HADOOP-13646. Remove outdated overview.html. Contributed By Brahma Reddy Battula.
This commit is contained in:
Brahma Reddy Battula
parent
a926f895c1
commit
afcf8d38e7
@ -1,274 +0,0 @@
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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
|
||||
contributor license agreements. See the NOTICE file distributed with
|
||||
this work for additional information regarding copyright ownership.
|
||||
The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
(the "License"); you may not use this file except in compliance with
|
||||
the License. You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
-->
|
||||
<head>
|
||||
<title>Hadoop</title>
|
||||
</head>
|
||||
<body>
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||||
|
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Hadoop is a distributed computing platform.
|
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|
||||
<p>Hadoop primarily consists of the <a
|
||||
href="http://hadoop.apache.org/hdfs/">Hadoop Distributed FileSystem
|
||||
(HDFS)</a> and an
|
||||
implementation of the <a href="http://hadoop.apache.org/mapreduce/">
|
||||
Map-Reduce</a> programming paradigm.</p>
|
||||
|
||||
|
||||
<p>Hadoop is a software framework that lets one easily write and run applications
|
||||
that process vast amounts of data. Here's what makes Hadoop especially useful:</p>
|
||||
<ul>
|
||||
<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
|
||||
of commonly available computers. These clusters can number into the thousands
|
||||
of nodes.
|
||||
</li>
|
||||
<li>
|
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<b>Efficient</b>: By distributing the data, Hadoop can process it in parallel
|
||||
on the nodes where the data is located. This makes it extremely rapid.
|
||||
</li>
|
||||
<li>
|
||||
<b>Reliable</b>: Hadoop automatically maintains multiple copies of data and
|
||||
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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|
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<h3>Platforms</h3>
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|
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<ul>
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<li>
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Hadoop has been demonstrated on GNU/Linux clusters with more than 4000 nodes.
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</li>
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<li>
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Windows is also a supported platform.
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</li>
|
||||
</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.
|
||||
</li>
|
||||
<li>
|
||||
ssh must be installed and sshd must be running to use Hadoop's
|
||||
scripts to manage remote Hadoop daemons.
|
||||
</li>
|
||||
<li>
|
||||
rsync may be installed to use Hadoop's scripts to manage remote
|
||||
Hadoop installations.
|
||||
</li>
|
||||
</ol>
|
||||
|
||||
<h3>Installing Required Software</h3>
|
||||
|
||||
<p>If your platform does not have the required software listed above, you
|
||||
will have to install it.</p>
|
||||
|
||||
<p>For example on Ubuntu Linux:</p>
|
||||
<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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<h2>Getting Started</h2>
|
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|
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<p>First, you need to get a copy of the Hadoop code.</p>
|
||||
|
||||
<p>Edit the file <tt>conf/hadoop-env.sh</tt> to define at least
|
||||
<tt>JAVA_HOME</tt>.</p>
|
||||
|
||||
<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>
|
||||
|
||||
<h2>Standalone operation</h2>
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||||
|
||||
<p>By default, Hadoop is configured to run things in a non-distributed
|
||||
mode, as a single Java process. This is useful for debugging, and can
|
||||
be demonstrated as follows:</p>
|
||||
<tt>
|
||||
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
|
||||
href="http://java.sun.com/j2se/1.4.2/docs/api/java/util/regex/Pattern.html">
|
||||
regular expression.</a></p>
|
||||
|
||||
<p>Note that input is specified as a <em>directory</em> containing input
|
||||
files and that output is also specified as a directory where parts are
|
||||
written.</p>
|
||||
|
||||
<h2>Distributed operation</h2>
|
||||
|
||||
To configure Hadoop for distributed operation you must specify the
|
||||
following:
|
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|
||||
<ol>
|
||||
|
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<li>The NameNode (Distributed Filesystem master) host. This is
|
||||
specified with the configuration property <tt><a
|
||||
href="../core-default.html#fs.default.name">fs.default.name</a></tt>.
|
||||
</li>
|
||||
|
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<li>The org.apache.hadoop.mapred.JobTracker (MapReduce master)
|
||||
host and port. This is specified with the configuration property
|
||||
<tt><a
|
||||
href="../mapred-default.html#mapred.job.tracker">mapred.job.tracker</a></tt>.
|
||||
</li>
|
||||
|
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<li>A <em>workers</em> file that lists the names of all the hosts in
|
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the cluster. The default workers file is <tt>conf/workers</tt>.
|
||||
|
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</ol>
|
||||
|
||||
<h3>Pseudo-distributed configuration</h3>
|
||||
|
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You can in fact run everything on a single host. To run things this
|
||||
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>
|
||||
</property>
|
||||
|
||||
</configuration></xmp>
|
||||
|
||||
conf/hdfs-site.xml:
|
||||
<xmp><configuration>
|
||||
|
||||
<property>
|
||||
<name>dfs.replication</name>
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||||
<value>1</value>
|
||||
</property>
|
||||
|
||||
</configuration></xmp>
|
||||
|
||||
conf/mapred-site.xml:
|
||||
<xmp><configuration>
|
||||
|
||||
<property>
|
||||
<name>mapred.job.tracker</name>
|
||||
<value>localhost:9001</value>
|
||||
</property>
|
||||
|
||||
</configuration></xmp>
|
||||
|
||||
<p>(We also set the HDFS replication level to 1 in order to
|
||||
reduce warnings when running on a single node.)</p>
|
||||
|
||||
<p>Now check that the command <br><tt>ssh localhost</tt><br> does not
|
||||
require a password. If it does, execute the following commands:</p>
|
||||
|
||||
<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>
|
||||
|
||||
<h3>Bootstrapping</h3>
|
||||
|
||||
<p>A new distributed filesystem must be formatted with the following
|
||||
command, run on the master node:</p>
|
||||
|
||||
<p><tt>bin/hadoop namenode -format</tt></p>
|
||||
|
||||
<p>The Hadoop daemons are started with the following command:</p>
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|
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<p><tt>bin/start-all.sh</tt></p>
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|
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<p>Daemon log output is written to the <tt>logs/</tt> directory.</p>
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|
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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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||||
|
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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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|
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<p>When you're done, stop the daemons with:</p>
|
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|
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<p><tt>bin/stop-all.sh</tt></p>
|
||||
|
||||
<h3>Fully-distributed operation</h3>
|
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|
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<p>Fully distributed operation is just like the pseudo-distributed operation
|
||||
described above, except, specify:</p>
|
||||
|
||||
<ol>
|
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|
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<li>The hostname or IP address of your master server in the value
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for <tt><a
|
||||
href="../core-default.html#fs.default.name">fs.default.name</a></tt>,
|
||||
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>
|
||||
as <tt><em>master.example.com</em>:<em>port</em></tt> in <tt>conf/mapred-site.xml</tt>.</li>
|
||||
|
||||
<li>Directories for <tt><a
|
||||
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 worker nodes respectively. Note
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that <tt>dfs.data.dir</tt> may contain a space- or comma-separated
|
||||
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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|
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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>.
|
||||
As a rule of thumb, use 10x the
|
||||
number of worker processors for <tt>mapred.map.tasks</tt>, and 2x the
|
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number of worker processors for <tt>mapred.reduce.tasks</tt>.</li>
|
||||
|
||||
</ol>
|
||||
|
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<p>Finally, list all worker hostnames or IP addresses in your
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<tt>conf/workers</tt> file, one per line. Then format your filesystem
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and start your cluster on your master node, as above.
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@ -1,274 +0,0 @@
|
||||
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
|
||||
<html>
|
||||
<!--
|
||||
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 regarding copyright ownership.
|
||||
The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
(the "License"); you may not use this file except in compliance with
|
||||
the License. You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
-->
|
||||
<head>
|
||||
<title>Hadoop</title>
|
||||
</head>
|
||||
<body>
|
||||
|
||||
Hadoop is a distributed computing platform.
|
||||
|
||||
<p>Hadoop primarily consists of the <a
|
||||
href="http://hadoop.apache.org/hdfs/">Hadoop Distributed FileSystem
|
||||
(HDFS)</a> and an
|
||||
implementation of the <a href="http://hadoop.apache.org/mapreduce/">
|
||||
Map-Reduce</a> programming paradigm.</p>
|
||||
|
||||
|
||||
<p>Hadoop is a software framework that lets one easily write and run applications
|
||||
that process vast amounts of data. Here's what makes Hadoop especially useful:</p>
|
||||
<ul>
|
||||
<li>
|
||||
<b>Scalable</b>: Hadoop can reliably store and process petabytes.
|
||||
</li>
|
||||
<li>
|
||||
<b>Economical</b>: It distributes the data and processing across clusters
|
||||
of commonly available computers. These clusters can number into the thousands
|
||||
of nodes.
|
||||
</li>
|
||||
<li>
|
||||
<b>Efficient</b>: By distributing the data, Hadoop can process it in parallel
|
||||
on the nodes where the data is located. This makes it extremely rapid.
|
||||
</li>
|
||||
<li>
|
||||
<b>Reliable</b>: Hadoop automatically maintains multiple copies of data and
|
||||
automatically redeploys computing tasks based on failures.
|
||||
</li>
|
||||
</ul>
|
||||
|
||||
<h2>Requirements</h2>
|
||||
|
||||
<h3>Platforms</h3>
|
||||
|
||||
<ul>
|
||||
<li>
|
||||
Hadoop was been demonstrated on GNU/Linux clusters with 2000 nodes.
|
||||
</li>
|
||||
<li>
|
||||
Windows is also a supported platform.
|
||||
</li>
|
||||
</ul>
|
||||
|
||||
<h3>Requisite Software</h3>
|
||||
|
||||
<ol>
|
||||
<li>
|
||||
Java 1.6.x, preferably from
|
||||
<a href="http://java.sun.com/javase/downloads/">Sun</a>.
|
||||
Set <tt>JAVA_HOME</tt> to the root of your Java installation.
|
||||
</li>
|
||||
<li>
|
||||
ssh must be installed and sshd must be running to use Hadoop's
|
||||
scripts to manage remote Hadoop daemons.
|
||||
</li>
|
||||
<li>
|
||||
rsync may be installed to use Hadoop's scripts to manage remote
|
||||
Hadoop installations.
|
||||
</li>
|
||||
</ol>
|
||||
|
||||
<h3>Installing Required Software</h3>
|
||||
|
||||
<p>If your platform does not have the required software listed above, you
|
||||
will have to install it.</p>
|
||||
|
||||
<p>For example on Ubuntu Linux:</p>
|
||||
<p><blockquote><pre>
|
||||
$ sudo apt-get install ssh<br>
|
||||
$ sudo apt-get install rsync<br>
|
||||
</pre></blockquote></p>
|
||||
|
||||
<h2>Getting Started</h2>
|
||||
|
||||
<p>First, you need to get a copy of the Hadoop code.</p>
|
||||
|
||||
<p>Edit the file <tt>conf/hadoop-env.sh</tt> to define at least
|
||||
<tt>JAVA_HOME</tt>.</p>
|
||||
|
||||
<p>Try the following command:</p>
|
||||
<tt>bin/hadoop</tt>
|
||||
<p>This will display the documentation for the Hadoop command script.</p>
|
||||
|
||||
<h2>Standalone operation</h2>
|
||||
|
||||
<p>By default, Hadoop is configured to run things in a non-distributed
|
||||
mode, as a single Java process. This is useful for debugging, and can
|
||||
be demonstrated as follows:</p>
|
||||
<tt>
|
||||
mkdir input<br>
|
||||
cp conf/*.xml input<br>
|
||||
bin/hadoop jar hadoop-*-examples.jar grep input output 'dfs[a-z.]+'<br>
|
||||
cat output/*
|
||||
</tt>
|
||||
<p>This will display counts for each match of the <a
|
||||
href="http://java.sun.com/j2se/1.4.2/docs/api/java/util/regex/Pattern.html">
|
||||
regular expression.</a></p>
|
||||
|
||||
<p>Note that input is specified as a <em>directory</em> containing input
|
||||
files and that output is also specified as a directory where parts are
|
||||
written.</p>
|
||||
|
||||
<h2>Distributed operation</h2>
|
||||
|
||||
To configure Hadoop for distributed operation you must specify the
|
||||
following:
|
||||
|
||||
<ol>
|
||||
|
||||
<li>The NameNode (Distributed Filesystem master) host. This is
|
||||
specified with the configuration property <tt><a
|
||||
href="../core-default.html#fs.default.name">fs.default.name</a></tt>.
|
||||
</li>
|
||||
|
||||
<li>The org.apache.hadoop.mapred.JobTracker (MapReduce master)
|
||||
host and port. This is specified with the configuration property
|
||||
<tt><a
|
||||
href="../mapred-default.html#mapred.job.tracker">mapred.job.tracker</a></tt>.
|
||||
</li>
|
||||
|
||||
<li>A <em>workers</em> file that lists the names of all the hosts in
|
||||
the cluster. The default workers file is <tt>conf/workers</tt>.
|
||||
|
||||
</ol>
|
||||
|
||||
<h3>Pseudo-distributed configuration</h3>
|
||||
|
||||
You can in fact run everything on a single host. To run things this
|
||||
way, put the following in:
|
||||
<br/>
|
||||
<br/>
|
||||
conf/core-site.xml:
|
||||
<xmp><configuration>
|
||||
|
||||
<property>
|
||||
<name>fs.default.name</name>
|
||||
<value>hdfs://localhost/</value>
|
||||
</property>
|
||||
|
||||
</configuration></xmp>
|
||||
|
||||
conf/hdfs-site.xml:
|
||||
<xmp><configuration>
|
||||
|
||||
<property>
|
||||
<name>dfs.replication</name>
|
||||
<value>1</value>
|
||||
</property>
|
||||
|
||||
</configuration></xmp>
|
||||
|
||||
conf/mapred-site.xml:
|
||||
<xmp><configuration>
|
||||
|
||||
<property>
|
||||
<name>mapred.job.tracker</name>
|
||||
<value>localhost:9001</value>
|
||||
</property>
|
||||
|
||||
</configuration></xmp>
|
||||
|
||||
<p>(We also set the HDFS replication level to 1 in order to
|
||||
reduce warnings when running on a single node.)</p>
|
||||
|
||||
<p>Now check that the command <br><tt>ssh localhost</tt><br> does not
|
||||
require a password. If it does, execute the following commands:</p>
|
||||
|
||||
<p><tt>ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa<br>
|
||||
cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys
|
||||
</tt></p>
|
||||
|
||||
<h3>Bootstrapping</h3>
|
||||
|
||||
<p>A new distributed filesystem must be formatted with the following
|
||||
command, run on the master node:</p>
|
||||
|
||||
<p><tt>bin/hadoop namenode -format</tt></p>
|
||||
|
||||
<p>The Hadoop daemons are started with the following command:</p>
|
||||
|
||||
<p><tt>bin/start-all.sh</tt></p>
|
||||
|
||||
<p>Daemon log output is written to the <tt>logs/</tt> directory.</p>
|
||||
|
||||
<p>Input files are copied into the distributed filesystem as follows:</p>
|
||||
|
||||
<p><tt>bin/hadoop fs -put input input</tt></p>
|
||||
|
||||
<h3>Distributed execution</h3>
|
||||
|
||||
<p>Things are run as before, but output must be copied locally to
|
||||
examine it:</p>
|
||||
|
||||
<tt>
|
||||
bin/hadoop jar hadoop-*-examples.jar grep input output 'dfs[a-z.]+'<br>
|
||||
bin/hadoop fs -get output output
|
||||
cat output/*
|
||||
</tt>
|
||||
|
||||
<p>When you're done, stop the daemons with:</p>
|
||||
|
||||
<p><tt>bin/stop-all.sh</tt></p>
|
||||
|
||||
<h3>Fully-distributed operation</h3>
|
||||
|
||||
<p>Fully distributed operation is just like the pseudo-distributed operation
|
||||
described above, except, specify:</p>
|
||||
|
||||
<ol>
|
||||
|
||||
<li>The hostname or IP address of your master server in the value
|
||||
for <tt><a
|
||||
href="../core-default.html#fs.default.name">fs.default.name</a></tt>,
|
||||
as <tt><em>hdfs://master.example.com/</em></tt> in <tt>conf/core-site.xml</tt>.</li>
|
||||
|
||||
<li>The host and port of the your master server in the value
|
||||
of <tt><a href="../mapred-default.html#mapred.job.tracker">mapred.job.tracker</a></tt>
|
||||
as <tt><em>master.example.com</em>:<em>port</em></tt> in <tt>conf/mapred-site.xml</tt>.</li>
|
||||
|
||||
<li>Directories for <tt><a
|
||||
href="../hdfs-default.html#dfs.name.dir">dfs.name.dir</a></tt> and
|
||||
<tt><a href="../hdfs-default.html#dfs.data.dir">dfs.data.dir</a>
|
||||
in <tt>conf/hdfs-site.xml</tt>.
|
||||
</tt>These are local directories used to hold distributed filesystem
|
||||
data on the master node and worker nodes respectively. Note
|
||||
that <tt>dfs.data.dir</tt> may contain a space- or comma-separated
|
||||
list of directory names, so that data may be stored on multiple local
|
||||
devices.</li>
|
||||
|
||||
<li><tt><a href="../mapred-default.html#mapred.local.dir">mapred.local.dir</a></tt>
|
||||
in <tt>conf/mapred-site.xml</tt>, the local directory where temporary
|
||||
MapReduce data is stored. It also may be a list of directories.</li>
|
||||
|
||||
<li><tt><a
|
||||
href="../mapred-default.html#mapred.map.tasks">mapred.map.tasks</a></tt>
|
||||
and <tt><a
|
||||
href="../mapred-default.html#mapred.reduce.tasks">mapred.reduce.tasks</a></tt>
|
||||
in <tt>conf/mapred-site.xml</tt>.
|
||||
As a rule of thumb, use 10x the
|
||||
number of worker processors for <tt>mapred.map.tasks</tt>, and 2x the
|
||||
number of worker processors for <tt>mapred.reduce.tasks</tt>.</li>
|
||||
|
||||
</ol>
|
||||
|
||||
<p>Finally, list all worker hostnames or IP addresses in your
|
||||
<tt>conf/workers</tt> file, one per line. Then format your filesystem
|
||||
and start your cluster on your master node, as above.
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
25
pom.xml
25
pom.xml
@ -556,31 +556,6 @@ xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xs
|
||||
</build>
|
||||
</profile>
|
||||
|
||||
<profile>
|
||||
<id>dist</id>
|
||||
<!-- Profile for generating all maven artifacts and documentation. -->
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-javadoc-plugin</artifactId>
|
||||
<inherited>false</inherited>
|
||||
<executions>
|
||||
<execution>
|
||||
<!-- build aggregate javadoc in parent only -->
|
||||
<id>default-cli</id>
|
||||
<goals>
|
||||
<goal>aggregate</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<overview>hadoop-common-project/hadoop-common/src/main/java/overview.html</overview>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
</profile>
|
||||
<profile>
|
||||
<id>sign</id>
|
||||
<build>
|
||||
|
||||
Loading…
Reference in New Issue
Block a user