Hadoop is a distributed computing platform.

Hadoop primarily consists of a distributed filesystem (DFS, in org.apache.hadoop.dfs) and an implementation of a MapReduce distributed data processor (in org.apache.hadoop.mapred ).

## Requirements

1. Java 1.5.x, preferably from Sun Set `JAVA_HOME` to the root of your Java installation.
2. ssh must be installed and sshd must be running to use Hadoop's scripts to manage remote Hadoop daemons. On Ubuntu, this may done with
   `sudo apt-get install ssh`
3. rsync must be installed to use Hadoop's scripts to manage remote Hadoop installations. On Ubuntu, this may done with
   `sudo apt-get install rsync`.
4. On Win32, cygwin, for shell support. To use Subversion on Win32, select the subversion package when you install, in the "Devel" category. Distributed operation has not been well tested on Win32, so this should primarily be considered a development platform at this point, not a production platform.

## Getting Started

First, you need to get a copy of the Hadoop code.

You can download a nightly build from http://cvs.apache.org/dist/lucene/hadoop/nightly/. Unpack the release and connect to its top-level directory.

Or, check out the code from subversion and build it with Ant.

Edit the file `conf/hadoop-env.sh` to define at least `JAVA_HOME`.

Try the following command:

`bin/hadoop`

This will display the documentation for the Hadoop command script.

## Standalone operation

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:

`mkdir input
cp conf/*.xml input
bin/hadoop jar hadoop-*-examples.jar grep input output 'dfs[a-z.]+'
cat output/*`

This will display counts for each match of the regular expression.

Note that input is specified as a directory containing input files and that output is also specified as a directory where parts are written.

## Distributed operation

To configure Hadoop for distributed operation you must specify the following:

1. The {@link org.apache.hadoop.dfs.NameNode} (Distributed Filesystem master) host and port. This is specified with the configuration property `fs.default.name`.
2. The {@link org.apache.hadoop.mapred.JobTracker} (MapReduce master) host and port. This is specified with the configuration property `mapred.job.tracker`.
3. A slaves file that lists the names of all the hosts in the cluster. The default slaves file is `conf/slaves`.

### Pseudo-distributed configuration

You can in fact run everything on a single host. To run things this way, put the following in conf/hadoop-site.xml:

    <configuration>

      <property>
        <name>fs.default.name</name>
        <value>localhost:9000</value>
      </property>

      <property>
        <name>mapred.job.tracker</name>
        <value>localhost:9001</value>
      </property>

      <property>
        <name>dfs.replication</name>
        <value>1</value>
      </property>

    </configuration>

(We also set the DFS replication level to 1 in order to reduce warnings when running on a single node.)

Now check that the command
`ssh localhost`
does not require a password. If it does, execute the following commands:

`ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa
cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys`

### Bootstrapping

A new distributed filesystem must be formatted with the following command, run on the master node:

`bin/hadoop namenode -format`

The Hadoop daemons are started with the following command:

`bin/start-all.sh`

Daemon log output is written to the `logs/` directory.

Input files are copied into the distributed filesystem as follows:

`bin/hadoop dfs -put input input`

### Distributed execution

Things are run as before, but output must be copied locally to examine it:

`bin/hadoop org.apache.hadoop.mapred.demo.Grep input output 'dfs[a-z.]+'
bin/hadoop dfs -get output output cat output/*`

When you're done, stop the daemons with:

`bin/stop-all.sh`

## Fully-distributed operation

Distributed operation is just like the pseudo-distributed operation described above, except:

1. Specify hostname or IP address of the master server in the values for `fs.default.name` and `mapred.job.tracker` in `conf/hadoop-site.xml`. These are specified as `host:port` pairs.
2. Specify directories for `dfs.name.dir` and `dfs.data.dir` in `conf/hadoop-site.xml`. These are used to hold distributed filesystem data on the master node and slave nodes respectively. Note that `dfs.data.dir` may contain a space- or comma-separated list of directory names, so that data may be stored on multiple devices.
3. Specify `mapred.local.dir` in `conf/hadoop-site.xml`. This determines where temporary MapReduce data is written. It also may be a list of directories.
4. Specify `mapred.map.tasks` and `mapred.reduce.tasks` in `conf/mapred-default.xml`. As a rule of thumb, use 10x the number of slave processors for `mapred.map.tasks`, and 2x the number of slave processors for `mapred.reduce.tasks`.
5. List all slave hostnames or IP addresses in your `conf/slaves` file, one per line.