issue_comments: 269572088
This data as json
| 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/1189#issuecomment-269572088 | https://api.github.com/repos/pydata/xarray/issues/1189 | 269572088 | MDEyOklzc3VlQ29tbWVudDI2OTU3MjA4OA== | 306380 | 2016-12-29T02:17:40Z | 2016-12-29T02:17:40Z | MEMBER | Can you remind me the motivation to use a spawning multiprocessing pool instead of a fork or forkserver solution? For mixed multi-threading/multi-processing would a local "distributed" scheduler suffice? This would be several single-threaded processes on a single machine. The scheduler would be aware of data locality and avoid inter-node communication when possible. |
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