apache-spark – 在localhost上运行的Spark BlockManager

2019年8月6日 376次阅读

我有一个简单的脚本文件,我试图在模拟教程
here的spark-shell中执行

import org.apache.spark.SparkConf
import org.apache.spark.SparkContext

sc.stop();

val conf = new SparkConf().setAppName("MyApp").setMaster("mesos://zk://172.24.51.171:2181/mesos").set("spark.executor.uri", "hdfs://172.24.51.171:8020/spark-1.3.0-bin-hadoop2.4.tgz").set("spark.driver.host", "172.24.51.142")

val sc2 = new SparkContext(conf)

val file = sc2.textFile("hdfs://172.24.51.171:8020/input/pg4300.txt")

val errors = file.filter(line => line.contains("ERROR"))

errors.count()

我的namenode和mesos master在172.24.51.171上,我的ip地址是172.24.51.142.我将这些行保存到文件中,然后使用以下命令启动：

/opt/spark-1.3.0-bin-hadoop2.4/bin/spark-shell -i WordCount.scala

我的远程执行器都死了,其错误类似于以下内容：

15/04/08 14:30:39 ERROR RetryingBlockFetcher: Exception while beginning fetch of 1 outstanding blocks 
java.io.IOException: Failed to connect to localhost/127.0.0.1:48554
    at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:191)
    at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:156)
    at org.apache.spark.network.netty.NettyBlockTransferService$$anon$1.createAndStart(NettyBlockTransferService.scala:78)
    at org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:140)
    at org.apache.spark.network.shuffle.RetryingBlockFetcher.start(RetryingBlockFetcher.java:120)
    at org.apache.spark.network.netty.NettyBlockTransferService.fetchBlocks(NettyBlockTransferService.scala:87)
    at org.apache.spark.network.BlockTransferService.fetchBlockSync(BlockTransferService.scala:89)
    at org.apache.spark.storage.BlockManager$$anonfun$doGetRemote$2.apply(BlockManager.scala:594)
    at org.apache.spark.storage.BlockManager$$anonfun$doGetRemote$2.apply(BlockManager.scala:592)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.storage.BlockManager.doGetRemote(BlockManager.scala:592)
    at org.apache.spark.storage.BlockManager.getRemoteBytes(BlockManager.scala:586)
    at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.org$apache$spark$broadcast$TorrentBroadcast$$anonfun$$getRemote$1(TorrentBroadcast.scala:126)
    at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1$$anonfun$1.apply(TorrentBroadcast.scala:136)
    at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1$$anonfun$1.apply(TorrentBroadcast.scala:136)
    at scala.Option.orElse(Option.scala:257)
    at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply$mcVI$sp(TorrentBroadcast.scala:136)
    at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:119)
    at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:119)
    at scala.collection.immutable.List.foreach(List.scala:318)
    at org.apache.spark.broadcast.TorrentBroadcast.org$apache$spark$broadcast$TorrentBroadcast$$readBlocks(TorrentBroadcast.scala:119)
    at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:174)
    at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1152)
    at org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:164)
    at org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64)
    at org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64)
    at org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:87)
    at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:58)
    at org.apache.spark.scheduler.Task.run(Task.scala:64)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused: localhost/127.0.0.1:48554
    at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
    at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:739)
    at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:208)
    at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:287)
    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:116)
    ... 1 more

运行errors.count()命令后发生此故障.在我的shell中,在创建新的SparkContext之后,我看到了这些行：

15/04/08 14:31:18 INFO NettyBlockTransferService: Server created on 48554
15/04/08 14:31:18 INFO BlockManagerMaster: Trying to register BlockManager
15/04/08 14:31:18 INFO BlockManagerMasterActor: Registering block manager localhost:48554 with 265.4 MB RAM, BlockManagerId(<driver>, localhost, 48554)
15/04/08 14:31:18 INFO BlockManagerMaster: Registered BlockManager

我想最新发生的事情是Spark将BlockManager的地址记录为localhost：48554,然后将其发送给尝试与其本地主机进行通信的所有执行程序：48554,而不是驱动程序在端口48554处的IP地址.为什么是spark使用localhost作为BlockManager的地址而不是spark.driver.host？

附加信息

>在Spark Config中有一个spark.blockManager.port但没有spark.blockManager.host？只有一个spark.driver.host,你可以在我的SparkConf中看到它.
>可能与JIRA Ticket有关,尽管这似乎是一个网络问题.我的网络配置了DNS就好了.

最佳答案 您可以尝试在调用spark-shell时使用–master参数提供Spark Master地址(或添加spark-defaults.conf).我遇到了类似的问题(请参阅我的文章
Spark Shell Listens on localhost instead of configured IP address),看起来BlockManager在shell中动态创建上下文时会监听localhost.

日志：

>使用原始上下文时(侦听主机名)
 BlockManagerInfo：在ubuntu64server2：33301的内存中添加了broadcast_1_piece0
>创建新上下文时(侦听localhost)
 BlockManagerInfo：在localhost：40235的内存中添加了broadcast_1_piece0

我必须连接到Cassandra集群,并且能够通过在spark-defaults.conf中提供spark.cassandra.connection.host并在spark shell中导入包com.datastax.spark.connector._来查询它.

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