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Posted to issues@spark.apache.org by "Cody Koeninger (JIRA)" <ji...@apache.org> on 2017/03/10 21:33:04 UTC
[jira] [Commented] (SPARK-19888) Seeing offsets not resetting even
when reset policy is configured explicitly
[ https://issues.apache.org/jira/browse/SPARK-19888?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15905730#comment-15905730 ]
Cody Koeninger commented on SPARK-19888:
----------------------------------------
That stacktrace also shows a concurrent modification exception, yes?. See SPARK-19185 for that
See e.g. SPARK-19680 for background on why offset out of range may occur on executor when it doesn't on driver. Although if you're using reset latest, unless you have really short retention this is kind of surprising.
> Seeing offsets not resetting even when reset policy is configured explicitly
> ----------------------------------------------------------------------------
>
> Key: SPARK-19888
> URL: https://issues.apache.org/jira/browse/SPARK-19888
> Project: Spark
> Issue Type: Bug
> Components: DStreams
> Affects Versions: 2.1.0
> Reporter: Justin Miller
>
> I was told to post this in a Spark ticket from KAFKA-4396:
> I've been seeing a curious error with kafka 0.10 (spark 2.11), these may be two separate errors, I'm not sure. What's puzzling is that I'm setting auto.offset.reset to latest and it's still throwing an OffsetOutOfRangeException, behavior that's contrary to the code. Please help! :)
> {code}
> val kafkaParams = Map[String, Object](
> "group.id" -> consumerGroup,
> "bootstrap.servers" -> bootstrapServers,
> "key.deserializer" -> classOf[ByteArrayDeserializer],
> "value.deserializer" -> classOf[MessageRowDeserializer],
> "auto.offset.reset" -> "latest",
> "enable.auto.commit" -> (false: java.lang.Boolean),
> "max.poll.records" -> persisterConfig.maxPollRecords,
> "request.timeout.ms" -> persisterConfig.requestTimeoutMs,
> "session.timeout.ms" -> persisterConfig.sessionTimeoutMs,
> "heartbeat.interval.ms" -> persisterConfig.heartbeatIntervalMs,
> "connections.max.idle.ms"-> persisterConfig.connectionsMaxIdleMs
> )
> {code}
> {code}
> 16/11/09 23:10:17 INFO BlockManagerInfo: Added broadcast_154_piece0 in memory on xyz (size: 146.3 KB, free: 8.4 GB)
> 16/11/09 23:10:23 WARN TaskSetManager: Lost task 15.0 in stage 151.0 (TID 38837, xyz): org.apache.kafka.clients.consumer.OffsetOutOfRangeException: Offsets out of range with no configured reset policy for partitions: {topic=231884473}
> at org.apache.kafka.clients.consumer.internals.Fetcher.parseFetchedData(Fetcher.java:588)
> at org.apache.kafka.clients.consumer.internals.Fetcher.fetchedRecords(Fetcher.java:354)
> at org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(KafkaConsumer.java:1000)
> at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:938)
> at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.poll(CachedKafkaConsumer.scala:99)
> at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:70)
> at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:227)
> at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:193)
> at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:438)
> at org.apache.spark.sql.execution.datasources.DynamicPartitionWriterContainer.writeRows(WriterContainer.scala:397)
> at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
> at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> 16/11/09 23:10:29 INFO TaskSetManager: Finished task 10.0 in stage 154.0 (TID 39388) in 12043 ms on xyz (1/16)
> 16/11/09 23:10:31 INFO TaskSetManager: Finished task 0.0 in stage 154.0 (TID 39375) in 13444 ms on xyz (2/16)
> 16/11/09 23:10:44 WARN TaskSetManager: Lost task 1.0 in stage 151.0 (TID 38843, xyz): java.util.ConcurrentModificationException: KafkaConsumer is not safe for multi-threaded access
> at org.apache.kafka.clients.consumer.KafkaConsumer.acquire(KafkaConsumer.java:1431)
> at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:929)
> at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.poll(CachedKafkaConsumer.scala:99)
> at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:73)
> at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:227)
> at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:193)
> at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
> {code}
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