hregion.memstore.mslab.chunksize</varname> to something less.
+ </para>
+ </section>
-<section><title>Distributed splitting is on by default
-</title>
-<para>Previous, WAL logs on crash were split by the Master alone. In 0.92.0, log splitting is done by the cluster (See See “HBASE-1364 [performance] Distributed splitting of regionserver commit logs”). This should cut down significantly on the amount of time it takes splitting logs and getting regions back online again.
-</para>
-</section>
+ <section>
+ <title>Distributed splitting is on by default </title>
+ <para>Previous, WAL logs on crash were split by the Master alone. In 0.92.0, log
+ splitting is done by the cluster (See See “HBASE-1364 [performance] Distributed
+ splitting of regionserver commit logs”). This should cut down significantly on the
+ amount of time it takes splitting logs and getting regions back online again.
+ </para>
+ </section>
-<section><title>Memory accounting is different now
-</title>
-<para>In 0.92.0, <xref linkend="hfilev2" /> indices and bloom filters take up residence in the same LRU used caching blocks that come from the filesystem.
-In 0.90.x, the HFile v1 indices lived outside of the LRU so they took up space even if the index was on a ‘cold’ file, one that wasn’t being actively used. With the indices now in the LRU, you may find you
-have less space for block caching. Adjust your block cache accordingly. See the <xref linkend="block.cache" /> for more detail.
-The block size default size has been changed in 0.92.0 from 0.2 (20 percent of heap) to 0.25.
-</para>
-</section>
+ <section>
+ <title>Memory accounting is different now </title>
+ <para>In 0.92.0, <xref
+ linkend="hfilev2" /> indices and bloom filters take up residence in the same LRU
+ used caching blocks that come from the filesystem. In 0.90.x, the HFile v1 indices
+ lived outside of the LRU so they took up space even if the index was on a ‘cold’
+ file, one that wasn’t being actively used. With the indices now in the LRU, you may
+ find you have less space for block caching. Adjust your block cache accordingly. See
+ the <xref
+ linkend="block.cache" /> for more detail. The block size default size has been
+ changed in 0.92.0 from 0.2 (20 percent of heap) to 0.25. </para>
+ </section>
-<section><title>On the Hadoop version to use
-</title>
-<para>Run 0.92.0 on Hadoop 1.0.x (or CDH3u3 when it ships). The performance benefits are worth making the move. Otherwise, our Hadoop prescription is as it has been; you need an Hadoop that supports a working sync. See <xref linkend="hadoop" />.
-</para>
+ <section>
+ <title>On the Hadoop version to use </title>
+ <para>Run 0.92.0 on Hadoop 1.0.x (or CDH3u3 when it ships). The performance benefits are
+ worth making the move. Otherwise, our Hadoop prescription is as it has been; you
+ need an Hadoop that supports a working sync. See <xref
+ linkend="hadoop" />. </para>
-<para>If running on Hadoop 1.0.x (or CDH3u3), enable local read. See <link xlink:href="http://files.meetup.com/1350427/hug_ebay_jdcryans.pdf">Practical Caching</link> presentation for ruminations on the performance benefits ‘going local’ (and for how to enable local reads).
-</para>
-</section>
-<section><title>HBase 0.92.0 ships with ZooKeeper 3.4.2
-</title>
-<para>If you can, upgrade your zookeeper. If you can’t, 3.4.2 clients should work against 3.3.X ensembles (HBase makes use of 3.4.2 API).
-</para>
-</section>
-<section>
-<title>Online alter is off by default
-</title>
-<para>In 0.92.0, we’ve added an experimental online schema alter facility (See <xref linkend="hbase.online.schema.update.enable" />). Its off by default. Enable it at your own risk. Online alter and splitting tables do not play well together so be sure your cluster quiescent using this feature (for now).
-</para>
-</section>
-<section>
-<title>WebUI
-</title>
-<para>The webui has had a few additions made in 0.92.0. It now shows a list of the regions currently transitioning, recent compactions/flushes, and a process list of running processes (usually empty if all is well and requests are being handled promptly). Other additions including requests by region, a debugging servlet dump, etc.
-</para>
-</section>
-<section>
-<title>Security tarball
-</title>
-<para>We now ship with two tarballs; secure and insecure HBase. Documentation on how to setup a secure HBase is on the way.
-</para>
-</section>
+ <para>If running on Hadoop 1.0.x (or CDH3u3), enable local read. See <link
+ xlink:href="http://files.meetup.com/1350427/hug_ebay_jdcryans.pdf">Practical
+ Caching</link> presentation for ruminations on the performance benefits ‘going
+ local’ (and for how to enable local reads). </para>
+ </section>
+ <section>
+ <title>HBase 0.92.0 ships with ZooKeeper 3.4.2 </title>
+ <para>If you can, upgrade your zookeeper. If you can’t, 3.4.2 clients should work
+ against 3.3.X ensembles (HBase makes use of 3.4.2 API). </para>
+ </section>
+ <section>
+ <title>Online alter is off by default </title>
+ <para>In 0.92.0, we’ve added an experimental online schema alter facility (See <xref
+ linkend="hbase.online.schema.update.enable" />). Its off by default. Enable it
+ at your own risk. Online alter and splitting tables do not play well together so be
+ sure your cluster quiescent using this feature (for now). </para>
+ </section>
+ <section>
+ <title>WebUI </title>
+ <para>The webui has had a few additions made in 0.92.0. It now shows a list of the
+ regions currently transitioning, recent compactions/flushes, and a process list of
+ running processes (usually empty if all is well and requests are being handled
+ promptly). Other additions including requests by region, a debugging servlet dump,
+ etc. </para>
+ </section>
+ <section>
+ <title>Security tarball </title>
+ <para>We now ship with two tarballs; secure and insecure HBase. Documentation on how to
+ setup a secure HBase is on the way. </para>
+ </section>
-<section xml:id="slabcache"><title>Experimental off-heap cache: SlabCache</title>
-<para>
-A new cache was contributed to 0.92.0 to act as a solution between using the “on-heap” cache which is the current LRU cache the region servers have and the operating system cache which is out of our control.
-To enable <emphasis>SlabCache</emphasis>, as this feature is being called, set “-XX:MaxDirectMemorySize” in hbase-env.sh to the value for maximum direct memory size and specify
-<property>hbase.offheapcache.percentage</property> in <filename>hbase-site.xml</filename> with the percentage that you want to dedicate to off-heap cache. This should only be set for servers and not for clients. Use at your own risk.
-See this blog post, <link xlink:href="http://www.cloudera.com/blog/2012/01/caching-in-hbase-slabcache/">Caching in Apache HBase: SlabCache</link>, for additional information on this new experimental feature.
-</para>
-<para>This feature has mostly been eclipsed in later HBases. See <link xlink:href="https://issues.apache.org/jira/browse/HBASE-7404 ">HBASE-7404 Bucket Cache:A solution about CMS,Heap Fragment and Big Cache on HBASE</link>, etc.</para>
-</section>
+ <section
+ xml:id="slabcache">
+ <title>Experimental off-heap cache: SlabCache</title>
+ <para> A new cache was contributed to 0.92.0 to act as a solution between using the
+ “on-heap” cache which is the current LRU cache the region servers have and the
+ operating system cache which is out of our control. To enable
+ <emphasis>SlabCache</emphasis>, as this feature is being called, set
+ “-XX:MaxDirectMemorySize” in hbase-env.sh to the value for maximum direct memory
+ size and specify <property>hbase.offheapcache.percentage</property> in
+ <filename>hbase-site.xml</filename> with the percentage that you want to
+ dedicate to off-heap cache. This should only be set for servers and not for clients.
+ Use at your own risk. See this blog post, <link
+ xlink:href="http://www.cloudera.com/blog/2012/01/caching-in-hbase-slabcache/">Caching
+ in Apache HBase: SlabCache</link>, for additional information on this new
+ experimental feature. </para>
+ <para>This feature has mostly been eclipsed in later HBases. See <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-7404 ">HBASE-7404 Bucket
+ Cache:A solution about CMS,Heap Fragment and Big Cache on HBASE</link>,
+ etc.</para>
+ </section>
-<section><title>Changes in HBase replication
-</title>
-<para>0.92.0 adds two new features: multi-slave and multi-master replication. The way to enable this is the same as adding a new peer, so in order to have multi-master you would just run add_peer for each cluster that acts as a master to the other slave clusters. Collisions are handled at the timestamp level which may or may not be what you want, this needs to be evaluated on a per use case basis. Replication is still experimental in 0.92 and is disabled by default, run it at your own risk.
-</para>
-</section>
+ <section>
+ <title>Changes in HBase replication </title>
+ <para>0.92.0 adds two new features: multi-slave and multi-master replication. The way to
+ enable this is the same as adding a new peer, so in order to have multi-master you
+ would just run add_peer for each cluster that acts as a master to the other slave
+ clusters. Collisions are handled at the timestamp level which may or may not be what
+ you want, this needs to be evaluated on a per use case basis. Replication is still
+ experimental in 0.92 and is disabled by default, run it at your own risk. </para>
+ </section>
-<section><title>RegionServer now aborts if OOME
-</title>
-<para>If an OOME, we now have the JVM kill -9 the regionserver process so it goes down fast. Previous, a RegionServer might stick around after incurring an OOME limping along in some wounded state. To disable this facility, and recommend you leave it in place, you’d need to edit the bin/hbase file. Look for the addition of the -XX:OnOutOfMemoryError="kill -9 %p" arguments (See [HBASE-4769] - ‘Abort RegionServer Immediately on OOME’)
-</para>
-</section>
+ <section>
+ <title>RegionServer now aborts if OOME </title>
+ <para>If an OOME, we now have the JVM kill -9 the regionserver process so it goes down
+ fast. Previous, a RegionServer might stick around after incurring an OOME limping
+ along in some wounded state. To disable this facility, and recommend you leave it in
+ place, you’d need to edit the bin/hbase file. Look for the addition of the
+ -XX:OnOutOfMemoryError="kill -9 %p" arguments (See [HBASE-4769] - ‘Abort
+ RegionServer Immediately on OOME’) </para>
+ </section>
-<section><title>HFile V2 and the “Bigger, Fewer” Tendency
-</title>
-<para>0.92.0 stores data in a new format, <xref linkend="hfilev2" />. As HBase runs, it will move all your data from HFile v1 to HFile v2 format. This auto-migration will run in the background as flushes and compactions run.
-HFile V2 allows HBase run with larger regions/files. In fact, we encourage that all HBasers going forward tend toward Facebook axiom #1, run with larger, fewer regions.
-If you have lots of regions now -- more than 100s per host -- you should look into setting your region size up after you move to 0.92.0 (In 0.92.0, default size is now 1G, up from 256M), and then running online merge tool (See “HBASE-1621 merge tool should work on online cluster, but disabled table”).
-</para>
-</section>
- </section>
- <section xml:id="upgrade0.90">
- <title>Upgrading to HBase 0.90.x from 0.20.x or 0.89.x</title>
- <para>This version of 0.90.x HBase can be started on data written by
- HBase 0.20.x or HBase 0.89.x. There is no need of a migration step.
- HBase 0.89.x and 0.90.x does write out the name of region directories
- differently -- it names them with a md5 hash of the region name rather
- than a jenkins hash -- so this means that once started, there is no
- going back to HBase 0.20.x.
- </para>
- <para>
- Be sure to remove the <filename>hbase-default.xml</filename> from
- your <filename>conf</filename>
- directory on upgrade. A 0.20.x version of this file will have
- sub-optimal configurations for 0.90.x HBase. The
- <filename>hbase-default.xml</filename> file is now bundled into the
- HBase jar and read from there. If you would like to review
- the content of this file, see it in the src tree at
- <filename>src/main/resources/hbase-default.xml</filename> or
- see <xref linkend="hbase_default_configurations" />.
- </para>
- <para>
- Finally, if upgrading from 0.20.x, check your
- <varname>.META.</varname> schema in the shell. In the past we would
- recommend that users run with a 16kb
- <varname>MEMSTORE_FLUSHSIZE</varname>.
- Run <code>hbase> scan '-ROOT-'</code> in the shell. This will output
- the current <varname>.META.</varname> schema. Check
- <varname>MEMSTORE_FLUSHSIZE</varname> size. Is it 16kb (16384)? If so, you will
- need to change this (The 'normal'/default value is 64MB (67108864)).
- Run the script <filename>bin/set_meta_memstore_size.rb</filename>.
- This will make the necessary edit to your <varname>.META.</varname> schema.
- Failure to run this change will make for a slow cluster <footnote>
- <para>
- See <link xlink:href="https://issues.apache.org/jira/browse/HBASE-3499">HBASE-3499 Users upgrading to 0.90.0 need to have their .META. table updated with the right MEMSTORE_SIZE</link>
+ <section>
+ <title>HFile V2 and the “Bigger, Fewer” Tendency </title>
+ <para>0.92.0 stores data in a new format, <xref
+ linkend="hfilev2" />. As HBase runs, it will move all your data from HFile v1 to
+ HFile v2 format. This auto-migration will run in the background as flushes and
+ compactions run. HFile V2 allows HBase run with larger regions/files. In fact, we
+ encourage that all HBasers going forward tend toward Facebook axiom #1, run with
+ larger, fewer regions. If you have lots of regions now -- more than 100s per host --
+ you should look into setting your region size up after you move to 0.92.0 (In
+ 0.92.0, default size is now 1G, up from 256M), and then running online merge tool
+ (See “HBASE-1621 merge tool should work on online cluster, but disabled table”).
</para>
- </footnote>
- .
-
- </para>
- </section>
- </chapter>
+ </section>
+ </section>
+ <section
+ xml:id="upgrade0.90">
+ <title>Upgrading to HBase 0.90.x from 0.20.x or 0.89.x</title>
+ <para>This version of 0.90.x HBase can be started on data written by HBase 0.20.x or HBase
+ 0.89.x. There is no need of a migration step. HBase 0.89.x and 0.90.x does write out the
+ name of region directories differently -- it names them with a md5 hash of the region
+ name rather than a jenkins hash -- so this means that once started, there is no going
+ back to HBase 0.20.x. </para>
+ <para> Be sure to remove the <filename>hbase-default.xml</filename> from your
+ <filename>conf</filename> directory on upgrade. A 0.20.x version of this file will
+ have sub-optimal configurations for 0.90.x HBase. The
+ <filename>hbase-default.xml</filename> file is now bundled into the HBase jar and
+ read from there. If you would like to review the content of this file, see it in the src
+ tree at <filename>src/main/resources/hbase-default.xml</filename> or see <xref
+ linkend="hbase_default_configurations" />. </para>
+ <para> Finally, if upgrading from 0.20.x, check your <varname>.META.</varname> schema in the
+ shell. In the past we would recommend that users run with a 16kb
+ <varname>MEMSTORE_FLUSHSIZE</varname>. Run <code>hbase> scan '-ROOT-'</code> in the
+ shell. This will output the current <varname>.META.</varname> schema. Check
+ <varname>MEMSTORE_FLUSHSIZE</varname> size. Is it 16kb (16384)? If so, you will need
+ to change this (The 'normal'/default value is 64MB (67108864)). Run the script
+ <filename>bin/set_meta_memstore_size.rb</filename>. This will make the necessary
+ edit to your <varname>.META.</varname> schema. Failure to run this change will make for
+ a slow cluster <footnote>
+ <para> See <link
+ xlink:href="https://issues.apache.org/jira/browse/HBASE-3499">HBASE-3499
+ Users upgrading to 0.90.0 need to have their .META. table updated with the
+ right MEMSTORE_SIZE</link>
+ </para>
+ </footnote> . </para>
+ </section>
+</chapter>
[05/14] HBASE-11199 One-time effort to pretty-print the Docbook XML,
to make further patch review easier (Misty Stanley-Jones)
Posted by st...@apache.org.
http://git-wip-us.apache.org/repos/asf/hbase/blob/63e8304e/src/main/docbkx/security.xml
----------------------------------------------------------------------
diff --git a/src/main/docbkx/security.xml b/src/main/docbkx/security.xml
index 1bac920..f0e327d 100644
--- a/src/main/docbkx/security.xml
+++ b/src/main/docbkx/security.xml
@@ -1,13 +1,15 @@
<?xml version="1.0" encoding="UTF-8"?>
-<chapter version="5.0" xml:id="security"
- xmlns="http://docbook.org/ns/docbook"
- xmlns:xlink="http://www.w3.org/1999/xlink"
- xmlns:xi="http://www.w3.org/2001/XInclude"
- xmlns:svg="http://www.w3.org/2000/svg"
- xmlns:m="http://www.w3.org/1998/Math/MathML"
- xmlns:html="http://www.w3.org/1999/xhtml"
- xmlns:db="http://docbook.org/ns/docbook">
-<!--
+<chapter
+ version="5.0"
+ xml:id="security"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:xi="http://www.w3.org/2001/XInclude"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:m="http://www.w3.org/1998/Math/MathML"
+ xmlns:html="http://www.w3.org/1999/xhtml"
+ xmlns:db="http://docbook.org/ns/docbook">
+ <!--
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
@@ -26,1040 +28,1030 @@
* limitations under the License.
*/
-->
-<title>Secure Apache HBase</title>
-<section xml:id="hbase.secure.configuration">
+ <title>Secure Apache HBase</title>
+ <section
+ xml:id="hbase.secure.configuration">
<title>Secure Client Access to Apache HBase</title>
- <para>Newer releases of Apache HBase (>= 0.92) support optional SASL authentication of clients<footnote><para>See
- also Matteo Bertozzi's article on <link xlink:href="http://www.cloudera.com/blog/2012/09/understanding-user-authentication-and-authorization-in-apache-hbase/">Understanding User Authentication and Authorization in Apache HBase</link>.</para></footnote>.</para>
- <para>This describes how to set up Apache HBase and clients for connection to secure HBase resources.</para>
+ <para>Newer releases of Apache HBase (>= 0.92) support optional SASL authentication of clients<footnote>
+ <para>See also Matteo Bertozzi's article on <link
+ xlink:href="http://www.cloudera.com/blog/2012/09/understanding-user-authentication-and-authorization-in-apache-hbase/">Understanding
+ User Authentication and Authorization in Apache HBase</link>.</para>
+ </footnote>.</para>
+ <para>This describes how to set up Apache HBase and clients for connection to secure HBase
+ resources.</para>
- <section><title>Prerequisites</title>
- <para>
- You need to have a working Kerberos KDC.
- </para>
- <para>
- A HBase configured for secure client access is expected to be running
- on top of a secured HDFS cluster. HBase must be able to authenticate
- to HDFS services. HBase needs Kerberos credentials to interact with
- the Kerberos-enabled HDFS daemons. Authenticating a service should be
- done using a keytab file. The procedure for creating keytabs for HBase
- service is the same as for creating keytabs for Hadoop. Those steps
- are omitted here. Copy the resulting keytab files to wherever HBase
- Master and RegionServer processes are deployed and make them readable
- only to the user account under which the HBase daemons will run.
- </para>
- <para>
- A Kerberos principal has three parts, with the form
- <code>username/fully.qualified.domain.name@YOUR-REALM.COM</code>. We
- recommend using <code>hbase</code> as the username portion.
- </para>
- <para>
- The following is an example of the configuration properties for
- Kerberos operation that must be added to the
- <code>hbase-site.xml</code> file on every server machine in the
- cluster. Required for even the most basic interactions with a
- secure Hadoop configuration, independent of HBase security.
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.regionserver.kerberos.principal</name>
- <value>hbase/_HOST@YOUR-REALM.COM</value>
- </property>
- <property>
- <name>hbase.regionserver.keytab.file</name>
- <value>/etc/hbase/conf/keytab.krb5</value>
- </property>
- <property>
- <name>hbase.master.kerberos.principal</name>
- <value>hbase/_HOST@YOUR-REALM.COM</value>
- </property>
- <property>
- <name>hbase.master.keytab.file</name>
- <value>/etc/hbase/conf/keytab.krb5</value>
- </property>
+ <section>
+ <title>Prerequisites</title>
+ <para> You need to have a working Kerberos KDC. </para>
+ <para> A HBase configured for secure client access is expected to be running on top of a
+ secured HDFS cluster. HBase must be able to authenticate to HDFS services. HBase needs
+ Kerberos credentials to interact with the Kerberos-enabled HDFS daemons. Authenticating a
+ service should be done using a keytab file. The procedure for creating keytabs for HBase
+ service is the same as for creating keytabs for Hadoop. Those steps are omitted here. Copy
+ the resulting keytab files to wherever HBase Master and RegionServer processes are deployed
+ and make them readable only to the user account under which the HBase daemons will run. </para>
+ <para> A Kerberos principal has three parts, with the form
+ <code>username/fully.qualified.domain.name@YOUR-REALM.COM</code>. We recommend using
+ <code>hbase</code> as the username portion. </para>
+ <para> The following is an example of the configuration properties for Kerberos operation that
+ must be added to the <code>hbase-site.xml</code> file on every server machine in the
+ cluster. Required for even the most basic interactions with a secure Hadoop configuration,
+ independent of HBase security. </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.regionserver.kerberos.principal</name>
+ <value>hbase/_HOST@YOUR-REALM.COM</value>
+</property>
+<property>
+ <name>hbase.regionserver.keytab.file</name>
+ <value>/etc/hbase/conf/keytab.krb5</value>
+</property>
+<property>
+ <name>hbase.master.kerberos.principal</name>
+ <value>hbase/_HOST@YOUR-REALM.COM</value>
+</property>
+<property>
+ <name>hbase.master.keytab.file</name>
+ <value>/etc/hbase/conf/keytab.krb5</value>
+</property>
]]></programlisting>
- <para>
- Each HBase client user should also be given a Kerberos principal. This
- principal should have a password assigned to it (as opposed to a
- keytab file). The client principal's <code>maxrenewlife</code> should
- be set so that it can be renewed enough times for the HBase client
- process to complete. For example, if a user runs a long-running HBase
- client process that takes at most 3 days, we might create this user's
- principal within <code>kadmin</code> with: <code>addprinc -maxrenewlife
- 3days</code>
- </para>
- <para>
- Long running daemons with indefinite lifetimes that require client
- access to HBase can instead be configured to log in from a keytab. For
- each host running such daemons, create a keytab with
- <code>kadmin</code> or <code>kadmin.local</code>. The procedure for
- creating keytabs for HBase service is the same as for creating
- keytabs for Hadoop. Those steps are omitted here. Copy the resulting
- keytab files to where the client daemon will execute and make them
- readable only to the user account under which the daemon will run.
- </para>
+ <para> Each HBase client user should also be given a Kerberos principal. This principal should
+ have a password assigned to it (as opposed to a keytab file). The client principal's
+ <code>maxrenewlife</code> should be set so that it can be renewed enough times for the
+ HBase client process to complete. For example, if a user runs a long-running HBase client
+ process that takes at most 3 days, we might create this user's principal within
+ <code>kadmin</code> with: <code>addprinc -maxrenewlife 3days</code>
+ </para>
+ <para> Long running daemons with indefinite lifetimes that require client access to HBase can
+ instead be configured to log in from a keytab. For each host running such daemons, create a
+ keytab with <code>kadmin</code> or <code>kadmin.local</code>. The procedure for creating
+ keytabs for HBase service is the same as for creating keytabs for Hadoop. Those steps are
+ omitted here. Copy the resulting keytab files to where the client daemon will execute and
+ make them readable only to the user account under which the daemon will run. </para>
</section>
- <section><title>Server-side Configuration for Secure Operation</title>
- <para>
- Add the following to the <code>hbase-site.xml</code> file on every server machine in the cluster:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.security.authentication</name>
- <value>kerberos</value>
- </property>
- <property>
- <name>hbase.security.authorization</name>
- <value>true</value>
- </property>
- <property>
- <name>hbase.coprocessor.region.classes</name>
- <value>org.apache.hadoop.hbase.security.token.TokenProvider</value>
- </property>
+ <section>
+ <title>Server-side Configuration for Secure Operation</title>
+ <para> Add the following to the <code>hbase-site.xml</code> file on every server machine in
+ the cluster: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.security.authentication</name>
+ <value>kerberos</value>
+</property>
+<property>
+ <name>hbase.security.authorization</name>
+ <value>true</value>
+</property>
+<property>
+<name>hbase.coprocessor.region.classes</name>
+ <value>org.apache.hadoop.hbase.security.token.TokenProvider</value>
+</property>
]]></programlisting>
- <para>
- A full shutdown and restart of HBase service is required when deploying
- these configuration changes.
- </para>
+ <para> A full shutdown and restart of HBase service is required when deploying these
+ configuration changes. </para>
</section>
- <section><title>Client-side Configuration for Secure Operation</title>
- <para>
- Add the following to the <code>hbase-site.xml</code> file on every client:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.security.authentication</name>
- <value>kerberos</value>
- </property>
+ <section>
+ <title>Client-side Configuration for Secure Operation</title>
+ <para> Add the following to the <code>hbase-site.xml</code> file on every client: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.security.authentication</name>
+ <value>kerberos</value>
+</property>
]]></programlisting>
- <para>
- The client environment must be logged in to Kerberos from KDC or
- keytab via the <code>kinit</code> command before communication with
- the HBase cluster will be possible.
- </para>
- <para>
- Be advised that if the <code>hbase.security.authentication</code>
- in the client- and server-side site files do not match, the client will
- not be able to communicate with the cluster.
- </para>
- <para>
- Once HBase is configured for secure RPC it is possible to optionally
- configure encrypted communication. To do so, add the following to the
- <code>hbase-site.xml</code> file on every client:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.rpc.protection</name>
- <value>privacy</value>
- </property>
+ <para> The client environment must be logged in to Kerberos from KDC or keytab via the
+ <code>kinit</code> command before communication with the HBase cluster will be possible. </para>
+ <para> Be advised that if the <code>hbase.security.authentication</code> in the client- and
+ server-side site files do not match, the client will not be able to communicate with the
+ cluster. </para>
+ <para> Once HBase is configured for secure RPC it is possible to optionally configure
+ encrypted communication. To do so, add the following to the <code>hbase-site.xml</code> file
+ on every client: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.rpc.protection</name>
+ <value>privacy</value>
+</property>
]]></programlisting>
- <para>
- This configuration property can also be set on a per connection basis.
- Set it in the <code>Configuration</code> supplied to
- <code>HTable</code>:
- </para>
- <programlisting>
- Configuration conf = HBaseConfiguration.create();
- conf.set("hbase.rpc.protection", "privacy");
- HTable table = new HTable(conf, tablename);
+ <para> This configuration property can also be set on a per connection basis. Set it in the
+ <code>Configuration</code> supplied to <code>HTable</code>: </para>
+ <programlisting>
+Configuration conf = HBaseConfiguration.create();
+conf.set("hbase.rpc.protection", "privacy");
+HTable table = new HTable(conf, tablename);
</programlisting>
- <para>
- Expect a ~10% performance penalty for encrypted communication.
- </para>
+ <para> Expect a ~10% performance penalty for encrypted communication. </para>
</section>
- <section><title>Client-side Configuration for Secure Operation - Thrift Gateway</title>
- <para>
- Add the following to the <code>hbase-site.xml</code> file for every Thrift gateway:
- <programlisting><![CDATA[
- <property>
- <name>hbase.thrift.keytab.file</name>
- <value>/etc/hbase/conf/hbase.keytab</value>
- </property>
- <property>
- <name>hbase.thrift.kerberos.principal</name>
- <value>$USER/_HOST@HADOOP.LOCALDOMAIN</value>
- <!-- TODO: This may need to be HTTP/_HOST@<REALM> and _HOST may not work.
- You may have to put the concrete full hostname.
- -->
- </property>
+ <section>
+ <title>Client-side Configuration for Secure Operation - Thrift Gateway</title>
+ <para> Add the following to the <code>hbase-site.xml</code> file for every Thrift gateway: <programlisting><![CDATA[
+<property>
+ <name>hbase.thrift.keytab.file</name>
+ <value>/etc/hbase/conf/hbase.keytab</value>
+</property>
+<property>
+ <name>hbase.thrift.kerberos.principal</name>
+ <value>$USER/_HOST@HADOOP.LOCALDOMAIN</value>
+ <!-- TODO: This may need to be HTTP/_HOST@<REALM> and _HOST may not work.
+ You may have to put the concrete full hostname.
+ -->
+</property>
]]></programlisting>
- </para>
- <para>
- Substitute the appropriate credential and keytab for $USER and $KEYTAB
- respectively.
- </para>
- <para>In order to use the Thrift API principal to interact with HBase, it is also necessary to add the <code>hbase.thrift.kerberos.principal</code> to the <code>_acl_</code> table. For example, to give the Thrift API principal, <code>thrift_server</code>, administrative access, a command such as this one will suffice:
- <programlisting><![CDATA[
- grant 'thrift_server', 'RWCA'
- ]]></programlisting> For more information about ACLs, please see the <link linkend='hbase.accesscontrol.configuration'>Access Control</link> section
- </para>
+ </para>
+ <para> Substitute the appropriate credential and keytab for $USER and $KEYTAB respectively. </para>
+ <para>In order to use the Thrift API principal to interact with HBase, it is also necessary to
+ add the <code>hbase.thrift.kerberos.principal</code> to the <code>_acl_</code> table. For
+ example, to give the Thrift API principal, <code>thrift_server</code>, administrative
+ access, a command such as this one will suffice: </para>
+ <programlisting><![CDATA[
+grant 'thrift_server', 'RWCA'
+ ]]></programlisting>
+ <para>For more information about ACLs, please see the <link
+ linkend="hbase.accesscontrol.configuration">Access Control</link> section </para>
- <para>
- The Thrift gateway will authenticate with HBase using the supplied
- credential. No authentication will be performed by the Thrift gateway
- itself. All client access via the Thrift gateway will use the Thrift
- gateway's credential and have its privilege.
- </para>
+ <para> The Thrift gateway will authenticate with HBase using the supplied credential. No
+ authentication will be performed by the Thrift gateway itself. All client access via the
+ Thrift gateway will use the Thrift gateway's credential and have its privilege. </para>
</section>
- <section><title>Client-side Configuration for Secure Operation - REST Gateway</title>
- <para>
- Add the following to the <code>hbase-site.xml</code> file for every REST gateway:
- <programlisting><![CDATA[
- <property>
- <name>hbase.rest.keytab.file</name>
- <value>$KEYTAB</value>
- </property>
- <property>
- <name>hbase.rest.kerberos.principal</name>
- <value>$USER/_HOST@HADOOP.LOCALDOMAIN</value>
- </property>
+ <section>
+ <title>Client-side Configuration for Secure Operation - REST Gateway</title>
+ <para> Add the following to the <code>hbase-site.xml</code> file for every REST gateway: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.rest.keytab.file</name>
+ <value>$KEYTAB</value>
+</property>
+<property>
+ <name>hbase.rest.kerberos.principal</name>
+ <value>$USER/_HOST@HADOOP.LOCALDOMAIN</value>
+</property>
]]></programlisting>
- </para>
- <para>
- Substitute the appropriate credential and keytab for $USER and $KEYTAB
- respectively.
- </para>
- <para>
- The REST gateway will authenticate with HBase using the supplied
- credential. No authentication will be performed by the REST gateway
- itself. All client access via the REST gateway will use the REST
- gateway's credential and have its privilege.
- </para>
- <para>In order to use the REST API principal to interact with HBase, it is also necessary to add the <code>hbase.rest.kerberos.principal</code> to the <code>_acl_</code> table. For example, to give the REST API principal, <code>rest_server</code>, administrative access, a command such as this one will suffice:
- <programlisting><![CDATA[
- grant 'rest_server', 'RWCA'
- ]]></programlisting> For more information about ACLs, please see the <link linkend='hbase.accesscontrol.configuration'>Access Control</link> section
- </para>
- <para>
- It should be possible for clients to authenticate with the HBase
- cluster through the REST gateway in a pass-through manner via SPEGNO
- HTTP authentication. This is future work.
- </para>
- </section>
+ <para> Substitute the appropriate credential and keytab for $USER and $KEYTAB respectively. </para>
+ <para> The REST gateway will authenticate with HBase using the supplied credential. No
+ authentication will be performed by the REST gateway itself. All client access via the REST
+ gateway will use the REST gateway's credential and have its privilege. </para>
+ <para>In order to use the REST API principal to interact with HBase, it is also necessary to
+ add the <code>hbase.rest.kerberos.principal</code> to the <code>_acl_</code> table. For
+ example, to give the REST API principal, <code>rest_server</code>, administrative access, a
+ command such as this one will suffice: </para>
+ <programlisting><![CDATA[
+grant 'rest_server', 'RWCA'
+ ]]></programlisting>
+ <para>For more information about ACLs, please see the <link
+ linkend="hbase.accesscontrol.configuration">Access Control</link> section </para>
+ <para> It should be possible for clients to authenticate with the HBase cluster through the
+ REST gateway in a pass-through manner via SPEGNO HTTP authentication. This is future work.
+ </para>
+ </section>
- <section><title>REST Gateway Impersonation Configuration</title>
- <para>
- By default, the REST gateway doesn't support impersonation. It accesses
- the HBase on behalf of clients as the user configured as in the previous
- section. To the HBase server, all requests are from the REST gateway user.
- The actual users are unknown. You can turn on the impersonation support.
- With impersonation, the REST gateway user is a proxy user. The HBase server
- knows the acutal/real user of each request. So it can apply proper
- authorizations.
- </para>
- <para>
- To turn on REST gateway impersonation, we need to configure HBase servers
- (masters and region servers) to allow proxy users; configure REST gateway
- to enable impersonation.
- </para>
- <para>
- To allow proxy users, add the following to the <code>hbase-site.xml</code>
- file for every HBase server:
- <programlisting><![CDATA[
- <property>
- <name>hadoop.security.authorization</name>
- <value>true</value>
- </property>
- <property>
- <name>hadoop.proxyuser.$USER.groups</name>
- <value>$GROUPS</value>
- </property>
- <property>
- <name>hadoop.proxyuser.$USER.hosts</name>
- <value>$GROUPS</value>
- </property>
+ <section>
+ <title>REST Gateway Impersonation Configuration</title>
+ <para> By default, the REST gateway doesn't support impersonation. It accesses the HBase on
+ behalf of clients as the user configured as in the previous section. To the HBase server,
+ all requests are from the REST gateway user. The actual users are unknown. You can turn on
+ the impersonation support. With impersonation, the REST gateway user is a proxy user. The
+ HBase server knows the acutal/real user of each request. So it can apply proper
+ authorizations. </para>
+ <para> To turn on REST gateway impersonation, we need to configure HBase servers (masters and
+ region servers) to allow proxy users; configure REST gateway to enable impersonation. </para>
+ <para> To allow proxy users, add the following to the <code>hbase-site.xml</code> file for
+ every HBase server: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hadoop.security.authorization</name>
+ <value>true</value>
+</property>
+<property>
+ <name>hadoop.proxyuser.$USER.groups</name>
+ <value>$GROUPS</value>
+</property>
+<property>
+ <name>hadoop.proxyuser.$USER.hosts</name>
+ <value>$GROUPS</value>
+</property>
]]></programlisting>
- </para>
- <para>
- Substitute the REST gateway proxy user for $USER, and the allowed
- group list for $GROUPS.
- </para>
- <para>
- To enable REST gateway impersonation, add the following to the
- <code>hbase-site.xml</code> file for every REST gateway.
- <programlisting><![CDATA[
- <property>
- <name>hbase.rest.authentication.type</name>
- <value>kerberos</value>
- </property>
- <property>
- <name>hbase.rest.authentication.kerberos.principal</name>
- <value>HTTP/_HOST@HADOOP.LOCALDOMAIN</value>
- </property>
- <property>
- <name>hbase.rest.authentication.kerberos.keytab</name>
- <value>$KEYTAB</value>
- </property>
+ <para> Substitute the REST gateway proxy user for $USER, and the allowed group list for
+ $GROUPS. </para>
+ <para> To enable REST gateway impersonation, add the following to the
+ <code>hbase-site.xml</code> file for every REST gateway. </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.rest.authentication.type</name>
+ <value>kerberos</value>
+</property>
+<property>
+ <name>hbase.rest.authentication.kerberos.principal</name>
+ <value>HTTP/_HOST@HADOOP.LOCALDOMAIN</value>
+</property>
+<property>
+ <name>hbase.rest.authentication.kerberos.keytab</name>
+ <value>$KEYTAB</value>
+</property>
]]></programlisting>
- </para>
- <para>
- Substitute the keytab for HTTP for $KEYTAB.
- </para>
- </section>
+ <para> Substitute the keytab for HTTP for $KEYTAB. </para>
+ </section>
-</section> <!-- Secure Client Access to HBase -->
+ </section>
+ <!-- Secure Client Access to HBase -->
-<section xml:id="hbase.secure.simpleconfiguration">
+ <section
+ xml:id="hbase.secure.simpleconfiguration">
<title>Simple User Access to Apache HBase</title>
- <para>Newer releases of Apache HBase (>= 0.92) support optional SASL authentication of clients<footnote><para>See
- also Matteo Bertozzi's article on <link xlink:href="http://www.cloudera.com/blog/2012/09/understanding-user-authentication-and-authorization-in-apache-hbase/">Understanding User Authentication and Authorization in Apache HBase</link>.</para></footnote>.</para>
- <para>This describes how to set up Apache HBase and clients for simple user access to HBase resources.</para>
+ <para>Newer releases of Apache HBase (>= 0.92) support optional SASL authentication of clients<footnote>
+ <para>See also Matteo Bertozzi's article on <link
+ xlink:href="http://www.cloudera.com/blog/2012/09/understanding-user-authentication-and-authorization-in-apache-hbase/">Understanding
+ User Authentication and Authorization in Apache HBase</link>.</para>
+ </footnote>.</para>
+ <para>This describes how to set up Apache HBase and clients for simple user access to HBase
+ resources.</para>
- <section><title>Simple Versus Secure Access</title>
- <para>
- The following section shows how to set up simple user access. Simple user access is
- not a secure method of operating HBase. This method is used to prevent users from making
- mistakes. It can be used to mimic the Access Control using on a development system without having to
- set up Kerberos.
- </para>
- <para>
- This method is not used to prevent malicious or hacking attempts. To make HBase secure against these
- types of attacks, you must configure HBase for secure operation. Refer to the section
- <link linkend='hbase.accesscontrol.configuration'>Secure Client Access to HBase</link> and complete all of the steps described
- there.
- </para>
+ <section>
+ <title>Simple Versus Secure Access</title>
+ <para> The following section shows how to set up simple user access. Simple user access is not
+ a secure method of operating HBase. This method is used to prevent users from making
+ mistakes. It can be used to mimic the Access Control using on a development system without
+ having to set up Kerberos. </para>
+ <para> This method is not used to prevent malicious or hacking attempts. To make HBase secure
+ against these types of attacks, you must configure HBase for secure operation. Refer to the
+ section <link
+ linkend="hbase.accesscontrol.configuration">Secure Client Access to HBase</link> and
+ complete all of the steps described there. </para>
- <section><title>Prerequisites</title>
- <para>
- None
- </para>
+ <section>
+ <title>Prerequisites</title>
+ <para> None </para>
- <section><title>Server-side Configuration for Simple User Access Operation</title>
- <para>
- Add the following to the <code>hbase-site.xml</code> file on every server machine in the cluster:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.security.authentication</name>
- <value>simple</value>
- </property>
- <property>
- <name>hbase.security.authorization</name>
- <value>true</value>
- </property>
- <property>
- <name>hbase.coprocessor.master.classes</name>
- <value>org.apache.hadoop.hbase.security.access.AccessController</value>
- </property>
- <property>
- <name>hbase.coprocessor.region.classes</name>
- <value>org.apache.hadoop.hbase.security.access.AccessController</value>
- </property>
+ <section>
+ <title>Server-side Configuration for Simple User Access Operation</title>
+ <para> Add the following to the <code>hbase-site.xml</code> file on every server machine
+ in the cluster: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.security.authentication</name>
+ <value>simple</value>
+</property>
+<property>
+ <name>hbase.security.authorization</name>
+ <value>true</value>
+</property>
+<property>
+ <name>hbase.coprocessor.master.classes</name>
+ <value>org.apache.hadoop.hbase.security.access.AccessController</value>
+</property>
+<property>
+ <name>hbase.coprocessor.region.classes</name>
+ <value>org.apache.hadoop.hbase.security.access.AccessController</value>
+</property>
]]></programlisting>
- <para>
- For 0.94, add the following to the <code>hbase-site.xml</code> file on every server machine in the cluster:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.rpc.engine</name>
- <value>org.apache.hadoop.hbase.ipc.SecureRpcEngine</value>
- </property>
- <property>
- <name>hbase.coprocessor.master.classes</name>
- <value>org.apache.hadoop.hbase.security.access.AccessController</value>
- </property>
- <property>
- <name>hbase.coprocessor.region.classes</name>
- <value>org.apache.hadoop.hbase.security.access.AccessController</value>
- </property>
+ <para> For 0.94, add the following to the <code>hbase-site.xml</code> file on every server
+ machine in the cluster: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.rpc.engine</name>
+ <value>org.apache.hadoop.hbase.ipc.SecureRpcEngine</value>
+</property>
+<property>
+ <name>hbase.coprocessor.master.classes</name>
+ <value>org.apache.hadoop.hbase.security.access.AccessController</value>
+</property>
+<property>
+ <name>hbase.coprocessor.region.classes</name>
+ <value>org.apache.hadoop.hbase.security.access.AccessController</value>
+</property>
]]></programlisting>
- <para>
- A full shutdown and restart of HBase service is required when deploying
- these configuration changes.
- </para>
- </section>
+ <para> A full shutdown and restart of HBase service is required when deploying these
+ configuration changes. </para>
+ </section>
- <section><title>Client-side Configuration for Simple User Access Operation</title>
- <para>
- Add the following to the <code>hbase-site.xml</code> file on every client:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.security.authentication</name>
- <value>simple</value>
- </property>
+ <section>
+ <title>Client-side Configuration for Simple User Access Operation</title>
+ <para> Add the following to the <code>hbase-site.xml</code> file on every client: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.security.authentication</name>
+ <value>simple</value>
+</property>
]]></programlisting>
- <para>
- For 0.94, add the following to the <code>hbase-site.xml</code> file on every server machine in the cluster:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.rpc.engine</name>
- <value>org.apache.hadoop.hbase.ipc.SecureRpcEngine</value>
- </property>
+ <para> For 0.94, add the following to the <code>hbase-site.xml</code> file on every server
+ machine in the cluster: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.rpc.engine</name>
+ <value>org.apache.hadoop.hbase.ipc.SecureRpcEngine</value>
+</property>
]]></programlisting>
- <para>
- Be advised that if the <code>hbase.security.authentication</code>
- in the client- and server-side site files do not match, the client will
- not be able to communicate with the cluster.
- </para>
- </section>
+ <para> Be advised that if the <code>hbase.security.authentication</code> in the client-
+ and server-side site files do not match, the client will not be able to communicate with
+ the cluster. </para>
+ </section>
- <section><title>Client-side Configuration for Simple User Access Operation - Thrift Gateway</title>
- <para>The Thrift gateway user will need access. For example, to give the Thrift API user, <code>thrift_server</code>, administrative access, a command such as this one will suffice:
- <programlisting><![CDATA[
- grant 'thrift_server', 'RWCA'
- ]]></programlisting> For more information about ACLs, please see the <link linkend='hbase.accesscontrol.configuration'>Access Control</link> section
- </para>
+ <section>
+ <title>Client-side Configuration for Simple User Access Operation - Thrift Gateway</title>
+ <para>The Thrift gateway user will need access. For example, to give the Thrift API user,
+ <code>thrift_server</code>, administrative access, a command such as this one will
+ suffice: </para>
+ <programlisting><![CDATA[
+grant 'thrift_server', 'RWCA'
+ ]]></programlisting>
+ <para>For more information about ACLs, please see the <link
+ linkend="hbase.accesscontrol.configuration">Access Control</link> section </para>
- <para>
- The Thrift gateway will authenticate with HBase using the supplied
- credential. No authentication will be performed by the Thrift gateway
- itself. All client access via the Thrift gateway will use the Thrift
- gateway's credential and have its privilege.
- </para>
- </section>
+ <para> The Thrift gateway will authenticate with HBase using the supplied credential. No
+ authentication will be performed by the Thrift gateway itself. All client access via the
+ Thrift gateway will use the Thrift gateway's credential and have its privilege. </para>
+ </section>
- <section><title>Client-side Configuration for Simple User Access Operation - REST Gateway</title>
+ <section>
+ <title>Client-side Configuration for Simple User Access Operation - REST Gateway</title>
- <para>
- The REST gateway will authenticate with HBase using the supplied
- credential. No authentication will be performed by the REST gateway
- itself. All client access via the REST gateway will use the REST
- gateway's credential and have its privilege.
- </para>
- <para>The REST gateway user will need access. For example, to give the REST API user, <code>rest_server</code>, administrative access, a command such as this one will suffice:
- <programlisting><![CDATA[
- grant 'rest_server', 'RWCA'
- ]]></programlisting> For more information about ACLs, please see the <link linkend='hbase.accesscontrol.configuration'>Access Control</link> section
- </para>
- <para>
- It should be possible for clients to authenticate with the HBase
- cluster through the REST gateway in a pass-through manner via SPEGNO
- HTTP authentication. This is future work.
- </para>
- </section>
- </section>
- </section>
+ <para> The REST gateway will authenticate with HBase using the supplied credential. No
+ authentication will be performed by the REST gateway itself. All client access via the
+ REST gateway will use the REST gateway's credential and have its privilege. </para>
+ <para>The REST gateway user will need access. For example, to give the REST API user,
+ <code>rest_server</code>, administrative access, a command such as this one will
+ suffice: </para>
+ <programlisting><![CDATA[
+grant 'rest_server', 'RWCA'
+ ]]></programlisting>
+ <para>For more information about ACLs, please see the <link
+ linkend="hbase.accesscontrol.configuration">Access Control</link> section </para>
+ <para> It should be possible for clients to authenticate with the HBase cluster through
+ the REST gateway in a pass-through manner via SPEGNO HTTP authentication. This is future
+ work. </para>
+ </section>
+ </section>
+ </section>
-</section> <!-- Simple User Access to Apache HBase -->
+ </section>
+ <!-- Simple User Access to Apache HBase -->
-<section xml:id="hbase.tags">
-<title>Tags</title>
-<para>
- Every cell can have metadata associated with it. Adding metadata in the data part of every cell would make things difficult.
-</para>
-<para>
- The 0.98 version of HBase solves this problem by providing Tags along with the cell format.
- Some of the usecases that uses the tags are Visibility labels, Cell level ACLs, etc.
-</para>
-<para>
- HFile V3 version from 0.98 onwards supports tags and this feature can be turned on using the following configuration
-</para>
-<programlisting><![CDATA[
- <property>
- <name>hfile.format.version</name>
- <value>3</value>
- </property>
+ <section
+ xml:id="hbase.tags">
+ <title>Tags</title>
+ <para> Every cell can have metadata associated with it. Adding metadata in the data part of
+ every cell would make things difficult. </para>
+ <para> The 0.98 version of HBase solves this problem by providing Tags along with the cell
+ format. Some of the usecases that uses the tags are Visibility labels, Cell level ACLs, etc. </para>
+ <para> HFile V3 version from 0.98 onwards supports tags and this feature can be turned on using
+ the following configuration </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hfile.format.version</name>
+ <value>3</value>
+</property>
]]></programlisting>
-<para>
- Every cell can have zero or more tags. Every tag has a type and the actual tag byte array.
- The types <command>0-31</command> are reserved for System tags. For example ‘1’ is reserved for ACL and ‘2’ is reserved for Visibility tags.
-</para>
-<para>
- The way rowkeys, column families, qualifiers and values are encoded using different Encoding Algos, similarly the tags can also be encoded.
- Tag encoding can be turned on per CF. Default is always turn ON.
- To turn on the tag encoding on the HFiles use
-</para>
-<programlisting><![CDATA[
- HColumnDescriptor#setCompressTags(boolean compressTags)
+ <para> Every cell can have zero or more tags. Every tag has a type and the actual tag byte
+ array. The types <command>0-31</command> are reserved for System tags. For example ‘1’ is
+ reserved for ACL and ‘2’ is reserved for Visibility tags. </para>
+ <para> The way rowkeys, column families, qualifiers and values are encoded using different
+ Encoding Algos, similarly the tags can also be encoded. Tag encoding can be turned on per CF.
+ Default is always turn ON. To turn on the tag encoding on the HFiles use </para>
+ <programlisting><![CDATA[
+HColumnDescriptor#setCompressTags(boolean compressTags)
]]></programlisting>
-<para>
- Note that encoding of tags takes place only if the DataBlockEncoder is enabled for the CF.
-</para>
-<para>
- As we compress the WAL entries using Dictionary the tags present in the WAL can also be compressed using Dictionary.
- Every tag is compressed individually using WAL Dictionary. To turn ON tag compression in WAL dictionary enable the property
-</para>
-<programlisting><![CDATA[
- <property>
- <name>hbase.regionserver.wal.tags.enablecompression</name>
- <value>true</value>
- </property>
+ <para> Note that encoding of tags takes place only if the DataBlockEncoder is enabled for the
+ CF. </para>
+ <para> As we compress the WAL entries using Dictionary the tags present in the WAL can also be
+ compressed using Dictionary. Every tag is compressed individually using WAL Dictionary. To
+ turn ON tag compression in WAL dictionary enable the property </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.regionserver.wal.tags.enablecompression</name>
+ <value>true</value>
+</property>
]]></programlisting>
-<para>
- To add tags to every cell during Puts, the following apis are provided
-</para>
-<programlisting><![CDATA[
- Put#add(byte[] family, byte [] qualifier, byte [] value, Tag[] tag)
- Put#add(byte[] family, byte[] qualifier, long ts, byte[] value, Tag[] tag)
+ <para> To add tags to every cell during Puts, the following apis are provided </para>
+ <programlisting><![CDATA[
+Put#add(byte[] family, byte [] qualifier, byte [] value, Tag[] tag)
+Put#add(byte[] family, byte[] qualifier, long ts, byte[] value, Tag[] tag)
]]></programlisting>
-<para>
- Some of the feature developed using tags are Cell level ACLs and Visibility labels.
- These are some features that use tags framework and allows users to gain better security features on cell level.
-</para>
-<para>
- For details checkout
-</para>
-<para>
- <link linkend='hbase.accesscontrol.configuration'>Access Control</link>
- <link linkend='hbase.visibility.labels'>Visibility labels</link>
-</para>
-</section>
-<section xml:id="hbase.accesscontrol.configuration">
- <title>Access Control</title>
+ <para> Some of the feature developed using tags are Cell level ACLs and Visibility labels. These
+ are some features that use tags framework and allows users to gain better security features on
+ cell level. </para>
+ <para> For details, see:</para>
<para>
- Newer releases of Apache HBase (>= 0.92) support optional access control
- list (ACL-) based protection of resources on a column family and/or
- table basis.
- </para>
- <para>
- This describes how to set up Secure HBase for access control, with an
- example of granting and revoking user permission on table resources
- provided.
+ <link
+ linkend="hbase.accesscontrol.configuration">Access Control</link>
+ <link
+ linkend="hbase.visibility.labels">Visibility labels</link>
</para>
+ </section>
+ <section
+ xml:id="hbase.accesscontrol.configuration">
+ <title>Access Control</title>
+ <para> Newer releases of Apache HBase (>= 0.92) support optional access control list (ACL-)
+ based protection of resources on a column family and/or table basis. </para>
+ <para> This describes how to set up Secure HBase for access control, with an example of granting
+ and revoking user permission on table resources provided. </para>
- <section><title>Prerequisites</title>
- <para>
- You must configure HBase for secure or simple user access operation. Refer to the
- <link linkend='hbase.accesscontrol.configuration'>Secure Client Access to HBase</link> or
- <link linkend='hbase.secure.simpleconfiguration'>Simple User Access to HBase</link>
- sections and complete all of the steps described
- there.
- </para>
- <para>
- For secure access, you must also configure ZooKeeper for secure operation. Changes to ACLs
- are synchronized throughout the cluster using ZooKeeper. Secure
- authentication to ZooKeeper must be enabled or otherwise it will be
- possible to subvert HBase access control via direct client access to
- ZooKeeper. Refer to the section on secure ZooKeeper configuration and
- complete all of the steps described there.
- </para>
+ <section>
+ <title>Prerequisites</title>
+ <para> You must configure HBase for secure or simple user access operation. Refer to the <link
+ linkend="hbase.accesscontrol.configuration">Secure Client Access to HBase</link> or <link
+ linkend="hbase.secure.simpleconfiguration">Simple User Access to HBase</link> sections and
+ complete all of the steps described there. </para>
+ <para> For secure access, you must also configure ZooKeeper for secure operation. Changes to
+ ACLs are synchronized throughout the cluster using ZooKeeper. Secure authentication to
+ ZooKeeper must be enabled or otherwise it will be possible to subvert HBase access control
+ via direct client access to ZooKeeper. Refer to the section on secure ZooKeeper
+ configuration and complete all of the steps described there. </para>
</section>
- <section><title>Overview</title>
- <para>
- With Secure RPC and Access Control enabled, client access to HBase is
- authenticated and user data is private unless access has been
- explicitly granted. Access to data can be granted at a table or per
- column family basis.
- </para>
- <para>
- However, the following items have been left out of the initial
- implementation for simplicity:
- </para>
- <orderedlist>
- <listitem>
- <para>Row-level or per value (cell): Using Tags in HFile V3</para>
- </listitem>
- <listitem>
- <para>Push down of file ownership to HDFS: HBase is not designed for the case where files may have different permissions than the HBase system principal. Pushing file ownership down into HDFS would necessitate changes to core code. Also, while HDFS file ownership would make applying quotas easy, and possibly make bulk imports more straightforward, it is not clear that it would offer a more secure setup.</para>
- </listitem>
- <listitem>
- <para>HBase managed "roles" as collections of permissions: We will not model "roles" internally in HBase to begin with. We instead allow group names to be granted permissions, which allows external modeling of roles via group membership. Groups are created and manipulated externally to HBase, via the Hadoop group mapping service.</para>
- </listitem>
- </orderedlist>
- <para>
-Access control mechanisms are mature and fairly standardized in the relational database world. The HBase implementation approximates current convention, but HBase has a simpler feature set than relational databases, especially in terms of client operations. We don't distinguish between an insert (new record) and update (of existing record), for example, as both collapse down into a Put. Accordingly, the important operations condense to four permissions: READ, WRITE, CREATE, and ADMIN.
- </para>
- <table>
- <title>Operation To Permission Mapping</title>
- <tgroup cols='2' align='left' colsep='1' rowsep='1'>
- <colspec colname='c1' align='center'/>
- <colspec colname='c2' align='left'/>
- <thead>
- <row>
- <entry>Permission</entry>
- <entry>Operation</entry>
- </row>
- </thead>
- <tbody>
- <!-- READ -->
- <row>
- <entry>Read</entry>
- <entry>Get</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Exists</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Scan</entry>
- </row>
- <!-- WRITE -->
- <row>
- <entry>Write</entry>
- <entry>Put</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Delete</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Lock/UnlockRow</entry>
- </row>
- <row>
- <entry></entry>
- <entry>IncrementColumnValue</entry>
- </row>
- <row>
- <entry></entry>
- <entry>CheckAndDelete/Put</entry>
- </row>
- <!-- CREATE -->
- <row>
- <entry>Create</entry>
- <entry>Create</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Alter</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Drop</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Bulk Load</entry>
- </row>
- <!-- ADMIN -->
- <row>
- <entry>Admin</entry>
- <entry>Enable/Disable</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Snapshot/Restore/Clone</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Split</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Flush</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Compact</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Major Compact</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Grant</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Revoke</entry>
- </row>
- <row>
- <entry></entry>
- <entry>Shutdown</entry>
- </row>
- </tbody>
- </tgroup>
- </table>
- <para>
- Permissions can be granted in any of the following scopes, though
- CREATE and ADMIN permissions are effective only at table scope.
- </para>
- <para>
- <itemizedlist>
- <listitem>
- <para>Table</para>
- <para>
- <itemizedlist>
- <listitem><para>Read: User can read from any column family in table</para></listitem>
- <listitem><para>Write: User can write to any column family in table</para></listitem>
- <listitem><para>Create: User can alter table attributes; add, alter, or drop column families; and drop the table.</para></listitem>
- <listitem><para>Admin: User can alter table attributes; add, alter, or drop column families; and enable, disable, or drop the table. User can also trigger region (re)assignments or relocation.</para></listitem>
- </itemizedlist>
- </para>
- </listitem>
- <listitem>
- <para>Column Family</para>
- <para>
- <itemizedlist>
- <listitem><para>Read: User can read from the column family</para></listitem>
- <listitem><para>Write: User can write to the column family</para></listitem>
- </itemizedlist>
- </para>
- </listitem>
- </itemizedlist>
- </para>
- <para>
- There is also an implicit global scope for the superuser.
- </para>
- <para>
- The superuser is a principal, specified in the HBase site configuration
- file, that has equivalent access to HBase as the 'root' user would on a
- UNIX derived system. Normally this is the principal that the HBase
- processes themselves authenticate as. Although future versions of HBase
- Access Control may support multiple superusers, the superuser privilege
- will always include the principal used to run the HMaster process. Only
- the superuser is allowed to create tables, switch the balancer on or
- off, or take other actions with global consequence. Furthermore, the
- superuser has an implicit grant of all permissions to all resources.
- </para>
- <para>
- Tables have a new metadata attribute: OWNER, the user principal who owns
- the table. By default this will be set to the user principal who creates
- the table, though it may be changed at table creation time or during an
- alter operation by setting or changing the OWNER table attribute. Only a
- single user principal can own a table at a given time. A table owner will
- have all permissions over a given table.
- </para>
+ <section>
+ <title>Overview</title>
+ <para> With Secure RPC and Access Control enabled, client access to HBase is authenticated and
+ user data is private unless access has been explicitly granted. Access to data can be
+ granted at a table or per column family basis. </para>
+ <para> However, the following items have been left out of the initial implementation for
+ simplicity: </para>
+ <orderedlist>
+ <listitem>
+ <para>Row-level or per value (cell): Using Tags in HFile V3</para>
+ </listitem>
+ <listitem>
+ <para>Push down of file ownership to HDFS: HBase is not designed for the case where files
+ may have different permissions than the HBase system principal. Pushing file ownership
+ down into HDFS would necessitate changes to core code. Also, while HDFS file ownership
+ would make applying quotas easy, and possibly make bulk imports more straightforward, it
+ is not clear that it would offer a more secure setup.</para>
+ </listitem>
+ <listitem>
+ <para>HBase managed "roles" as collections of permissions: We will not model "roles"
+ internally in HBase to begin with. We instead allow group names to be granted
+ permissions, which allows external modeling of roles via group membership. Groups are
+ created and manipulated externally to HBase, via the Hadoop group mapping
+ service.</para>
+ </listitem>
+ </orderedlist>
+ <para> Access control mechanisms are mature and fairly standardized in the relational database
+ world. The HBase implementation approximates current convention, but HBase has a simpler
+ feature set than relational databases, especially in terms of client operations. We don't
+ distinguish between an insert (new record) and update (of existing record), for example, as
+ both collapse down into a Put. Accordingly, the important operations condense to four
+ permissions: READ, WRITE, CREATE, and ADMIN. </para>
+ <table>
+ <title>Operation To Permission Mapping</title>
+ <tgroup
+ cols="2"
+ align="left"
+ colsep="1"
+ rowsep="1">
+ <colspec
+ colname="c1"
+ align="center" />
+ <colspec
+ colname="c2"
+ align="left" />
+ <thead>
+ <row>
+ <entry>Permission</entry>
+ <entry>Operation</entry>
+ </row>
+ </thead>
+ <tbody>
+ <!-- READ -->
+ <row>
+ <entry>Read</entry>
+ <entry>Get</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Exists</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Scan</entry>
+ </row>
+ <!-- WRITE -->
+ <row>
+ <entry>Write</entry>
+ <entry>Put</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Delete</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Lock/UnlockRow</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>IncrementColumnValue</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>CheckAndDelete/Put</entry>
+ </row>
+ <!-- CREATE -->
+ <row>
+ <entry>Create</entry>
+ <entry>Create</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Alter</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Drop</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Bulk Load</entry>
+ </row>
+ <!-- ADMIN -->
+ <row>
+ <entry>Admin</entry>
+ <entry>Enable/Disable</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Snapshot/Restore/Clone</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Split</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Flush</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Compact</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Major Compact</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Grant</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Revoke</entry>
+ </row>
+ <row>
+ <entry />
+ <entry>Shutdown</entry>
+ </row>
+ </tbody>
+ </tgroup>
+ </table>
+ <para> Permissions can be granted in any of the following scopes, though CREATE and ADMIN
+ permissions are effective only at table scope. </para>
+ <itemizedlist>
+ <listitem>
+ <para>Table</para>
+ <para>
+ <itemizedlist>
+ <listitem>
+ <para>Read: User can read from any column family in table</para>
+ </listitem>
+ <listitem>
+ <para>Write: User can write to any column family in table</para>
+ </listitem>
+ <listitem>
+ <para>Create: User can alter table attributes; add, alter, or drop column families;
+ and drop the table.</para>
+ </listitem>
+ <listitem>
+ <para>Admin: User can alter table attributes; add, alter, or drop column families;
+ and enable, disable, or drop the table. User can also trigger region
+ (re)assignments or relocation.</para>
+ </listitem>
+ </itemizedlist>
+ </para>
+ </listitem>
+ <listitem>
+ <para>Column Family</para>
+ <para>
+ <itemizedlist>
+ <listitem>
+ <para>Read: User can read from the column family</para>
+ </listitem>
+ <listitem>
+ <para>Write: User can write to the column family</para>
+ </listitem>
+ </itemizedlist>
+ </para>
+ </listitem>
+ </itemizedlist>
+
+ <para> There is also an implicit global scope for the superuser. </para>
+ <para> The superuser is a principal, specified in the HBase site configuration file, that has
+ equivalent access to HBase as the 'root' user would on a UNIX derived system. Normally this
+ is the principal that the HBase processes themselves authenticate as. Although future
+ versions of HBase Access Control may support multiple superusers, the superuser privilege
+ will always include the principal used to run the HMaster process. Only the superuser is
+ allowed to create tables, switch the balancer on or off, or take other actions with global
+ consequence. Furthermore, the superuser has an implicit grant of all permissions to all
+ resources. </para>
+ <para> Tables have a new metadata attribute: OWNER, the user principal who owns the table. By
+ default this will be set to the user principal who creates the table, though it may be
+ changed at table creation time or during an alter operation by setting or changing the OWNER
+ table attribute. Only a single user principal can own a table at a given time. A table owner
+ will have all permissions over a given table. </para>
</section>
- <section><title>Server-side Configuration for Access Control</title>
- <para>
- Enable the AccessController coprocessor in the cluster configuration
- and restart HBase. The restart can be a rolling one. Complete the
- restart of all Master and RegionServer processes before setting up
- ACLs.
- </para>
- <para>
- To enable the AccessController, modify the <code>hbase-site.xml</code> file on every server machine in the cluster to look like:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.coprocessor.master.classes</name>
- <value>org.apache.hadoop.hbase.security.access.AccessController</value>
- </property>
- <property>
- <name>hbase.coprocessor.region.classes</name>
- <value>org.apache.hadoop.hbase.security.token.TokenProvider,
- org.apache.hadoop.hbase.security.access.AccessController</value>
- </property>
+ <section>
+ <title>Server-side Configuration for Access Control</title>
+ <para> Enable the AccessController coprocessor in the cluster configuration and restart HBase.
+ The restart can be a rolling one. Complete the restart of all Master and RegionServer
+ processes before setting up ACLs. </para>
+ <para> To enable the AccessController, modify the <code>hbase-site.xml</code> file on every
+ server machine in the cluster to look like: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.coprocessor.master.classes</name>
+ <value>org.apache.hadoop.hbase.security.access.AccessController</value>
+</property>
+<property>
+<name>hbase.coprocessor.region.classes</name>
+ <value>org.apache.hadoop.hbase.security.token.TokenProvider,
+ org.apache.hadoop.hbase.security.access.AccessController</value>
+</property>
]]></programlisting>
</section>
<section>
- <title>Cell level Access Control using Tags</title>
- <para>
- Prior to HBase 0.98 access control was restricted to table and column family level. Thanks to tags feature in 0.98 that allows Access control on a cell level.
- The existing Access Controller coprocessor helps in achieving cell level access control also.
- For details on configuring it refer to <link linkend='hbase.accesscontrol.configuration'>Access Control</link> section.
- </para>
- <para>
- The ACLs can be specified for every mutation using the APIs
- </para>
- <programlisting><![CDATA[
- Mutation.setACL(String user, Permission perms)
- Mutation.setACL(Map<String, Permission> perms)
+ <title>Cell level Access Control using Tags</title>
+ <para> Prior to HBase 0.98 access control was restricted to table and column family level.
+ Thanks to tags feature in 0.98 that allows Access control on a cell level. The existing
+ Access Controller coprocessor helps in achieving cell level access control also. For details
+ on configuring it refer to <link
+ linkend="hbase.accesscontrol.configuration">Access Control</link> section. </para>
+ <para> The ACLs can be specified for every mutation using the APIs </para>
+ <programlisting><![CDATA[
+Mutation.setACL(String user, Permission perms)
+Mutation.setACL(Map<String, Permission> perms)
]]></programlisting>
- <para>
- For example, to provide read permission to an user ‘user1’ then
- </para>
- <programlisting><![CDATA[
- put.setACL(“user1”, new Permission(Permission.Action.READ))
+ <para> For example, to provide read permission to an user ‘user1’ then </para>
+ <programlisting><![CDATA[
+put.setACL(“user1”, new Permission(Permission.Action.READ))
]]></programlisting>
- <para>
- Generally the ACL applied on the table and CF takes precedence over Cell level ACL. In order to make the cell level ACL to take precedence use the following API,
- </para>
- <programlisting><![CDATA[
- Mutation.setACLStrategy(boolean cellFirstStrategy)
+ <para> Generally the ACL applied on the table and CF takes precedence over Cell level ACL. In
+ order to make the cell level ACL to take precedence use the following API, </para>
+ <programlisting><![CDATA[
+Mutation.setACLStrategy(boolean cellFirstStrategy)
]]></programlisting>
- <para>
- Please note that inorder to use this feature, HFile V3 version should be turned on.
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hfile.format.version</name>
- <value>3</value>
- </property>
+ <para> Please note that inorder to use this feature, HFile V3 version should be turned on. </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hfile.format.version</name>
+ <value>3</value>
+</property>
]]></programlisting>
- <para>
- Note that deletes with ACLs do not have any effect.
- To keep things simple the ACLs applied on the current Put does not change the ACL of any previous Put in the sense
- that the ACL on the current put does not affect older versions of Put for the same row.
- </para>
+ <para> Note that deletes with ACLs do not have any effect. To keep things simple the ACLs
+ applied on the current Put does not change the ACL of any previous Put in the sense that the
+ ACL on the current put does not affect older versions of Put for the same row. </para>
</section>
- <section><title>Shell Enhancements for Access Control</title>
- <para>
-The HBase shell has been extended to provide simple commands for editing and updating user permissions. The following commands have been added for access control list management:
- </para>
+ <section>
+ <title>Shell Enhancements for Access Control</title>
+ <para> The HBase shell has been extended to provide simple commands for editing and updating
+ user permissions. The following commands have been added for access control list management: </para>
- <example>
- <title>Grant</title>
- <programlisting>
- grant <user|@group> <permissions> [ <table> [ <column family> [ <column qualifier> ] ] ]
- </programlisting></example>
-
- <para>
- <code><user|@group></code> is user or group (start with character '@'), Groups are created and manipulated via the Hadoop group mapping service.
- </para>
- <para>
- <code><permissions></code> is zero or more letters from the set "RWCA": READ('R'), WRITE('W'), CREATE('C'), ADMIN('A').
- </para>
- <para>
- Note: Grants and revocations of individual permissions on a resource are both accomplished using the <code>grant</code> command. A separate <code>revoke</code> command is also provided by the shell, but this is for fast revocation of all of a user's access rights to a given resource only.
- </para>
- <example>
- <title>Revoke</title>
+ <example>
+ <title>Grant</title>
+ <programlisting><![CDATA[
+grant <us...@group> <permissions> [ <table> [ <column family> [ <column qualifier> ] ] ]
+ ]]></programlisting>
+ </example>
- <programlisting>
- revoke <user|@group> [ <table> [ <column family> [ <column qualifier> ] ] ]
- </programlisting>
- </example>
-<example>
- <title>Alter</title>
+ <para>
+ <code><user|@group></code> is user or group (start with character '@'), Groups are
+ created and manipulated via the Hadoop group mapping service. </para>
+ <para>
+ <code><permissions></code> is zero or more letters from the set "RWCA": READ('R'),
+ WRITE('W'), CREATE('C'), ADMIN('A'). </para>
+ <para> Note: Grants and revocations of individual permissions on a resource are both
+ accomplished using the <code>grant</code> command. A separate <code>revoke</code> command is
+ also provided by the shell, but this is for fast revocation of all of a user's access rights
+ to a given resource only. </para>
+ <example>
+ <title>Revoke</title>
- <para>
- The <code>alter</code> command has been extended to allow ownership assignment:</para>
- <programlisting>
- alter 'tablename', {OWNER => 'username|@group'}
- </programlisting>
-</example>
-
-<example>
- <title>User Permission</title>
+ <programlisting><![CDATA[
+revoke <us...@group> [ <table> [ <column family> [ <column qualifier> ] ] ]
+ ]]></programlisting>
+ </example>
+ <example>
+ <title>Alter</title>
- <para>
- The <code>user_permission</code> command shows all access permissions for the current user for a given table:</para>
- <programlisting>
- user_permission <table>
- </programlisting>
-</example>
- </section>
+ <para> The <code>alter</code> command has been extended to allow ownership
+ assignment:</para>
+ <programlisting><![CDATA[
+alter 'tablename', {OWNER => 'username|@group'}
+]]></programlisting>
+ </example>
-</section> <!-- Access Control -->
+ <example>
+ <title>User Permission</title>
-<section xml:id="hbase.secure.bulkload">
+ <para> The <code>user_permission</code> command shows all access permissions for the current
+ user for a given table:</para>
+ <programlisting><![CDATA[
+user_permission <table>
+ ]]></programlisting>
+ </example>
+ </section>
+
+ </section>
+ <!-- Access Control -->
+
+ <section
+ xml:id="hbase.secure.bulkload">
<title>Secure Bulk Load</title>
- <para>
- Bulk loading in secure mode is a bit more involved than normal setup, since the client has to transfer the ownership of the files generated from the mapreduce job to HBase. Secure bulk loading is implemented by a coprocessor, named <link xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/security/access/SecureBulkLoadEndpoint.html">SecureBulkLoadEndpoint</link>. SecureBulkLoadEndpoint uses a staging directory <code>"hbase.bulkload.staging.dir"</code>, which defaults to <code>/tmp/hbase-staging/</code>. The algorithm is as follows.
- <itemizedlist>
- <listitem><para>Create an hbase owned staging directory which is world traversable (<code>-rwx--x--x, 711</code>) <code>/tmp/hbase-staging</code>. </para></listitem>
- <listitem><para>A user writes out data to his secure output directory: /user/foo/data </para></listitem>
- <listitem><para>A call is made to hbase to create a secret staging directory
- which is globally readable/writable (<code>-rwxrwxrwx, 777</code>): /tmp/hbase-staging/averylongandrandomdirectoryname</para></listitem>
- <listitem><para>The user makes the data world readable and writable, then moves it
- into the random staging directory, then calls bulkLoadHFiles()</para></listitem>
- </itemizedlist>
- </para>
- <para>
- Like delegation tokens the strength of the security lies in the length
- and randomness of the secret directory.
- </para>
+ <para> Bulk loading in secure mode is a bit more involved than normal setup, since the client
+ has to transfer the ownership of the files generated from the mapreduce job to HBase. Secure
+ bulk loading is implemented by a coprocessor, named <link
+ xlink:href="http://hbase.apache.org/apidocs/org/apache/hadoop/hbase/security/access/SecureBulkLoadEndpoint.html">SecureBulkLoadEndpoint</link>.
+ SecureBulkLoadEndpoint uses a staging directory <code>"hbase.bulkload.staging.dir"</code>,
+ which defaults to <code>/tmp/hbase-staging/</code>. The algorithm is as follows. </para>
+ <itemizedlist>
+ <listitem>
+ <para>Create an hbase owned staging directory which is world traversable (<code>-rwx--x--x,
+ 711</code>) <code>/tmp/hbase-staging</code>. </para>
+ </listitem>
+ <listitem>
+ <para>A user writes out data to his secure output directory: /user/foo/data </para>
+ </listitem>
+ <listitem>
+ <para>A call is made to hbase to create a secret staging directory which is globally
+ readable/writable (<code>-rwxrwxrwx, 777</code>):
+ /tmp/hbase-staging/averylongandrandomdirectoryname</para>
+ </listitem>
+ <listitem>
+ <para>The user makes the data world readable and writable, then moves it into the random
+ staging directory, then calls bulkLoadHFiles()</para>
+ </listitem>
+ </itemizedlist>
+ <para> Like delegation tokens the strength of the security lies in the length and randomness of
+ the secret directory. </para>
- <para>
- You have to enable the secure bulk load to work properly. You can modify the <code>hbase-site.xml</code> file on every server machine in the cluster and add the SecureBulkLoadEndpoint class to the list of regionserver coprocessors:
- </para>
+ <para> You have to enable the secure bulk load to work properly. You can modify the
+ <code>hbase-site.xml</code> file on every server machine in the cluster and add the
+ SecureBulkLoadEndpoint class to the list of regionserver coprocessors: </para>
<programlisting><![CDATA[
- <property>
- <name>hbase.bulkload.staging.dir</name>
- <value>/tmp/hbase-staging</value>
- </property>
- <property>
- <name>hbase.coprocessor.region.classes</name>
- <value>org.apache.hadoop.hbase.security.token.TokenProvider,
- org.apache.hadoop.hbase.security.access.AccessController,org.apache.hadoop.hbase.security.access.SecureBulkLoadEndpoint</value>
- </property>
+<property>
+ <name>hbase.bulkload.staging.dir</name>
+ <value>/tmp/hbase-staging</value>
+</property>
+<property>
+ <name>hbase.coprocessor.region.classes</name>
+ <value>org.apache.hadoop.hbase.security.token.TokenProvider,
+ org.apache.hadoop.hbase.security.access.AccessController,org.apache.hadoop.hbase.security.access.SecureBulkLoadEndpoint</value>
+</property>
]]></programlisting>
-</section> <!-- Secure Bulk Load -->
+ </section>
+ <!-- Secure Bulk Load -->
-<section xml:id="hbase.visibility.labels">
+ <section
+ xml:id="hbase.visibility.labels">
<title>Visibility Labels</title>
- <para>
- This feature provides cell level security with labeled visibility for the cells. Cells can be associated with a visibility expression. The visibility expression can contain labels joined with logical expressions '&', '|' and '!'. Also using '(', ')' one can specify the precedence order. For example, consider the label set { confidential, secret, topsecret, probationary }, where the first three are sensitivity classifications and the last describes if an employee is probationary or not. If a cell is stored with this visibility expression:
- ( secret | topsecret ) & !probationary
- </para>
- <para>
- Then any user associated with the secret or topsecret label will be able to view the cell, as long as the user is not also associated with the probationary label. Furthermore, any user only associated with the confidential label, whether probationary or not, will not see the cell or even know of its existence.
- </para>
- <para>
- Visibility expressions like the above can be added when storing or mutating a cell using the API,
- </para>
- <programlisting>Mutation#setCellVisibility(new CellVisibility(String labelExpession));</programlisting>
-<para> Where the labelExpression could be '( secret | topsecret ) & !probationary'
-</para>
- <para>
- We build the user's label set in the RPC context when a request is first received by the HBase RegionServer. How users are associated with labels is pluggable. The default plugin passes through labels specified in Authorizations added to the Get or Scan and checks those against the calling user's authenticated labels list. When client passes some labels for which the user is not authenticated, this default algorithm will drop those. One can pass a subset of user authenticated labels via the Scan/Get authorizations.
- </para>
- <para><code>Get#setAuthorizations(new Authorizations(String,...));</code></para>
- <para><code>Scan#setAuthorizations(new Authorizations(String,...));</code></para>
+ <para> This feature provides cell level security with labeled visibility for the cells. Cells
+ can be associated with a visibility expression. The visibility expression can contain labels
+ joined with logical expressions '&', '|' and '!'. Also using
+ '(', ')' one can specify the precedence order. For example, consider the label
+ set { confidential, secret, topsecret, probationary }, where the first three are sensitivity
+ classifications and the last describes if an employee is probationary or not. If a cell is
+ stored with this visibility expression: ( secret | topsecret ) & !probationary </para>
+ <para> Then any user associated with the secret or topsecret label will be able to view the
+ cell, as long as the user is not also associated with the probationary label. Furthermore, any
+ user only associated with the confidential label, whether probationary or not, will not see
+ the cell or even know of its existence. </para>
+ <para> Visibility expressions like the above can be added when storing or mutating a cell using
+ the API, </para>
+ <programlisting>Mutation#setCellVisibility(new CellVisibility(String labelExpession));</programlisting>
+ <para> Where the labelExpression could be '( secret | topsecret ) & !probationary' </para>
+ <para> We build the user's label set in the RPC context when a request is first received by
+ the HBase RegionServer. How users are associated with labels is pluggable. The default plugin
+ passes through labels specified in Authorizations added to the Get or Scan and checks those
+ against the calling user's authenticated labels list. When client passes some labels for
+ which the user is not authenticated, this default algorithm will drop those. One can pass a
+ subset of user authenticated labels via the Scan/Get authorizations. </para>
+ <para><code>Get#setAuthorizations(new Authorizations(String,...));</code></para>
+ <para><code>Scan#setAuthorizations(new Authorizations(String,...));</code></para>
- <section xml:id="hbase.visibility.label.administration">
- <title>Visibility Label Administration</title>
- <para>
- There are new client side Java APIs and shell commands for performing visibility labels administrative actions. Only the HBase super user is authorized to perform these operations.
- </para>
+ <section
+ xml:id="hbase.visibility.label.administration">
+ <title>Visibility Label Administration</title>
+ <para> There are new client side Java APIs and shell commands for performing visibility labels
+ administrative actions. Only the HBase super user is authorized to perform these operations. </para>
- <section xml:id="hbase.visibility.label.administration.add.label">
- <title>Adding Labels</title>
- <para>A set of labels can be added to the system either by using the Java API</para>
- <para><code>VisibilityClient#addLabels(Configuration conf, final String[] labels)</code></para>
- <para>Or by using the shell command</para>
- <para><code>add_labels [label1, label2]</code></para>
- <para>
- Valid label can include alphanumeric characters and characters '-', '_', ':', '.' and '/'
- </para>
- </section>
+ <section
+ xml:id="hbase.visibility.label.administration.add.label">
+ <title>Adding Labels</title>
+ <para>A set of labels can be added to the system either by using the Java API</para>
+ <para><code>VisibilityClient#addLabels(Configuration conf, final String[]
+ labels)</code></para>
+ <para>Or by using the shell command</para>
+ <para><code>add_labels [label1, label2]</code></para>
+ <para> Valid label can include alphanumeric characters and characters '-',
+ '_', ':', '.' and '/' </para>
+ </section>
- <section xml:id="hbase.visibility.label.administration.add.label2">
- <title>User Label Association</title>
- <para>A set of labels can be associated with a user by using the API</para>
- <para><code>VisibilityClient#setAuths(Configuration conf, final String[] auths, final String user)</code></para>
- <para>Or by using the shell command</para>
- <para><code>set_auths user,[label1, label2].</code></para>
- <para>Labels can be disassociated from a user using API</para>
- <para><code>VisibilityClient#clearAuths(Configuration conf, final String[] auths, final String user)</code></para>
- <para>Or by using shell command</para>
- <para><code>clear_auths user,[label1, label2]</code></para>
- <para>
- One can use the API <code>VisibilityClient#getAuths(Configuration conf, final String user)</code> or <code>get_auths</code> shell command to get the list of labels associated for a given user. The labels and user auths information will be stored in the system table "labels".
- </para>
- </section>
- </section>
+ <section
+ xml:id="hbase.visibility.label.administration.add.label2">
+ <title>User Label Association</title>
+ <para>A set of labels can be associated with a user by using the API</para>
+ <para><code>VisibilityClient#setAuths(Configuration conf, final String[] auths, final String
+ user)</code></para>
+ <para>Or by using the shell command</para>
+ <para><code>set_auths user,[label1, label2].</code></para>
+ <para>Labels can be disassociated from a user using API</para>
+ <para><code>VisibilityClient#clearAuths(Configuration conf, final String[] auths, final
+ String user)</code></para>
+ <para>Or by using shell command</para>
+ <para><code>clear_auths user,[label1, label2]</code></para>
+ <para> One can use the API <code>VisibilityClient#getAuths(Configuration conf, final String
+ user)</code> or <code>get_auths</code> shell command to get the list of labels
+ associated for a given user. The labels and user auths information will be stored in the
+ system table "labels". </para>
+ </section>
+ </section>
- <section xml:id="hbase.visibility.label.configuration">
- <title>Server Side Configuration</title>
- <para>
- HBase stores cell level labels as cell tags. HFile version 3 adds the cell tags support. Be sure to use HFile version 3 by setting this property in every server site configuration file:
- </para>
- <programlisting><![CDATA[
+ <section
+ xml:id="hbase.visibility.label.configuration">
+ <title>Server Side Configuration</title>
+ <para> HBase stores cell level labels as cell tags. HFile version 3 adds the cell tags
+ support. Be sure to use HFile version 3 by setting this property in every server site
+ configuration file: </para>
+ <programlisting><![CDATA[
<property>
<name>hfile.format.version</name>
<value>3</value>
</property>
]]></programlisting>
- <para>
- You will also need to make sure the VisibilityController coprocessor is active on every table to protect by adding it to the list of system coprocessors in the server site configuration files:
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.coprocessor.master.classes</name>
- <value>org.apache.hadoop.hbase.security.visibility.VisibilityController</value>
- </property>
- <property>
- <name>hbase.coprocessor.region.classes</name>
- <value>org.apache.hadoop.hbase.security.visibility.VisibilityController</value>
- </property>
+ <para> You will also need to make sure the VisibilityController coprocessor is active on every
+ table to protect by adding it to the list of system coprocessors in the server site
+ configuration files: </para>
+ <programlisting><![CDATA[
+<property>
+ <name>hbase.coprocessor.master.classes</name>
+<value>org.apache.hadoop.hbase.security.visibility.VisibilityController</value>
+</property>
+<property>
+ <name>hbase.coprocessor.region.classes</name>
+<value>org.apache.hadoop.hbase.security.visibility.VisibilityController</value>
+</property>
]]></programlisting>
- <para>
- As said above, finding out labels authenticated for a given get/scan request is a pluggable algorithm. A custom implementation can be plugged in using the property <code>hbase.regionserver.scan.visibility.label.generator.class</code>. The default implementation class is <code>org.apache.hadoop.hbase.security.visibility.DefaultScanLabelGenerator</code>. One can configure a set of ScanLabelGenerators to be used by the system. For this, a comma separated set of implementation class names to be configured.
- </para>
- </section>
-</section>
+ <para> As said above, finding out labels authenticated for a given get/scan request is a
+ pluggable algorithm. A custom implementation can be plugged in using the property
+ <code>hbase.regionserver.scan.visibility.label.generator.class</code>. The default
+ implementation class is
+ <code>org.apache.hadoop.hbase.security.visibility.DefaultScanLabelGenerator</code>. One
+ can configure a set of ScanLabelGenerators to be used by the system. For this, a comma
+ separated set of implementation class names to be configured. </para>
+ </section>
+ </section>
-<section xml:id="hbase.encryption.server">
+ <section
+ xml:id="hbase.encryption.server">
<title>Transparent Server Side Encryption</title>
- <para>
-This feature provides transparent encryption for protecting HFile and WAL data at rest, using a two-tier key architecture for flexible and non-intrusive key rotation.
- </para>
- <para>
-First, the administrator provisions a cluster master key, stored into a key provider accessable to every trusted HBase process: the Master, the RegionServers, and clients (e.g. the shell) on administrative workstations. The default key provider integrates with the Java KeyStore API and any key management system with support for it. How HBase retrieves key material is configurable via the site file. The master key may be stored on the cluster servers, protected by a secure KeyStore file, or on an external keyserver, or in a hardware security module. This master key is resolved as needed by HBase processes through the configured key provider.
- </para>
- <para>
-Then, encryption keys can be specified in schema on a per column family basis, by creating or modifying a column descriptor to include two additional attributes: the name of the encryption algorithm to use (currently only "AES" is supported), and, optionally, a data key wrapped (encrypted) with the cluster master key. Per CF keys facilitates low impact incremental key rotation and reduces the scope of any external leak of key material. The wrapped data key is stored in the CF schema metadata, and in each HFile for the CF, encrypted with the cluster master key. Once the CF is configured for encryption, any new HFiles will be written encrypted. To insure encryption of all HFiles, trigger a major compaction after first enabling this feature. The key for decryption, encrypted with the cluster master key, is stored in the HFiles in a new meta block. At file open time the data key will be extracted from the HFile, decrypted with the cluster master key, and used for decryption of the remai
nder of the HFile. The HFile will be unreadable if the master key is not available. Should remote users somehow acquire access to the HFile data because of some lapse in HDFS permissions or from inappropriately discarded media, there will be no means to decrypt either the data key or the file data.
- </para>
- <para>
-Specifying a data key in the CF schema is optional. If one is not present, a random data key will be created for each HFile.
- </para>
- <para>
-A new configuration option for encrypting the WAL is also introduced. Even though WALs are transient, it is necessary to encrypt the WALEdits to avoid circumventing HFile protections for encrypted column families.
- </para>
- <section xml:id="hbase.encryption.server.configuration">
- <title>Configuration</title>
- <para>
-Create a secret key of appropriate length for AES.
- </para>
- <programlisting><![CDATA[
- $ keytool -keystore /path/to/hbase/conf/hbase.jks \
- -storetype jceks -storepass <password> \
- -genseckey -keyalg AES -keysize 128 \
- -alias <alias>
- ]]></programlisting>
- <para>
-where <password> is the password for the KeyStore file and <alias>is the user name of the HBase service account, typically "hbase". Simply press RETURN to store the key with the same password as the store. The resulting file should be distributed to all nodes running HBase daemons, with file ownership and permissions set to be readable only by the HBase service account.
- </para>
- <para>
-Configure HBase daemons to use a key provider backed by the KeyStore files for retrieving the cluster master key as needed.
- </para>
- <programlisting><![CDATA[
- <property>
- <name>hbase.crypto.keyprovider</name>
- <value>org.apache.hadoop.hbase.io.crypto.KeyStoreKeyProvider</value>
- </property>
-
<TRUNCATED>