我有一个简单的脚本文件,正在尝试在Spark-shell中执行,该文件类似于此处的教程
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该文件:
/opt/spark-1.3.0-bin-hadoop2.4/bin/spark-shell -i WordCount.scala
我的远程执行者都死于类似于以下的错误:
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
我运行errors.count()命令后,将发生此故障。在我的外壳中,在创建新的SparkContext之后,我看到了以下几行:
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
我猜发生了什么事情,Spark正在将BlockManager的地址记录为localhost:48554,然后将其发送到所有尝试与localhost:48554对话的执行程序,而不是驱动程序的IP地址在端口48554上。为什么是spark使用本地主机作为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,您可以看到我在我的SparkConf中设置的内容。
可能与此JIRA票证有关,尽管这似乎是网络问题。我的网络配置了DNS就很好了。
您可以在调用spark-shell时使用--master参数提供Spark Master地址吗(或添加spark-defaults.conf)。我有一个类似的问题(请参阅我的文章Spark Shell在本地主机上监听而不是配置的IP地址),并且在shell中动态创建上下文时,看起来BlockManager在本地主机上监听。
日志:
使用原始上下文时(在主机名上监听)BlockManagerInfo:在ubuntu64server2:33301的内存中添加了broadcast_1_piece0
创建新上下文时(在localhost上监听)BlockManagerInfo:在localhost:40235的内存中添加了broadcast_1_piece0
我必须连接到Cassandra集群,并能够通过在spark-defaults.conf中提供spark.cassandra.connection.host并在spark shell中导入包com.datastax.spark.connector._进行查询。
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