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  • jhamman · 2 ✖

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  • Should we be testing against multiple dask schedulers? · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
453865008 https://github.com/pydata/xarray/issues/1971#issuecomment-453865008 https://api.github.com/repos/pydata/xarray/issues/1971 MDEyOklzc3VlQ29tbWVudDQ1Mzg2NTAwOA== jhamman 2443309 2019-01-13T20:58:20Z 2019-01-13T20:58:20Z MEMBER

Closing this now. The distributed integration test module seems to be covering our IO use cases well enough. I don't think we need to do anything here at this time.

 
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   Should we be testing against multiple dask schedulers? 302930480
371334589 https://github.com/pydata/xarray/issues/1971#issuecomment-371334589 https://api.github.com/repos/pydata/xarray/issues/1971 MDEyOklzc3VlQ29tbWVudDM3MTMzNDU4OQ== jhamman 2443309 2018-03-08T00:27:52Z 2018-03-08T00:27:52Z MEMBER

I managed to dig up some more information here. I was having a test failure in test_serializable_locks resulting in a traceback that looks like. ``` ... timeout_handle = self.add_timeout(self.time() + timeout, self.stop) self.start() if timeout is not None: self.remove_timeout(timeout_handle) if not future_cell[0].done():

      raise TimeoutError('Operation timed out after %s seconds' % timeout)

E tornado.ioloop.TimeoutError: Operation timed out after 10 seconds

../../../anaconda/envs/xarray36/lib/python3.6/site-packages/tornado/ioloop.py:457: TimeoutError ```

From then on we were using the distributed scheduler and any tests that used dask resulted in a additional timeout (or similar error).

Unfortunately, my attempts to provide a mcve have come up short. If I can come up with one, I'll report upstream but as it is, I can't really transfer this behavior outside of my example.

cc @mrocklin 

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   Should we be testing against multiple dask schedulers? 302930480

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