[Datasets] Implement push-based shuffle #24281
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Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
Co-authored-by: Clark Zinzow <clarkzinzow@gmail.com>
stephanie-wang
requested review from
ericl,
scv119,
clarkzinzow and
jjyao
as code owners
clarkzinzow
approved these changes
Apr 28, 2022
ericl
approved these changes
Apr 28, 2022
scv119
approved these changes
Apr 28, 2022
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The simple shuffle currently implemented in Datasets does not reliably scale past 1000+ partitions due to metadata and I/O overhead.
This PR adds an experimental shuffle implementation for a "push-based shuffle", as described in this paper draft. This algorithm should see better performance at larger data scales. The algorithm works by merging intermediate map outputs at the reducer side while other map tasks are executing. Then, a final reduce task merges these merged outputs.
Currently, the PR exposes this option through the DatasetContext. It can also be set through a hidden OS environment variable (RAY_DATASET_PUSH_BASED_SHUFFLE). Once we have more comprehensive benchmarks, we can better document this option and allow the algorithm to be chosen at run time.
Redo for #23758 to fix CI.