Help Center/ MapReduce Service/ Component Operation Guide (LTS)/ Using MapReduce/ Common Issues About MapReduce/ Why Physical Memory Overflow Occurs If a MapReduce Task Fails?
Updated on 2023-04-28 GMT+08:00

Why Physical Memory Overflow Occurs If a MapReduce Task Fails?

Question

The HBase bulkload task has 210,000 Map tasks and 10,000 Reduce tasks. The MapReduce task fails to be executed, and the physical memory of ApplicationMaster overflows.

For more detailed output, check the application tracking page:https://bigdata-55:8090/cluster/app/application_1449841777199_0003 
Then click on links to logs of each attempt.
Diagnostics: Container [pid=21557,containerID=container_1449841777199_0003_02_000001]  is running beyond physical memory limits 
Current usage: 1.0 GB of 1 GB physical memory used; 3.6 GB of 5 GB virtual memory used. Killing container.
Dump of the process-tree for container_1449841777199_0003_02_000001 :
|- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES) RSSMEM_USAGE(PAGES) FULL_CMD_LINE
|- 21584 21557 21557 21557 (java) 12342 1627 3871748096 271331 ${BIGDATA_HOME}/jdk1.8.0_51//bin/java 
-Djava.io.tmpdir=/srv/BigData/hadoop/data1/nm/localdir/usercache/hbase/appcache/application_1449841777199_0003/container_1449841777199_0003_02_000001/tmp -Dlog4j.configuration=container-log4j.properties 
-Dyarn.app.container.log.dir=/srv/BigData/hadoop/data1/nm/containerlogs/application_1449841777199_0003/container_1449841777199_0003_02_000001 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA 
-Dhadoop.root.logfile=syslog -Xmx784m org.apache.hadoop.mapreduce.v2.app.MRAppMaster
|- 21557 21547 21557 21557 (bash) 0 0 13074432 368 /bin/bash -c ${BIGDATA_HOME}/jdk1.8.0_51//bin/java
-Djava.io.tmpdir=/srv/BigData/hadoop/data1/nm/localdir/usercache/hbase/appcache/application_1449841777199_0003/container_1449841777199_0003_02_000001/tmp -Dlog4j.configuration=container-log4j.properties 
-Dyarn.app.container.log.dir=/srv/BigData/hadoop/data1/nm/containerlogs/application_1449841777199_0003/container_1449841777199_0003_02_000001 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA 
-Dhadoop.root.logfile=syslog -Xmx784m org.apache.hadoop.mapreduce.v2.app.MRAppMaster 1>/srv/BigData/hadoop/data1/nm/containerlogs/application_1449841777199_0003/container_1449841777199_0003_02_000001/stdout 
2>/srv/BigData/hadoop/data1/nm/containerlogs/application_1449841777199_0003/container_1449841777199_0003_02_000001/stderr
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
Failing this attempt. Failing the application.

Answer

This is a performance specification problem. The root cause of the MapReduce task execution failure is the memory overflow of ApplicationMaster, that is, the NodeManager kills the task due to the physical memory overflow.

Solutions:

Increase the memory of ApplicationMaster and optimize the following parameters in the client installation path/Yarn/config/mapred-site.xml configuration file on the client:

  • yarn.app.mapreduce.am.resource.mb
  • yarn.app.mapreduce.am.command-opts. The recommended value of -Xmx is 0.8 x yarn.app.mapreduce.am.resource.mb.

Specification:

ApplicationMaster supports 24,000 concurrent containers when the configuration is as follows:

  • yarn.app.mapreduce.am.resource.mb=2048
  • In yarn.app.mapreduce.am.command-opts, -Xmx is 1638m.