Intellij connect hortonwork spark remotely failed - apache-spark

Question

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
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)

Answer 1

It turns out I need to setup my hortonworks Spark as master server every time server restart. Then use my intellij dev environment to connect with hdp as slave. Just run ./sbin/start-master.sh in hdp as this link.