I took a look at
https://github.com/JodaOrg/joda-time/blob/master/src/main/java/org/joda/time/DateTime.java
Looks like the NPE came from line below:
long instant = getChronology().days().add(getMillis(), days);
Maybe catch the NPE and print out the value of currentDate to see if there
is more clue ?
Cheers
On Tue, Nov 10, 2015 at 12:55 PM, Romain Sagean <romain.sag...@hupi.fr>
wrote:
> see below a more complete version of the code.
> the firstDate (previously minDate) should not be null, I even added an extra
> "filter( _._2 != null)" before the flatMap and the error is still there.
>
> What I don't understand is why I have the error on dateSeq.las.plusDays and
> not on dateSeq.last.isBefore (in the condition).
>
> I also tried changing the allDates function to use a while loop but i got the
> same error.
>
> def allDates(dateStart: DateTime, dateEnd: DateTime): Seq[DateTime] = {
> var dateSeq = Seq(dateStart)
> var currentDate = dateStart
> while (currentDate.isBefore(dateEnd)){
> dateSeq = dateSeq :+ currentDate
> currentDate = currentDate.plusDays(1)
> }
> return dateSeq
> }
>
> val videoAllDates = events.select("player_id", "current_ts")
> .filter("player_id is not null") .filter("current_ts is not null")
> .map( row => (row.getString(0), timestampToDate(row.getString(1))))
> .filter(r => r._2.isAfter(minimumDate)) .reduceByKey(minDateTime)
> .flatMapValues( firstDate => allDates(firstDate, endDate))
>
>
> And the stack trace.
>
> 15/11/10 21:10:36 INFO MapOutputTrackerMasterActor: Asked to send map
> output locations for shuffle 2 to sparkexecu...@r610-2.pro.hupi.loc:50821
> 15/11/10 21:10:36 INFO MapOutputTrackerMaster: Size of output statuses for
> shuffle 2 is 695 bytes
> 15/11/10 21:10:36 INFO MapOutputTrackerMasterActor: Asked to send map
> output locations for shuffle 1 to sparkexecu...@r610-2.pro.hupi.loc:50821
> 15/11/10 21:10:36 INFO MapOutputTrackerMaster: Size of output statuses for
> shuffle 1 is 680 bytes
> 15/11/10 21:10:36 INFO TaskSetManager: Starting task 206.0 in stage 3.0
> (TID 798, R610-2.pro.hupi.loc, PROCESS_LOCAL, 4416 bytes)
> 15/11/10 21:10:36 WARN TaskSetManager: Lost task 205.0 in stage 3.0 (TID
> 797, R610-2.pro.hupi.loc): java.lang.NullPointerException
> at org.joda.time.DateTime.plusDays(DateTime.java:1070)
> at Heatmap$.allDates(heatmap.scala:34)
> at Heatmap$$anonfun$12.apply(heatmap.scala:97)
> at Heatmap$$anonfun$12.apply(heatmap.scala:97)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$flatMapValues$1$$anonfun$apply$16.apply(PairRDDFunctions.scala:686)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$flatMapValues$1$$anonfun$apply$16.apply(PairRDDFunctions.scala:685)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:125)
> at
> org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:160)
> at
> org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
> at
> scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
> at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:159)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:87)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:64)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
> 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)
>
> 15/11/10 21:10:36 INFO TaskSetManager: Starting task 205.1 in stage 3.0
> (TID 799, R610-2.pro.hupi.loc, PROCESS_LOCAL, 4416 bytes)
> 15/11/10 21:10:36 INFO TaskSetManager: Finished task 206.0 in stage 3.0
> (TID 798) in 13 ms on R610-2.pro.hupi.loc (182/410)
> 15/11/10 21:10:36 INFO TaskSetManager: Starting task 207.0 in stage 3.0
> (TID 800, R610-2.pro.hupi.loc, PROCESS_LOCAL, 4416 bytes)
> 15/11/10 21:10:36 INFO TaskSetManager: Lost task 205.1 in stage 3.0 (TID
> 799) on executor R610-2.pro.hupi.loc: java.lang.NullPointerException (null)
> [duplicate 1]
> 15/11/10 21:10:36 INFO TaskSetManager: Starting task 205.2 in stage 3.0
> (TID 801, R610-2.pro.hupi.loc, PROCESS_LOCAL, 4416 bytes)
> 15/11/10 21:10:36 INFO TaskSetManager: Finished task 207.0 in stage 3.0
> (TID 800) in 14 ms on R610-2.pro.hupi.loc (183/410)
> 15/11/10 21:10:36 INFO TaskSetManager: Starting task 208.0 in stage 3.0
> (TID 802, R610-2.pro.hupi.loc, PROCESS_LOCAL, 4416 bytes)
> 15/11/10 21:10:36 INFO TaskSetManager: Lost task 205.2 in stage 3.0 (TID
> 801) on executor R610-2.pro.hupi.loc: java.lang.NullPointerException (null)
> [duplicate 2]
> 15/11/10 21:10:36 INFO TaskSetManager: Starting task 205.3 in stage 3.0
> (TID 803, R610-2.pro.hupi.loc, PROCESS_LOCAL, 4416 bytes)
> 15/11/10 21:10:36 INFO TaskSetManager: Finished task 208.0 in stage 3.0
> (TID 802) in 12 ms on R610-2.pro.hupi.loc (184/410)
> 15/11/10 21:10:36 INFO TaskSetManager: Starting task 209.0 in stage 3.0
> (TID 804, R610-2.pro.hupi.loc, PROCESS_LOCAL, 4416 bytes)
> 15/11/10 21:10:36 INFO TaskSetManager: Lost task 205.3 in stage 3.0 (TID
> 803) on executor R610-2.pro.hupi.loc: java.lang.NullPointerException (null)
> [duplicate 3]
> 15/11/10 21:10:36 ERROR TaskSetManager: Task 205 in stage 3.0 failed 4
> times; aborting job
> 15/11/10 21:10:36 INFO YarnScheduler: Cancelling stage 3
> 15/11/10 21:10:36 INFO YarnScheduler: Stage 3 was cancelled
> 15/11/10 21:10:36 INFO DAGScheduler: Job 1 failed: saveAsTextFile at
> heatmap.scala:116, took 45,476562 s
> Exception in thread "main" org.apache.spark.SparkException: Job aborted
> due to stage failure: Task 205 in stage 3.0 failed 4 times, most recent
> failure: Lost task 205.3 in stage 3.0 (TID 803, R610-2.pro.hupi.loc):
> java.lang.NullPointerException
> at org.joda.time.DateTime.plusDays(DateTime.java:1070)
> at Heatmap$.allDates(heatmap.scala:34)
> at Heatmap$$anonfun$12.apply(heatmap.scala:97)
> at Heatmap$$anonfun$12.apply(heatmap.scala:97)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$flatMapValues$1$$anonfun$apply$16.apply(PairRDDFunctions.scala:686)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$flatMapValues$1$$anonfun$apply$16.apply(PairRDDFunctions.scala:685)
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at
> org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:125)
> at
> org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:160)
> at
> org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
> at
> scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
> at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:159)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:87)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:64)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
> 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)
>
> Driver stacktrace:
> at org.apache.spark.scheduler.DAGScheduler.org
> $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1210)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1199)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1198)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1198)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1400)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1361)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> 15/11/10 21:10:36 WARN TaskSetManager: Lost task 209.0 in stage 3.0 (TID
> 804, R610-2.pro.hupi.loc): TaskKilled (killed intentionally)
> SLF4J: Class path contains multiple SLF4J bindings.
> SLF4J: Found binding in
> [jar:file:/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/jars/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
> SLF4J: Found binding in
> [jar:file:/opt/cloudera/parcels/CDH-5.4.7-1.cdh5.4.7.p0.3/jars/avro-tools-1.7.6-cdh5.4.7.jar!/org/slf4j/impl/StaticLoggerBinder.class]
> SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an
> explanation.
> SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
>
>
> 2015-11-10 18:39 GMT+01:00 Ted Yu <yuzhih...@gmail.com>:
>
>> Can you show the stack trace for the NPE ?
>>
>> Which release of Spark are you using ?
>>
>> Cheers
>>
>> On Tue, Nov 10, 2015 at 8:20 AM, romain sagean <romain.sag...@hupi.fr>
>> wrote:
>>
>>> Hi community,
>>> I try to apply the function below during a flatMapValues or a map but I
>>> get a nullPointerException with the plusDays(1). What did I miss ?
>>>
>>> def allDates(dateSeq: Seq[DateTime], dateEnd: DateTime): Seq[DateTime] =
>>> {
>>> if (dateSeq.last.isBefore(dateEnd)){
>>> allDates(dateSeq:+ dateSeq.last.plusDays(1), dateEnd)
>>> } else {
>>> dateSeq
>>> }
>>> }
>>>
>>> val videoAllDates = .select("player_id", "mindate").flatMapValues(
>>> minDate => allDates(Seq(minDate), endDate))
>>>
>>>
>>> ---------------------------------------------------------------------
>>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
>>> For additional commands, e-mail: user-h...@spark.apache.org
>>>
>>>
>>
>
>
> --
> *Romain Sagean*
>
> *romain.sag...@hupi.fr <romain.sag...@hupi.fr>*
>
>
