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https://issues.apache.org/jira/browse/SPARK-19147?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15837333#comment-15837333
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Genmao Yu commented on SPARK-19147:
-----------------------------------
After dig into code, this issue may occurs when executor is existing and at the
same time some tasks are running. There are some scenes in which this NPE will
be thrown:
1. AM re-registers after a failure, and this will resets the state of
CoarseGrainedSchedulerBackend to the initial state, then old executors will be
removed. This will only occurs in yarn-client mode.
2. Master may will remove executor when a work is lost, and at the same time
some tasks may be running.
3. Some other scenes i do not know.
As for as I know, this NPE harms nothing, but may confuse users. Maybe, we
should improve this exception message to tell users it is safe. What is your
opinion? [~zsxwing]
> netty throw NPE
> ---------------
>
> Key: SPARK-19147
> URL: https://issues.apache.org/jira/browse/SPARK-19147
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.0
> Reporter: cen yuhai
>
> {code}
> 17/01/10 19:17:20 ERROR ShuffleBlockFetcherIterator: Failed to get block(s)
> from bigdata-hdp-apache1828.xg01.diditaxi.com:7337
> java.lang.NullPointerException: group
> at io.netty.bootstrap.AbstractBootstrap.group(AbstractBootstrap.java:80)
> at
> org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:203)
> at
> org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:181)
> at
> org.apache.spark.network.shuffle.ExternalShuffleClient$1.createAndStart(ExternalShuffleClient.java:105)
> at
> org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:140)
> at
> org.apache.spark.network.shuffle.RetryingBlockFetcher.start(RetryingBlockFetcher.java:120)
> at
> org.apache.spark.network.shuffle.ExternalShuffleClient.fetchBlocks(ExternalShuffleClient.java:114)
> at
> org.apache.spark.storage.ShuffleBlockFetcherIterator.sendRequest(ShuffleBlockFetcherIterator.scala:169)
> at
> org.apache.spark.storage.ShuffleBlockFetcherIterator.fetchUpToMaxBytes(ShuffleBlockFetcherIterator.scala:354)
> at
> org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:332)
> at
> org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:54)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$$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
> org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.sort_addToSorter$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.findNextInnerJoinRows$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$2.hasNext(WholeStageCodegenExec.scala:396)
> at
> org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$1$$anon$1.hasNext(InMemoryRelation.scala:138)
> at
> org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:215)
> at
> org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:957)
> at
> org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:948)
> at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:888)
> at
> org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:948)
> at
> org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:694)
> at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> at org.apache.spark.scheduler.Task.run(Task.scala:99)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
> 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)
> {code}
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