293 lines
8.7 KiB
HTML
293 lines
8.7 KiB
HTML
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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
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<html>
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<!--
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Licensed to the Apache Software Foundation (ASF) under one or more
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contributor license agreements. See the NOTICE file distributed with
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this work for additional information regarding copyright ownership.
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The ASF licenses this file to You under the Apache License, Version 2.0
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(the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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<head>
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<title>Hadoop</title>
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</head>
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<body>
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Hadoop is a distributed computing platform.
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<p>Hadoop primarily consists of the <a
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href="org/apache/hadoop/hdfs/package-summary.html">Hadoop Distributed FileSystem
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(HDFS)</a> and an
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implementation of the <a href="org/apache/hadoop/mapred/package-summary.html">
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Map-Reduce</a> programming paradigm.</p>
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<p>Hadoop is a software framework that lets one easily write and run applications
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that process vast amounts of data. Here's what makes Hadoop especially useful:</p>
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<ul>
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<li>
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<b>Scalable</b>: Hadoop can reliably store and process petabytes.
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</li>
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<li>
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<b>Economical</b>: It distributes the data and processing across clusters
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of commonly available computers. These clusters can number into the thousands
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of nodes.
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</li>
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<li>
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<b>Efficient</b>: By distributing the data, Hadoop can process it in parallel
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on the nodes where the data is located. This makes it extremely rapid.
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</li>
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<li>
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<b>Reliable</b>: Hadoop automatically maintains multiple copies of data and
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automatically redeploys computing tasks based on failures.
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</li>
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</ul>
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<h2>Requirements</h2>
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<h3>Platforms</h3>
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<ul>
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<li>
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Hadoop was been demonstrated on GNU/Linux clusters with 2000 nodes.
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</li>
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<li>
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Win32 is supported as a <i>development</i> platform. Distributed operation
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has not been well tested on Win32, so this is not a <i>production</i>
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platform.
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</li>
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</ul>
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<h3>Requisite Software</h3>
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<ol>
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<li>
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Java 1.6.x, preferably from
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<a href="http://java.sun.com/javase/downloads/">Sun</a>.
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Set <tt>JAVA_HOME</tt> to the root of your Java installation.
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</li>
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<li>
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ssh must be installed and sshd must be running to use Hadoop's
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scripts to manage remote Hadoop daemons.
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</li>
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<li>
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rsync may be installed to use Hadoop's scripts to manage remote
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Hadoop installations.
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</li>
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</ol>
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<h4>Additional requirements for Windows</h4>
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<ol>
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<li>
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<a href="http://www.cygwin.com/">Cygwin</a> - Required for shell support in
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addition to the required software above.
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</li>
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</ol>
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<h3>Installing Required Software</h3>
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<p>If your platform does not have the required software listed above, you
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will have to install it.</p>
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<p>For example on Ubuntu Linux:</p>
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<p><blockquote><pre>
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$ sudo apt-get install ssh<br>
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$ sudo apt-get install rsync<br>
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</pre></blockquote></p>
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<p>On Windows, if you did not install the required software when you
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installed cygwin, start the cygwin installer and select the packages:</p>
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<ul>
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<li>openssh - the "Net" category</li>
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<li>rsync - the "Net" category</li>
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</ul>
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<h2>Getting Started</h2>
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<p>First, you need to get a copy of the Hadoop code.</p>
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<p>Edit the file <tt>conf/hadoop-env.sh</tt> to define at least
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<tt>JAVA_HOME</tt>.</p>
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<p>Try the following command:</p>
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<tt>bin/hadoop</tt>
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<p>This will display the documentation for the Hadoop command script.</p>
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<h2>Standalone operation</h2>
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<p>By default, Hadoop is configured to run things in a non-distributed
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mode, as a single Java process. This is useful for debugging, and can
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be demonstrated as follows:</p>
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<tt>
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mkdir input<br>
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cp conf/*.xml input<br>
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bin/hadoop jar hadoop-*-examples.jar grep input output 'dfs[a-z.]+'<br>
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cat output/*
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</tt>
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<p>This will display counts for each match of the <a
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href="http://java.sun.com/j2se/1.4.2/docs/api/java/util/regex/Pattern.html">
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regular expression.</a></p>
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<p>Note that input is specified as a <em>directory</em> containing input
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files and that output is also specified as a directory where parts are
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written.</p>
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<h2>Distributed operation</h2>
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To configure Hadoop for distributed operation you must specify the
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following:
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<ol>
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<li>The NameNode (Distributed Filesystem master) host. This is
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specified with the configuration property <tt><a
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href="../core-default.html#fs.default.name">fs.default.name</a></tt>.
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</li>
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<li>The {@link org.apache.hadoop.mapred.JobTracker} (MapReduce master)
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host and port. This is specified with the configuration property
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<tt><a
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href="../mapred-default.html#mapred.job.tracker">mapred.job.tracker</a></tt>.
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</li>
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<li>A <em>slaves</em> file that lists the names of all the hosts in
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the cluster. The default slaves file is <tt>conf/slaves</tt>.
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</ol>
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<h3>Pseudo-distributed configuration</h3>
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You can in fact run everything on a single host. To run things this
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way, put the following in:
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<br/>
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<br/>
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conf/core-site.xml:
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<xmp><configuration>
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<property>
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<name>fs.default.name</name>
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<value>hdfs://localhost/</value>
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</property>
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</configuration></xmp>
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conf/hdfs-site.xml:
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<xmp><configuration>
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<property>
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<name>dfs.replication</name>
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<value>1</value>
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</property>
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</configuration></xmp>
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conf/mapred-site.xml:
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<xmp><configuration>
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<property>
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<name>mapred.job.tracker</name>
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<value>localhost:9001</value>
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</property>
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</configuration></xmp>
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<p>(We also set the HDFS replication level to 1 in order to
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reduce warnings when running on a single node.)</p>
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<p>Now check that the command <br><tt>ssh localhost</tt><br> does not
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require a password. If it does, execute the following commands:</p>
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<p><tt>ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa<br>
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cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys
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</tt></p>
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<h3>Bootstrapping</h3>
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<p>A new distributed filesystem must be formatted with the following
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command, run on the master node:</p>
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<p><tt>bin/hadoop namenode -format</tt></p>
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<p>The Hadoop daemons are started with the following command:</p>
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<p><tt>bin/start-all.sh</tt></p>
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<p>Daemon log output is written to the <tt>logs/</tt> directory.</p>
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<p>Input files are copied into the distributed filesystem as follows:</p>
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<p><tt>bin/hadoop fs -put input input</tt></p>
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<h3>Distributed execution</h3>
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<p>Things are run as before, but output must be copied locally to
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examine it:</p>
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<tt>
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bin/hadoop jar hadoop-*-examples.jar grep input output 'dfs[a-z.]+'<br>
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bin/hadoop fs -get output output
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cat output/*
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</tt>
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<p>When you're done, stop the daemons with:</p>
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<p><tt>bin/stop-all.sh</tt></p>
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<h3>Fully-distributed operation</h3>
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<p>Fully distributed operation is just like the pseudo-distributed operation
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described above, except, specify:</p>
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<ol>
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<li>The hostname or IP address of your master server in the value
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for <tt><a
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href="../core-default.html#fs.default.name">fs.default.name</a></tt>,
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as <tt><em>hdfs://master.example.com/</em></tt> in <tt>conf/core-site.xml</tt>.</li>
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<li>The host and port of the your master server in the value
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of <tt><a href="../mapred-default.html#mapred.job.tracker">mapred.job.tracker</a></tt>
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as <tt><em>master.example.com</em>:<em>port</em></tt> in <tt>conf/mapred-site.xml</tt>.</li>
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<li>Directories for <tt><a
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href="../hdfs-default.html#dfs.name.dir">dfs.name.dir</a></tt> and
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<tt><a href="../hdfs-default.html#dfs.data.dir">dfs.data.dir</a>
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in <tt>conf/hdfs-site.xml</tt>.
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</tt>These are local directories used to hold distributed filesystem
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data on the master node and slave nodes respectively. Note
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that <tt>dfs.data.dir</tt> may contain a space- or comma-separated
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list of directory names, so that data may be stored on multiple local
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devices.</li>
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<li><tt><a href="../mapred-default.html#mapred.local.dir">mapred.local.dir</a></tt>
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in <tt>conf/mapred-site.xml</tt>, the local directory where temporary
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MapReduce data is stored. It also may be a list of directories.</li>
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<li><tt><a
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href="../mapred-default.html#mapred.map.tasks">mapred.map.tasks</a></tt>
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and <tt><a
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href="../mapred-default.html#mapred.reduce.tasks">mapred.reduce.tasks</a></tt>
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in <tt>conf/mapred-site.xml</tt>.
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As a rule of thumb, use 10x the
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number of slave processors for <tt>mapred.map.tasks</tt>, and 2x the
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number of slave processors for <tt>mapred.reduce.tasks</tt>.</li>
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</ol>
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<p>Finally, list all slave hostnames or IP addresses in your
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<tt>conf/slaves</tt> file, one per line. Then format your filesystem
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and start your cluster on your master node, as above.
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</body>
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</html>
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