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Posted to issues@spark.apache.org by "Thomas Graves (JIRA)" <ji...@apache.org> on 2015/09/21 21:09:04 UTC
[jira] [Created] (SPARK-10735) CatalystTypeConverters MatchError
converting RDD with customer object to dataframe
Thomas Graves created SPARK-10735:
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Summary: CatalystTypeConverters MatchError converting RDD with customer object to dataframe
Key: SPARK-10735
URL: https://issues.apache.org/jira/browse/SPARK-10735
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.5.0
Reporter: Thomas Graves
In spark 1.5.0 we are now seeing an exception when converting an RDD with custom object to a dataframe. Note this works with Spark 1.4.1.
RDD<BasicData>
where BasicData classhas a field ArrayList<Beacon> where Beacon is a user defined class now converting RDD<BasicData> to DataFrame is causing the issue:
15/09/21 18:53:16 ERROR executor.Executor: Managed memory leak detected; size = 2097152 bytes, TID = 408
15/09/21 18:53:16 ERROR executor.Executor: Exception in task 0.0 in stage 4.0 (TID 408)
scala.MatchError: foo.Beacon@5c289b39 (of class foo.Beacon)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:250)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:245)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$ArrayConverter.toCatalystImpl(CatalystTypeConverters.scala:164)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$ArrayConverter.toCatalystImpl(CatalystTypeConverters.scala:148)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
at org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToCatalystConverter$2.apply(CatalystTypeConverters.scala:396)
at org.apache.spark.sql.SQLContext$$anonfun$9$$anonfun$apply$1$$anonfun$apply$2.apply(SQLContext.scala:494)
at org.apache.spark.sql.SQLContext$$anonfun$9$$anonfun$apply$1$$anonfun$apply$2.apply(SQLContext.scala:494)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at org.apache.spark.sql.SQLContext$$anonfun$9$$anonfun$apply$1.apply(SQLContext.scala:494)
at org.apache.spark.sql.SQLContext$$anonfun$9$$anonfun$apply$1.apply(SQLContext.scala:492)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:372)
at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.start(TungstenAggregationIterator.scala:622)
at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1.org$apache$spark$sql$execution$aggregate$TungstenAggregate$$anonfun$$executePartition$1(TungstenAggregate.scala:110)
at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:119)
at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:119)
at org.apache.spark.rdd.MapPartitionsWithPreparationRDD.compute(MapPartitionsWithPreparationRDD.scala:64)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
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