HADOOP-6616. Improve documentation for rack awareness. Contributed by Adam Faris.
git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/trunk@1411359 13f79535-47bb-0310-9956-ffa450edef68
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@ -132,6 +132,8 @@ Trunk (Unreleased)
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HADOOP-9004. Allow security unit tests to use external KDC. (Stephen Chu
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via suresh)
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HADOOP-6616. Improve documentation for rack awareness. (Adam Faris via jghoman)
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BUG FIXES
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HADOOP-8177. MBeans shouldn't try to register when it fails to create MBeanName.
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@ -1292,23 +1292,139 @@
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<section>
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<title>Hadoop Rack Awareness</title>
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<p>The HDFS and the Map/Reduce components are rack-aware.</p>
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<p>The <code>NameNode</code> and the <code>JobTracker</code> obtains the
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<code>rack id</code> of the slaves in the cluster by invoking an API
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<a href="ext:api/org/apache/hadoop/net/dnstoswitchmapping/resolve
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">resolve</a> in an administrator configured
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module. The API resolves the slave's DNS name (also IP address) to a
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rack id. What module to use can be configured using the configuration
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item <code>net.topology.node.switch.mapping.impl</code>. The default
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implementation of the same runs a script/command configured using
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<code>net.topology.script.file.name</code>. If topology.script.file.name is
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not set, the rack id <code>/default-rack</code> is returned for any
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passed IP address. The additional configuration in the Map/Reduce
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part is <code>mapred.cache.task.levels</code> which determines the number
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of levels (in the network topology) of caches. So, for example, if it is
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the default value of 2, two levels of caches will be constructed -
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one for hosts (host -> task mapping) and another for racks
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(rack -> task mapping).
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<p>
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Both HDFS and Map/Reduce components are rack-aware. HDFS block placement will use rack
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awareness for fault tolerance by placing one block replica on a different rack. This provides
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data availability in the event of a network switch failure within the cluster. The jobtracker uses rack
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awareness to reduce network transfers of HDFS data blocks by attempting to schedule tasks on datanodes with a local
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copy of needed HDFS blocks. If the tasks cannot be scheduled on the datanodes
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containing the needed HDFS blocks, then the tasks will be scheduled on the same rack to reduce network transfers if possible.
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</p>
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<p>The NameNode and the JobTracker obtain the rack id of the cluster slaves by invoking either
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an external script or java class as specified by configuration files. Using either the
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java class or external script for topology, output must adhere to the java
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<a href="ext:api/org/apache/hadoop/net/dnstoswitchmapping/resolve">DNSToSwitchMapping</a>
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interface. The interface expects a one-to-one correspondence to be maintained
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and the topology information in the format of '/myrack/myhost', where '/' is the topology
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delimiter, 'myrack' is the rack identifier, and 'myhost' is the individual host. Assuming
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a single /24 subnet per rack, one could use the format of '/192.168.100.0/192.168.100.5' as a
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unique rack-host topology mapping.
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</p>
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<p>
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To use the java class for topology mapping, the class name is specified by the
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<code>'topology.node.switch.mapping.impl'</code> parameter in the configuration file.
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An example, NetworkTopology.java, is included with the hadoop distribution and can be customized
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by the hadoop administrator. If not included with your distribution, NetworkTopology.java can also be found in the Hadoop
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<a href="http://svn.apache.org/viewvc/hadoop/common/trunk/hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/net/NetworkTopology.java?view=markup">
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subversion tree</a>. Using a java class instead of an external script has a slight performance benefit in
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that it doesn't need to fork an external process when a new slave node registers itself with the jobtracker or namenode.
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As this class is only used during slave node registration, the performance benefit is limited.
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</p>
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<p>
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If implementing an external script, it will be specified with the
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<code>topology.script.file.name</code> parameter in the configuration files. Unlike the java
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class, the external topology script is not included with the Hadoop distribution and is provided by the
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administrator. Hadoop will send multiple IP addresses to ARGV when forking the topology script. The
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number of IP addresses sent to the topology script is controlled with <code>net.topology.script.number.args</code>
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and defaults to 100. If <code>net.topology.script.number.args</code> was changed to 1, a topology script would
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get forked for each IP submitted by datanodes and/or tasktrackers. Below are example topology scripts.
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</p>
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<section>
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<title>Python example</title>
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<source>
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<code>
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#!/usr/bin/python
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# this script makes assumptions about the physical environment.
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# 1) each rack is its own layer 3 network with a /24 subnet, which could be typical where each rack has its own
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# switch with uplinks to a central core router.
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#
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# +-----------+
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# |core router|
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# +-----------+
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# / \
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# +-----------+ +-----------+
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# |rack switch| |rack switch|
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# +-----------+ +-----------+
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# | data node | | data node |
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# +-----------+ +-----------+
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# | data node | | data node |
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# +-----------+ +-----------+
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#
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# 2) topology script gets list of IP's as input, calculates network address, and prints '/network_address/ip'.
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import netaddr
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import sys
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sys.argv.pop(0) # discard name of topology script from argv list as we just want IP addresses
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netmask = '255.255.255.0' # set netmask to what's being used in your environment. The example uses a /24
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for ip in sys.argv: # loop over list of datanode IP's
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address = '{0}/{1}'.format(ip, netmask) # format address string so it looks like 'ip/netmask' to make netaddr work
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try:
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network_address = netaddr.IPNetwork(address).network # calculate and print network address
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print "/{0}".format(network_address)
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except:
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print "/rack-unknown" # print catch-all value if unable to calculate network address
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</code>
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</source>
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</section>
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<section>
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<title>Bash example</title>
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<source>
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<code>
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#!/bin/bash
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# Here's a bash example to show just how simple these scripts can be
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# Assuming we have flat network with everything on a single switch, we can fake a rack topology.
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# This could occur in a lab environment where we have limited nodes,like 2-8 physical machines on a unmanaged switch.
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# This may also apply to multiple virtual machines running on the same physical hardware.
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# The number of machines isn't important, but that we are trying to fake a network topology when there isn't one.
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#
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# +----------+ +--------+
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# |jobtracker| |datanode|
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# +----------+ +--------+
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# \ /
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# +--------+ +--------+ +--------+
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# |datanode|--| switch |--|datanode|
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# +--------+ +--------+ +--------+
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# / \
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# +--------+ +--------+
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# |datanode| |namenode|
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# +--------+ +--------+
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#
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# With this network topology, we are treating each host as a rack. This is being done by taking the last octet
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# in the datanode's IP and prepending it with the word '/rack-'. The advantage for doing this is so HDFS
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# can create its 'off-rack' block copy.
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# 1) 'echo $@' will echo all ARGV values to xargs.
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# 2) 'xargs' will enforce that we print a single argv value per line
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# 3) 'awk' will split fields on dots and append the last field to the string '/rack-'. If awk
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# fails to split on four dots, it will still print '/rack-' last field value
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echo $@ | xargs -n 1 | awk -F '.' '{print "/rack-"$NF}'
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</code>
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</source>
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</section>
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<p>
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If <code>topology.script.file.name</code> or <code>topology.node.switch.mapping.impl</code> is
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not set, the rack id '/default-rack' is returned for any passed IP address.
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While this behavior appears desirable, it can cause issues with HDFS block replication as
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default behavior is to write one replicated block off rack and is unable to do so as there is
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only a single rack named '/default-rack'.
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</p>
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<p>
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An additional configuration setting is <code>mapred.cache.task.levels</code> which determines
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the number of levels (in the network topology) of caches. So, for example, if it is the
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default value of 2, two levels of caches will be constructed - one for hosts
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(host -> task mapping) and another for racks (rack -> task mapping). Giving us our one-to-one
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mapping of '/myrack/myhost'
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</p>
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</section>
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