All I am a new comer for Hadoop, I have run the hadoop-mapreduce-examples-2.2.0.jar wordcount, but the result is that it always pending at map 100% and reduce %0.
14/03/25 20:19:20 INFO client.RMProxy: Connecting to ResourceManager at master/159.99.249.63:8032 14/03/25 20:19:20 INFO input.FileInputFormat: Total input paths to process : 1 14/03/25 20:19:20 INFO mapreduce.JobSubmitter: number of splits:1 14/03/25 20:19:20 INFO Configuration.deprecation: user.name is deprecated. Instead, use mapreduce.job.user.name 14/03/25 20:19:20 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar 14/03/25 20:19:20 INFO Configuration.deprecation: mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class 14/03/25 20:19:20 INFO Configuration.deprecation: mapreduce.combine.class is deprecated. Instead, use mapreduce.job.combine.class 14/03/25 20:19:20 INFO Configuration.deprecation: mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class 14/03/25 20:19:20 INFO Configuration.deprecation: mapred.job.name is deprecated. Instead, use mapreduce.job.name 14/03/25 20:19:20 INFO Configuration.deprecation: mapreduce.reduce.class is deprecated. Instead, use mapreduce.job.reduce.class 14/03/25 20:19:20 INFO Configuration.deprecation: mapred.input.dir is deprecated. Instead, use mapreduce.input.fileinputformat.inputdir 14/03/25 20:19:20 INFO Configuration.deprecation: mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir 14/03/25 20:19:20 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps 14/03/25 20:19:20 INFO Configuration.deprecation: mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class 14/03/25 20:19:20 INFO Configuration.deprecation: mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir 14/03/25 20:19:20 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1395747600383_0002 14/03/25 20:19:20 INFO impl.YarnClientImpl: Submitted application application_1395747600383_0002 to ResourceManager at master/ 159.99.249.63:8032 14/03/25 20:19:20 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1395747600383_0002/ 14/03/25 20:19:20 INFO mapreduce.Job: Running job: job_1395747600383_0002 14/03/25 20:19:24 INFO mapreduce.Job: Job job_1395747600383_0002 running in uber mode : false 14/03/25 20:19:24 INFO mapreduce.Job: map 0% reduce 0% 14/03/25 20:19:28 INFO mapreduce.Job: map 100% reduce 0% 14/03/25 20:19:31 INFO mapreduce.Job: Task Id : attempt_1395747600383_0002_r_000000_0, Status : FAILED Error: org.apache.hadoop.mapreduce.task.reduce.Shuffle$ShuffleError: error in shuffle in fetcher#5 at org.apache.hadoop.mapreduce.task.reduce.Shuffle.run(Shuffle.java:121) at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:380) at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:162) at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs(Subject.java:415) at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1491) at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:157) Caused by: java.io.IOException: Exceeded MAX_FAILED_UNIQUE_FETCHES; bailing-out. at org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl.checkReducerHealth(ShuffleSchedulerImpl.java:323) at org.apache.hadoop.mapreduce.task.reduce.ShuffleSchedulerImpl.copyFailed(ShuffleSchedulerImpl.java:245) at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:347) at org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:165) someone says that this is caused by hosts configure .I have checked my /etc/hosts on all Mater & slaves: 127.0.0.1 localhost.localdomain localhost 159.99.249.63 master 159.99.249.203 slave1 159.99.249.99 slave2 159.99.249.88 slave3 Would you please help me to fix the issue, many thanks . my yarn-site.xml <?xml version="1.0"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <description>The hostname of the RM.</description> <name>yarn.resourcemanager.hostname</name> <value>master</value> </property> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> <property> <description>The address of the container manager in the NM.</description> <name>yarn.nodemanager.address</name> <value>${yarn.nodemanager.hostname}:8041</value> </property> </configuration> my mapred-site.xml <configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapreduce.reduce.shuffle.merge.percent</name> <value>0.33</value> <description>The usage threshold at which an in-memory merge will be initiated, expressed as a percentage of the total memory allocated to storing in-memory map outputs, as defined by mapreduce.reduce.shuffle.input.buffer.percent. </description> </property> <property> <name>mapreduce.reduce.shuffle.input.buffer.percent</name> <value>0.35</value> <description>The percentage of memory to be allocated from the maximum heap size to storing map outputs during the shuffle. </description> </property> <property> <name>mapreduce.reduce.shuffle.memory.limit.percent</name> <value>0.12</value> <description>Expert: Maximum percentage of the in-memory limit that a single shuffle can consume</description> </property> </configuration> -- BR, Vincent.Wei
