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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/07/27 06:34:04 UTC
[jira] [Assigned] (SPARK-9362) Exception when using DataFrame
groupby().sum on Decimal type in Python
[ https://issues.apache.org/jira/browse/SPARK-9362?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-9362:
-----------------------------------
Assignee: (was: Apache Spark)
> Exception when using DataFrame groupby().sum on Decimal type in Python
> ----------------------------------------------------------------------
>
> Key: SPARK-9362
> URL: https://issues.apache.org/jira/browse/SPARK-9362
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.4.0
> Reporter: Jeffrey Chan
>
> Please see below. It works with integer, but not with decimal.
> bash-4.1# pyspark
> Python 2.6.6 (r266:84292, Jan 22 2014, 09:42:36)
> [GCC 4.4.7 20120313 (Red Hat 4.4.7-4)] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
> Welcome to
> ____ __
> / __/__ ___ _____/ /__
> _\ \/ _ \/ _ `/ __/ '_/
> /__ / .__/\_,_/_/ /_/\_\ version 1.4.0
> /_/
> Using Python version 2.6.6 (r266:84292, Jan 22 2014 09:42:36)
> SparkContext available as sc, HiveContext available as sqlContext.
> >>> from decimal import *
> >>> from pyspark.sql import SQLContext
> >>> sqlContext = SQLContext(sc)
> >>> l1 = [('a', 1), ('b', 2), ('a', 3)]
> >>> rdd1 = sc.parallelize(l1)
> >>> df1 = sqlContext.createDataFrame(rdd1, ['key', 'value'])
> >>> df1.collect()
> [Row(key=u'a', value=1), Row(key=u'b', value=2), Row(key=u'a', value=3)]
> >>> df1.groupBy("key").sum("value").collect()
> [Row(key=u'a', SUM(value)=4), Row(key=u'b', SUM(value)=2)]
> >>> l2 = [('a', Decimal('1.1')), ('b', Decimal('2.3')), ('a', Decimal('3.4'))]
> >>> rdd2 = sc.parallelize(l2)
> >>> df2 = sqlContext.createDataFrame(rdd2, ['key', 'value'])
> >>> df2.collect()
> [Row(key=u'a', value=Decimal('1.1')), Row(key=u'b', value=Decimal('2.3')), Row(key=u'a', value=Decimal('3.4'))]
> >>> df2.groupBy("key").sum("value").collect()
> 15/07/26 14:58:50 ERROR Executor: Exception in task 1.0 in stage 12.0 (TID 215)
> java.lang.ClassCastException: java.math.BigDecimal cannot be cast to org.apache.spark.sql.types.Decimal
> at org.apache.spark.sql.types.Decimal$DecimalIsFractional$.plus(Decimal.scala:330)
> at org.apache.spark.sql.catalyst.expressions.Add.eval(arithmetic.scala:125)
> at org.apache.spark.sql.catalyst.expressions.Coalesce.eval(nullFunctions.scala:51)
> at org.apache.spark.sql.catalyst.expressions.MutableLiteral.update(literals.scala:91)
> at org.apache.spark.sql.catalyst.expressions.SumFunction.update(aggregates.scala:625)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$7.apply(Aggregate.scala:165)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$7.apply(Aggregate.scala:149)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:70)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
> 15/07/26 14:58:50 ERROR Executor: Exception in task 0.0 in stage 12.0 (TID 214)
> java.lang.ClassCastException: java.math.BigDecimal cannot be cast to org.apache.spark.sql.types.Decimal
> at org.apache.spark.sql.types.Decimal$DecimalIsFractional$.plus(Decimal.scala:330)
> at org.apache.spark.sql.catalyst.expressions.Add.eval(arithmetic.scala:125)
> at org.apache.spark.sql.catalyst.expressions.Coalesce.eval(nullFunctions.scala:51)
> at org.apache.spark.sql.catalyst.expressions.MutableLiteral.update(literals.scala:91)
> at org.apache.spark.sql.catalyst.expressions.SumFunction.update(aggregates.scala:625)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$7.apply(Aggregate.scala:165)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$7.apply(Aggregate.scala:149)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:70)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
> 15/07/26 14:58:50 ERROR TaskSetManager: Task 1 in stage 12.0 failed 1 times; aborting job
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/usr/local/spark/python/pyspark/sql/dataframe.py", line 314, in collect
> port = self._sc._jvm.PythonRDD.collectAndServe(self._jdf.javaToPython().rdd())
> File "/usr/local/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
> File "/usr/local/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 12.0 failed 1 times, most recent failure: Lost task 1.0 in stage 12.0 (TID 215, localhost): java.lang.ClassCastException: java.math.BigDecimal cannot be cast to org.apache.spark.sql.types.Decimal
> at org.apache.spark.sql.types.Decimal$DecimalIsFractional$.plus(Decimal.scala:330)
> at org.apache.spark.sql.catalyst.expressions.Add.eval(arithmetic.scala:125)
> at org.apache.spark.sql.catalyst.expressions.Coalesce.eval(nullFunctions.scala:51)
> at org.apache.spark.sql.catalyst.expressions.MutableLiteral.update(literals.scala:91)
> at org.apache.spark.sql.catalyst.expressions.SumFunction.update(aggregates.scala:625)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$7.apply(Aggregate.scala:165)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$7.apply(Aggregate.scala:149)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:70)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
> Driver stacktrace:
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1266)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1257)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1256)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1256)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
> at scala.Option.foreach(Option.scala:236)
> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1450)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1411)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> >>>
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