Hive-Container killed by YARN for exceeding memory limits. 9.2 GB of 9 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead.

复制代码
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 0.0 failed 4 times, most recent failure: Lost task 3.3 in stage 0.0 (TID 62, hadoop7, executor 17): ExecutorLostFailure (executor 17 exited caused by one of the running tasks) Reason: Container killed by YARN for exceeding memory limits. 9.2 GB of 9 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead.
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1524)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1512)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1511)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1511)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1739)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1694)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1683)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)

ERROR : FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Spark job failed because of out of memory.
INFO : Completed executing command(queryId=hive_20190529100107_063ed2a4-e3b0-48a9-9bcc-49acd51925c1); Time taken: 1441.753 seconds
Error: Error while processing statement: FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Spark job failed because of out of memory. (state=42000,code=3)
Closing: 0: jdbc:hive2://hadoop1:10000/pdw_nameonce
复制代码

Hive on spark时报错

解决
a.set spark.yarn.executor.memoryOverhead=512G 调大(权宜之计),excutor-momery + memoryOverhead不能大于集群内存
b.该问题的原因是因为OS层面虚拟内存分配导致,物理内存没有占用多少,但检查虚拟内存的时候却发现OOM,因此可以通过关闭虚拟内存检查来解决该问题,yarn.nodemanager.vmem-check-enabled=false 将虚拟内存检测设置为false

posted on   嘣嘣嚓  阅读(962)  评论(0编辑  收藏  举报

编辑推荐:
· 记一次.NET内存居高不下排查解决与启示
· 探究高空视频全景AR技术的实现原理
· 理解Rust引用及其生命周期标识(上)
· 浏览器原生「磁吸」效果!Anchor Positioning 锚点定位神器解析
· 没有源码,如何修改代码逻辑?
阅读排行:
· 分享4款.NET开源、免费、实用的商城系统
· 全程不用写代码,我用AI程序员写了一个飞机大战
· MongoDB 8.0这个新功能碉堡了,比商业数据库还牛
· 白话解读 Dapr 1.15:你的「微服务管家」又秀新绝活了
· 记一次.NET内存居高不下排查解决与启示

导航

< 2025年3月 >
23 24 25 26 27 28 1
2 3 4 5 6 7 8
9 10 11 12 13 14 15
16 17 18 19 20 21 22
23 24 25 26 27 28 29
30 31 1 2 3 4 5
点击右上角即可分享
微信分享提示