我设置显示正确连接到调度器(3 Linux操作系统Ubuntu 18.04和3吨款Windows 10的机器,调度是对运10台机器之一)集群。我得到的代码超时错误,我有当所有的操作系统都是赢10点前成功运行。
这是在其所有的荣耀错误:
tornado.application - ERROR - Multiple exceptions in yield list
Traceback (most recent call last):
File "C:\Apps\Anaconda\lib\site-packages\distributed\comm\core.py", line 186, in connect
quiet_exceptions=EnvironmentError)
File "C:\Apps\Anaconda\lib\site-packages\tornado\gen.py", line 1133, in run
value = future.result()
tornado.util.TimeoutError: Timeout
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Apps\Anaconda\lib\site-packages\tornado\gen.py", line 883, in callback
result_list.append(f.result())
File "C:\Apps\Anaconda\lib\site-packages\tornado\gen.py", line 1141, in run
yielded = self.gen.throw(*exc_info)
File "C:\Apps\Anaconda\lib\site-packages\distributed\core.py", line 634, in send_recv_from_rpc
comm = yield self.pool.connect(self.addr)
File "C:\Apps\Anaconda\lib\site-packages\tornado\gen.py", line 1133, in run
value = future.result()
File "C:\Apps\Anaconda\lib\site-packages\tornado\gen.py", line 1141, in run
yielded = self.gen.throw(*exc_info)
File "C:\Apps\Anaconda\lib\site-packages\distributed\core.py", line 745, in connect
connection_args=self.connection_args)
File "C:\Apps\Anaconda\lib\site-packages\tornado\gen.py", line 1133, in run
value = future.result()
File "C:\Apps\Anaconda\lib\site-packages\tornado\gen.py", line 1141, in run
yielded = self.gen.throw(*exc_info)
File "C:\Apps\Anaconda\lib\site-packages\distributed\comm\core.py", line 195, in connect
_raise(error)
File "C:\Apps\Anaconda\lib\site-packages\distributed\comm\core.py", line 178, in _raise
raise IOError(msg)
OSError: Timed out trying to connect to 'tcp://138.55.36.169:43033' after 10 s: connect() didn't finish in time
所以这个错误重复3次,每个IP是我的Linux机器之一。这使我相信,也许我不能在DASK集群中的多个操作系统,但我一直没能找到文件,说这样东西。我做得不对还是我只是错过这个地方?
工人们都需要能够序列化和反序列化有效功能。所以,如果您使用的是可以在一个操作系统被序列化和反序列化对其他仍然执行的功能和数据,那么事情应该罚款。
原则上,这是事实。 Python函数应该在任何地方工作。但在实践中,如果,例如,您目前有一台机器上,但没有其他话就不会有问题库这可能会断裂。
你提出的错误可能是出于多种原因,包括不同版本的Python或网络问题。
我建议致电以下检查相关库的版本是在您DASK工人和客户端一样。
client.get_versions(check=True)