I am getting below error on Gridgain cluster and cluster is not coming up.
Any idea?
Thread [name="main", id=1, state=WAITING, blockCnt=1, waitCnt=16]
Lock [object=java.util.concurrent.CountDownLatch$Sync#5d0db03c, ownerName=null, ownerId=-1]
at sun.misc.Unsafe.park(Native Method)
at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
at java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedInterruptibly(AbstractQueuedSynchronizer.java:997)
at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireSharedInterruptibly(AbstractQueuedSynchronizer.java:1304)
at java.util.concurrent.CountDownLatch.await(CountDownLatch.java:231)
at o.a.i.startup.cmdline.CommandLineStartup.main(CommandLineStartup.java:323)
[09:48:08,150][WARNING][client-connector-#82][CacheDiagnosticManager] Page locks dump:
[09:48:08,150][SEVERE][client-connector-#82][] JVM will be halted immediately due to the failure: [failureCtx=FailureContext [type=CRITICAL_ERROR, err=class o.a.i.i.processors.cache.persistence.StorageException: Failed to initialize partition file: /database/ignite/ignite_data/db/myIgnite_Node1/cache-customerAddressCache/part-728.bin]]
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I need help please getting spark working in windows cluster of 3 nodes. I am able to download and configure and run the master node and worker nodes. the worker nodes are registered successfully with the master. Im able to see both worker nodes in the Master UI. When I try to submit a job using:
spark-submit --master spark://IP:7077 hello_world.py
Spark continuously try to start multiple executors but the all failed with code exit 1 and it doesnt stop until I kill it. when I check the log in the UI for each worker Im seeing the following error:
Using Spark's default log4j profile: org/apache/spark/log4j2-defaults.properties
Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1894)
at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:61)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.run(CoarseGrainedExecutorBackend.scala:424)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.main(CoarseGrainedExecutorBackend.scala:413)
at org.apache.spark.executor.CoarseGrainedExecutorBackend.main(CoarseGrainedExecutorBackend.scala)
Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:301)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:102)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.$anonfun$run$9(CoarseGrainedExecutorBackend.scala:444)
at scala.runtime.java8.JFunction1$mcVI$sp.apply(JFunction1$mcVI$sp.java:23)
at scala.collection.TraversableLike$WithFilter.$anonfun$foreach$1(TraversableLike.scala:985)
at scala.collection.immutable.Range.foreach(Range.scala:158)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:984)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.$anonfun$run$7(CoarseGrainedExecutorBackend.scala:442)
at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:62)
at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:61)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1878)
... 4 more
**Caused by: java.io.IOException: Failed to connect to <Master DNS>/<Master IP>:56785
at **org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:288)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:230)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:204)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:202)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:198)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: io.netty.channel.AbstractChannel$AnnotatedConnectException: Connection refused: no further information: <Master DNS>/<Master IP>:56785
Caused by: java.net.ConnectException: Connection refused: no further information
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:715)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:330)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:334)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:710)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:658)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:584)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:496)
at io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:986)
at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.lang.Thread.run(Thread.java:748)
Im using Spark: spark-3.3.1-bin-hadoop3
Please help.
Thanks
The application to run
I have a Spark application that should be tested in both local mode & local-cluster mode, using scalatest.
The local-cluster mode is submitted using this method:
How to scala-test a Spark program under "local-cluster" mode?
The test run successfully, but when terminating the test I got the following error in the log:
22/05/16 17:45:25 ERROR TaskSchedulerImpl: Lost executor 0 on 172.16.224.18: Remote RPC client disassociated. Likely due to containers exceeding thresholds, or network issues. Check driver logs for WARN messages.
22/05/16 17:45:25 ERROR Worker: Failed to launch executor app-20220516174449-0000/2 for Test.
java.lang.IllegalStateException: Shutdown hooks cannot be modified during shutdown.
at org.apache.spark.util.SparkShutdownHookManager.add(ShutdownHookManager.scala:195)
at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:153)
at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:142)
at org.apache.spark.deploy.worker.ExecutorRunner.start(ExecutorRunner.scala:77)
at org.apache.spark.deploy.worker.Worker$$anonfun$receive$1.applyOrElse(Worker.scala:547)
at org.apache.spark.rpc.netty.Inbox.$anonfun$process$1(Inbox.scala:117)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:215)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:102)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:221)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
22/05/16 17:45:25 ERROR Worker: Failed to launch executor app-20220516174449-0000/3 for Test.
java.lang.IllegalStateException: Shutdown hooks cannot be modified during shutdown.
at org.apache.spark.util.SparkShutdownHookManager.add(ShutdownHookManager.scala:195)
at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:153)
at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:142)
at org.apache.spark.deploy.worker.ExecutorRunner.start(ExecutorRunner.scala:77)
at org.apache.spark.deploy.worker.Worker$$anonfun$receive$1.applyOrElse(Worker.scala:547)
at org.apache.spark.rpc.netty.Inbox.$anonfun$process$1(Inbox.scala:117)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:215)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:102)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:221)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
22/05/16 17:45:25 ERROR Worker: Failed to launch executor app-20220516174449-0000/4 for Test.
java.lang.IllegalStateException: Shutdown hooks cannot be modified during shutdown.
at org.apache.spark.util.SparkShutdownHookManager.add(ShutdownHookManager.scala:195)
at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:153)
at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:142)
at org.apache.spark.deploy.worker.ExecutorRunner.start(ExecutorRunner.scala:77)
at org.apache.spark.deploy.worker.Worker$$anonfun$receive$1.applyOrElse(Worker.scala:547)
at org.apache.spark.rpc.netty.Inbox.$anonfun$process$1(Inbox.scala:117)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:215)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:102)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:221)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
22/05/16 17:45:25 ERROR Worker: Failed to launch executor app-20220516174449-0000/5 for Test.
java.lang.IllegalStateException: Shutdown hooks cannot be modified during shutdown.
at org.apache.spark.util.SparkShutdownHookManager.add(ShutdownHookManager.scala:195)
at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:153)
at org.apache.spark.util.ShutdownHookManager$.addShutdownHook(ShutdownHookManager.scala:142)
at org.apache.spark.deploy.worker.ExecutorRunner.start(ExecutorRunner.scala:77)
at org.apache.spark.deploy.worker.Worker$$anonfun$receive$1.applyOrElse(Worker.scala:547)
at org.apache.spark.rpc.netty.Inbox.$anonfun$process$1(Inbox.scala:117)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:215)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:102)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dis
...
It turns out executor 0 was dropped before the SparkContext is stopped, this triggered a violent self-healing reaction from Spark master that tries to repeatedly launch new executors to compensate for the loss. How do I prevent this from happening?
Spark attempts to recover from failed tasks by attempting to run them again. What you can do to avoid this is to set some properties to 1 in
spark.task.maxFailures (default is 4)
spark.stage.maxConsecutiveAttempts (default is 4)
These properties can be set in $SPARK_HOME/conf/spark-defaults.conf or given as options to spark-submit:
spark-submit --conf spark.task.maxFailures=1 --conf spark.stage.maxConsecutiveAttempts=1
or in the Spark context/session configuration before starting the session.
EDIT:
It looks like your executors are lost due to insufficient memory. You could try to increase:
spark.executor.memory
spark.executor.memoryOverhead
spark.memory.offHeap.size with (spark.memory.offHeap.enabled=true)
(see Spark configuration)
The maximum memory size of container to running executor is determined by the sum of spark.executor.memoryOverhead, spark.executor.memory, spark.memory.offHeap.size and spark.executor.pyspark.memory.
I have a Spark (1.4.1) application, running on Yarn, that fails with the following executor log entry:
16/07/21 23:09:08 ERROR executor.CoarseGrainedExecutorBackend: Driver 9.4.136.20:55995 disassociated! Shutting down.
16/07/21 23:09:08 ERROR storage.DiskBlockObjectWriter: Uncaught exception while reverting partial writes to file /dfs1/hadoop/yarn/local/usercache/mitchus/appcache/application_1465987751317_1172/blockmgr-f367f43b-f4c8-4faf-a829-530da30fb040/1c/temp_shuffle_581adb36-1561-4db8-a556-c4ac0e6400ed
java.io.FileNotFoundException: /dfs1/hadoop/yarn/local/usercache/mitchus/appcache/application_1465987751317_1172/blockmgr-f367f43b-f4c8-4faf-a829-530da30fb040/1c/temp_shuffle_581adb36-1561-4db8-a556-c4ac0e6400ed (No such file or directory)
at java.io.FileOutputStream.open0(Native Method)
at java.io.FileOutputStream.open(FileOutputStream.java:270)
at java.io.FileOutputStream.<init>(FileOutputStream.java:213)
at org.apache.spark.storage.DiskBlockObjectWriter.revertPartialWritesAndClose(BlockObjectWriter.scala:189)
at org.apache.spark.util.collection.ExternalSorter.spillToMergeableFile(ExternalSorter.scala:328)
at org.apache.spark.util.collection.ExternalSorter.spill(ExternalSorter.scala:257)
at org.apache.spark.util.collection.ExternalSorter.spill(ExternalSorter.scala:95)
at org.apache.spark.util.collection.Spillable$class.maybeSpill(Spillable.scala:83)
at org.apache.spark.util.collection.ExternalSorter.maybeSpill(ExternalSorter.scala:95)
at org.apache.spark.util.collection.ExternalSorter.maybeSpillCollection(ExternalSorter.scala:240)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:220)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:62)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:70)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Any clues as to what might have gone wrong?
The reason caused by temp shuffle file is deleted. There are many reasons, for one which I met is because the other executor was killed by Yarn. After the executor killed, a SHUT_DOWN signal will be sent to other executors, then the ShutdownHookManager will delete all the temp files which have registered to ShutdownHookManager. That's why you see the error. So you maybe need to check whether there are any ShutdownHookManager called log.
You can try to improve spark.yarn.executor.memoryOverhead.
I am running a spark streaming application with spark version 1.4.0
If I kill the worker (using kill -9) when my job is running, then the worker and executor both on that node dies,but it still shows up in the executors tab of the UI. The number of active tasks sometimes shows as negative on those executors.
Because of this the jobs keep on failing with the following exception
16/04/01 23:54:20 WARN TaskSetManager: Lost task 141.0 in stage 19859.0 (TID 190333, 192.168.33.96): java.io.IOException: Failed to connect to /192.168.33.97:63276
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:193)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:156)
at org.apache.spark.network.netty.NettyBlockTransferService$$anon$1.createAndStart(NettyBlockTransferService.scala:88)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:140)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.access$200(RetryingBlockFetcher.java:43)
at org.apache.spark.network.shuffle.RetryingBlockFetcher$1.run(RetryingBlockFetcher.java:170)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused: /192.168.33.97:63276
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:716)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:208)
at io.netty.channel.nio.AbstractNioChannel$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$2.run(SingleThreadEventExecutor.java:116)
... 1 more
On relaunching the worker a new executor is allocated but the old (dead) executor's entry is still there and the stages fail with "java.io.IOException: Failed to connect to " error.
We have been running Cassandra 1.0.2 in production for many months, with minimal trouble. Lately, we have started to see consistent failures in all nodes, with this error:
ERROR [CompactionExecutor:199] 2013-03-02 00:21:26,179 AbstractCassandraDaemon.java (line 133) Fatal exception in thread Thread[CompactionExecutor:199,1,RMI Runtime]
java.io.IOError: java.io.IOException: Map failed
at org.apache.cassandra.io.util.MmappedSegmentedFile$Builder.createSegments(MmappedSegmentedFile.java:225)
at org.apache.cassandra.io.util.MmappedSegmentedFile$Builder.complete(MmappedSegmentedFile.java:202)
at org.apache.cassandra.io.sstable.SSTableWriter.closeAndOpenReader(SSTableWriter.java:308)
at org.apache.cassandra.db.compaction.CompactionTask.execute(CompactionTask.java:174)
at org.apache.cassandra.db.compaction.CompactionManager$4.call(CompactionManager.java:275)
at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:303)
at java.util.concurrent.FutureTask.run(FutureTask.java:138)
at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)
at java.lang.Thread.run(Thread.java:619)
Caused by: java.io.IOException: Map failed
at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:758)
at org.apache.cassandra.io.util.MmappedSegmentedFile$Builder.createSegments(MmappedSegmentedFile.java:217)
... 9 more
Caused by: java.lang.OutOfMemoryError: Map failed
at sun.nio.ch.FileChannelImpl.map0(Native Method)
at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:755)
... 10 more
INFO [Thread-2] 2013-03-02 00:21:26,222 MessagingService.java (line 488) Shutting down MessageService...
The node dies after this. We remove the oldest data files and start the node again. The node runs for a while, then dies again. This happens for all eight nodes in our ring.
We are using the default compaction strategy (size tiered) and we think it is the best choice for our problem domain.
Q: Why is this happening and what should we do to fix it?