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https://issues.apache.org/jira/browse/SPARK-20178?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15969388#comment-15969388
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Thomas Graves commented on SPARK-20178:
---------------------------------------
One thing I ran into today which is somewhat related to this is a combination
of failure types. In this case it was broadcast fetch failures combined with
shuffle fetch failures which lead to 4 task failures and failed the job. I
believe they were all from the same host and happened really quickly (within 3
seconds). This seems like this should fall under the fetch failure case as
well.
Failed to get broadcast_646_piece0 of broadcast_646
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1222)
at
org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:165)
at
org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64)
at
org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64)
at
org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:88)
at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
at
org.apache.spark.MapOutputTracker$.deserializeMapStatuses(MapOutputTracker.scala:691)
at
org.apache.spark.MapOutputTracker.getStatuses(MapOutputTracker.scala:204)
at
org.apache.spark.MapOutputTracker.getMapSizesByExecutorId(MapOutputTracker.scala:143)
at
org.apache.spark.shuffle.BlockStoreShuffleReader.read(BlockStoreShuffleReader.scala:47)
at
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$2.apply(CoGroupedRDD.scala:147)
at
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$2.apply(CoGroupedRDD.scala:136)
at
scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
at scala.collection.immutable.List.foreach(List.scala:318)
at
scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:136)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> Improve Scheduler fetch failures
> --------------------------------
>
> Key: SPARK-20178
> URL: https://issues.apache.org/jira/browse/SPARK-20178
> Project: Spark
> Issue Type: Epic
> Components: Scheduler
> Affects Versions: 2.1.0
> Reporter: Thomas Graves
>
> We have been having a lot of discussions around improving the handling of
> fetch failures. There are 4 jira currently related to this.
> We should try to get a list of things we want to improve and come up with one
> cohesive design.
> SPARK-20163, SPARK-20091, SPARK-14649 , and SPARK-19753
> I will put my initial thoughts in a follow on comment.
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