Member since
03-21-2016
7
Posts
5
Kudos Received
2
Solutions
My Accepted Solutions
Title | Views | Posted |
---|---|---|
1727 | 05-12-2016 10:01 PM | |
8636 | 03-22-2016 09:45 PM |
05-12-2016
10:01 PM
1 Kudo
It's a known issue for HDP 2.4 release, BUG-51292. And there is no workaround....
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05-12-2016
06:42 PM
I'm using exactly the same broker list and topics in both command. So I think that won't be the cause.
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05-11-2016
09:03 PM
I'm testing spark streaming from Kafka code from Spark example in HDP 2.4 and Spark 1.6. I tried KafkaWordCount.scala example successful with `$ bin/run-example org.apache.spark.examples.streaming.KafkaWordCount zoo01,zoo02,zoo03 my-consumer-group topic1,topic2 1` But DirectKafkaWordCount.scala failed with below query and error bin/run-example streaming.DirectKafkaWordCount broker1-host:port,broker2-host:port topic1,topic2 16/05/11 13:52:02 INFO SimpleConsumer: Reconnect due to socket error: java.io.EOFException: Received -1 when reading from channel, socket has likely been closed.
org.apache.spark.SparkException: java.io.EOFException: Received -1 when reading from channel, socket has likely been closed.
at org.apache.spark.streaming.kafka.KafkaCluster$anonfun$checkErrors$1.apply(KafkaCluster.scala:366)
at org.apache.spark.streaming.kafka.KafkaCluster$anonfun$checkErrors$1.apply(KafkaCluster.scala:366)
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Labels:
- Labels:
-
Apache Kafka
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Apache Spark
03-22-2016
09:45 PM
1 Kudo
Finally figure it out by myself. I need to setup my hortonworks Spark as master server, and use my intellij dev environment as slave to connect hdp. Just run ./sbin/start-master.sh in hdp as this link.
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03-22-2016
05:03 PM
1 Kudo
@azeltov I was using VMplayer 6.0 bridged network. To set up port forwarding, I switch to NAT network and add an entry "7077 = 192.168.159.129:7077"to vmnetnat.conf seems doesn't work. How should I do port forwarding?
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03-22-2016
05:00 PM
1 Kudo
@Jitendra Yadav I cannot telnet myhostname 7077 using PuTTy while ssh myhostname 22 working. It not seems like a fireware issue since I install vmplayer in my desktop. For spark UI, I can login spark history server by myhostname:18080, but attempt to connect myhostname:7077 alway get refused. What should I do?
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03-22-2016
12:59 AM
1 Kudo
I have a hortonwork sandbox 2.4 with spark 1.6 set up. Then I create Intellij spark development environment in windows using hdp spark jar and scala 2.10.5. So both spark and scala version are matched between my windows and hdp environment as indicated here. And my Intellij dev environment works with local as Master. Then I'm trying to connect hdp in windows using below code val sparkConf = new SparkConf()
.setAppName("spark-word-count")
.setMaster("spark://10.33.241.160:7077") And I get below error information and have no clue to resolve it. Please help! 6/03/21 16:27:40 INFO SparkUI: Started SparkUI at http://10.33.240.126:4040
16/03/21 16:27:40 INFO AppClient$ClientEndpoint: Connecting to master spark://10.33.241.160:7077...
16/03/21 16:27:41 WARN AppClient$ClientEndpoint: Failed to connect to master 10.33.241.160:7077
java.io.IOException: Failed to connect to /10.33.241.160:7077
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:216)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:167)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:200)
at org.apache.spark.rpc.netty.Outbox$anon$1.call(Outbox.scala:187)
at org.apache.spark.rpc.netty.Outbox$anon$1.call(Outbox.scala:183)
at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:334)
at java.util.concurrent.FutureTask.run(FutureTask.java:166)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:722)
Caused by: java.net.ConnectException: Connection refused: no further information: /10.33.241.160:7077
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:692)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224)
at io.netty.channel.nio.AbstractNioChannel$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$2.run(SingleThreadEventExecutor.java:111)
... 1 more
16/03/21 16:28:40 ERROR MapOutputTrackerMaster: Error communicating with MapOutputTracker
java.lang.InterruptedException
at java.util.concurrent.locks.AbstractQueuedSynchronizer.tryAcquireSharedNanos(AbstractQueuedSynchronizer.java:1325)
at scala.concurrent.impl.Promise$DefaultPromise.tryAwait(Promise.scala:208)
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:218)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
at scala.concurrent.Await$anonfun$result$1.apply(package.scala:107)
at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53)
at scala.concurrent.Await$.result(package.scala:107)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:101)
at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:77)
at org.apache.spark.MapOutputTracker.askTracker(MapOutputTracker.scala:110)
at org.apache.spark.MapOutputTracker.sendTracker(MapOutputTracker.scala:120)
at org.apache.spark.MapOutputTrackerMaster.stop(MapOutputTracker.scala:462)
at org.apache.spark.SparkEnv.stop(SparkEnv.scala:93)
at org.apache.spark.SparkContext$anonfun$stop$12.apply$mcV$sp(SparkContext.scala:1756)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1229)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1755)
at org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend.dead(SparkDeploySchedulerBackend.scala:127)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint.markDead(AppClient.scala:264)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint$anon$2$anonfun$run$1.apply$mcV$sp(AppClient.scala:134)
at org.apache.spark.util.Utils$.tryOrExit(Utils.scala:1163)
at org.apache.spark.deploy.client.AppClient$ClientEndpoint$anon$2.run(AppClient.scala:129)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
at java.util.concurrent.FutureTask$Sync.innerRunAndReset(FutureTask.java:351)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:178)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
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:722)
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Labels:
- Labels:
-
Apache Spark