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/pull/1517#issuecomment-330701921,https://api.github.com/repos/pydata/xarray/issues/1517,330701921,MDEyOklzc3VlQ29tbWVudDMzMDcwMTkyMQ==,306380,2017-09-19T23:27:49Z,2017-09-19T23:27:49Z,MEMBER,"The heuristics we have are I think just of the form ""did you make way more chunks than you had previously"".  I can imagine other heuristics of the form ""some of your new chunks are several times larger than your previous chunks"".  In general these heuristics might be useful in several places.  It might make sense to build them in a `dask/array/utils.py` file.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,252358450
https://github.com/pydata/xarray/pull/1517#issuecomment-324732814,https://api.github.com/repos/pydata/xarray/issues/1517,324732814,MDEyOklzc3VlQ29tbWVudDMyNDczMjgxNA==,306380,2017-08-24T19:25:32Z,2017-08-24T19:25:32Z,MEMBER,"Yes if you don't care strongly about deduplication.  The following will be slower:

    b = (a.chunk(...) + 1) + (a.chunk(...) + 1)

In current operation this will be optimized to 

    tmp = a.chunk(...) + 1
    b = tmp + tmp

So you'll lose that, but I suspect that in your case chunking the same dataset many times is somewhat rare.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,252358450
https://github.com/pydata/xarray/pull/1517#issuecomment-324722153,https://api.github.com/repos/pydata/xarray/issues/1517,324722153,MDEyOklzc3VlQ29tbWVudDMyNDcyMjE1Mw==,306380,2017-08-24T18:43:30Z,2017-08-24T18:43:30Z,MEMBER,"I'm curious, how long does this line take:

    r = spearman_correlation(array1.chunk({'place': 10}), array2.chunk({'place': 10}), 'time')

Have you consider setting `name=False` in your from_array call by default when doing this?  I often avoid creating deterministic names when going back and forth rapidly between dask.array and numpy. 
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,252358450