Hi
I wrote a map function to aggregate data in a partition, and this function
using itertools.groupby for more than twice, then there comes the pickle
error .
Here is what I do
===Driver Code===
pair_count = df.mapPartitions(lambda iterable: pair_func_cnt(iterable))
pair_count.collection()
===Map Function ===
def pair_func_cnt(iterable):
from itertools import groupby
ls = [[1,2,3],[1,2,5],[1,3,5],[2,4,6]]
grp1 = [(k,g) for k,g in groupby(ls, lambda e: e[0])]
grp2 = [(k,g) for k,g in groupby(grp1, lambda e: e[1])]
return iter(grp2)
===Error Message===
Caused by: org.apache.spark.api.python.PythonException: Traceback
(most recent call last):
File
"/opt/zeppelin-0.6.0-bin-netinst/interpreter/spark/pyspark/pyspark.zip/pyspark/worker.py",
line 111, in main
process()
File
"/opt/zeppelin-0.6.0-bin-netinst/interpreter/spark/pyspark/pyspark.zip/pyspark/worker.py",
line 106, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File
"/opt/zeppelin-0.6.0-bin-netinst/interpreter/spark/pyspark/pyspark.zip/pyspark/serializers.py",
line 267, in dump_stream
bytes = self.serializer.dumps(vs)
File
"/opt/zeppelin-0.6.0-bin-netinst/interpreter/spark/pyspark/pyspark.zip/pyspark/serializers.py",
line 415, in dumps
return pickle.dumps(obj, protocol)PicklingError: Can't pickle
<type 'itertools._grouper'>: attribute lookup itertools._grouper
failed
at
org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at
org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$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
