我编写了一个map函数来使用itertools.groupby,我所做的事情如下。在
驱动程序代码
pair_count = df.mapPartitions(lambda iterable: pair_func_cnt(iterable))
pair_count.collection()
映射函数
^{pr2}$但它给出了以下错误
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$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
Python
pickle
无法序列化匿名函数。让我们用一个简单的例子来说明:在序列化之前,应删除对
^{pr2}$lambdas
的所有引用:或者不要使用
lambda
表达式:相关问题 更多 >
编程相关推荐