Even if log4j didn't work, you can still get some clue by wrapping the following call with try block:
currentDate = currentDate.plusDays(1) catching NPE and rethrowing with an exception that shows the value of currentDate Cheers On Thu, Nov 12, 2015 at 1:56 AM, Romain Sagean <romain.sag...@hupi.fr> wrote: > I Still can't make the logger work inside a map function. I can use > "logInfo("")" in the main but not in the function. Anyway I rewrite my > program to use java.util.Date instead joda time and I don't have NPE > anymore. > > I will stick with this solution for the moment even if I find java Date > ugly. > > Thanks for your help. > > 2015-11-11 15:54 GMT+01:00 Ted Yu <yuzhih...@gmail.com>: > >> In case you need to adjust log4j properties, see the following thread: >> >> >> http://search-hadoop.com/m/q3RTtJHkzb1t0J66&subj=Re+Spark+Streaming+Log4j+Inside+Eclipse >> >> Cheers >> >> On Tue, Nov 10, 2015 at 1:28 PM, Ted Yu <yuzhih...@gmail.com> wrote: >> >>> 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>* >>>> >>>> >>> >> > > > -- > *Romain Sagean* > > *romain.sag...@hupi.fr <romain.sag...@hupi.fr>* > >