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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/07/14 19:34:20 UTC
[jira] [Updated] (SPARK-16550) Caching data with replication
doesn't replicate data
[ https://issues.apache.org/jira/browse/SPARK-16550?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen updated SPARK-16550:
------------------------------
Priority: Major (was: Blocker)
> Caching data with replication doesn't replicate data
> ----------------------------------------------------
>
> Key: SPARK-16550
> URL: https://issues.apache.org/jira/browse/SPARK-16550
> Project: Spark
> Issue Type: Bug
> Components: Block Manager, Spark Core
> Affects Versions: 2.0.0
> Reporter: Shubham Chopra
>
> Caching multiple replicas of blocks is currently broken. The following examples show replication doesn't happen for various use-cases:
> These were run using Spark 2.0.0-preview, in local-cluster[2,1,1024] mode
> case class TestInteger(i: Int)
> val data = sc.parallelize((1 to 1000).map(TestInteger(_)), 10).persist(MEMORY_ONLY_2)
> data.count
> sc.getExecutorStorageStatus.map(s => s.rddBlocksById(data.id).size).sum shows only 10 blocks as opposed to the expected 20
> Block replication fails on the executors with a java.lang.RuntimeException: java.lang.ClassNotFoundException: $line14.$read$$iw$$iw$TestInteger
> val data1 = sc.parallelize(1 to 1000, 10).persist(org.apache.spark.storage.StorageLevel.MEMORY_ONLY_2)
> data1.count
> Block replication again fails with the following errors:
> 16/07/14 14:50:40 ERROR TransportRequestHandler: Error while invoking RpcHandler#receive() on RPC id 8567643992794608648
> com.esotericsoftware.kryo.KryoException: Encountered unregistered class ID: 13994
> at com.esotericsoftware.kryo.util.DefaultClassResolver.readClass(DefaultClassResolver.java:137)
> at com.esotericsoftware.kryo.Kryo.readClass(Kryo.java:670)
> at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:781)
> at org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:229)
> at org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:169)
> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
> at org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:213)
> at org.apache.spark.storage.BlockManager$$anonfun$doPutBytes$1.apply(BlockManager.scala:775)
> at org.apache.spark.storage.BlockManager$$anonfun$doPutBytes$1.apply(BlockManager.scala:753)
> sc.getExecutorStorageStatus.map(s => s.rddBlocksById(data1.id).size).sum again shows 10 blocks
> Caching serialized data works for native types, but not for custom classes
> val data3 = sc.parallelize(1 to 1000, 10).persist(MEMORY_ONLY_SER_2)
> data3.count
> works as intended.
> But
> val data4 = sc.parallelize((1 to 1000).map(TestInteger(_)), 10).persist(MEMORY_ONLY_SER_2)
> data4.count
> Again doesn't replicate data and executors show the same ClassNotFoundException
> These examples worked fine and showed expected results with Spark 1.6.2
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