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https://issues.apache.org/jira/browse/HIVE-9781?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xuefu Zhang updated HIVE-9781:
------------------------------
Fix Version/s: (was: spark-branch)
1.2.0
> Utilize spark.kryo.classesToRegister [Spark Branch]
> ---------------------------------------------------
>
> Key: HIVE-9781
> URL: https://issues.apache.org/jira/browse/HIVE-9781
> Project: Hive
> Issue Type: Sub-task
> Components: Spark
> Reporter: Brock Noland
> Assignee: Jimmy Xiang
> Fix For: 1.2.0
>
> Attachments: HIVE-9781.1.patch, HIVE-9781.2.patch, HIVE-9781.3.patch,
> HIVE-9781.4.patch
>
>
> I noticed in several thread dumps that it appears kyro is serializing the
> class names associated with our keys and values.
> Kyro supports pre-registering classes so that you don't have to serialize the
> class name and spark supports this via the {{spark.kryo.registrator}}
> property. We should do this so we don't have to serialize class names.
> {noformat}
> Thread 12154: (state = BLOCKED)
> - java.lang.Object.hashCode() @bci=0 (Compiled frame; information may be
> imprecise)
> - com.esotericsoftware.kryo.util.ObjectMap.get(java.lang.Object) @bci=1,
> line=265 (Compiled frame)
> -
> com.esotericsoftware.kryo.util.DefaultClassResolver.getRegistration(java.lang.Class)
> @bci=18, line=61 (Compiled frame)
> - com.esotericsoftware.kryo.Kryo.getRegistration(java.lang.Class) @bci=20,
> line=429 (Compiled frame)
> -
> com.esotericsoftware.kryo.util.DefaultClassResolver.readName(com.esotericsoftware.kryo.io.Input)
> @bci=242, line=148 (Compiled frame)
> -
> com.esotericsoftware.kryo.util.DefaultClassResolver.readClass(com.esotericsoftware.kryo.io.Input)
> @bci=65, line=115 (Compiled frame)
> -
> com.esotericsoftware.kryo.Kryo.readClass(com.esotericsoftware.kryo.io.Input)
> @bci=20, line=610 (Compiled frame)
> -
> com.esotericsoftware.kryo.Kryo.readClassAndObject(com.esotericsoftware.kryo.io.Input)
> @bci=21, line=721 (Compiled frame)
> - com.twitter.chill.Tuple2Serializer.read(com.esotericsoftware.kryo.Kryo,
> com.esotericsoftware.kryo.io.Input, java.lang.Class) @bci=6, line=41
> (Compiled frame)
> - com.twitter.chill.Tuple2Serializer.read(com.esotericsoftware.kryo.Kryo,
> com.esotericsoftware.kryo.io.Input, java.lang.Class) @bci=4, line=33
> (Compiled frame)
> -
> com.esotericsoftware.kryo.Kryo.readClassAndObject(com.esotericsoftware.kryo.io.Input)
> @bci=126, line=729 (Compiled frame)
> -
> org.apache.spark.serializer.KryoDeserializationStream.readObject(scala.reflect.ClassTag)
> @bci=8, line=142 (Compiled frame)
> - org.apache.spark.serializer.DeserializationStream$$anon$1.getNext()
> @bci=10, line=133 (Compiled frame)
> - org.apache.spark.util.NextIterator.hasNext() @bci=16, line=71 (Compiled
> frame)
> - org.apache.spark.util.CompletionIterator.hasNext() @bci=4, line=32
> (Compiled frame)
> - scala.collection.Iterator$$anon$13.hasNext() @bci=4, line=371 (Compiled
> frame)
> - org.apache.spark.util.CompletionIterator.hasNext() @bci=4, line=32
> (Compiled frame)
> - org.apache.spark.InterruptibleIterator.hasNext() @bci=22, line=39
> (Compiled frame)
> - scala.collection.Iterator$$anon$11.hasNext() @bci=4, line=327 (Compiled
> frame)
> -
> org.apache.spark.util.collection.ExternalSorter.insertAll(scala.collection.Iterator)
> @bci=191, line=217 (Compiled frame)
> - org.apache.spark.shuffle.hash.HashShuffleReader.read() @bci=278, line=61
> (Interpreted frame)
> - org.apache.spark.rdd.ShuffledRDD.compute(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=46, line=92 (Interpreted frame)
> -
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=26, line=263 (Interpreted frame)
> - org.apache.spark.rdd.RDD.iterator(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=33, line=230 (Interpreted frame)
> - org.apache.spark.rdd.MapPartitionsRDD.compute(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=24, line=35 (Interpreted frame)
> -
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=26, line=263 (Interpreted frame)
> - org.apache.spark.rdd.RDD.iterator(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=33, line=230 (Interpreted frame)
> - org.apache.spark.rdd.MapPartitionsRDD.compute(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=24, line=35 (Interpreted frame)
> -
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=26, line=263 (Interpreted frame)
> - org.apache.spark.rdd.RDD.iterator(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=33, line=230 (Interpreted frame)
> - org.apache.spark.rdd.UnionRDD.compute(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=22, line=87 (Interpreted frame)
> -
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=26, line=263 (Interpreted frame)
> - org.apache.spark.rdd.RDD.iterator(org.apache.spark.Partition,
> org.apache.spark.TaskContext) @bci=33, line=230 (Interpreted frame)
> -
> org.apache.spark.scheduler.ShuffleMapTask.runTask(org.apache.spark.TaskContext)
> @bci=166, line=68 (Interpreted frame)
> -
> org.apache.spark.scheduler.ShuffleMapTask.runTask(org.apache.spark.TaskContext)
> @bci=2, line=41 (Interpreted frame)
> - org.apache.spark.scheduler.Task.run(long) @bci=77, line=56 (Interpreted
> frame)
> - org.apache.spark.executor.Executor$TaskRunner.run() @bci=310, line=196
> (Interpreted frame)
> -
> java.util.concurrent.ThreadPoolExecutor.runWorker(java.util.concurrent.ThreadPoolExecutor$Worker)
> @bci=95, line=1145 (Interpreted frame)
> - java.util.concurrent.ThreadPoolExecutor$Worker.run() @bci=5, line=615
> (Interpreted frame)
> - java.lang.Thread.run() @bci=11, line=745 (Interpreted frame)
> {noformat}
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