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Posted to issues@spark.apache.org by "Bago Amirbekian (JIRA)" <ji...@apache.org> on 2017/10/10 02:57:00 UTC
[jira] [Commented] (SPARK-22232) Row objects in pyspark using the
`Row(**kwars)` syntax do not get serialized/deserialized properly
[ https://issues.apache.org/jira/browse/SPARK-22232?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16198068#comment-16198068 ]
Bago Amirbekian commented on SPARK-22232:
-----------------------------------------
Full trace:
{code:none}
[Row(a=u'a', c=3.0, b=2), Row(a=u'a', c=3.0, b=2)]
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<command-4880785> in <module>()
17
18 # If we introduce a shuffle we have issues
---> 19 print rdd.repartition(3).toDF(schema).take(2)
/databricks/spark/python/pyspark/sql/dataframe.pyc in take(self, num)
475 [Row(age=2, name=u'Alice'), Row(age=5, name=u'Bob')]
476 """
--> 477 return self.limit(num).collect()
478
479 @since(1.3)
/databricks/spark/python/pyspark/sql/dataframe.pyc in collect(self)
437 """
438 with SCCallSiteSync(self._sc) as css:
--> 439 port = self._jdf.collectToPython()
440 return list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
441
/databricks/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in __call__(self, *args)
1131 answer = self.gateway_client.send_command(command)
1132 return_value = get_return_value(
-> 1133 answer, self.gateway_client, self.target_id, self.name)
1134
1135 for temp_arg in temp_args:
/databricks/spark/python/pyspark/sql/utils.pyc in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/databricks/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
317 raise Py4JJavaError(
318 "An error occurred while calling {0}{1}{2}.\n".
--> 319 format(target_id, ".", name), value)
320 else:
321 raise Py4JError(
Py4JJavaError: An error occurred while calling o204.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 161.0 failed 4 times, most recent failure: Lost task 0.3 in stage 161.0 (TID 433, 10.0.195.33, executor 0): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/databricks/spark/python/pyspark/worker.py", line 177, in main
process()
File "/databricks/spark/python/pyspark/worker.py", line 172, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/databricks/spark/python/pyspark/serializers.py", line 285, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/databricks/spark/python/pyspark/sql/session.py", line 520, in prepare
verify_func(obj, schema)
File "/databricks/spark/python/pyspark/sql/types.py", line 1458, in _verify_type
_verify_type(v, f.dataType, f.nullable)
File "/databricks/spark/python/pyspark/sql/types.py", line 1422, in _verify_type
raise TypeError("%s can not accept object %r in type %s" % (dataType, obj, type(obj)))
TypeError: FloatType can not accept object 2 in type <type 'int'>
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:346)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1676)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1664)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1663)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1663)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:930)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:930)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:930)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1896)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1847)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1835)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:732)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2076)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2095)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:361)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:2865)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2862)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2862)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:80)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:99)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2895)
at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:2862)
at sun.reflect.GeneratedMethodAccessor338.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/databricks/spark/python/pyspark/worker.py", line 177, in main
process()
File "/databricks/spark/python/pyspark/worker.py", line 172, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/databricks/spark/python/pyspark/serializers.py", line 285, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "/databricks/spark/python/pyspark/sql/session.py", line 520, in prepare
verify_func(obj, schema)
File "/databricks/spark/python/pyspark/sql/types.py", line 1458, in _verify_type
_verify_type(v, f.dataType, f.nullable)
File "/databricks/spark/python/pyspark/sql/types.py", line 1422, in _verify_type
raise TypeError("%s can not accept object %r in type %s" % (dataType, obj, type(obj)))
TypeError: FloatType can not accept object 2 in type <type 'int'>
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:346)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
{code}
> Row objects in pyspark using the `Row(**kwars)` syntax do not get serialized/deserialized properly
> --------------------------------------------------------------------------------------------------
>
> Key: SPARK-22232
> URL: https://issues.apache.org/jira/browse/SPARK-22232
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.2.0
> Reporter: Bago Amirbekian
>
> The fields in a Row object created from a dict (ie {{Row(**kwargs)}}) should be accessed by field name, not by position because {{Row.__new__}} sorts the fields alphabetically by name. It seems like this promise is not being honored when these Row objects are shuffled. I've included an example to help reproduce the issue.
> {code:none}
> from pyspark.sql.types import *
> from pyspark.sql import *
> def toRow(i):
> return Row(a="a", c=3.0, b=2)
> schema = StructType([
> # Putting fields in alphabetical order masks the issue
> StructField("a", StringType(), False),
> StructField("c", FloatType(), False),
> StructField("b", IntegerType(), False),
> ])
> rdd = sc.parallelize(range(10)).repartition(2).map(lambda i: toRow(i))
> # As long as we don't shuffle things work fine.
> print rdd.toDF(schema).take(2)
> # If we introduce a shuffle we have issues
> print rdd.repartition(3).toDF(schema).take(2)
> {code}
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