memoryUsed:获取已经使用的内存大小 memoryFree:获取内存池的空闲空间 incrementPoolSize:给内存池扩展delta给定的大小 decrementPoolSize:将内存池缩小delta给定的大小 Spark中一共有两种MemoryPool的具体实现,分别为StorageMemoryPool和ExecutionMemoryPool。StorageMemoryPool是存储体系用到的内存池,而ExecutionMemoryPool则是计...
Spark根据spark.executor.memory+spark.yarn.executor.memoryOverhead的值向RM申请一个容器,当executor运行时使用的内存超过这个限制时,会被yarn kill掉。在spark UI中相应失败的task错误信息为: Container killed by YARN for exceeding memory limits. XXX of YYY physical memory used. Consider boosting spark.yarn....
java.lang.OutOfMemoryError: Java heap space Container killed by YARN for exceeding memory limits. 1*.4 GB of 1* GB physical memory used. shuffle file cannot find, executor lost、 task lost 该类错误一般是由于Heap已达上限,Task需要更多的内存,而又得不到足够的内存而导致。因此,解决方案要从增加...
相信在Yarn上跑过Spark程序的朋友都会碰到过这个问题:Current usage: 12.1 GB of 12 GB physical memory used; 13.9 GB of 48 GB virtual memory used. Killing container。 在同样的参数下,在Spark 1.4上正常运行的程序,在Spark 1.6上运行很容易出现这个问题。Spark在向Yarn申请内存的时候,一共申请了(execuor内...
[pid=3882745,containerID=container_e520_1663584041666_52155_03_000001] is running beyond virtual memory limits. Current usage: 259.8 MB of 1 GB physical memory used; 2.2 GB of 2.1 GB virtual memory used. Killing container. 配置 $SPARK_HOME/bin/spark-submit ...
Container killedbyYARN for exceeding memory limits.1*.4GB of1* GB physical memory used. Considerboostingspark.yarn.executor.memoryOverhead. 基本内容介绍: 1.executor 和 container01.Spark中的 executor 进程是跑在 container 中,所以container的最大内存会直接影响到executor的最大可用内存02.yarn.nodemanager...
Container [xxx] is running beyond virtual memory limits. Current usage: 324 MB of 1 GB physical memory used; 2.3 GB of 2.1 GB virtual memory used. Killing container. 原来是超出了内存的限制,所以改配置文件就可以了,我就顺手改了配置,将yarn.nodemanager.resource.memory-mb的值改为了8192,结果还是...
Diagnostics: Container [pid=5064,containerID=container_e62_1547156777102_0243_02_000001] is running beyond physical memory limits. Current usage: 4.6 GB of 4.5 GB physical memory used; 6.3 GB of 22.5 GB virtual memory used. Killing container. ...
Spark作业中,内存相关进程被终止,out of memory的报错时有发生。常见的报错信息如:ExecutorLostFailure (executor 9 exited caused by one of the running tasks) Reason: Container killed by YARN for exceeding memory limits. 22.1 GB of 22 GB physical memory used. Consider boosting spark.yarn.executor....
Container [xxx] is running beyond virtual memory limits. Current usage: 324 MB of 1 GB physical memory used; 2.3 GB of 2.1 GB virtual memory used. Killing container.原来是超出了内存的限制，所以改配置文件就可以了，我就顺手改了配置，将 yarn.nodemanager.resource.memory-mb 的值...