Question

在使用dask.distributed时，我尝试在S3上的CSV中加载dask数据帧，如下所示：

@delayed
def func1():
    ...
    return df.read_csv(*s3_url*, ...)

read_csv（）不需要与分布式客户端进行交互，所以我认为它是可能的。然后在客户端计算机上，我计算 func1 返回的延迟对象。

res = func1()
future = client.compute(res)
progress(future)
frame = client.gather(future)

直到那一点看起来不错，打印结果

    Dask DataFrame Structure:
              COL1 COL2
npartitions=9
                      object           object
                         ...              ...
...                      ...              ...
                         ...              ...
                         ...              ...
Dask Name: from-delayed, 27 tasks

然而，当我尝试进一步处理它时，它失败了Failed to serialize (<dask.bytes.core.OpenFile object at ...>, ..., ..., '\n'). Exception: can't pickle thread.lock objects，例如

client.compute(frame)

有没有办法让这个方案奏效，或者我在这里错过了一些更基本的限制？

PS。我得到的错误日志：

.pickle - Failed to serialize (<dask.bytes.core.OpenFile object at ...>, 20971520, 10485760, '\n'). Exception: can't pickle thread.lock objects
ERROR:2017-11-10 15:31:31:root:Exception while executing graph: can't pickle thread.lock objects
Traceback (most recent call last):
  ...
    client.compute(res.data)
  File ".../python2.7/site-packages/distributed/client.py", line 2089, in compute
    resources=resources)
  File ".../python2.7/site-packages/distributed/client.py", line 1906, in _graph_to_futures
    'tasks': valmap(dumps_task, dsk3),
  File ".../python2.7/site-packages/toolz-0.8.2-py2.7.egg/toolz/dicttoolz.py", line 84, in valmap
    rv.update(zip(iterkeys(d), map(func, itervalues(d))))
  File ".../python2.7/site-packages/distributed/worker.py", line 731, in dumps_task
    'args': pickle.dumps(task[1:])}
  File ".../python2.7/site-packages/distributed/protocol/pickle.py", line 51, in dumps
    return cloudpickle.dumps(x, protocol=pickle.HIGHEST_PROTOCOL)
  File ".../python2.7/site-packages/cloudpickle/cloudpickle.py", line 829, in dumps
    cp.dump(obj)
  File ".../python2.7/site-packages/cloudpickle/cloudpickle.py", line 233, in dump
    return Pickler.dump(self, obj)
  File "...python2.7/pickle.py", line 224, in dump
    self.save(obj)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "...python2.7/pickle.py", line 568, in save_tuple
    save(element)
  File "...python2.7/pickle.py", line 331, in save
    self.save_reduce(obj=obj, *rv)
  File ".../python2.7/site-packages/cloudpickle/cloudpickle.py", line 727, in save_reduce
    save(state)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "...python2.7/pickle.py", line 655, in save_dict
    self._batch_setitems(obj.iteritems())
  File "...python2.7/pickle.py", line 687, in _batch_setitems
    save(v)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File ".../python2.7/site-packages/cloudpickle/cloudpickle.py", line 564, in save_instancemethod
    obj=obj)
  File ".../python2.7/site-packages/cloudpickle/cloudpickle.py", line 709, in save_reduce
    save(args)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "...python2.7/pickle.py", line 554, in save_tuple
    save(element)
  File "...python2.7/pickle.py", line 331, in save
    self.save_reduce(obj=obj, *rv)
  File ".../python2.7/site-packages/cloudpickle/cloudpickle.py", line 727, in save_reduce
    save(state)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "...python2.7/pickle.py", line 655, in save_dict
    self._batch_setitems(obj.iteritems())
  File "...python2.7/pickle.py", line 687, in _batch_setitems
    save(v)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "...python2.7/pickle.py", line 655, in save_dict
    self._batch_setitems(obj.iteritems())
  File "...python2.7/pickle.py", line 692, in _batch_setitems
    save(v)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "...python2.7/pickle.py", line 554, in save_tuple
    save(element)
  File "...python2.7/pickle.py", line 331, in save
    self.save_reduce(obj=obj, *rv)
  File ".../python2.7/site-packages/cloudpickle/cloudpickle.py", line 727, in save_reduce
    save(state)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "...python2.7/pickle.py", line 655, in save_dict
    self._batch_setitems(obj.iteritems())
  File "...python2.7/pickle.py", line 687, in _batch_setitems
    save(v)
  File "...python2.7/pickle.py", line 331, in save
    self.save_reduce(obj=obj, *rv)
  File ".../python2.7/site-packages/cloudpickle/cloudpickle.py", line 727, in save_reduce
    save(state)
  File "...python2.7/pickle.py", line 286, in save
    f(self, obj) # Call unbound method with explicit self
  File "...python2.7/pickle.py", line 655, in save_dict
    self._batch_setitems(obj.iteritems())
  File "...python2.7/pickle.py", line 687, in _batch_setitems
    save(v)
  File "...python2.7/pickle.py", line 306, in save
    rv = reduce(self.proto)
TypeError: can't pickle thread.lock objects

从懒惰加载来自CSV的dask数据帧（内部延迟）

0 个答案: