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Posted to issues@spark.apache.org by "Ruben Berenguel (JIRA)" <ji...@apache.org> on 2019/04/05 17:01:00 UTC

[jira] [Commented] (SPARK-20787) PySpark can't handle datetimes before 1900

    [ https://issues.apache.org/jira/browse/SPARK-20787?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16811044#comment-16811044 ] 

Ruben Berenguel commented on SPARK-20787:
-----------------------------------------

Hi [~AdiC], indeed, I have not added additional work. So far I haven't found any way of fixing it in a way which does not introduce what is effectively a breaking change to the behaviour of dates when using Python. 

If anyone else wants to pick this ticket up, please do.

> PySpark can't handle datetimes before 1900
> ------------------------------------------
>
>                 Key: SPARK-20787
>                 URL: https://issues.apache.org/jira/browse/SPARK-20787
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 2.1.0, 2.1.1
>            Reporter: Keith Bourgoin
>            Priority: Major
>
> When trying to put a datetime before 1900 into a DataFrame, it throws an error because of the use of time.mktime.
> {code}
> Python 2.7.13 (default, Mar  8 2017, 17:29:55)
> Type "copyright", "credits" or "license" for more information.
> IPython 5.3.0 -- An enhanced Interactive Python.
> ?         -> Introduction and overview of IPython's features.
> %quickref -> Quick reference.
> help      -> Python's own help system.
> object?   -> Details about 'object', use 'object??' for extra details.
> Setting default log level to "WARN".
> To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
> 17/05/17 12:45:59 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
> 17/05/17 12:46:02 WARN ObjectStore: Failed to get database global_temp, returning NoSuchObjectException
> Welcome to
>       ____              __
>      / __/__  ___ _____/ /__
>     _\ \/ _ \/ _ `/ __/  '_/
>    /__ / .__/\_,_/_/ /_/\_\   version 2.1.0
>       /_/
> Using Python version 2.7.13 (default, Mar  8 2017 17:29:55)
> SparkSession available as 'spark'.
> In [1]: import datetime as dt
> In [2]: sqlContext.createDataFrame(sc.parallelize([[dt.datetime(1899,12,31)]])).count()
> 17/05/17 12:46:16 ERROR Executor: Exception in task 3.0 in stage 2.0 (TID 7)
> org.apache.spark.api.python.PythonException: Traceback (most recent call last):
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/worker.py", line 174, in main
>     process()
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/worker.py", line 169, in process
>     serializer.dump_stream(func(split_index, iterator), outfile)
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 268, in dump_stream
>     vs = list(itertools.islice(iterator, batch))
>   File "/home/kfb/src/projects/spark/python/pyspark/sql/types.py", line 576, in toInternal
>     return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
>   File "/home/kfb/src/projects/spark/python/pyspark/sql/types.py", line 576, in <genexpr>
>     return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 436, in toInternal
>     return self.dataType.toInternal(obj)
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 191, in toInternal
>     else time.mktime(dt.timetuple()))
> ValueError: year out of range
> 	at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
> 	at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
> 	at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
> 	at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:99)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> 	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)
> 17/05/17 12:46:16 WARN TaskSetManager: Lost task 3.0 in stage 2.0 (TID 7, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/worker.py", line 174, in main
>     process()
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/worker.py", line 169, in process
>     serializer.dump_stream(func(split_index, iterator), outfile)
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 268, in dump_stream
>     vs = list(itertools.islice(iterator, batch))
>   File "/home/kfb/src/projects/spark/python/pyspark/sql/types.py", line 576, in toInternal
>     return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
>   File "/home/kfb/src/projects/spark/python/pyspark/sql/types.py", line 576, in <genexpr>
>     return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 436, in toInternal
>     return self.dataType.toInternal(obj)
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 191, in toInternal
>     else time.mktime(dt.timetuple()))
> ValueError: year out of range
> 	at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
> 	at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
> 	at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
> 	at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:99)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> 	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)
> 17/05/17 12:46:16 ERROR TaskSetManager: Task 3 in stage 2.0 failed 1 times; aborting job
> 17/05/17 12:46:16 WARN TaskSetManager: Lost task 1.0 in stage 2.0 (TID 5, localhost, executor driver): TaskKilled (killed intentionally)
> 17/05/17 12:46:16 WARN TaskSetManager: Lost task 2.0 in stage 2.0 (TID 6, localhost, executor driver): TaskKilled (killed intentionally)
> 17/05/17 12:46:16 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 4, localhost, executor driver): TaskKilled (killed intentionally)
> ---------------------------------------------------------------------------
> Py4JJavaError                             Traceback (most recent call last)
> <ipython-input-2-7e1f7293354f> in <module>()
> ----> 1 sqlContext.createDataFrame(sc.parallelize([[dt.datetime(1899,12,31)]])).count()
> /home/kfb/src/projects/spark/python/pyspark/sql/dataframe.pyc in count(self)
>     378         2
>     379         """
> --> 380         return int(self._jdf.count())
>     381
>     382     @ignore_unicode_prefix
> /home/kfb/src/projects/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:
> /home/kfb/src/projects/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()
> /home/kfb/src/projects/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 o58.count.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 2.0 failed 1 times, most recent failure: Lost task 3.0 in stage 2.0 (TID 7, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/worker.py", line 174, in main
>     process()
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/worker.py", line 169, in process
>     serializer.dump_stream(func(split_index, iterator), outfile)
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 268, in dump_stream
>     vs = list(itertools.islice(iterator, batch))
>   File "/home/kfb/src/projects/spark/python/pyspark/sql/types.py", line 576, in toInternal
>     return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
>   File "/home/kfb/src/projects/spark/python/pyspark/sql/types.py", line 576, in <genexpr>
>     return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 436, in toInternal
>     return self.dataType.toInternal(obj)
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 191, in toInternal
>     else time.mktime(dt.timetuple()))
> ValueError: year out of range
> 	at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
> 	at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
> 	at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
> 	at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:99)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> 	at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> 	at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
> 	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> 	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> 	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
> 	at scala.Option.foreach(Option.scala:257)
> 	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
> 	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
> 	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
> 	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
> 	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> 	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
> 	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
> 	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
> 	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
> 	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958)
> 	at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:935)
> 	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> 	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> 	at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
> 	at org.apache.spark.rdd.RDD.collect(RDD.scala:934)
> 	at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275)
> 	at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2371)
> 	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> 	at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)
> 	at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2370)
> 	at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2377)
> 	at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2405)
> 	at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2404)
> 	at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2778)
> 	at org.apache.spark.sql.Dataset.count(Dataset.scala:2404)
> 	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: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:745)
> Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/worker.py", line 174, in main
>     process()
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/worker.py", line 169, in process
>     serializer.dump_stream(func(split_index, iterator), outfile)
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 268, in dump_stream
>     vs = list(itertools.islice(iterator, batch))
>   File "/home/kfb/src/projects/spark/python/pyspark/sql/types.py", line 576, in toInternal
>     return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
>   File "/home/kfb/src/projects/spark/python/pyspark/sql/types.py", line 576, in <genexpr>
>     return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 436, in toInternal
>     return self.dataType.toInternal(obj)
>   File "/home/kfb/src/projects/spark/python/lib/pyspark.zip/pyspark/sql/types.py", line 191, in toInternal
>     else time.mktime(dt.timetuple()))
> ValueError: year out of range
> 	at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
> 	at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
> 	at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
> 	at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:99)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> 	... 1 more
> In [3]: sqlContext.createDataFrame(sc.parallelize([[dt.datetime(1900,1,1)]])).count()
> Out[3]: 1
> {code}



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