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Sean Owen commented on SPARK-16232: ----------------------------------- There isn't a resolution; this isn't actionable in its current state. The error here still isn't showing what went wrong. You can help by narrowing it down to a short and reproducible snippet. Generally, if it's a question only, ask at user@ > Getting error by making columns using DataFrame > ------------------------------------------------ > > Key: SPARK-16232 > URL: https://issues.apache.org/jira/browse/SPARK-16232 > Project: Spark > Issue Type: Question > Components: MLilb, PySpark > Affects Versions: 1.5.1 > Environment: Winodws, ipython notebook > Reporter: Inam Ur Rehman > Labels: ipython, pandas, pyspark, python > > I am using pyspark in ipython notebook for analysis. > I am following an example toturial this > http://nbviewer.jupyter.org/github/bensadeghi/pyspark-churn-prediction/blob/master/churn-prediction.ipynb > I am getting error on this step in the 7th cell of notebook > pd.DataFrame(CV_data.take(5), columns=CV_data.columns) > Py4JJavaError: An error occurred while calling > z:org.apache.spark.sql.execution.EvaluatePython.takeAndServe. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 > in stage 11.0 failed 1 times, most recent failure: Lost task 0.0 in stage > 11.0 (TID 18, localhost): org.apache.spark.api.python.PythonException: > Traceback (most recent call last): > Here is the full error : > Py4JJavaError Traceback (most recent call last) > <ipython-input-10-d3dfeab0b119> in <module>() > ----> 1 pd.DataFrame(CV_data.take(5), columns=CV_data.columns) > C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\pyspark\sql\dataframe.py > in take(self, num) > 303 with SCCallSiteSync(self._sc) as css: > 304 port = > self._sc._jvm.org.apache.spark.sql.execution.EvaluatePython.takeAndServe( > --> 305 self._jdf, num) > 306 return list(_load_from_socket(port, > BatchedSerializer(PickleSerializer()))) > 307 > C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\lib\py4j-0.8.2.1-src.zip\py4j\java_gateway.py > in __call__(self, *args) > 536 answer = self.gateway_client.send_command(command) > 537 return_value = get_return_value(answer, self.gateway_client, > --> 538 self.target_id, self.name) > 539 > 540 for temp_arg in temp_args: > C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\pyspark\sql\utils.py > in deco(*a, **kw) > 34 def deco(*a, **kw): > 35 try: > ---> 36 return f(*a, **kw) > 37 except py4j.protocol.Py4JJavaError as e: > 38 s = e.java_exception.toString() > C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\lib\py4j-0.8.2.1-src.zip\py4j\protocol.py > in get_return_value(answer, gateway_client, target_id, name) > 298 raise Py4JJavaError( > 299 'An error occurred while calling {0}{1}{2}.\n'. > --> 300 format(target_id, '.', name), value) > 301 else: > 302 raise Py4JError( > Py4JJavaError: An error occurred while calling > z:org.apache.spark.sql.execution.EvaluatePython.takeAndServe. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 > in stage 11.0 failed 1 times, most recent failure: Lost task 0.0 in stage > 11.0 (TID 18, localhost): org.apache.spark.api.python.PythonException: > Traceback (most recent call last): > File > "C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", > line 111, in main > File > "C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", > line 106, in process > File > "C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\serializers.py", > line 263, in dump_stream > vs = list(itertools.islice(iterator, batch)) > File > "C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\pyspark\sql\functions.py", > line 1417, in <lambda> > func = lambda _, it: map(lambda x: returnType.toInternal(f(*x)), it) > File "<ipython-input-7-6db2287430d4>", line 5, in <lambda> > KeyError: False > at > org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166) > at > org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207) > at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125) > at > org.apache.spark.sql.execution.BatchPythonEvaluation$$anonfun$doExecute$1.apply(python.scala:397) > at > org.apache.spark.sql.execution.BatchPythonEvaluation$$anonfun$doExecute$1.apply(python.scala:362) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:706) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:706) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:262) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > at org.apache.spark.scheduler.Task.run(Task.scala:88) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > 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$$failJobAndIndependentStages(DAGScheduler.scala:1283) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697) > at scala.Option.foreach(Option.scala:236) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1822) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1835) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1848) > at > org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:215) > at > org.apache.spark.sql.execution.Limit.executeCollect(basicOperators.scala:207) > at > org.apache.spark.sql.DataFrame$$anonfun$collect$1.apply(DataFrame.scala:1385) > at > org.apache.spark.sql.DataFrame$$anonfun$collect$1.apply(DataFrame.scala:1385) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56) > at > org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:1903) > at org.apache.spark.sql.DataFrame.collect(DataFrame.scala:1384) > at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1314) > at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1377) > at > org.apache.spark.sql.execution.EvaluatePython$.takeAndServe(python.scala:127) > at > org.apache.spark.sql.execution.EvaluatePython.takeAndServe(python.scala) > 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:497) > at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) > at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379) > at py4j.Gateway.invoke(Gateway.java:259) > at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133) > at py4j.commands.CallCommand.execute(CallCommand.java:79) > at py4j.GatewayConnection.run(GatewayConnection.java:207) > at java.lang.Thread.run(Thread.java:745) > Caused by: org.apache.spark.api.python.PythonException: Traceback (most > recent call last): > File > "C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", > line 111, in main > File > "C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", > line 106, in process > File > "C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\serializers.py", > line 263, in dump_stream > vs = list(itertools.islice(iterator, batch)) > File > "C:\Users\InAm-Ur-Rehman\spark-1.5.1-bin-hadoop2.6\python\pyspark\sql\functions.py", > line 1417, in <lambda> > func = lambda _, it: map(lambda x: returnType.toInternal(f(*x)), it) > File "<ipython-input-7-6db2287430d4>", line 5, in <lambda> > KeyError: False > at > org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166) > at > org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207) > at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125) > at > org.apache.spark.sql.execution.BatchPythonEvaluation$$anonfun$doExecute$1.apply(python.scala:397) > at > org.apache.spark.sql.execution.BatchPythonEvaluation$$anonfun$doExecute$1.apply(python.scala:362) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:706) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:706) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:262) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > at org.apache.spark.scheduler.Task.run(Task.scala:88) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > ... 1 more > In [ ]: > -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org