I'm trying to consume messages from RabbitMQ in Spark Streaming following this answer: https://stackoverflow.com/a/38172737/1344854. I'm failing with IllegalArgumentException and I don't know why.
6/09/05 13:23:22 ERROR ReceiverTracker: Deregistered receiver for stream 0: Error starting receiver 0 - java.lang.IllegalArgumentException: ssl://user:password#bunny.cloudamqp.com:8883/vhost
at org.eclipse.paho.client.mqttv3.MqttConnectOptions.validateURI(MqttConnectOptions.java:458)
at org.eclipse.paho.client.mqttv3.MqttAsyncClient.<init>(MqttAsyncClient.java:273)
at org.eclipse.paho.client.mqttv3.MqttAsyncClient.<init>(MqttAsyncClient.java:167)
at org.eclipse.paho.client.mqttv3.MqttClient.<init>(MqttClient.java:224)
at org.apache.spark.streaming.mqtt.MQTTReceiver.onStart(MQTTInputDStream.scala:71)
at org.apache.spark.streaming.receiver.ReceiverSupervisor.startReceiver(ReceiverSupervisor.scala:148)
at org.apache.spark.streaming.receiver.ReceiverSupervisor.start(ReceiverSupervisor.scala:130)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:575)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:565)
at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1992)
at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1992)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
I tried passing various combinations of brokerUrl argument to the MQTTUtils.createStream constructor including tcp:
tcp://user:password#bunny.cloudamqp.com:1883/vhost
Why is it failing to validate and how to fix it?
Related
Cassandra is giving digest mismatch error. Restarting service on all nodes isn't helping.
ERROR 10:55:11 Exception in thread Thread[HintsDispatcher:2,1,main]
org.apache.cassandra.io.FSReadError: java.io.IOException: Digest mismatch exception
at org.apache.cassandra.hints.HintsReader$HintsIterator.computeNext(HintsReader.java:199) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsReader$HintsIterator.computeNext(HintsReader.java:164) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.utils.AbstractIterator.hasNext(AbstractIterator.java:47) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsDispatcher.sendHints(HintsDispatcher.java:157) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsDispatcher.sendHintsAndAwait(HintsDispatcher.java:139) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsDispatcher.dispatch(HintsDispatcher.java:123) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsDispatcher.dispatch(HintsDispatcher.java:95) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsDispatchExecutor$DispatchHintsTask.deliver(HintsDispatchExecutor.java:268) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsDispatchExecutor$DispatchHintsTask.dispatch(HintsDispatchExecutor.java:251) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsDispatchExecutor$DispatchHintsTask.dispatch(HintsDispatchExecutor.java:229) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsDispatchExecutor$DispatchHintsTask.run(HintsDispatchExecutor.java:208) ~[apache-cassandra-3.0.14.jar:3.0.14]
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) ~[na:1.8.0_131]
at java.util.concurrent.FutureTask.run(FutureTask.java:266) ~[na:1.8.0_131]
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) ~[na:1.8.0_131]
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) [na:1.8.0_131]
at org.apache.cassandra.concurrent.NamedThreadFactory.lambda$threadLocalDeallocator$0(NamedThreadFactory.java:79) [apache-cassandra-3.0.14.jar:3.0.14]
at java.lang.Thread.run(Thread.java:748) ~[na:1.8.0_131]
Caused by: java.io.IOException: Digest mismatch exception
at org.apache.cassandra.hints.HintsReader$HintsIterator.computeNextInternal(HintsReader.java:216) ~[apache-cassandra-3.0.14.jar:3.0.14]
at org.apache.cassandra.hints.HintsReader$HintsIterator.computeNext(HintsReader.java:190) ~[apache-cassandra-3.0.14.jar:3.0.14]
... 16 common frames omitted
After some digging I found this https://issues.apache.org/jira/browse/CASSANDRA-13696 and I think I need to delete hintfiles so nodes can come to a consistent state, but cassandra is running in DCOS/mesosphere and I am not able to connect nodetool to truncate hintfiles
Any way I can delete hintfiles? Or any other way to make cluster consistent? Thanks in Advance.
Your files are probably getting corrupted.
I would try to keep your data in mount points managed by something like Rex-Ray
I have a 24x7 streaming job , which is running very well for first 44 hrs , after that suddenly all the executor is removed from the cluster and giving the error
java.net.BindException: Cannot assign requested address
at sun.nio.ch.Net.connect0(Native Method)
at sun.nio.ch.Net.connect(Net.java:465)
at sun.nio.ch.Net.connect(Net.java:457)
at sun.nio.ch.SocketChannelImpl.connect(SocketChannelImpl.java:670)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:192)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:530)
at org.apache.hadoop.hdfs.DFSClient.newConnectedPeer(DFSClient.java:3519)
at org.apache.hadoop.hdfs.BlockReaderFactory.nextTcpPeer(BlockReaderFactory.java:840)
at org.apache.hadoop.hdfs.BlockReaderFactory.getRemoteBlockReaderFromTcp(BlockReaderFactory.java:755)
at org.apache.hadoop.hdfs.BlockReaderFactory.build(BlockReaderFactory.java:376)
at org.apache.hadoop.hdfs.DFSInputStream.blockSeekTo(DFSInputStream.java:662)
at org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy(DFSInputStream.java:889)
at org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:942)
at org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:742)
at java.io.FilterInputStream.read(FilterInputStream.java:83)
at parquet.bytes.BytesUtils.readIntLittleEndian(BytesUtils.java:66)
at parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:419)
at parquet.hadoop.ParquetFileReader$2.call(ParquetFileReader.java:238)
at parquet.hadoop.ParquetFileReader$2.call(ParquetFileReader.java:234)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
[2017-01-18 03:11:15,943] WARN Failed to connect to /hostname:50010 for block, add to deadNodes and continue. java.net.BindException: Cannot assign requested address (org.apache.hadoop.hdfs.DFSClient)
java.net.BindException: Cannot assign requested address
at sun.nio.ch.Net.connect0(Native Method)
at sun.nio.ch.Net.connect(Net.java:465)
at sun.nio.ch.Net.connect(Net.java:457)
at sun.nio.ch.SocketChannelImpl.connect(SocketChannelImpl.java:670)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:192)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:530)
at org.apache.hadoop.hdfs.DFSClient.newConnectedPeer(DFSClient.java:3519)
at org.apache.hadoop.hdfs.BlockReaderFactory.nextTcpPeer(BlockReaderFactory.java:840)
at org.apache.hadoop.hdfs.BlockReaderFactory.getRemoteBlockReaderFromTcp(BlockReaderFactory.java:755)
at org.apache.hadoop.hdfs.BlockReaderFactory.build(BlockReaderFactory.java:376)
at org.apache.hadoop.hdfs.DFSInputStream.blockSeekTo(DFSInputStream.java:662)
at org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy(DFSInputStream.java:889)
at org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:942)
at org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:742)
at java.io.FilterInputStream.read(FilterInputStream.java:83)
at parquet.bytes.BytesUtils.readIntLittleEndian(BytesUtils.java:66)
at parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:419)
at parquet.hadoop.ParquetFileReader$2.call(ParquetFileReader.java:238)
at parquet.hadoop.ParquetFileReader$2.call(ParquetFileReader.java:234)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
i am doing so many join operations inside the streaming and also i can see that shuffle is increasing every batch not clearing out. Also i am not using any cache() operations in it. I tried setting spark.cleaner.ttl but no imapact is seen. I have attached the executor section of spark ui.
What will be the reason for this behaviour? what i should do to overcome this ?
6
I tried to implement what is explained here. It is working when i keep number of partition in custom partition equal to one but when i change this keep any other value it gives out array out of bound exception
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 6, deenbandhu): java.lang.ArrayIndexOutOfBoundsException: -2
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:920)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:918)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:918)
at DataSetCreation$.main(CreateDataSet.scala:100)
at DataSetCreation.main(CreateDataSet.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.ArrayIndexOutOfBoundsException: -2
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:151)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
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)
I am unable to figure it out what is causing this error.
Thanks in advance
I found the issue in my Custom partitoner when calculating hashcode and getting partition number it is giving negative number and hence giving array out of bound error now i have taken the absolute value and it is working fine now.
I'm having issues with the longevity of Spark-Kinesis Streaming application running on spark standalone cluster manager. The program runs for around 50 hours and stops receiving data from kinesis without giving any valid error why it stopped. But if i restart the application, it works for another day and half or so.
I'm seeing whole lot of errors during the program execution. I'm not sure this is the related to unexpected stoppage of events. Because these errors are there in logs even when the spark application is working fine.
There is no error specific to stoppage in driver or executor.Also I checked if there is any out of memory error but I was not able to spot in the logs. Could you please help me understand what are these error message means? Is this having anything to do with the longevity? Where do you think i should debug to understand whats happening with this?
2016-04-15 13:32:19 INFO KinesisRecordProcessor:58 - Shutdown: Shutting down workerId ip-10-205-1-150.us-west-2.compute.internal:6394789f-acb9-4702-8ea2-c2a3637d925a with reason ZOMBIE
2016-04-15 13:32:19 ERROR ShutdownTask:123 - Application exception.
java.lang.NullPointerException
at java.util.concurrent.ConcurrentHashMap.hash(ConcurrentHashMap.java:333)
at java.util.concurrent.ConcurrentHashMap.remove(ConcurrentHashMap.java:1175)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.removeCheckpointer(KinesisCheckpointer.scala:66)
at org.apache.spark.streaming.kinesis.KinesisReceiver.removeCheckpointer(KinesisReceiver.scala:249)
at org.apache.spark.streaming.kinesis.KinesisRecordProcessor.shutdown(KinesisRecordProcessor.scala:124)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.V1ToV2RecordProcessorAdapter.shutdown(V1ToV2RecordProcessorAdapter.java:48)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.ShutdownTask.call(ShutdownTask.java:94)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.MetricsCollectingTaskDecorator.call(MetricsCollectingTaskDecorator.java:48)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.MetricsCollectingTaskDecorator.call(MetricsCollectingTaskDecorator.java:23)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
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)
2016-04-15 13:32:19 ERROR ShutdownTask:123 - Application exception.
java.lang.NullPointerException
at java.util.concurrent.ConcurrentHashMap.hash(ConcurrentHashMap.java:333)
at java.util.concurrent.ConcurrentHashMap.remove(ConcurrentHashMap.java:1175)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.removeCheckpointer(KinesisCheckpointer.scala:66)
at org.apache.spark.streaming.kinesis.KinesisReceiver.removeCheckpointer(KinesisReceiver.scala:249)
at org.apache.spark.streaming.kinesis.KinesisRecordProcessor.shutdown(KinesisRecordProcessor.scala:124)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.V1ToV2RecordProcessorAdapter.shutdown(V1ToV2RecordProcessorAdapter.java:48)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.ShutdownTask.call(ShutdownTask.java:94)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.MetricsCollectingTaskDecorator.call(MetricsCollectingTaskDecorator.java:48)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.MetricsCollectingTaskDecorator.call(MetricsCollectingTaskDecorator.java:23)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
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)
016-04-15 13:33:12 INFO LeaseRenewer:235 - Worker ip-10-205-1-151.us-west-2.compute.internal:188bd3f5-095b-405f-ac9f-b7eff11e16d1 lost lease with key shardId-000000000046 - discovered during update
2016-04-15 13:33:12 WARN MetricsHelper:67 - No metrics scope set in thread RecurringTimer - Kinesis Checkpointer - Worker ip-10-205-1-151.us-west-2.compute.internal:188bd3f5- 095b-405f-ac9f-b7eff11e16d1, getMetricsScope returning NullMetricsScope.
2016-04-15 13:33:12 ERROR KinesisRecordProcessor:95 - ShutdownException: Caught shutdown exception, skipping checkpoint.
com.amazonaws.services.kinesis.clientlibrary.exceptions.ShutdownException: Can't update checkpoint - instance doesn't hold the lease for this shard
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.KinesisClientLibLeaseCoordinator.setCheckpoint(KinesisClientLibLeaseCoordinator.java:120)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.RecordProcessorCheckpointer.advancePosition(RecordProcessorCheckpointer.java:216)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.RecordProcessorCheckpointer.checkpoint(RecordProcessorCheckpointer.java:137)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.RecordProcessorCheckpointer.checkpoint(RecordProcessorCheckpointer.java:103)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1$$anonfun$apply$1.apply$mcV$sp(KinesisCheckpointer.scala:81)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1$$anonfun$apply$1.apply(KinesisCheckpointer.scala:81)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1$$anonfun$apply$1.apply(KinesisCheckpointer.scala:81)
at scala.util.Try$.apply(Try.scala:161)
at org.apache.spark.streaming.kinesis.KinesisRecordProcessor$.retryRandom(KinesisRecordProcessor.scala:145)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1.apply(KinesisCheckpointer.scala:81)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1.apply(KinesisCheckpointer.scala:75)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.checkpoint(KinesisCheckpointer.scala:75)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.org$apache$spark$streaming$kinesis$KinesisCheckpointer$$checkpointAll(KinesisCheckpointer.scala:103)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$1.apply$mcVJ$sp(KinesisCheckpointer.scala:117)
at org.apache.spark.streaming.util.RecurringTimer.triggerActionForNextInterval(RecurringTimer.scala:94)
at org.apache.spark.streaming.util.RecurringTimer.org$apache$spark$streaming$util$RecurringTimer$$loop(RecurringTimer.scala:106)
at org.apache.spark.streaming.util.RecurringTimer$$anon$1.run(RecurringTimer.scala:29)
2016-04-15 13:33:12 WARN KinesisCheckpointer:91 - Failed to checkpoint shardId shardId-000000000046 to DynamoDB.
com.amazonaws.services.kinesis.clientlibrary.exceptions.ShutdownException: Can't update checkpoint - instance doesn't hold the lease for this shard
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.KinesisClientLibLeaseCoordinator.setCheckpoint(KinesisClientLibLeaseCoordinator.java:120)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.RecordProcessorCheckpointer.advancePosition(RecordProcessorCheckpointer.java:216)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.RecordProcessorCheckpointer.checkpoint(RecordProcessorCheckpointer.java:137)
at com.amazonaws.services.kinesis.clientlibrary.lib.worker.RecordProcessorCheckpointer.checkpoint(RecordProcessorCheckpointer.java:103)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1$$anonfun$apply$1.apply$mcV$sp(KinesisCheckpointer.scala:81)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1$$anonfun$apply$1.apply(KinesisCheckpointer.scala:81)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1$$anonfun$apply$1.apply(KinesisCheckpointer.scala:81)
at scala.util.Try$.apply(Try.scala:161)
at org.apache.spark.streaming.kinesis.KinesisRecordProcessor$.retryRandom(KinesisRecordProcessor.scala:145)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1.apply(KinesisCheckpointer.scala:81)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$checkpoint$1.apply(KinesisCheckpointer.scala:75)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.checkpoint(KinesisCheckpointer.scala:75)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.org$apache$spark$streaming$kinesis$KinesisCheckpointer$$checkpointAll(KinesisCheckpointer.scala:103)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer$$anonfun$1.apply$mcVJ$sp(KinesisCheckpointer.scala:117)
at org.apache.spark.streaming.util.RecurringTimer.triggerActionForNextInterval(RecurringTimer.scala:94)
at org.apache.spark.streaming.util.RecurringTimer.org$apache$spark$streaming$util$RecurringTimer$$loop(RecurringTimer.scala:106)
at org.apache.spark.streaming.util.RecurringTimer$$anon$1.run(RecurringTimer.scala:29)
2016-04-15 13:33:12 INFO LeaseRenewer:116 - Worker ip-10-205-1-151.us-west-2.compute.internal:188bd3f5-095b-405f-ac9f-b7eff11e16d1 lost lease with key shardId-000000000046
2016-04-15 13:33:12 INFO MemoryStore:58 - Block input-2-1460727103359 stored as values in memory (estimated size 120.3 KB, free 171.8 MB)
I am running a spark streaming application with the input source as Kafka. The version of spark is 1.4.0.
My application runs fine under, but now when I enable checkpointing, run the job and then restart the job to see if check-pointing is working properly I get the following flooded into the logs and the job halts.
Could you help me in resolving this issue. Please let me know if any other information is needed. Basically I want to add the checkpointing feature to my spark streaming application.
15/10/30 13:23:00 INFO TorrentBroadcast: Started reading broadcast variable 4
java.io.IOException: org.apache.spark.SparkException: Failed to get broadcast_4_piece0 of broadcast_4
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1257)
at org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:165)
at org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64)
at org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64)
at org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:88)
at com.toi.columbia.aggregate.util.CalendarUtil.isRecordCassandraInsertableV1(CalendarUtil.java:103)
at com.toi.columbia.aggregate.stream.v1.AdvPublisherV1$3.call(AdvPublisherV1.java:124)
at com.toi.columbia.aggregate.stream.v1.AdvPublisherV1$3.call(AdvPublisherV1.java:110)
at org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$fn$1$1.apply(JavaDStreamLike.scala:172)
at org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$fn$1$1.apply(JavaDStreamLike.scala:172)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at com.datastax.spark.connector.util.CountingIterator.hasNext(CountingIterator.scala:10)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at com.datastax.spark.connector.writer.TableWriter.measureMaxInsertSize(TableWriter.scala:89)
at com.datastax.spark.connector.writer.TableWriter.com$datastax$spark$connector$writer$TableWriter$$optimumBatchSize(TableWriter.scala:107)
at com.datastax.spark.connector.writer.TableWriter$$anonfun$write$1.apply(TableWriter.scala:133)
at com.datastax.spark.connector.writer.TableWriter$$anonfun$write$1.apply(TableWriter.scala:127)
at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$withSessionDo$1.apply(CassandraConnector.scala:98)
at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$withSessionDo$1.apply(CassandraConnector.scala:97)
at com.datastax.spark.connector.cql.CassandraConnector.closeResourceAfterUse(CassandraConnector.scala:149)
at com.datastax.spark.connector.cql.CassandraConnector.withSessionDo(CassandraConnector.scala:97)
at com.datastax.spark.connector.writer.TableWriter.write(TableWriter.scala:127)
at com.datastax.spark.connector.streaming.DStreamFunctions$$anonfun$saveToCassandra$1$$anonfun$apply$1.apply(DStreamFunctions.scala:26)
at com.datastax.spark.connector.streaming.DStreamFunctions$$anonfun$saveToCassandra$1$$anonfun$apply$1.apply(DStreamFunctions.scala:26)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63)
at org.apache.spark.scheduler.Task.run(Task.scala:70)
at org.apache.spark.executor.Executor$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)
Caused by: org.apache.spark.SparkException: Failed to get broadcast_4_piece0 of broadcast_4
at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1$$anonfun$2.apply(TorrentBroadcast.scala:138)
at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1$$anonfun$2.apply(TorrentBroadcast.scala:138)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply$mcVI$sp(TorrentBroadcast.scala:137)
at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:120)
at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:120)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.broadcast.TorrentBroadcast.org$apache$spark$broadcast$TorrentBroadcast$$readBlocks(TorrentBroadcast.scala:120)
at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:175)
at org.apache.spark.u
maybe you forgot to increase the spark.cleaner.ttl so the task gets cleaned.
see here https://issues.apache.org/jira/browse/SPARK-5594
I believe you are creating the broadcast variables inside
JavaStreamingContextFactory factory = new JavaStreamingContextFactory() {}
Try creating the broadcast variables outside this overridden method.
As is clear from you exception - the broadcast variables are not being intitialized when you restart your chekpointed application.
cheers!