html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1440#issuecomment-306617217,https://api.github.com/repos/pydata/xarray/issues/1440,306617217,MDEyOklzc3VlQ29tbWVudDMwNjYxNzIxNw==,1217238,2017-06-06T21:05:56Z,2017-06-06T21:05:56Z,MEMBER,"I think its unavoidable that users understand how their data will be processed (e.g., whether operations will be mapped over time or space). But maybe some sort of heuristics (if not a fully automated solution) are possible.

For example, maybe `chunks={'time'}` (note the `set` rather than a `dict`) could indicate ""divide me into automatically chosen chunks over the `time` dimension"". It's still explicit about how chunking is being done, but comes closer to expressing the intent rather than the details.","{""total_count"": 5, ""+1"": 5, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,233350060
https://github.com/pydata/xarray/issues/1440#issuecomment-306009664,https://api.github.com/repos/pydata/xarray/issues/1440,306009664,MDEyOklzc3VlQ29tbWVudDMwNjAwOTY2NA==,1217238,2017-06-04T00:28:19Z,2017-06-04T00:28:19Z,MEMBER,"My main concern is that netCDF4 chunk sizes (e.g., ~10-100KB in that blog post) are often much smaller than well sized dask chunks (10-100MB, per the [Dask FAQ](http://dask.pydata.org/en/latest/faq.html)).

I do think it would be appropriate to issue a warning if you are making dask chunks that *don't* line up nicely with chunks on disk to avoid performance issues (in general each chunk on disk should usually end up on only one chunk in dask), but there are lots of options for aggregating to larger chunks and it's hard to choose the best way to do that without knowing how the data will be used.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,233350060