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>*
