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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2019/03/26 08:52:24 UTC
[GitHub] [spark] vkrot opened a new pull request #24218:
[SPARK-27281][DStreams] Change the way latest kafka offsets are retrieved
to consumer#endOffsets
vkrot opened a new pull request #24218: [SPARK-27281][DStreams] Change the way latest kafka offsets are retrieved to consumer#endOffsets
URL: https://github.com/apache/spark/pull/24218
## What changes were proposed in this pull request?
Change the way latest kafka offsets are retrieved in `latestOffsets` methods from
```
consumer#seekToEnd(tp)
consumer#position(tp)
```
to
```
consumer#endOffsets(partitions)
```
This fixed the issue from corresponding jira issue.
With existing code from time to time I get an error
```
java.lang.IllegalArgumentException: requirement failed: numRecords must not be negative
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.streaming.scheduler.StreamInputInfo.<init>(InputInfoTracker.scala:38)
at org.apache.spark.streaming.kafka010.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:250)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:336)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:334)
at scala.Option.orElse(Option.scala:289)
at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:331)
at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:48)
at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:122)
at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:121)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:121)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:249)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:247)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:247)
at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:183)
at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:89)
at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:88)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
19/01/29 13:10:00 ERROR apps.BusinessRuleEngine: Job failed. Stopping JVM
java.lang.IllegalArgumentException: requirement failed: numRecords must not be negative
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.streaming.scheduler.StreamInputInfo.<init>(InputInfoTracker.scala:38)
at org.apache.spark.streaming.kafka010.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:250)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:336)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:334)
at scala.Option.orElse(Option.scala:289)
at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:331)
at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:48)
at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:122)
at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:121)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:121)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:249)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:247)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:247)
at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:183)
at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:89)
at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:88)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
java.lang.IllegalArgumentException: requirement failed: numRecords must not be negative
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.streaming.scheduler.StreamInputInfo.<init>(InputInfoTracker.scala:38)
at org.apache.spark.streaming.kafka010.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:250)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:336)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:334)
at scala.Option.orElse(Option.scala:289)
at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:331)
at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:48)
at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:122)
at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:121)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:121)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:249)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:247)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:247)
at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:183)
at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:89)
at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:88)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
```
With 10+ jobs consuming 100+ partitions this happens only once a day - once a week. The code seekToEnd returns offsets that are lower that `currentOffsets`, while `consumer#endOffsets` returns correct end offsets
## How was this patch tested?
Existing tests
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