Spark:找不到CoarseGrainedScheduler [英] Spark: Could not find CoarseGrainedScheduler

问题描述

不确定运行几小时后运行我的Spark作业的异常是什么导致的.

Am not sure what's causing this exception running my Spark job after running for some few hours.

正在运行Spark 2.0.2

Am running Spark 2.0.2

任何调试技巧?

2016-12-27 03:11:22,199 [shuffle-server-3] ERROR org.apache.spark.network.server.TransportRequestHandler - Error while invoking RpcHandler#receive() for one-way message.
org.apache.spark.SparkException: Could not find CoarseGrainedScheduler.
    at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:154)
    at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:134)
    at org.apache.spark.rpc.netty.NettyRpcHandler.receive(NettyRpcEnv.scala:571)
    at org.apache.spark.network.server.TransportRequestHandler.processOneWayMessage(TransportRequestHandler.java:180)
    at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:109)
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:119)
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
    at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
    at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
    at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
    at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:85)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
    at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846)
    at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
    at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
    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(SingleThreadEve

推荐答案

是的，现在我知道了该隐式异常的含义，执行器由于超出了容器内存阈值而被杀死.
有几种可能的原因，但首要原因是检查您的工作(例如重新分区)或尝试向集群中添加更多的节点/执行器.

Yeah now I know the meaning of that cryptic exception, the executor got killed because it exceeds the container memory threshold.
There are couple of reasons that could happen but the first culprit is to check your job (e.g. repartition) or try adding more nodes/executors to your cluster.

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