I made some modifications to my code where I broadcast the Dataframe I want
to join directly through the SparkContext, and that seems to work as
expected. Still don't understand what is going wrong with the missing Plan.
On Thu, Jan 21, 2016 at 3:36 PM, Ted Yu <yuzhih...@gmail.com> wrote:
> 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
>>>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>>>>
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>>>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
>>>> For additional commands, e-mail: user-h...@spark.apache.org
>>>>
>>>>
>>>
>>
>
