[ 
https://issues.apache.org/jira/browse/SPARK-3990?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Gen TANG updated SPARK-3990:
----------------------------
    Description: 
When we tried ALS.trainImplicit() in pyspark environment, it only works for 
iterations = 1. What is more strange, it is that if we try the same code in 
Scala, it works very well.(I did several test, by now, in Scala 
ALS.trainImplicit works)

For example, the following code:
{code:title=test.py|borderStyle=solid}
  r1 = (1, 1, 1.0) 
  r2 = (1, 2, 2.0) 
  r3 = (2, 1, 2.0) 
  ratings = sc.parallelize([r1, r2, r3]) 
  model = ALS.trainImplicit(ratings, 1) 
'''by default iterations = 5 or model = ALS.trainImplicit(ratings, 1, 2)'''
{code}


It will cause the failed stage at count at ALS.scala:314 Info as:
{code:title=error information provided by ganglia}
Job aborted due to stage failure: Task 6 in stage 90.0 failed 4 times, most 
recent failure: Lost task 6.3 in stage 90.0 (TID 484, 
ip-172-31-35-238.ec2.internal): com.esotericsoftware.kryo.KryoException: 
java.lang.ArrayStoreException: scala.collection.mutable.HashSet
Serialization trace:
shouldSend (org.apache.spark.mllib.recommendation.OutLinkBlock)
        
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)
        
com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
        com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
        com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:43)
        com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:34)
        com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
        
org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:133)
        
org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:133)
        org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
        
org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
        scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
        
org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:137)
        
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
        
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:158)
        
scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
        
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        
scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
        org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:158)
        org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31)
        org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        
org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31)
        org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33)
        org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
        org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
        org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        org.apache.spark.scheduler.Task.run(Task.scala:54)
        org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
        
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
{code}
In the log of slave which failed the task, it has:

{code:title=error information in the log of slave}
14/10/17 13:20:54 ERROR executor.Executor: Exception in task 6.0 in stage 90.0 
(TID 465)
com.esotericsoftware.kryo.KryoException: java.lang.ArrayStoreException: 
scala.collection.mutable.HashSet
Serialization trace:
shouldSend (org.apache.spark.mllib.recommendation.OutLinkBlock)
        at 
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)
        at 
com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
        at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
        at com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:43)
        at com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:34)
        at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
        at 
org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:133)
        at 
org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:133)
        at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
        at 
org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
        at 
org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:137)
        at 
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
        at 
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:158)
        at 
scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
        at 
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at 
scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
        at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:158)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at 
org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at 
org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        at org.apache.spark.scheduler.Task.run(Task.scala:54)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ArrayStoreException: scala.collection.mutable.HashSet
        at 
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:338)
        at 
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:293)
        at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:648)
        at 
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:605)
        ... 36 more
{code}



  was:
When we tried ALS.trainImplicit() in pyspark environment, it only works for 
iterations = 1. For example, the following code:

r1 = (1, 1, 1.0) 
r2 = (1, 2, 2.0) 
r3 = (2, 1, 2.0) 
ratings = sc.parallelize([r1, r2, r3]) 
model = ALS.trainImplicit(ratings, 1) [by default iterations = 5] or model = 
ALS.trainImplicit(ratings, 1, 2)

It will cause the failed stage at count at ALS.scala:314 Info as:

Job aborted due to stage failure: Task 6 in stage 90.0 failed 4 times, most 
recent failure: Lost task 6.3 in stage 90.0 (TID 484, 
ip-172-31-35-238.ec2.internal): com.esotericsoftware.kryo.KryoException: 
java.lang.ArrayStoreException: scala.collection.mutable.HashSet
Serialization trace:
shouldSend (org.apache.spark.mllib.recommendation.OutLinkBlock)
        
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)
        
com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
        com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
        com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:43)
        com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:34)
        com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
        
org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:133)
        
org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:133)
        org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
        
org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
        scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
        
org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:137)
        
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
        
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:158)
        
scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
        
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        
scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
        org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:158)
        org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31)
        org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        
org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31)
        org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33)
        org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
        org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
        org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        org.apache.spark.scheduler.Task.run(Task.scala:54)
        org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
        
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        java.lang.Thread.run(Thread.java:745)
Driver stacktrace:

In the log of slave which failed the task, it has:
14/10/17 13:20:54 ERROR executor.Executor: Exception in task 6.0 in stage 90.0 
(TID 465)
com.esotericsoftware.kryo.KryoException: java.lang.ArrayStoreException: 
scala.collection.mutable.HashSet
Serialization trace:
shouldSend (org.apache.spark.mllib.recommendation.OutLinkBlock)
        at 
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)
        at 
com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
        at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
        at com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:43)
        at com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:34)
        at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
        at 
org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:133)
        at 
org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:133)
        at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
        at 
org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
        at 
org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:137)
        at 
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
        at 
org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:158)
        at 
scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
        at 
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at 
scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
        at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:158)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at 
org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at 
org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
        at org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
        at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
        at org.apache.spark.scheduler.Task.run(Task.scala:54)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ArrayStoreException: scala.collection.mutable.HashSet
        at 
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:338)
        at 
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:293)
        at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:648)
        at 
com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:605)
        ... 36 more

More strange, if we try the same code in Scala, it works very well.(I did 
several test, by now, in Scala ALS.trainImplicit works)



> kryo.KryoException caused by ALS.trainImplicit in pyspark
> ---------------------------------------------------------
>
>                 Key: SPARK-3990
>                 URL: https://issues.apache.org/jira/browse/SPARK-3990
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib, PySpark
>    Affects Versions: 1.1.0
>         Environment: 5 slaves cluster(m3.large) in AWS launched by spark-ec2
> Linux
> Python 2.6.8
>            Reporter: Gen TANG
>              Labels: test
>
> When we tried ALS.trainImplicit() in pyspark environment, it only works for 
> iterations = 1. What is more strange, it is that if we try the same code in 
> Scala, it works very well.(I did several test, by now, in Scala 
> ALS.trainImplicit works)
> For example, the following code:
> {code:title=test.py|borderStyle=solid}
>   r1 = (1, 1, 1.0) 
>   r2 = (1, 2, 2.0) 
>   r3 = (2, 1, 2.0) 
>   ratings = sc.parallelize([r1, r2, r3]) 
>   model = ALS.trainImplicit(ratings, 1) 
> '''by default iterations = 5 or model = ALS.trainImplicit(ratings, 1, 2)'''
> {code}
> It will cause the failed stage at count at ALS.scala:314 Info as:
> {code:title=error information provided by ganglia}
> Job aborted due to stage failure: Task 6 in stage 90.0 failed 4 times, most 
> recent failure: Lost task 6.3 in stage 90.0 (TID 484, 
> ip-172-31-35-238.ec2.internal): com.esotericsoftware.kryo.KryoException: 
> java.lang.ArrayStoreException: scala.collection.mutable.HashSet
> Serialization trace:
> shouldSend (org.apache.spark.mllib.recommendation.OutLinkBlock)
>         
> com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)
>         
> com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
>         com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
>         com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:43)
>         com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:34)
>         com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
>         
> org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:133)
>         
> org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:133)
>         org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
>         
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
>         scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>         
> org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:137)
>         
> org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
>         
> org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:158)
>         
> scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
>         
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>         scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>         
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
>         org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:158)
>         org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>         org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31)
>         org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>         
> org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31)
>         org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>         org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33)
>         org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>         org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
>         org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
>         org.apache.spark.scheduler.Task.run(Task.scala:54)
>         org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
>         
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> {code}
> In the log of slave which failed the task, it has:
> {code:title=error information in the log of slave}
> 14/10/17 13:20:54 ERROR executor.Executor: Exception in task 6.0 in stage 
> 90.0 (TID 465)
> com.esotericsoftware.kryo.KryoException: java.lang.ArrayStoreException: 
> scala.collection.mutable.HashSet
> Serialization trace:
> shouldSend (org.apache.spark.mllib.recommendation.OutLinkBlock)
>       at 
> com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626)
>       at 
> com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221)
>       at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
>       at com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:43)
>       at com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:34)
>       at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)
>       at 
> org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:133)
>       at 
> org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:133)
>       at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
>       at 
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
>       at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>       at 
> org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:137)
>       at 
> org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
>       at 
> org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:158)
>       at 
> scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
>       at 
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>       at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>       at 
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
>       at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:158)
>       at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>       at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>       at 
> org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31)
>       at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>       at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>       at 
> org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31)
>       at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>       at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>       at org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33)
>       at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>       at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
>       at org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
>       at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
>       at org.apache.spark.scheduler.Task.run(Task.scala:54)
>       at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
>       at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>       at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>       at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.ArrayStoreException: scala.collection.mutable.HashSet
>       at 
> com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:338)
>       at 
> com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:293)
>       at com.esotericsoftware.kryo.Kryo.readObject(Kryo.java:648)
>       at 
> com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:605)
>       ... 36 more
> {code}



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