[jira] [Updated] (SPARK-14804) Graph vertexRDD/EdgeRDD checkpoint results ClassCastException:

[Joseph K. Bradley (JIRA)]

 [ 
https://issues.apache.org/jira/browse/SPARK-14804?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Joseph K. Bradley updated SPARK-14804:
--
Fix Version/s: (was: 3.0.0)
   2.2.0

> Graph vertexRDD/EdgeRDD checkpoint results ClassCastException: 
> ---
>
> Key: SPARK-14804
> URL: https://issues.apache.org/jira/browse/SPARK-14804
> Project: Spark
>  Issue Type: Bug
>  Components: GraphX
>Affects Versions: 1.6.1
>Reporter: SuYan
>Assignee: Tathagata Das
>Priority: Minor
> Fix For: 2.0.3, 2.1.1, 2.2.0
>
>
> {code}
> graph3.vertices.checkpoint()
> graph3.vertices.count()
> graph3.vertices.map(_._2).count()
> {code}
> 16/04/21 21:04:43 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 4.0 
> (TID 13, localhost): java.lang.ClassCastException: 
> org.apache.spark.graphx.impl.ShippableVertexPartition cannot be cast to 
> scala.Tuple2
>   at 
> com.xiaomi.infra.codelab.spark.Graph2$$anonfun$main$1.apply(Graph2.scala:80)
>   at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>   at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1597)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
>   at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>   at org.apache.spark.scheduler.Task.run(Task.scala:91)
>   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:219)
>   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)
> look at the code:
> {code}
>   private[spark] def computeOrReadCheckpoint(split: Partition, context: 
> TaskContext): Iterator[T] =
>   {
> if (isCheckpointedAndMaterialized) {
>   firstParent[T].iterator(split, context)
> } else {
>   compute(split, context)
> }
>   }
>  private[spark] def isCheckpointedAndMaterialized: Boolean = isCheckpointed
>  override def isCheckpointed: Boolean = {
>firstParent[(PartitionID, EdgePartition[ED, VD])].isCheckpointed
>  }
> {code}
> for VertexRDD or EdgeRDD, first parent is its partitionRDD  
> RDD[ShippableVertexPartition[VD]]/RDD[(PartitionID, EdgePartition[ED, VD])]
> 1. we call vertexRDD.checkpoint, it partitionRDD will checkpoint, so 
> VertexRDD.isCheckpointedAndMaterialized=true.
> 2. then we call vertexRDD.iterator, because checkoint=true it called 
> firstParent.iterator(which is not CheckpointRDD, actually is partitionRDD). 
>  
> so returned iterator is iterator[ShippableVertexPartition] not expect 
> iterator[(VertexId, VD)]]



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[jira] [Updated] (SPARK-14804) Graph vertexRDD/EdgeRDD checkpoint results ClassCastException:

[Joseph K. Bradley (JIRA)]

 [ 
https://issues.apache.org/jira/browse/SPARK-14804?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Joseph K. Bradley updated SPARK-14804:
--
Assignee: Tathagata Das

> Graph vertexRDD/EdgeRDD checkpoint results ClassCastException: 
> ---
>
> Key: SPARK-14804
> URL: https://issues.apache.org/jira/browse/SPARK-14804
> Project: Spark
>  Issue Type: Bug
>  Components: GraphX
>Affects Versions: 1.6.1
>Reporter: SuYan
>Assignee: Tathagata Das
>Priority: Minor
> Fix For: 2.0.3, 2.1.1, 3.0.0
>
>
> {code}
> graph3.vertices.checkpoint()
> graph3.vertices.count()
> graph3.vertices.map(_._2).count()
> {code}
> 16/04/21 21:04:43 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 4.0 
> (TID 13, localhost): java.lang.ClassCastException: 
> org.apache.spark.graphx.impl.ShippableVertexPartition cannot be cast to 
> scala.Tuple2
>   at 
> com.xiaomi.infra.codelab.spark.Graph2$$anonfun$main$1.apply(Graph2.scala:80)
>   at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>   at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1597)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
>   at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>   at org.apache.spark.scheduler.Task.run(Task.scala:91)
>   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:219)
>   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)
> look at the code:
> {code}
>   private[spark] def computeOrReadCheckpoint(split: Partition, context: 
> TaskContext): Iterator[T] =
>   {
> if (isCheckpointedAndMaterialized) {
>   firstParent[T].iterator(split, context)
> } else {
>   compute(split, context)
> }
>   }
>  private[spark] def isCheckpointedAndMaterialized: Boolean = isCheckpointed
>  override def isCheckpointed: Boolean = {
>firstParent[(PartitionID, EdgePartition[ED, VD])].isCheckpointed
>  }
> {code}
> for VertexRDD or EdgeRDD, first parent is its partitionRDD  
> RDD[ShippableVertexPartition[VD]]/RDD[(PartitionID, EdgePartition[ED, VD])]
> 1. we call vertexRDD.checkpoint, it partitionRDD will checkpoint, so 
> VertexRDD.isCheckpointedAndMaterialized=true.
> 2. then we call vertexRDD.iterator, because checkoint=true it called 
> firstParent.iterator(which is not CheckpointRDD, actually is partitionRDD). 
>  
> so returned iterator is iterator[ShippableVertexPartition] not expect 
> iterator[(VertexId, VD)]]



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[jira] [Updated] (SPARK-14804) Graph vertexRDD/EdgeRDD checkpoint results ClassCastException:

[SuYan (JIRA)]

 [ 
https://issues.apache.org/jira/browse/SPARK-14804?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

SuYan updated SPARK-14804:
--
Priority: Minor  (was: Major)

> Graph vertexRDD/EdgeRDD checkpoint results ClassCastException: 
> ---
>
> Key: SPARK-14804
> URL: https://issues.apache.org/jira/browse/SPARK-14804
> Project: Spark
>  Issue Type: Bug
>  Components: GraphX
>Affects Versions: 1.6.1
>Reporter: SuYan
>Priority: Minor
>
> {code}
> graph3.vertices.checkpoint()
> graph3.vertices.count()
> graph3.vertices.map(_._2).count()
> {code}
> 16/04/21 21:04:43 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 4.0 
> (TID 13, localhost): java.lang.ClassCastException: 
> org.apache.spark.graphx.impl.ShippableVertexPartition cannot be cast to 
> scala.Tuple2
>   at 
> com.xiaomi.infra.codelab.spark.Graph2$$anonfun$main$1.apply(Graph2.scala:80)
>   at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>   at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1597)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
>   at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>   at org.apache.spark.scheduler.Task.run(Task.scala:91)
>   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:219)
>   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)
> look at the code:
> {code}
>   private[spark] def computeOrReadCheckpoint(split: Partition, context: 
> TaskContext): Iterator[T] =
>   {
> if (isCheckpointedAndMaterialized) {
>   firstParent[T].iterator(split, context)
> } else {
>   compute(split, context)
> }
>   }
>  private[spark] def isCheckpointedAndMaterialized: Boolean = isCheckpointed
>  override def isCheckpointed: Boolean = {
>firstParent[(PartitionID, EdgePartition[ED, VD])].isCheckpointed
>  }
> {code}
> for VertexRDD or EdgeRDD, first parent is its partitionRDD  
> RDD[ShippableVertexPartition[VD]]/RDD[(PartitionID, EdgePartition[ED, VD])]
> 1. we call vertexRDD.checkpoint, it partitionRDD will checkpoint, so 
> VertexRDD.isCheckpointedAndMaterialized=true.
> 2. then we call vertexRDD.iterator, because checkoint=true it called 
> firstParent.iterator(which is not CheckpointRDD, actually is partitionRDD). 
>  
> so returned iterator is iterator[ShippableVertexPartition] not expect 
> iterator[(VertexId, VD)]]



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[jira] [Updated] (SPARK-14804) Graph vertexRDD/EdgeRDD checkpoint results ClassCastException:

[SuYan (JIRA)]

 [ 
https://issues.apache.org/jira/browse/SPARK-14804?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

SuYan updated SPARK-14804:
--
Description: 
{code}
graph3.vertices.checkpoint()
graph3.vertices.count()
graph3.vertices.map(_._2).count()
{code}


16/04/21 21:04:43 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 4.0 
(TID 13, localhost): java.lang.ClassCastException: 
org.apache.spark.graphx.impl.ShippableVertexPartition cannot be cast to 
scala.Tuple2
at 
com.xiaomi.infra.codelab.spark.Graph2$$anonfun$main$1.apply(Graph2.scala:80)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1597)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
at 
org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
at 
org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:91)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:219)
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)


look at the code:
{code}

  private[spark] def computeOrReadCheckpoint(split: Partition, context: 
TaskContext): Iterator[T] =
  {
if (isCheckpointedAndMaterialized) {
  firstParent[T].iterator(split, context)
} else {
  compute(split, context)
}
  }

 private[spark] def isCheckpointedAndMaterialized: Boolean = isCheckpointed

 override def isCheckpointed: Boolean = {
   firstParent[(PartitionID, EdgePartition[ED, VD])].isCheckpointed
 }

{code}

for VertexRDD or EdgeRDD, first parent is its partitionRDD  
RDD[ShippableVertexPartition[VD]]/RDD[(PartitionID, EdgePartition[ED, VD])]

1. we call vertexRDD.checkpoint, it partitionRDD will checkpoint, so 
VertexRDD.isCheckpointedAndMaterialized=true.
2. then we call vertexRDD.iterator, because checkoint=true it called 
firstParent.iterator(which is not CheckpointRDD, actually is partitionRDD). 
 
so returned iterator is iterator[ShippableVertexPartition] not expect 
iterator[(VertexId, VD)]]


  was:

{code}
graph3.vertices.checkpoint()
graph3.vertices.count()
graph3.vertices.map(_._2).count()
{code}


16/04/21 21:04:43 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 4.0 
(TID 13, localhost): java.lang.ClassCastException: 
org.apache.spark.graphx.impl.ShippableVertexPartition cannot be cast to 
scala.Tuple2
at 
com.xiaomi.infra.codelab.spark.Graph2$$anonfun$main$1.apply(Graph2.scala:80)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1597)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1161)
at 
org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
at 
org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1863)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:91)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:219)
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)


look at the code:
{ code }

  private[spark] def computeOrReadCheckpoint(split: Partition, context: 
TaskContext): Iterator[T] =
  {
if (isCheckpointedAndMaterialized) {
  firstParent[T].iterator(split, context)
} else {
  compute(split, context)
}
  }

 private[spark] def isCheckpointedAndMaterialized: Boolean = isCheckpointed

 override def isCheckpointed: Boolean = {
   firstParent[(PartitionID, EdgePartition[ED, VD])].isCheckpointed
 }

{code}

for VertexRDD or EdgeRDD, first parent is its partitionRDD  
RDD[ShippableVertexPartition[VD]]/RDD[(PartitionID, EdgePartition[ED, VD])]

1. we call vertexRDD.checkpoint, it partitionRDD will checkpoint, so 
VertexRDD.isCheckpointedAndMaterialized=true.
2. then we call vertexRDD.iterator, because checkoint=true it called 
firstParent.iterator(which is not CheckpointRDD, actually is partitionRDD). 
 
so returned iterator is iterator[ShippableVertexPartition] not expect 
iterator[(VertexId, VD)]]



> Graph vertexRDD/EdgeRDD checkpoint results ClassCastException: 
> ---
>
>