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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2020/06/01 00:47:00 UTC
[jira] [Assigned] (SPARK-31849) Improve Python exception messages
to be more Pythonic
[ https://issues.apache.org/jira/browse/SPARK-31849?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon reassigned SPARK-31849:
------------------------------------
Assignee: Hyukjin Kwon
> Improve Python exception messages to be more Pythonic
> -----------------------------------------------------
>
> Key: SPARK-31849
> URL: https://issues.apache.org/jira/browse/SPARK-31849
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
> Affects Versions: 3.0.0
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Major
> Fix For: 3.0.0
>
>
> Current PySpark exceptions are pretty ugly, and probably the most frequently reported compliant from PySpark users.
> For example, simple udf that throws a {{ZeroDivisionError}}:
> {code}
> from pyspark.sql.functions import udf
> @udf
> def divide_by_zero(v):
> raise v / 0
> spark.range(1).select(divide_by_zero("id")).show()
> {code}
> shows a bunch of JVM stacktrace which is very hard for Python users to understand:
> {code}
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/.../spark-2.4.5-bin-hadoop2.7/python/pyspark/sql/dataframe.py", line 380, in show
> print(self._jdf.showString(n, 20, vertical))
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
> File "/.../spark-2.4.5-bin-hadoop2.7/python/pyspark/sql/utils.py", line 63, in deco
> return f(*a, **kw)
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling o84.showString.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 2.0 failed 1 times, most recent failure: Lost task 6.0 in stage 2.0 (TID 11, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
> process()
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
> serializer.dump_stream(func(split_index, iterator), outfile)
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 352, in dump_stream
> self.serializer.dump_stream(self._batched(iterator), stream)
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 142, in dump_stream
> for obj in iterator:
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 341, in _batched
> for item in iterator:
> File "<string>", line 1, in <lambda>
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
> return lambda *a: f(*a)
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
> return f(*args, **kwargs)
> File "<stdin>", line 3, in divide_by_zero
> ZeroDivisionError: division by zero
> at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:456)
> at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:81)
> at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:64)
> at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:410)
> at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:858)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:858)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:346)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:310)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:346)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:310)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:123)
> at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at java.util.concurrent.ThreadPoolExecutor$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$$failJobAndIndependentStages(DAGScheduler.scala:1891)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1879)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1878)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1878)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:927)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:927)
> at scala.Option.foreach(Option.scala:257)
> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:927)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2112)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2061)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2050)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:738)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:365)
> at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
> at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
> at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:80)
> at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127)
> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3369)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2764)
> at org.apache.spark.sql.Dataset.getRows(Dataset.scala:254)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:291)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> 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:282)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:238)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
> process()
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
> serializer.dump_stream(func(split_index, iterator), outfile)
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 352, in dump_stream
> self.serializer.dump_stream(self._batched(iterator), stream)
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 142, in dump_stream
> for obj in iterator:
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 341, in _batched
> for item in iterator:
> File "<string>", line 1, in <lambda>
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
> return lambda *a: f(*a)
> File "/.../spark-2.4.5-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
> return f(*args, **kwargs)
> File "<stdin>", line 3, in divide_by_zero
> ZeroDivisionError: division by zero
> at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:456)
> at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:81)
> at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:64)
> at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:410)
> at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:858)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:858)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:346)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:310)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:346)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:310)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:123)
> at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> ... 1 more
> {code}
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