pull_requests: 1586558819
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| id | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
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| 1586558819 | PR_kwDOAMm_X85ekPdj | 8412 | closed | 0 | Minimize duplication in `map_blocks` task graph | 2448579 | Builds on #8560 - [x] Closes #8409 - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` cc @max-sixty ``` print(len(cloudpickle.dumps(da.chunk(lat=1, lon=1).map_blocks(lambda x: x)))) # 779354739 -> 47699827 print(len(cloudpickle.dumps(da.chunk(lat=1, lon=1).drop_vars(da.indexes).map_blocks(lambda x: x)))) # 15981508 ``` This is a quick attempt. I think we can generalize this to minimize duplication. The downside is that the graphs are not totally embarrassingly parallel any more. This PR:  vs main:  | 2023-11-03T18:30:02Z | 2024-01-03T04:10:17Z | 2024-01-03T04:10:15Z | 2024-01-03T04:10:15Z | d87ba61c957fc3af77251ca6db0f6bccca1acb82 | 0 | 3989c089f0eb9a9bfdcd95174ebb1e28bbe4b846 | 41d33f52f709a765fb0dbfb5b9b4f5ea55173053 | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/8412 |
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