Spark BlockManager running on localhost - apache-spark

Question

I have a simple script file I am trying to execute in the spark-shell that mimics the tutorial here
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()
My namenode and mesos master are on 172.24.51.171, my ip address is 172.24.51.142. I have these line saved to a file, which I then launch using the command:
/opt/spark-1.3.0-bin-hadoop2.4/bin/spark-shell -i WordCount.scala
My remote executors are all dying with errors similar to the following:
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
This failure happens after I run the errors.count() command. Earlier in my shell, after I create the new SparkContext I see the lines:
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
I guess whats happening is Spark is recording the address of the BlockManager as localhost:48554, which is then getting sent to all the executors who try to talk to their localhosts:48554, instead of the driver's ip address at port 48554. Why is spark using localhost as the address of the BlockManager and not spark.driver.host?
Additional Information
In the Spark Config there is a spark.blockManager.port but no spark.blockManager.host? There is only a spark.driver.host, which you can see I set in my SparkConf.
Possibly related to this JIRA Ticket although that seemed like a network issue. My network is configured with DNS just fine.

Answer 1

Can you try by providing Spark Master address using --master parameter when invoking the spark-shell (or add in spark-defaults.conf). I had a similar issue (see my post Spark Shell Listens on localhost instead of configured IP address) and it looks like BlockManager listens on localhost when the context is dynamically created in the shell.
Logs:
When original context is used (listens on hostname)
BlockManagerInfo: Added broadcast_1_piece0 in memory on ubuntu64server2:33301
When new context is created (listens on localhost)
BlockManagerInfo: Added broadcast_1_piece0 in memory on localhost:40235
I had to connect to a Cassandra cluster and was able to query it by providing spark.cassandra.connection.host in spark-defaults.conf and importing packages com.datastax.spark.connector._ in the spark shell.

Answer 2

Try setting SPARK_LOCAL_IP (on the command line) or spark.local.ip through the sparkConf object.