Spark任务偶现Task卡住很长时间导致Stage整体耗时长

原始文章链接：https://alphablacktan.github.io/bigdata/2018/08/13/Spark任务偶现Task卡住很长时间导致Stage整体耗时长/

问题现象

提交大量Spark任务，概率性出现个别Task卡住一段时间，进而导致Stage整体耗时开销异常。

问题分析

采样Job836

异常Stage2249 -> 卡住Task8：

对应Executor日志：

...
INFO | [Executor task launch worker-78] | Running task 8.0 in stage 2249.0 (TID 222920) | org.apache.spark.Logging$class.logInfo(Logging.scala:59)
ERROR | [shuffle-client-1] | Connection is dead; please adjust spark.network.timeout if this is wrong | org.apache.spark.network.server.TransportChannelHandler.userEventTriggered(TransportChannelHandler.java:128)
ERROR | [shuffle-client-1] | Still have 2 requests outstanding when connection form /10.12.122.244:27337 us closed | org.apache.spark.network.server.TransportChannelHandler.channelUnregistered(TransportChannelHandler.java:102)
INFO | [shuffle-client-1] | Retrying fetch (1/3) for 1 outstanding blocks after 5000 ms | org.apache.spark.network.shuffle.RetryingBlockFetcher.initiateRetry(RetryingBlockFetcher.java:163)
ERROR | [shuffle-client-1] | Failed while starting block fetches | org.apache.spark.network.shuffle.OneForOneBlockFetcher$1.onFailure(OneForOneBlockFetcher.java:151)
java.io.IOException: Connection from /10.12.122.244:27337 closed
	at org.apache.spark.network.server.TransportChannelHandler.channelUnregistered(TransportChannelHandler.java:104)
	at org.apache.spark.network.server.TransportChannelHandler.channelUnregistered(TransportChannelHandler.java:94)
	...
INFO | [shuffle-client-1] | Retrying fetch (1/3) for 1 outstanding blocks after 5000 ms | org.apache.spark.network.shuffle.RetryingBlockFetcher.initiateRetry(RetryingBlockFetcher.java:163)
...

查看主机10.12.122.244的端口27337发现为NodeManager。查看其内存开销发现其内存已经用尽，进一步查看其GC日志，发现NodeManager存在频繁的长时间Full GC，进而导致其在GC阶段长时间无法响应Executor的请求，进而导致Executor卡住。

问题解决方案

调整NodeManager堆内存，适应业务场景开销。