文档首页/
MapReduce服务 MRS/
组件操作指南(普通版)/
使用Spark2x(MRS 3.x及之后版本)/
Spark2x常见问题/
Spark Core/
网络连接超时导致FetchFailedException
更新时间:2022-09-30 GMT+08:00
网络连接超时导致FetchFailedException
问题
在380节点的大集群上,运行29T数据量的HiBench测试套中ScalaSort测试用例,使用以下关键配置(--executor-cores 4)出现如下异常:
org.apache.spark.shuffle.FetchFailedException: Failed to connect to /192.168.114.12:23242
at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:321)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:306)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:51)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:217)
at org.apache.spark.shuffle.hash.HashShuffleReader.read(HashShuffleReader.scala:102)
at org.apache.spark.rdd.ShuffledRDD.compute(ShuffledRDD.scala:90)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:301)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:265)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:301)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:265)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:301)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:265)
at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:87)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:301)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:265)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:87)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: Failed to connect to /192.168.114.12:23242
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:167)
at org.apache.spark.network.netty.NettyBlockTransferService$$anon$1.createAndStart(NettyBlockTransferService.scala:91)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:140)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.access$200(RetryingBlockFetcher.java:43)
at org.apache.spark.network.shuffle.RetryingBlockFetcher$1.run(RetryingBlockFetcher.java:170)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
... 3 more
Caused by: java.net.ConnectException: Connection timed out: /192.168.114.12:23242
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:289)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
... 1 more
回答
在运行应用程序时,使用Executor参数“--executor-cores 4”,单进程中并行度高导致IO非常繁忙,以至于任务运行缓慢。
16/02/26 10:04:53 INFO TaskSetManager: Finished task 2139.0 in stage 1.0 (TID 151149) in 376455 ms on 10-196-115-2 (694/153378)
单个任务运行时间超过6分钟,从而导致连接超时问题,最终使得任务失败。
将参数中的核数设置为1,“--executor-cores 1”,任务正常完成,单个任务处理时间在合理范围之内(15秒左右)。
16/02/29 02:24:46 INFO TaskSetManager: Finished task 59564.0 in stage 1.0 (TID 208574) in 15088 ms on 10-196-115-6 (59515/153378)
因此,处理这类网络超时任务,可以减少单个Executor的核数来规避该类问题。
父主题: Spark Core