我有两个工作节点的集群。 Worker_Node_1 - 64GB RAM Worker_Node_2 - 32GB RAM
背景概述 : 我正在尝试在yarn-cluster上执行spark-submit,对图形应用Pregel计算从一个源顶点到所有其他顶点的最短路径距离,并将值打印在控制台上。 实验:
- 对于具有15个顶点的小图,执行完成,应用程序最终状态为:SUCCEEDED
- 我的代码可以完美地为源顶点计算241个顶点图的最短距离,但是存在问题。
问题 : 当我查看日志文件时,任务在4分钟26秒内成功完成,但终端仍然显示应用程序状态为Running,大约12分钟后任务执行终止,显示 -
Application application_1447669815913_0002 failed 2 times due to AM Container for appattempt_1447669815913_0002_000002 exited with exitCode: -104 For more detailed output, check application tracking page:http://myserver.com:8088/proxy/application_1447669815913_0002/
Then, click on links to logs of each attempt.
Diagnostics: Container [pid=47384,containerID=container_1447669815913_0002_02_000001] is running beyond physical memory limits. Current usage: 17.9 GB of 17.5 GB physical memory used; 18.7 GB of 36.8 GB virtual memory used. Killing container.
Dump of the process-tree for container_1447669815913_0002_02_000001 :
|- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES) RSSMEM_USAGE(PAGES) FULL_CMD_LINE
|- 47387 47384 47384 47384 (java) 100525 13746 20105633792 4682973 /usr/lib/jvm/java-7-oracle-cloudera/bin/java -server -Xmx16384m -Djava.io.tmpdir=/yarn/nm/usercache/cloudera/appcache/application_1447669815913_0002/container_1447669815913_0002_02_000001/tmp -Dspark.eventLog.enabled=true -Dspark.eventLog.dir=hdfs://myserver.com:8020/user/spark/applicationHistory -Dspark.executor.memory=14g -Dspark.shuffle.service.enabled=false -Dspark.yarn.executor.memoryOverhead=2048 -Dspark.yarn.historyServer.address=http://myserver.com:18088 -Dspark.driver.extraLibraryPath=/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/hadoop/lib/native -Dspark.shuffle.service.port=7337 -Dspark.yarn.jar=local:/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/spark/lib/spark-assembly.jar -Dspark.serializer=org.apache.spark.serializer.KryoSerializer -Dspark.authenticate=false -Dspark.app.name=com.path.PathFinder -Dspark.master=yarn-cluster -Dspark.executor.extraLibraryPath=/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/hadoop/lib/native -Dspark.yarn.am.extraLibraryPath=/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/hadoop/lib/native -Dspark.yarn.app.container.log.dir=/var/log/hadoop-yarn/container/application_1447669815913_0002/container_1447669815913_0002_02_000001 org.apache.spark.deploy.yarn.ApplicationMaster --class com.path.PathFinder --jar file:/home/cloudera/Documents/Longest_Path_Data_1/Jars/ShortestPath_Loop-1.0.jar --arg /home/cloudera/workspace/Spark-Integration/LongestWorstPath/configFile --executor-memory 14336m --executor-cores 32 --num-executors 2
|- 47384 47382 47384 47384 (bash) 2 0 17379328 853 /bin/bash -c LD_LIBRARY_PATH=/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/hadoop/lib/native::/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/hadoop/lib/native /usr/lib/jvm/java-7-oracle-cloudera/bin/java -server -Xmx16384m -Djava.io.tmpdir=/yarn/nm/usercache/cloudera/appcache/application_1447669815913_0002/container_1447669815913_0002_02_000001/tmp '-Dspark.eventLog.enabled=true' '-Dspark.eventLog.dir=hdfs://myserver.com:8020/user/spark/applicationHistory' '-Dspark.executor.memory=14g' '-Dspark.shuffle.service.enabled=false' '-Dspark.yarn.executor.memoryOverhead=2048' '-Dspark.yarn.historyServer.address=http://myserver.com:18088' '-Dspark.driver.extraLibraryPath=/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/hadoop/lib/native' '-Dspark.shuffle.service.port=7337' '-Dspark.yarn.jar=local:/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/spark/lib/spark-assembly.jar' '-Dspark.serializer=org.apache.spark.serializer.KryoSerializer' '-Dspark.authenticate=false' '-Dspark.app.name=com.path.PathFinder' '-Dspark.master=yarn-cluster' '-Dspark.executor.extraLibraryPath=/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/hadoop/lib/native' '-Dspark.yarn.am.extraLibraryPath=/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/lib/hadoop/lib/native' -Dspark.yarn.app.container.log.dir=/var/log/hadoop-yarn/container/application_1447669815913_0002/container_1447669815913_0002_02_000001 org.apache.spark.deploy.yarn.ApplicationMaster --class 'com.path.PathFinder' --jar file:/home/cloudera/Documents/Longest_Path_Data_1/Jars/ShortestPath_Loop-1.0.jar --arg '/home/cloudera/workspace/Spark-Integration/LongestWorstPath/configFile' --executor-memory 14336m --executor-cores 32 --num-executors 2 1> /var/log/hadoop-yarn/container/application_1447669815913_0002/container_1447669815913_0002_02_000001/stdout 2> /var/log/hadoop-yarn/container/application_1447669815913_0002/container_1447669815913_0002_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.
我尝试过的事情:
- yarn.scheduler.maximum-allocation-mb - 32GB
- mapreduce.map.memory.mb = 2048(以前是1024)
- 尝试将--driver-memory变化到24g
请问如何配置资源管理器以处理大型图形(> 300K个顶点)?谢谢。