Thanks Jeff, please find the stack trace below:
Py4JJavaError Traceback (most recent call last)
<ipython-input-43-e2e9b4ed4aea> in <module>()
1 BB = B.groupByKey()
----> 2 BB.take(1)
C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\rdd.py in take(self, num)
1222
1223 p = range(partsScanned, min(partsScanned +
numPartsToTry, totalParts))
-> 1224 res = self.context.runJob(self, takeUpToNumLeft, p, True)
1225
1226 items += res
C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\context.py in
runJob(self, rdd, partitionFunc, partitions, allowLocal)
840 mappedRDD = rdd.mapPartitions(partitionFunc)
841 port = self._jvm.PythonRDD.runJob(self._jsc.sc(),
mappedRDD._jrdd, javaPartitions,
--> 842 allowLocal)
843 return list(_load_from_socket(port,
mappedRDD._jrdd_deserializer))
844
C:\apps\dist\IPython-3.1.0.0.0.0.0-0001\lib\site-packages\py4j\java_gateway.pyc
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:\apps\dist\IPython-3.1.0.0.0.0.0-0001\lib\site-packages\py4j\protocol.pyc
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.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure:
Task 4 in stage 19.0 failed 4 times, most recent failure: Lost task
4.3 in stage 19.0 (TID 95,
workernode15.expediademocluster.j1.internal.cloudapp.net):
org.apache.spark.api.python.PythonException: Traceback (most recent
call last):
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\worker.py",
line 101, in main
process()
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\worker.py",
line 96, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\serializers.py",
line 125, in dump_stream
for obj in iterator:
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\rdd.py",
line 1626, in add_shuffle_key
for k, v in iterator:
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\shuffle.py",
line 383, in _external_items
False)
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\shuffle.py",
line 288, in mergeCombiners
for k, v in iterator:
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\serializers.py",
line 131, in load_stream
yield self._read_with_length(stream)
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\serializers.py",
line 148, in _read_with_length
length = read_int(stream)
File "C:\apps\dist\spark-1.3.1.2.2.7.1-0004\python\pyspark\serializers.py",
line 529, in read_int
return struct.unpack("!i", length)[0]
error: unpack requires a string argument of length 4
at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:135)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:176)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:94)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:311)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
On Sun, Oct 18, 2015 at 11:17 PM, Jeff Zhang <zjf...@gmail.com> wrote:
> Stacktrace would be helpful if you can provide that.
>
>
>
> On Mon, Oct 19, 2015 at 1:42 PM, fahad shah <sfaha...@gmail.com> wrote:
>>
>> Hi
>>
>> I am trying to do pair rdd's, group by the key assign id based on key.
>> I am using Pyspark with spark 1.3, for some reason, I am getting this
>> error that I am unable to figure out - any help much appreciated.
>>
>> Things I tried (but to no effect),
>>
>> 1. make sure I am not doing any conversions on the strings
>> 2. make sure that the fields used in the key are all there and not
>> empty string (or else I toss the row out)
>>
>> My code is along following lines (split is using stringio to parse
>> csv, header removes the header row and parse_train is putting the 54
>> fields into named tuple after whitespace/quote removal):
>>
>> #Error for string argument is thrown on the BB.take(1) where the
>> groupbykey is evaluated
>>
>> A = sc.textFile("train.csv").filter(lambda x:not
>> isHeader(x)).map(split).map(parse_train).filter(lambda x: not x is
>> None)
>>
>> A.count()
>>
>> B = A.map(lambda k:
>>
>> ((k.srch_destination_id,k.srch_length_of_stay,k.srch_booking_window,k.srch_adults_count,
>> k.srch_children_count,k.srch_room_count),
>> (k[0:54])))
>> BB = B.groupByKey()
>> BB.take(1)
>>
>>
>> best fahad
>>
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>>
>
>
>
> --
> Best Regards
>
> Jeff Zhang
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