[jira] [Assigned] (SPARK-6660) MLLibPythonAPI.pythonToJava doesn't recognize object arrays

2015-04-01 Thread Apache Spark (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-6660?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-6660:
---

Assignee: Xiangrui Meng  (was: Apache Spark)

> MLLibPythonAPI.pythonToJava doesn't recognize object arrays
> ---
>
> Key: SPARK-6660
> URL: https://issues.apache.org/jira/browse/SPARK-6660
> Project: Spark
>  Issue Type: Bug
>  Components: MLlib, PySpark
>Reporter: Xiangrui Meng
>Assignee: Xiangrui Meng
>Priority: Critical
>
> {code}
> points = MLUtils.loadLabeledPoints(sc, "...")
> _to_java_object_rdd(points).count()
> {code}
> throws exception
> {code}
> ---
> Py4JJavaError Traceback (most recent call last)
>  in ()
> > 1 jrdd.count()
> /home/ubuntu/databricks/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py
>  in __call__(self, *args)
> 536 answer = self.gateway_client.send_command(command)
> 537 return_value = get_return_value(answer, self.gateway_client,
> --> 538 self.target_id, self.name)
> 539 
> 540 for temp_arg in temp_args:
> /home/ubuntu/databricks/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py
>  in get_return_value(answer, gateway_client, target_id, name)
> 298 raise Py4JJavaError(
> 299 'An error occurred while calling {0}{1}{2}.\n'.
> --> 300 format(target_id, '.', name), value)
> 301 else:
> 302 raise Py4JError(
> Py4JJavaError: An error occurred while calling o510.count.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 18 
> in stage 114.0 failed 4 times, most recent failure: Lost task 18.3 in stage 
> 114.0 (TID 1133, ip-10-0-130-35.us-west-2.compute.internal): 
> java.lang.ClassCastException: [Ljava.lang.Object; cannot be cast to 
> java.util.ArrayList
>   at 
> org.apache.spark.mllib.api.python.SerDe$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(PythonMLLibAPI.scala:1090)
>   at 
> org.apache.spark.mllib.api.python.SerDe$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(PythonMLLibAPI.scala:1087)
>   at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
>   at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1472)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1006)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1006)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1497)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1497)
>   at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
>   at org.apache.spark.scheduler.Task.run(Task.scala:64)
>   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
>   at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>   at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>   at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
>   at 
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1203)
>   at 
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
>   at 
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1191)
>   at 
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>   at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>   at 
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1191)
>   at 
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
>   at 
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
>   at scala.Option.foreach(Option.scala:236)
>   at 
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
>   at 
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
>   at 
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
>   at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> {code}



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[jira] [Assigned] (SPARK-6660) MLLibPythonAPI.pythonToJava doesn't recognize object arrays

2015-04-01 Thread Apache Spark (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-6660?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-6660:
---

Assignee: Apache Spark  (was: Xiangrui Meng)

> MLLibPythonAPI.pythonToJava doesn't recognize object arrays
> ---
>
> Key: SPARK-6660
> URL: https://issues.apache.org/jira/browse/SPARK-6660
> Project: Spark
>  Issue Type: Bug
>  Components: MLlib, PySpark
>Reporter: Xiangrui Meng
>Assignee: Apache Spark
>Priority: Critical
>
> {code}
> points = MLUtils.loadLabeledPoints(sc, "...")
> _to_java_object_rdd(points).count()
> {code}
> throws exception
> {code}
> ---
> Py4JJavaError Traceback (most recent call last)
>  in ()
> > 1 jrdd.count()
> /home/ubuntu/databricks/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py
>  in __call__(self, *args)
> 536 answer = self.gateway_client.send_command(command)
> 537 return_value = get_return_value(answer, self.gateway_client,
> --> 538 self.target_id, self.name)
> 539 
> 540 for temp_arg in temp_args:
> /home/ubuntu/databricks/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py
>  in get_return_value(answer, gateway_client, target_id, name)
> 298 raise Py4JJavaError(
> 299 'An error occurred while calling {0}{1}{2}.\n'.
> --> 300 format(target_id, '.', name), value)
> 301 else:
> 302 raise Py4JError(
> Py4JJavaError: An error occurred while calling o510.count.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 18 
> in stage 114.0 failed 4 times, most recent failure: Lost task 18.3 in stage 
> 114.0 (TID 1133, ip-10-0-130-35.us-west-2.compute.internal): 
> java.lang.ClassCastException: [Ljava.lang.Object; cannot be cast to 
> java.util.ArrayList
>   at 
> org.apache.spark.mllib.api.python.SerDe$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(PythonMLLibAPI.scala:1090)
>   at 
> org.apache.spark.mllib.api.python.SerDe$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(PythonMLLibAPI.scala:1087)
>   at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
>   at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1472)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1006)
>   at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1006)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1497)
>   at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1497)
>   at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
>   at org.apache.spark.scheduler.Task.run(Task.scala:64)
>   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
>   at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>   at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>   at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
>   at 
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1203)
>   at 
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
>   at 
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1191)
>   at 
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>   at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>   at 
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1191)
>   at 
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
>   at 
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
>   at scala.Option.foreach(Option.scala:236)
>   at 
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
>   at 
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
>   at 
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
>   at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> {code}



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