Getting started with hadoop --- quick start

Prepare to Start the Hadoop Cluster

Unpack the downloaded Hadoop distribution. In the distribution, edit the file conf/hadoop-env.sh to define at least JAVA_HOME to be the root of your Java installation.

Try the following command:

$ bin/hadoop

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:

• Local (Standalone) Mode
• Pseudo-Distributed Mode
• Fully-Distributed Mode

Standalone Operation

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 conf

10/04/27 18:33:27 INFO namenode.FSNamesystem: fsOwner=root,root

10/04/27 18:33:27 INFO namenode.FSNamesystem: supergroup=supergroup

10/04/27 18:33:27 INFO namenode.FSNamesystem: isPermissionEnabled=true

10/04/27 18:33:27 INFO common.Storage: Image file of size 94 saved in 0 seconds.

10/04/27 18:33:27 INFO common.Storage: Storage directory /tmp/hadoop-root/dfs/name has been successfully formatted.

10/04/27 18:33:27 INFO namenode.NameNode: SHUTDOWN_MSG:

# bin/hadoop fs -put conf input

# bin/hadoop jar hadoop-*-examples.jar grep input output 'dfs[a-z.]+'

10/04/27 19:07:00 INFO mapred.FileInputFormat: Total input paths to process : 17

10/04/27 19:07:01 INFO mapred.JobClient: Running job: job_201004271837_0001

10/04/27 19:07:02 INFO mapred.JobClient:  map 0% reduce 0%

10/04/27 19:07:12 INFO mapred.JobClient:  map 5% reduce 0%

10/04/27 19:07:16 INFO mapred.JobClient:  map 11% reduce 0%

10/04/27 19:07:19 INFO mapred.JobClient:  map 23% reduce 0%

10/04/27 19:07:25 INFO mapred.JobClient:  map 35% reduce 3%

10/04/27 19:07:28 INFO mapred.JobClient:  map 41% reduce 7%

10/04/27 19:07:31 INFO mapred.JobClient:  map 52% reduce 11%

10/04/27 19:07:34 INFO mapred.JobClient:  map 58% reduce 11%

10/04/27 19:07:37 INFO mapred.JobClient:  map 70% reduce 11%

10/04/27 19:07:40 INFO mapred.JobClient:  map 70% reduce 13%

10/04/27 19:07:43 INFO mapred.JobClient:  map 82% reduce 13%

10/04/27 19:07:46 INFO mapred.JobClient:  map 82% reduce 23%

10/04/27 19:07:49 INFO mapred.JobClient:  map 94% reduce 23%

10/04/27 19:07:52 INFO mapred.JobClient:  map 100% reduce 27%

10/04/27 19:07:58 INFO mapred.JobClient:  map 100% reduce 31%

10/04/27 19:08:05 INFO mapred.JobClient:  map 100% reduce 100%

10/04/27 19:08:06 INFO mapred.JobClient: Job complete: job_201004271837_0001

10/04/27 19:08:06 INFO mapred.JobClient: Counters: 18

10/04/27 19:08:06 INFO mapred.JobClient:   Job Counters

10/04/27 19:08:06 INFO mapred.JobClient:     Launched reduce tasks=1

10/04/27 19:08:06 INFO mapred.JobClient:     Launched map tasks=17

10/04/27 19:08:06 INFO mapred.JobClient:     Data-local map tasks=17

10/04/27 19:08:06 INFO mapred.JobClient:   FileSystemCounters

10/04/27 19:08:06 INFO mapred.JobClient:     FILE_BYTES_READ=158

10/04/27 19:08:06 INFO mapred.JobClient:     HDFS_BYTES_READ=21046

10/04/27 19:08:06 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=956

10/04/27 19:08:06 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=280

10/04/27 19:08:06 INFO mapred.JobClient:   Map-Reduce Framework

10/04/27 19:08:06 INFO mapred.JobClient:     Reduce input groups=7

10/04/27 19:08:06 INFO mapred.JobClient:     Combine output records=7

10/04/27 19:08:06 INFO mapred.JobClient:     Map input records=632

10/04/27 19:08:06 INFO mapred.JobClient:     Reduce shuffle bytes=254

10/04/27 19:08:06 INFO mapred.JobClient:     Reduce output records=7

10/04/27 19:08:06 INFO mapred.JobClient:     Spilled Records=14

10/04/27 19:08:06 INFO mapred.JobClient:     Map output bytes=193

10/04/27 19:08:06 INFO mapred.JobClient:     Map input bytes=21046

10/04/27 19:08:06 INFO mapred.JobClient:     Combine input records=10

10/04/27 19:08:06 INFO mapred.JobClient:     Map output records=10

10/04/27 19:08:06 INFO mapred.JobClient:     Reduce input records=7

10/04/27 19:08:06 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.

10/04/27 19:08:07 INFO mapred.FileInputFormat: Total input paths to process : 1

10/04/27 19:08:08 INFO mapred.JobClient: Running job: job_201004271837_0002

10/04/27 19:08:09 INFO mapred.JobClient:  map 0% reduce 0%

10/04/27 19:08:20 INFO mapred.JobClient:  map 100% reduce 0%

10/04/27 19:08:32 INFO mapred.JobClient:  map 100% reduce 100%

10/04/27 19:08:34 INFO mapred.JobClient: Job complete: job_201004271837_0002

10/04/27 19:08:34 INFO mapred.JobClient: Counters: 18

10/04/27 19:08:34 INFO mapred.JobClient:   Job Counters

10/04/27 19:08:34 INFO mapred.JobClient:     Launched reduce tasks=1

10/04/27 19:08:34 INFO mapred.JobClient:     Launched map tasks=1

10/04/27 19:08:34 INFO mapred.JobClient:     Data-local map tasks=1

10/04/27 19:08:34 INFO mapred.JobClient:   FileSystemCounters

10/04/27 19:08:34 INFO mapred.JobClient:     FILE_BYTES_READ=158

10/04/27 19:08:34 INFO mapred.JobClient:     HDFS_BYTES_READ=280

10/04/27 19:08:34 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=348

10/04/27 19:08:34 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=96

10/04/27 19:08:34 INFO mapred.JobClient:   Map-Reduce Framework

10/04/27 19:08:34 INFO mapred.JobClient:     Reduce input groups=3

10/04/27 19:08:34 INFO mapred.JobClient:     Combine output records=0

10/04/27 19:08:34 INFO mapred.JobClient:     Map input records=7

10/04/27 19:08:34 INFO mapred.JobClient:     Reduce shuffle bytes=158

10/04/27 19:08:34 INFO mapred.JobClient:     Reduce output records=7

10/04/27 19:08:34 INFO mapred.JobClient:     Spilled Records=14

10/04/27 19:08:34 INFO mapred.JobClient:     Map output bytes=138

10/04/27 19:08:34 INFO mapred.JobClient:     Map input bytes=194

10/04/27 19:08:34 INFO mapred.JobClient:     Combine input records=0

10/04/27 19:08:34 INFO mapred.JobClient:     Map output records=7

10/04/27 19:08:34 INFO mapred.JobClient:     Reduce input records=7

# bin/hadoop fs -cat output/*

3    dfs.class

2    dfs.period

1    dfs.file

1    dfs.replication

1    dfs.servers

1    dfsadmin

1    dfsmetrics.log

# bin/stop-all.sh

stopping jobtracker

localhost: stopping tasktracker

stopping namenode

localhost: stopping datanode

localhost: stopping secondarynamenode

Fully-Distributed Operation

For information on setting up fully-distributed, non-trivial clusters see Hadoop Cluster Setup .

next step, I'll digest