Modified subject to reflect new error encountered.
Interesting - SPARK-12275 is marked fixed against 1.6.0
On Thu, Jan 21, 2016 at 7:30 AM, Sebastian Piu <sebastian....@gmail.com>
wrote:
> I'm using Spark 1.6.0.
>
> I tried removing Kryo and reverting back to Java Serialisation, and get a
> different error which maybe points in the right direction...
>
> java.lang.AssertionError: assertion failed: No plan for BroadcastHint
> +- InMemoryRelation
> [tradeId#30,tradeVersion#31,agreement#49,counterParty#38], true, 10000,
> StorageLevel(true, true, false, true, 1), Union,
> Some(ingest_all_union_trades)
>
> at scala.Predef$.assert(Predef.scala:179)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:336)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$EquiJoinSelection$.apply(SparkStrategies.scala:105)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:336)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$Aggregation$.apply(SparkStrategies.scala:217)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:47)
> at
> org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:45)
> at
> org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:52)
> at
> org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:52)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:53)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:108)
> at
> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
> at
> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
> at
> org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:125)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> at
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:125)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
> at
> org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:242)
> at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:148)
> at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:139)
> at
> com.hsbc.rsl.spark.streaming.receiver.functions.PersistLevel3WithDataframes.preAggregateL4(PersistLevel3WithDataframes.java:133)
> at
> com.hsbc.rsl.spark.streaming.receiver.functions.PersistLevel3WithDataframes.call(PersistLevel3WithDataframes.java:93)
> at
> com.hsbc.rsl.spark.streaming.receiver.functions.PersistLevel3WithDataframes.call(PersistLevel3WithDataframes.java:27)
> at
> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$3.apply(JavaDStreamLike.scala:335)
> at
> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$3.apply(JavaDStreamLike.scala:335)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:656)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:656)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:50)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:49)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
> at scala.util.Try$.apply(Try.scala:161)
> at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
> at
> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:224)
> at
> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
> at
> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
> at
> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:223)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> 2016-01-21 15:28:32 ERROR RslApp:60 - ERROR executing the application
> java.lang.AssertionError: assertion failed: No plan for BroadcastHint
> +- InMemoryRelation
> [tradeId#30,tradeVersion#31,agreement#49,counterParty#38], true, 10000,
> StorageLevel(true, true, false, true, 1), Union,
> Some(ingest_all_union_trades)
>
> at scala.Predef$.assert(Predef.scala:179)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:336)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$EquiJoinSelection$.apply(SparkStrategies.scala:105)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:336)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
> at
> org.apache.spark.sql.execution.SparkStrategies$Aggregation$.apply(SparkStrategies.scala:217)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:59)
> at
> org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:47)
> at
> org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:45)
> at
> org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:52)
> at
> org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:52)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:53)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:108)
> at
> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
> at
> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
> at
> org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:125)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> at
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:125)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
> at
> org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:242)
> at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:148)
> at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:139)
> at
> com.hsbc.rsl.spark.streaming.receiver.functions.PersistLevel3WithDataframes.preAggregateL4(PersistLevel3WithDataframes.java:133)
> at
> com.hsbc.rsl.spark.streaming.receiver.functions.PersistLevel3WithDataframes.call(PersistLevel3WithDataframes.java:93)
> at
> com.hsbc.rsl.spark.streaming.receiver.functions.PersistLevel3WithDataframes.call(PersistLevel3WithDataframes.java:27)
> at
> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$3.apply(JavaDStreamLike.scala:335)
> at
> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$3.apply(JavaDStreamLike.scala:335)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:656)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:656)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:50)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:49)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
> at
> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
> at scala.util.Try$.apply(Try.scala:161)
> at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
> at
> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:224)
> at
> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
> at
> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
> at
> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:223)
> 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)
>
>
> On Thu, Jan 21, 2016 at 3:17 PM, Ted Yu <yuzhih...@gmail.com> wrote:
>
>> You were using Kryo serialization ?
>>
>> If you switch to Java serialization, your job should run fine.
>>
>> Which Spark release are you using ?
>>
>> Thanks
>>
>> On Thu, Jan 21, 2016 at 6:59 AM, sebastian.piu <sebastian....@gmail.com>
>> wrote:
>>
>>> Hi all,
>>>
>>> I'm trying to work out a problem when using Spark Streaming, currently I
>>> have the following piece of code inside a foreachRDD call:
>>>
>>> Dataframe results = ... //some dataframe created from the incoming rdd -
>>> moderately big, I don't want this to be shuffled
>>> DataFrame t = sqlContext.table("a_temp_cached_table"); //a very small
>>> table
>>> - that might mutate over time
>>> DataFrame x = results.join(*broadcast(t)*, JOIN_COLUMNS_SEQ)
>>> .groupBy("column1").count()
>>> .write()
>>> .mode(SaveMode.Append)
>>> .save("/some-path/");
>>>
>>> The intention of the code above is to distribute the "t" dataframe if
>>> required, but avoid shuffling the "results".
>>>
>>> This works fine when ran on scala-shell / spark-submit, but when ran from
>>> within my executors I get the exception below...
>>>
>>> Any thoughts? If I remove the *broadcast(t)* then it works fine but
>>> where my
>>> big table is shuffled around.
>>>
>>> 2016-01-21 14:47:00 ERROR JobScheduler:95 - Error running job streaming
>>> job
>>> 1453387560000 ms.0
>>> java.lang.ArrayIndexOutOfBoundsException: 8388607
>>> at
>>>
>>> com.esotericsoftware.kryo.util.IdentityObjectIntMap.clear(IdentityObjectIntMap.java:345)
>>> at
>>>
>>> com.esotericsoftware.kryo.util.MapReferenceResolver.reset(MapReferenceResolver.java:47)
>>> at com.esotericsoftware.kryo.Kryo.reset(Kryo.java:804)
>>> at
>>> com.esotericsoftware.kryo.Kryo.writeClassAndObject(Kryo.java:570)
>>> at
>>>
>>> org.apache.spark.serializer.KryoSerializationStream.writeObject(KryoSerializer.scala:194)
>>> at
>>>
>>> org.apache.spark.broadcast.TorrentBroadcast$.blockifyObject(TorrentBroadcast.scala:203)
>>> at
>>>
>>> org.apache.spark.broadcast.TorrentBroadcast.writeBlocks(TorrentBroadcast.scala:102)
>>> at
>>>
>>> org.apache.spark.broadcast.TorrentBroadcast.<init>(TorrentBroadcast.scala:85)
>>> at
>>>
>>> org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast(TorrentBroadcastFactory.scala:34)
>>> at
>>>
>>> org.apache.spark.broadcast.BroadcastManager.newBroadcast(BroadcastManager.scala:63)
>>> at
>>> org.apache.spark.SparkContext.broadcast(SparkContext.scala:1326)
>>> at
>>>
>>> org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$broadcastFuture$1$$anonfun$apply$1.apply(BroadcastHashJoin.scala:91)
>>> at
>>>
>>> org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$broadcastFuture$1$$anonfun$apply$1.apply(BroadcastHashJoin.scala:79)
>>> at
>>>
>>> org.apache.spark.sql.execution.SQLExecution$.withExecutionId(SQLExecution.scala:100)
>>> at
>>>
>>> org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$broadcastFuture$1.apply(BroadcastHashJoin.scala:79)
>>> at
>>>
>>> org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$broadcastFuture$1.apply(BroadcastHashJoin.scala:79)
>>> at
>>>
>>> scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
>>> at
>>>
>>> scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
>>> at
>>>
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>>> at
>>>
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>>> at java.lang.Thread.run(Thread.java:745)
>>> 2016-01-21 14:47:00 ERROR RslApp:60 - ERROR executing the application
>>> java.lang.ArrayIndexOutOfBoundsException: 8388607
>>> at
>>>
>>> com.esotericsoftware.kryo.util.IdentityObjectIntMap.clear(IdentityObjectIntMap.java:345)
>>> at
>>>
>>> com.esotericsoftware.kryo.util.MapReferenceResolver.reset(MapReferenceResolver.java:47)
>>> at com.esotericsoftware.kryo.Kryo.reset(Kryo.java:804)
>>> at
>>> com.esotericsoftware.kryo.Kryo.writeClassAndObject(Kryo.java:570)
>>> at
>>>
>>> org.apache.spark.serializer.KryoSerializationStream.writeObject(KryoSerializer.scala:194)
>>> at
>>>
>>> org.apache.spark.broadcast.TorrentBroadcast$.blockifyObject(TorrentBroadcast.scala:203)
>>> at
>>>
>>> org.apache.spark.broadcast.TorrentBroadcast.writeBlocks(TorrentBroadcast.scala:102)
>>> at
>>>
>>> org.apache.spark.broadcast.TorrentBroadcast.<init>(TorrentBroadcast.scala:85)
>>> at
>>>
>>> org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast(TorrentBroadcastFactory.scala:34)
>>> at
>>>
>>> org.apache.spark.broadcast.BroadcastManager.newBroadcast(BroadcastManager.scala:63)
>>> at
>>> org.apache.spark.SparkContext.broadcast(SparkContext.scala:1326)
>>> at
>>>
>>> org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$broadcastFuture$1$$anonfun$apply$1.apply(BroadcastHashJoin.scala:91)
>>> at
>>>
>>> org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$broadcastFuture$1$$anonfun$apply$1.apply(BroadcastHashJoin.scala:79)
>>> at
>>>
>>> org.apache.spark.sql.execution.SQLExecution$.withExecutionId(SQLExecution.scala:100)
>>> at
>>>
>>> org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$broadcastFuture$1.apply(BroadcastHashJoin.scala:79)
>>> at
>>>
>>> org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$broadcastFuture$1.apply(BroadcastHashJoin.scala:79)
>>> at
>>>
>>> scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
>>> at
>>>
>>> scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
>>> 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)
>>> [Stage 10:> (0 +
>>> 24) /
>>> 24]2016-01-21 14:47:02 ERROR InsertIntoHadoopFsRelation:95 - Aborting
>>> job.
>>> java.lang.InterruptedException
>>> at java.lang.Object.wait(Native Method)
>>> at java.lang.Object.wait(Object.java:502)
>>> at
>>> org.apache.spark.scheduler.JobWaiter.awaitResult(JobWaiter.scala:73)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:612)
>>> 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:1922)
>>> at
>>>
>>> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelation.scala:150)
>>> at
>>>
>>> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply(InsertIntoHadoopFsRelation.scala:108)
>>> at
>>>
>>> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply(InsertIntoHadoopFsRelation.scala:108)
>>> at
>>>
>>> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
>>> at
>>>
>>> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:108)
>>> at
>>>
>>> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
>>> at
>>>
>>> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
>>> at
>>>
>>> org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
>>> at
>>>
>>> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:127)
>>> at
>>>
>>> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:125)
>>> at
>>>
>>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
>>> at
>>> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:125)
>>> at
>>>
>>> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55)
>>> at
>>>
>>> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55)
>>> at
>>>
>>> org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:242)
>>> at
>>> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:148)
>>> at
>>> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:139)
>>> at
>>>
>>> com.hsbc.rsl.spark.streaming.receiver.functions.PersistLevel3WithDataframes.call(PersistLevel3WithDataframes.java:84)
>>> at
>>>
>>> com.hsbc.rsl.spark.streaming.receiver.functions.PersistLevel3WithDataframes.call(PersistLevel3WithDataframes.java:27)
>>> at
>>>
>>> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$3.apply(JavaDStreamLike.scala:335)
>>> at
>>>
>>> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$3.apply(JavaDStreamLike.scala:335)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:656)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:656)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:50)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:49)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
>>> at
>>>
>>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
>>> at scala.util.Try$.apply(Try.scala:161)
>>> at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
>>> at
>>>
>>> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:224)
>>> at
>>>
>>> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
>>> at
>>>
>>> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:224)
>>> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
>>> at
>>>
>>> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:223)
>>> 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)
>>> 2016-01-21 14:47:02 ERROR DefaultWriterContainer:74 - Job
>>> job_201601211447_0000 aborted.
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> --
>>> View this message in context:
>>> http://apache-spark-user-list.1001560.n3.nabble.com/java-lang-ArrayIndexOutOfBoundsException-when-attempting-broadcastjoin-tp26034.html
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>>>
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>>>
>>
>
