当我将 local
的值设置为1时,操作正常,但设置为2时,错误消息报告如下
from pyspark import SparkContext
# Changing 1 to 2 will give you an error
sc = SparkContext("local[2]", "sort")
class MySort:
def __init__(self, tup):
self.tup = tup
def __gt__(self, other):
if self.tup[0] > other.tup[0]:
return True
elif self.tup[0] == other.tup[0]:
if self.tup[1] >= other.tup[1]:
return True
else:
return False
else:
return False
r1 = sc.parallelize([(1, 2), (2, 2), (2, 3), (2, 1), (1, 3)])
r2 = r1.sortBy(MySort)
print(r2.collect())
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "E:\spark2.3.1\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 230, in main
File "E:\spark2.3.1\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 225, in process
File "E:\spark2.3.1\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 376, in dump_stream
bytes = self.serializer.dumps(vs)
File "E:\spark2.3.1\spark-2.3.1-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 555, in dumps
return pickle.dumps(obj, protocol)
_pickle.PicklingError: Can't pickle : attribute lookup MySort on __main__ failed
2 回答
我认为你需要在你的 class 中使用文件添加参数spark-submit:
--py-files your_file.py
因为spark需要将此类传递给另一个worker .
它真正有趣的属性我以前不知道它 . 我认为当你使用单核时,类不会被腌制(在其他地方使用类需要pickle) . 但你仍然可以使用函数(我假设你按前两个值排序值):