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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} -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org