Release 2022.9.0

[jrbourbeau]

Release version	2022.9.0
Planned release date	2022-09-02
Status	On-track
Release manager	@jrbourbeau

Best effort

Try to close before the release but will not block the release

• Enable automatic column projection for groupby aggregations dask#9442
• Shuffle-based groupby aggregation by default dask#9406
• Support tornado 6.2 distributed#6991

Blocker

Issues that would cause us to block and postpone the release if not fixed

• Revert "Fix co-assignment for binary operations" distributed#6985
• Revert "Limit incoming data transfers by amount of data" distributed#6994

Comments

cc @ian-r-rose @fjetter @quasiben @jakirkham

[fjetter]

dask/distributed#6614 introduced a significant performance regressions for at least one common type of dataframe operations (repartition + align + reduce), see also coiled/benchmarks#295

The regression increases average memory usage in our benchmarks by more than a factor of two, i.e. if a workload is affected this can cause critical failure and this should be treated as a release blocker.

[gjoseph92]

dask/distributed#6985 is the potential fix. I think getting this in should probably block the release so we can do more performance testing and tuning before releasing this behavior change.

[fjetter]

I suggest to include dask/distributed#6991 if nothing pops up there (tornado 6.2 support)

[fjetter]

Mea culpa. I got too excited and merged a PR we preferred to only merge after the release. dask/distributed#6994 for the revert

[jrbourbeau]

Alright, thanks all for the input here. All reported blockers have been resolves, so I'll start pushing out the release in a few minutes

[jrbourbeau]

2022.9.0 is on PyPI and conda-forge PRs are open:

• Release 2022.9.0 conda-forge/dask-core-feedstock#139
• Release 2022.9.0 conda-forge/distributed-feedstock#221
• Release 2022.9.0 conda-forge/dask-feedstock#194

[jrbourbeau]

Packages are on conda-forge and Docker images have been published. Thanks all!