This document describes how to set up and configure a single-node Hadoop installation so that you can quickly perform simple operations using Hadoop MapReduce and the Hadoop Distributed File System (HDFS).
Required software for Linux include:
To get a Hadoop distribution, download a recent stable release from one of the Apache Download Mirrors.
Unpack the downloaded Hadoop distribution. In the distribution, edit the file etc/hadoop/hadoop-env.sh to define some parameters as follows:
# set to the root of your Java installation export JAVA_HOME=/usr/java/latest # Assuming your installation directory is /usr/local/hadoop export HADOOP_PREFIX=/usr/local/hadoop
Try the following command:
This will display the usage documentation for the hadoop script.
Now you are ready to start your Hadoop cluster in one of the three supported modes:
By default, Hadoop is configured to run in a non-distributed mode, as a single Java process. This is useful for debugging.
The following example copies the unpacked conf directory to use as input and then finds and displays every match of the given regular expression. Output is written to the given output directory.
$ mkdir input $ cp etc/hadoop/*.xml input $ bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0.jar grep input output 'dfs[a-z.]+' $ cat output/*
Hadoop can also be run on a single-node in a pseudo-distributed mode where each Hadoop daemon runs in a separate Java process.
Use the following:
<configuration> <property> <name>fs.defaultFS</name> <value>hdfs://localhost:9000</value> </property> </configuration>
<configuration> <property> <name>dfs.replication</name> <value>1</value> </property> </configuration>
Now check that you can ssh to the localhost without a passphrase:
$ ssh localhost
If you cannot ssh to localhost without a passphrase, execute the following commands:
$ ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa $ cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys
The following instructions are to run a MapReduce job locally. If you want to execute a job on YARN, see YARN on Single Node.
$ bin/hdfs namenode -format
$ bin/hdfs dfs -mkdir /user $ bin/hdfs dfs -mkdir /user/<username>
$ bin/hdfs dfs -put etc/hadoop input
$ bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0.jar grep input output 'dfs[a-z.]+'
Copy the output files from the distributed filesystem to the local filesystem and examine them:
$ bin/hdfs dfs -get output output $ cat output/*
View the output files on the distributed filesystem:
$ bin/hdfs dfs -cat output/*
You can run a MapReduce job on YARN in a pseudo-distributed mode by setting a few parameters and running ResourceManager daemon and NodeManager daemon in addition.
The following instructions assume that 1. ~ 4. steps of the above instructions are already executed.
<configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> </configuration>
<configuration> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> </configuration>
For information on setting up fully-distributed, non-trivial clusters see Cluster Setup.