MapReduce in Hadoop 2.2.0 not working

Question

After installing and configuring my Hadoop 2.2.0 in pseudo-distributed mode everything is running, as you can see in the jps:

$ jps
2287 JobHistoryServer
1926 ResourceManager
2162 NodeManager
1834 DataNode
1756 NameNode
3013 Jps

Then I ran the wordcount example with

hadoop jar $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar wordcount /user/hdfs/file /output

And the execution frezees (?) as follows:

$ hadoop jar $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar wordcount /user/hdfs/file /output                                          
OpenJDK 64-Bit Server VM warning: You have loaded library /home/hduser/hadoop-src/hadoop-2.2.0/lib/native/libhadoop.so.1.0.0 which might have disabled stack guard. The VM will try to fix the stack guard now.
It's highly recommended that you fix the library with 'execstack -c <libfile>', or link it with '-z noexecstack'.
14/04/22 22:17:24 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
14/04/22 22:17:25 INFO client.RMProxy: Connecting to ResourceManager at /192.168.33.10:8032
14/04/22 22:17:25 INFO input.FileInputFormat: Total input paths to process : 1
14/04/22 22:17:25 INFO mapreduce.JobSubmitter: number of splits:1
14/04/22 22:17:25 INFO Configuration.deprecation: user.name is deprecated. Instead, use mapreduce.job.user.name
14/04/22 22:17:25 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
14/04/22 22:17:25 INFO Configuration.deprecation: mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
14/04/22 22:17:25 INFO Configuration.deprecation: mapreduce.combine.class is deprecated. Instead, use mapreduce.job.combine.class
14/04/22 22:17:25 INFO Configuration.deprecation: mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
14/04/22 22:17:25 INFO Configuration.deprecation: mapred.job.name is deprecated. Instead, use mapreduce.job.name
14/04/22 22:17:25 INFO Configuration.deprecation: mapreduce.reduce.class is deprecated. Instead, use mapreduce.job.reduce.class
14/04/22 22:17:25 INFO Configuration.deprecation: mapred.input.dir is deprecated. Instead, use mapreduce.input.fileinputformat.inputdir
14/04/22 22:17:25 INFO Configuration.deprecation: mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
14/04/22 22:17:25 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
14/04/22 22:17:25 INFO Configuration.deprecation: mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
14/04/22 22:17:25 INFO Configuration.deprecation: mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
14/04/22 22:17:26 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1398204897594_0002
14/04/22 22:17:26 INFO impl.YarnClientImpl: Submitted application application_1398204897594_0002 to ResourceManager at /192.168.33.10:8032
14/04/22 22:17:26 INFO mapreduce.Job: The url to track the job: http://vagrant-ubuntu-saucy-64:8088/proxy/application_1398204897594_0002/
14/04/22 22:17:26 INFO mapreduce.Job: Running job: job_1398204897594_0002
14/04/22 22:17:36 INFO mapreduce.Job: Job job_1398204897594_0002 running in uber mode : false
14/04/22 22:17:36 INFO mapreduce.Job:  map 0% reduce 0%

Any ideas?

Grissel

It seems related to #18525854, but the suggested answers are for hadoop 1x not for hadoop 2.2.0 – Grissel

Answer 1

The problem was in the file yarn-site.xml. The property must be larger than 3072 Mb, and I had it configured to 1024 Mb, so the correct way is

<property>
    <name>yarn.nodemanager.resource.memory-mb</name>
    <value>4096</value>
    <description>Physical memory, in MB, to be made available to running containers</description>
</property>

Grissel

I increased the memory as you said. But it still freezes for me? – Crosspurpose

Can you please post the user logs for that container? – Pilar

Answer 2

I think the log is not detailed enough，you can first Open the debug mode：

export HADOOP_ROOT_LOGGER=DEBUG,console

then run wordcount job for see more log and paste

Chronicles