pickle.PicklingError：无法腌制未打开读取的文件

我在 Dataproc 上运行 PySpark 作业时收到此错误。可能是什么原因？

这是错误的堆栈跟踪。

  File "/usr/lib/python2.7/pickle.py", line 331, in save
  self.save_reduce(obj=obj, *rv)
  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/cloudpickle.py", 
  line 553, in save_reduce
  File "/usr/lib/python2.7/pickle.py", line 286, in save
  f(self, obj) # Call unbound method with explicit self
  File "/usr/lib/python2.7/pickle.py", line 649, in save_dict
  self._batch_setitems(obj.iteritems())
  File "/usr/lib/python2.7/pickle.py", line 681, in _batch_setitems
  save(v)
  File "/usr/lib/python2.7/pickle.py", line 286, in save
  f(self, obj) # Call unbound method with explicit self
  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/cloudpickle.py", 
  line 582, in save_file
  pickle.PicklingError: Cannot pickle files that are not opened for reading

问题是我在 Map 函数中使用了字典。 它失败的原因是：工作节点无法访问我在映射函数中传递的字典。

解决方案：

I broadcasted the dictionary and then used it in function (Map)
sc =  SparkContext()
lookup_bc = sc.broadcast(lookup_dict)

然后在函数中，我通过使用这个来获取价值：

data = lookup_bc.value.get(key)