issue_comments: 399320127
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html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
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https://github.com/pydata/xarray/issues/2242#issuecomment-399320127 | https://api.github.com/repos/pydata/xarray/issues/2242 | 399320127 | MDEyOklzc3VlQ29tbWVudDM5OTMyMDEyNw== | 2443309 | 2018-06-22T04:51:54Z | 2018-06-22T04:51:54Z | MEMBER | I think, at least to some extent, the performance hit is to be expected. I don't think we should be opening the file more than once when using the serial or threaded schedulers so that may be a place where you can find some improvement. There will always be a performance hit when writing dask arrays to netcdf files chunk-by-chunk. For 1, there is a threading lock that limits parallel throughput. More importantly, the chunked writes are going to always be slower than larger reads coming directly from numpy arrays. In your example above, the snippit @shoyer mentions should evaluate to |
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