hive任务优化-Current usage: 2.0 GB of 2 GB physical memory used; 4.0 GB of 16.2 GB virtual memory used.
目录
错误背景
错误信息定位
client端日志
APPlication日志
map和reduce单个错误日志
错误分析
解决方案
1. 取消虚拟内存的检查（不建议）：
2.增大mapreduce.map.memory.mb 或者 mapreduce.reduce.memory.mb （建议）
3.适当增大 yarn.nodemanager.vmem-pmem-ratio的大小
4.换成sparkSQL任务（骚的一比，强烈推荐）
小结
错误背景
大概是job运行超过了map和reduce设置的内存大小，导致任务失败 ，就是写了一个hql语句运行在大数据平台上面，发现报错了。
错误信息定位
client端日志
INFO : converting to local hdfs://hacluster/tenant/yxs/product/resources/resources/jar/f3c06465-4af1-4756-894e-ce74ec11b9c3.jar
INFO : Added [/opt/huawei/Bigdata/tmp/hivelocaltmp/session_resources/2d0a2efc-776c-4ccc-957d-927079862ab2_resources/f3c06465-4af1-4756-894e-ce74ec11b9c3.jar] to class path
INFO : Added resources: [hdfs://hacluster/tenant/yxs/product/resources/resources/jar/f3c06465-4af1-4756-894e-ce74ec11b9c3.jar]
INFO : Number of reduce tasks not specified. Estimated from input data size: 2
INFO : In order to change the average load for a reducer (in bytes):
INFO : set hive.exec.reducers.bytes.per.reducer=
INFO : In order to limit the maximum number of reducers:
INFO : set hive.exec.reducers.max=
INFO : In order to set a constant number of reducers:
INFO : set mapreduce.job.reduces=
INFO : number of splits:10
INFO : Submitting tokens for job: job_1567609664100_85580
INFO : Kind: HDFS_DELEGATION_TOKEN, Service: ha-hdfs:hacluster
INFO : Kind: HIVE_DELEGATION_TOKEN, Service: HiveServer2ImpersonationToken
INFO : The url to track the job: https://yiclouddata03-szzb:26001/proxy/application_1567609664100_85580/
INFO : Starting Job = job_1567609664100_85580, Tracking URL = https://yiclouddata03-szzb:26001/proxy/application_1567609664100_85580/
INFO : Kill Command = /opt/huawei/Bigdata/FusionInsight_HD_V100R002C80SPC203/install/FusionInsight-Hive-1.3.0/hive-1.3.0/bin/..//../hadoop/bin/hadoop job -kill job_1567609664100_85580
INFO : Hadoop job information for Stage-6: number of mappers: 10; number of reducers: 2
INFO : 2019-09-24 16:16:17,686 Stage-6 map = 0%, reduce = 0%
INFO : 2019-09-24 16:16:27,299 Stage-6 map = 20%, reduce = 0%, Cumulative CPU 10.12 sec
INFO : 2019-09-24 16:16:28,474 Stage-6 map = 30%, reduce = 0%, Cumulative CPU 30.4 sec
INFO : 2019-09-24 16:16:29,664 Stage-6 map = 70%, reduce = 0%, Cumulative CPU 83.44 sec
INFO : 2019-09-24 16:16:30,841 Stage-6 map = 90%, reduce = 0%, Cumulative CPU 115.79 sec
INFO : 2019-09-24 16:16:32,004 Stage-6 map = 91%, reduce = 0%, Cumulative CPU 134.73 sec
INFO : 2019-09-24 16:16:44,928 Stage-6 map = 92%, reduce = 0%, Cumulative CPU 223.25 sec
INFO : 2019-09-24 16:16:55,613 Stage-6 map = 93%, reduce = 0%, Cumulative CPU 284.27 sec
INFO : 2019-09-24 16:17:03,797 Stage-6 map = 94%, reduce = 0%, Cumulative CPU 313.69 sec
INFO : 2019-09-24 16:17:11,881 Stage-6 map = 90%, reduce = 0%, Cumulative CPU 115.79 sec
INFO : 2019-09-24 16:18:12,546 Stage-6 map = 90%, reduce = 0%, Cumulative CPU 115.79 sec
INFO : 2019-09-24 16:19:04,473 Stage-6 map = 91%, reduce = 0%, Cumulative CPU 185.47 sec
INFO : 2019-09-24 16:19:13,683 Stage-6 map = 92%, reduce = 0%, Cumulative CPU 223.35 sec
INFO : 2019-09-24 16:19:22,825 Stage-6 map = 93%, reduce = 0%, Cumulative CPU 281.97 sec
INFO : 2019-09-24 16:19:32,053 Stage-6 map = 94%, reduce = 0%, Cumulative CPU 314.97 sec
INFO : 2019-09-24 16:19:54,143 Stage-6 map = 95%, reduce = 0%, Cumulative CPU 377.36 sec
INFO : 2019-09-24 16:19:56,520 Stage-6 map = 90%, reduce = 0%, Cumulative CPU 115.79 sec
INFO : 2019-09-24 16:20:09,338 Stage-6 map = 91%, reduce = 0%, Cumulative CPU 181.59 sec
INFO : 2019-09-24 16:20:18,574 Stage-6 map = 92%, reduce = 0%, Cumulative CPU 217.27 sec
INFO : 2019-09-24 16:20:27,772 Stage-6 map = 93%, reduce = 0%, Cumulative CPU 266.25 sec
INFO : 2019-09-24 16:20:40,439 Stage-6 map = 94%, reduce = 0%, Cumulative CPU 305.32 sec
INFO : 2019-09-24 16:20:57,751 Stage-6 map = 90%, reduce = 0%, Cumulative CPU 115.79 sec
INFO : 2019-09-24 16:21:11,624 Stage-6 map = 91%, reduce = 0%, Cumulative CPU 183.87 sec
INFO : 2019-09-24 16:21:20,948 Stage-6 map = 92%, reduce = 0%, Cumulative CPU 219.12 sec
INFO : 2019-09-24 16:21:31,427 Stage-6 map = 93%, reduce = 0%, Cumulative CPU 282.71 sec
INFO : 2019-09-24 16:21:39,754 Stage-6 map = 94%, reduce = 0%, Cumulative CPU 317.99 sec
INFO : 2019-09-24 16:21:45,519 Stage-6 map = 100%, reduce = 100%, Cumulative CPU 115.79 sec
INFO : MapReduce Total cumulative CPU time: 1 minutes 55 seconds 790 msec
ERROR : Ended Job = job_1567609664100_85580 with errors
任务-T_6260893799950704_20190924161555945_1_1 运行失败，失败原因：java.sql.SQLException: Error while processing statement: FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask
at org.apache.hive.jdbc.HiveStatement.execute(HiveStatement.java:283)
at org.apache.hive.jdbc.HiveStatement.executeQuery(HiveStatement.java:379)
at com.dtwave.dipper.dubhe.node.executor.runner.impl.Hive2TaskRunner.doRun(Hive2TaskRunner.java:244)
at com.dtwave.dipper.dubhe.node.executor.runner.BasicTaskRunner.execute(BasicTaskRunner.java:100)
at com.dtwave.dipper.dubhe.node.executor.TaskExecutor.run(TaskExecutor.java:32)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
任务运行失败(Failed) 看完错误是不是一脸懵逼，两眼茫然...怀疑人生，哈哈...
APPlication日志
看这个能看出啥错误呀，需要去yarn里面看application任务运行日志如下所示：
2019-09-24 16:16:27,712 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Num completed Tasks: 3
2019-09-24 16:16:27,712 INFO [ContainerLauncher #2] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: Processing the event EventType: CONTAINER_REMOTE_CLEANUP for container container_e29_1567609664100_85580_01_000011 taskAttempt attempt_1567609664100_85580_m_000009_0
2019-09-24 16:16:27,713 INFO [ContainerLauncher #2] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: KILLING attempt_1567609664100_85580_m_000009_0
2019-09-24 16:16:27,713 INFO [ContainerLauncher #2] org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy: Opening proxy : yiclouddata04-SZZB:26009
2019-09-24 16:16:27,997 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Before Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:10 AssignedReds:0 CompletedMaps:3 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:16:28,005 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000009
2019-09-24 16:16:28,006 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000011
2019-09-24 16:16:28,006 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000003
2019-09-24 16:16:28,006 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:28,006 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:16:28,006 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: After Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:7 AssignedReds:0 CompletedMaps:3 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:16:28,006 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000008_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:28,006 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000009_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:28,006 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000007_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:28,557 INFO [IPC Server handler 7 on 27102] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Done acknowledgement from attempt_1567609664100_85580_m_000006_0
2019-09-24 16:16:28,558 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Task Attempt attempt_1567609664100_85580_m_000006_0 finished. Firing CONTAINER_AVAILABLE_FOR_REUSE event to ContainerAllocator
2019-09-24 16:16:28,558 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1567609664100_85580_m_000006_0 TaskAttempt Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:28,558 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: Task succeeded with attempt attempt_1567609664100_85580_m_000006_0
2019-09-24 16:16:28,558 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1567609664100_85580_m_000006 Task Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:28,559 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Num completed Tasks: 4
2019-09-24 16:16:28,560 INFO [ContainerLauncher #5] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: Processing the event EventType: CONTAINER_REMOTE_CLEANUP for container container_e29_1567609664100_85580_01_000007 taskAttempt attempt_1567609664100_85580_m_000006_0
2019-09-24 16:16:28,560 INFO [ContainerLauncher #5] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: KILLING attempt_1567609664100_85580_m_000006_0
2019-09-24 16:16:28,560 INFO [ContainerLauncher #5] org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy: Opening proxy : yiclouddata05-SZZB:26009
2019-09-24 16:16:28,851 INFO [IPC Server handler 10 on 27102] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Done acknowledgement from attempt_1567609664100_85580_m_000005_0
2019-09-24 16:16:28,852 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Task Attempt attempt_1567609664100_85580_m_000005_0 finished. Firing CONTAINER_AVAILABLE_FOR_REUSE event to ContainerAllocator
2019-09-24 16:16:28,852 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1567609664100_85580_m_000005_0 TaskAttempt Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:28,852 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: Task succeeded with attempt attempt_1567609664100_85580_m_000005_0
2019-09-24 16:16:28,852 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1567609664100_85580_m_000005 Task Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:28,853 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Num completed Tasks: 5
2019-09-24 16:16:28,856 INFO [ContainerLauncher #8] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: Processing the event EventType: CONTAINER_REMOTE_CLEANUP for container container_e29_1567609664100_85580_01_000008 taskAttempt attempt_1567609664100_85580_m_000005_0
2019-09-24 16:16:28,856 INFO [ContainerLauncher #8] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: KILLING attempt_1567609664100_85580_m_000005_0
2019-09-24 16:16:28,856 INFO [ContainerLauncher #8] org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy: Opening proxy : yiclouddata16-SZZB:26009
2019-09-24 16:16:28,986 INFO [IPC Server handler 16 on 27102] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Done acknowledgement from attempt_1567609664100_85580_m_000004_0
2019-09-24 16:16:28,987 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Task Attempt attempt_1567609664100_85580_m_000004_0 finished. Firing CONTAINER_AVAILABLE_FOR_REUSE event to ContainerAllocator
2019-09-24 16:16:28,987 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1567609664100_85580_m_000004_0 TaskAttempt Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:28,987 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: Task succeeded with attempt attempt_1567609664100_85580_m_000004_0
2019-09-24 16:16:28,988 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1567609664100_85580_m_000004 Task Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:28,989 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Num completed Tasks: 6
2019-09-24 16:16:28,989 INFO [ContainerLauncher #6] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: Processing the event EventType: CONTAINER_REMOTE_CLEANUP for container container_e29_1567609664100_85580_01_000005 taskAttempt attempt_1567609664100_85580_m_000004_0
2019-09-24 16:16:28,990 INFO [ContainerLauncher #6] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: KILLING attempt_1567609664100_85580_m_000004_0
2019-09-24 16:16:28,990 INFO [ContainerLauncher #6] org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy: Opening proxy : yiclouddata10-SZZB:26009
2019-09-24 16:16:29,006 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Before Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:7 AssignedReds:0 CompletedMaps:6 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:16:29,008 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000008
2019-09-24 16:16:29,009 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000007
2019-09-24 16:16:29,009 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000005_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:29,009 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:29,009 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:16:29,009 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000006_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:29,009 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: After Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:5 AssignedReds:0 CompletedMaps:6 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:16:29,582 INFO [IPC Server handler 12 on 27102] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Done acknowledgement from attempt_1567609664100_85580_m_000002_0
2019-09-24 16:16:29,584 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Task Attempt attempt_1567609664100_85580_m_000002_0 finished. Firing CONTAINER_AVAILABLE_FOR_REUSE event to ContainerAllocator
2019-09-24 16:16:29,584 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1567609664100_85580_m_000002_0 TaskAttempt Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:29,584 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: Task succeeded with attempt attempt_1567609664100_85580_m_000002_0
2019-09-24 16:16:29,584 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1567609664100_85580_m_000002 Task Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:29,584 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Num completed Tasks: 7
2019-09-24 16:16:29,585 INFO [ContainerLauncher #4] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: Processing the event EventType: CONTAINER_REMOTE_CLEANUP for container container_e29_1567609664100_85580_01_000010 taskAttempt attempt_1567609664100_85580_m_000002_0
2019-09-24 16:16:29,586 INFO [ContainerLauncher #4] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: KILLING attempt_1567609664100_85580_m_000002_0
2019-09-24 16:16:29,586 INFO [ContainerLauncher #4] org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy: Opening proxy : yiclouddata14-SZZB:26009
2019-09-24 16:16:30,009 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Before Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:5 AssignedReds:0 CompletedMaps:7 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:16:30,013 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000010
2019-09-24 16:16:30,013 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000005
2019-09-24 16:16:30,013 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000002_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:30,013 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:30,013 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:16:30,013 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: After Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:3 AssignedReds:0 CompletedMaps:7 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:16:30,013 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000004_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:30,416 INFO [IPC Server handler 6 on 27102] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Done acknowledgement from attempt_1567609664100_85580_m_000001_0
2019-09-24 16:16:30,417 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Task Attempt attempt_1567609664100_85580_m_000001_0 finished. Firing CONTAINER_AVAILABLE_FOR_REUSE event to ContainerAllocator
2019-09-24 16:16:30,417 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1567609664100_85580_m_000001_0 TaskAttempt Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:30,417 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: Task succeeded with attempt attempt_1567609664100_85580_m_000001_0
2019-09-24 16:16:30,418 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1567609664100_85580_m_000001 Task Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:30,418 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Num completed Tasks: 8
2019-09-24 16:16:30,419 INFO [ContainerLauncher #3] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: Processing the event EventType: CONTAINER_REMOTE_CLEANUP for container container_e29_1567609664100_85580_01_000004 taskAttempt attempt_1567609664100_85580_m_000001_0
2019-09-24 16:16:30,419 INFO [ContainerLauncher #3] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: KILLING attempt_1567609664100_85580_m_000001_0
2019-09-24 16:16:30,419 INFO [ContainerLauncher #3] org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy: Opening proxy : yiclouddata12-SZZB:26009
2019-09-24 16:16:30,440 INFO [IPC Server handler 7 on 27102] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Done acknowledgement from attempt_1567609664100_85580_m_000003_0
2019-09-24 16:16:30,442 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Task Attempt attempt_1567609664100_85580_m_000003_0 finished. Firing CONTAINER_AVAILABLE_FOR_REUSE event to ContainerAllocator
2019-09-24 16:16:30,442 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: attempt_1567609664100_85580_m_000003_0 TaskAttempt Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:30,442 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: Task succeeded with attempt attempt_1567609664100_85580_m_000003_0
2019-09-24 16:16:30,442 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskImpl: task_1567609664100_85580_m_000003 Task Transitioned from RUNNING to SUCCEEDED
2019-09-24 16:16:30,442 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.JobImpl: Num completed Tasks: 9
2019-09-24 16:16:30,443 INFO [ContainerLauncher #7] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: Processing the event EventType: CONTAINER_REMOTE_CLEANUP for container container_e29_1567609664100_85580_01_000002 taskAttempt attempt_1567609664100_85580_m_000003_0
2019-09-24 16:16:30,446 INFO [ContainerLauncher #7] org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: KILLING attempt_1567609664100_85580_m_000003_0
2019-09-24 16:16:30,447 INFO [ContainerLauncher #7] org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy: Opening proxy : yiclouddata11-SZZB:26009
2019-09-24 16:16:30,556 INFO [IPC Server handler 8 on 27102] org.apache.hadoop.mapred.TaskAttemptListenerImpl: JVM with ID : jvm_1567609664100_85580_m_31885837205506 asked for a task
2019-09-24 16:16:30,556 INFO [IPC Server handler 8 on 27102] org.apache.hadoop.mapred.TaskAttemptListenerImpl: JVM with ID: jvm_1567609664100_85580_m_31885837205506 is invalid and will be killed.
2019-09-24 16:16:31,013 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Before Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:3 AssignedReds:0 CompletedMaps:9 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:16:31,017 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000004
2019-09-24 16:16:31,017 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000002
2019-09-24 16:16:31,017 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:31,017 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000001_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:31,017 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:16:31,017 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: After Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:1 AssignedReds:0 CompletedMaps:9 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:16:31,017 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000003_0: Container killed by the ApplicationMaster.
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
2019-09-24 16:16:34,026 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:34,026 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:16:36,032 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:36,032 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:16:47,061 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:47,061 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:16:58,089 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:58,090 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:16:59,092 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:16:59,092 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:17:06,109 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:17:06,109 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:17:08,113 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:17:08,113 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:17:09,115 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:17:09,115 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:17:10,117 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:17:10,117 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:17:11,121 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Received completed container container_e29_1567609664100_85580_01_000006
2019-09-24 16:17:11,122 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=
2019-09-24 16:17:11,122 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 10
2019-09-24 16:17:11,122 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: After Scheduling: PendingReds:2 ScheduledMaps:0 ScheduledReds:0 AssignedMaps:0 AssignedReds:0 CompletedMaps:9 CompletedReds:0 ContAlloc:10 ContRel:0 HostLocal:8 RackLocal:1
2019-09-24 16:17:11,122 INFO [AsyncDispatcher event handler] org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1567609664100_85580_m_000000_0: Container [pid=44860,containerID=container_e29_1567609664100_85580_01_000006] is running beyond physical memory limits. Current usage: 2.0 GB of 2 GB physical memory used; 4.0 GB of 16.2 GB virtual memory used. Killing container.
Dump of the process-tree for container_e29_1567609664100_85580_01_000006 :
|- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES) RSSMEM_USAGE(PAGES) FULL_CMD_LINE
|- 44881 44860 44860 44860 (java) 21865 1198 4183670784 526521 /opt/huawei/Bigdata/common/runtime0/jdk1.8.0_162//bin/java -Djava.security.auth.login.config=/opt/huawei/Bigdata/FusionInsight_Current/1_11_NodeManager/etc/jaas-zk.conf -Dzookeeper.server.principal=zookeeper/hadoop.hadoop.com -Dzookeeper.request.timeout=120000 -server -XX:NewRatio=8 -Djava.net.preferIPv4Stack=true -Xmx2048M -Djava.net.preferIPv4Stack=true -Djava.security.krb5.conf=/opt/huawei/Bigdata/common/runtime/krb5.conf -Djava.io.tmpdir=/srv/BigData/hadoop/data6/nm/localdir/usercache/yxs_product/appcache/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006/tmp -Dlog4j.configuration=container-log4j.properties -Dyarn.app.container.log.dir=/srv/BigData/hadoop/data10/nm/containerlogs/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA -Dhadoop.root.logfile=syslog org.apache.hadoop.mapred.YarnChild 10.240.250.133 27102 attempt_1567609664100_85580_m_000000_0 31885837205510
|- 44860 44857 44860 44860 (bash) 2 1 116031488 374 /bin/bash -c /opt/huawei/Bigdata/common/runtime0/jdk1.8.0_162//bin/java -Djava.security.auth.login.config=/opt/huawei/Bigdata/FusionInsight_Current/1_11_NodeManager/etc/jaas-zk.conf -Dzookeeper.server.principal=zookeeper/hadoop.hadoop.com -Dzookeeper.request.timeout=120000 -server -XX:NewRatio=8 -Djava.net.preferIPv4Stack=true -Xmx2048M -Djava.net.preferIPv4Stack=true -Djava.security.krb5.conf=/opt/huawei/Bigdata/common/runtime/krb5.conf -Djava.io.tmpdir=/srv/BigData/hadoop/data6/nm/localdir/usercache/yxs_product/appcache/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006/tmp -Dlog4j.configuration=container-log4j.properties -Dyarn.app.container.log.dir=/srv/BigData/hadoop/data10/nm/containerlogs/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA -Dhadoop.root.logfile=syslog org.apache.hadoop.mapred.YarnChild 10.240.250.133 27102 attempt_1567609664100_85580_m_000000_0 31885837205510 1>/srv/BigData/hadoop/data10/nm/containerlogs/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006/stdout 2>/srv/BigData/hadoop/data10/nm/containerlogs/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006/stderr
Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143 map和reduce单个错误日志
然后我其实还是没有看出来有啥子错误，继续找详细看map和reduce报错信息：
错误日志如下
Container [pid=44860,containerID=container_e29_1567609664100_85580_01_000006] is running beyond physical memory limits. Current usage: 2.0 GB of 2 GB physical memory used; 4.0 GB of 16.2 GB virtual memory used. Killing container. Dump of the process-tree for container_e29_1567609664100_85580_01_000006 : |- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES) RSSMEM_USAGE(PAGES) FULL_CMD_LINE |- 44881 44860 44860 44860 (java) 21865 1198 4183670784 526521 /opt/huawei/Bigdata/common/runtime0/jdk1.8.0_162//bin/java -Djava.security.auth.login.config=/opt/huawei/Bigdata/FusionInsight_Current/1_11_NodeManager/etc/jaas-zk.conf -Dzookeeper.server.principal=zookeeper/hadoop.hadoop.com -Dzookeeper.request.timeout=120000 -server -XX:NewRatio=8 -Djava.net.preferIPv4Stack=true -Xmx2048M -Djava.net.preferIPv4Stack=true -Djava.security.krb5.conf=/opt/huawei/Bigdata/common/runtime/krb5.conf -Djava.io.tmpdir=/srv/BigData/hadoop/data6/nm/localdir/usercache/yxs_product/appcache/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006/tmp -Dlog4j.configuration=container-log4j.properties -Dyarn.app.container.log.dir=/srv/BigData/hadoop/data10/nm/containerlogs/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA -Dhadoop.root.logfile=syslog org.apache.hadoop.mapred.YarnChild 10.240.250.133 27102 attempt_1567609664100_85580_m_000000_0 31885837205510 |- 44860 44857 44860 44860 (bash) 2 1 116031488 374 /bin/bash -c /opt/huawei/Bigdata/common/runtime0/jdk1.8.0_162//bin/java -Djava.security.auth.login.config=/opt/huawei/Bigdata/FusionInsight_Current/1_11_NodeManager/etc/jaas-zk.conf -Dzookeeper.server.principal=zookeeper/hadoop.hadoop.com -Dzookeeper.request.timeout=120000 -server -XX:NewRatio=8 -Djava.net.preferIPv4Stack=true -Xmx2048M -Djava.net.preferIPv4Stack=true -Djava.security.krb5.conf=/opt/huawei/Bigdata/common/runtime/krb5.conf -Djava.io.tmpdir=/srv/BigData/hadoop/data6/nm/localdir/usercache/yxs_product/appcache/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006/tmp -Dlog4j.configuration=container-log4j.properties -Dyarn.app.container.log.dir=/srv/BigData/hadoop/data10/nm/containerlogs/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA -Dhadoop.root.logfile=syslog org.apache.hadoop.mapred.YarnChild 10.240.250.133 27102 attempt_1567609664100_85580_m_000000_0 31885837205510 1>/srv/BigData/hadoop/data10/nm/containerlogs/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006/stdout 2>/srv/BigData/hadoop/data10/nm/containerlogs/application_1567609664100_85580/container_e29_1567609664100_85580_01_000006/stderr Container killed on request. Exit code is 143 Container exited with a non-zero exit code 143Container [pid=44860,containerID=container_e29_1567609664100_85580_01_000006] is running beyond physical memory limits. Current usage: 2.0 GB of 2 GB physical memory used; 4.0 GB of 16.2 GB virtual memory used. Killing container.
ok，看到这里终于找到错误原因了。
错误分析
首先检查yarn上面配置信息
ERROR：Container [pid=44860,containerID=container_e29_1567609664100_85580_01_000006] is running beyond physical memory limits. Current usage: 2.0 GB of 2 GB physical memory used; 4.0 GB of 16.2 GB virtual memory used. Killing container.
2.0 GB：任务所占的物理内存
2GB： mapreduce.map.memory.mb 参数默认设置大小
4.0 GB：程序占用的虚拟内存
16.2 GB： mapreduce.map.memory.mb 乘以 yarn.nodemanager.vmem-pmem-ratio 得到的
其中 yarn.nodemanager.vmem-pmem-ratio 是 虚拟内存和物理内存比例，在yarn-site.xml中设置，默认是2.1
很明显，container需要占用了超过了任务的物理内存限制（running beyond physical memory limits）。所以kill掉了这个container。
上面只是map中产生的报错，当然也有可能在reduce中报错，如果是reduce中，那么就是mapreduce.reduce.memory.db * yarn.nodemanager.vmem-pmem-ratio
物理内存：真实的硬件设备（内存条）
虚拟内存：利用磁盘空间虚拟出的一块逻辑内存，用作虚拟内存的磁盘空间被称为交换空间（Swap Space）。（为了满足物理内存的不足而提出的策略）
linux会在物理内存不足时，使用交换分区的虚拟内存。内核会将暂时不用的内存块信息写到交换空间，这样以来，物理内存得到了释放，这块内存就可以用于其它目的，当需要用到原始的内容时，这些信息会被重新从交换空间读入物理内存。
解决方案
1. 取消虚拟内存的检查（不建议）：
在yarn-site.xml或者程序中中设置yarn.nodemanager.vmem-check-enabled为false
yarn.nodemanager.vmem-check-enabled
false
Whether virtual memory limits will be enforced for containers.
除了物理内存超了，也有可能是虚拟内存超了，同样也可以设置物理内存的检查为
yarn.nodemanager.pmem-check-enabled ：false个人认为这种办法并不太好，如果程序有内存泄漏等问题，取消这个检查，可能会导致集群崩溃。
2.增大mapreduce.map.memory.mb 或者 mapreduce.reduce.memory.mb （建议）
3.适当增大 yarn.nodemanager.vmem-pmem-ratio的大小
为物理内存增大对应的虚拟内存， 但是这个参数也不能太离谱
4.换成sparkSQL任务（骚的一比，强烈推荐）
小结
任务内存问题，主要分为两块，一块是物理内存，一块是虚拟内存，哪个超过了任务都会报错的，适当地修改对应的参数，就可以将任务继续运行了。如果任务所占用的内存太过离谱，更多考虑的应该是程序是否有内存泄漏，是否存在数据倾斜等，优先程序解决此类问题。终极解法：拆分数据，将数据均分成多个任务，进行操作~
或者选择spark哦~
6 的飞起！！！