Comments (5)
Are there cases where shuffle=
isn't specific enough? All other things being equal, I think a shorter name is better
from dask.
shuffle for me is just very unspecific, could be a bool or something else. shuffle_method expresses the intent of the option very clearly. It's inconsistent with the config option as well
from dask.
shuffle for me is just very unspecific, could be a bool or something else. shuffle_method expresses the intent of the option very clearly. It's inconsistent with the config option as well
+1
from dask.
Hmm, there's a tradeoff between making things very explicit and having overly long parameter names. In my mind shuffle="p2p"
is clear enough (especially if it's clearly documented and used consistently as a keyword).
Though to be clear, I don't care a ton about this specific case -- my hope is most people are happy with the default shuffle algorithm and won't ever need to specify this option. I mostly just want to bring up the explicit vs. concise tradeoff to make sure we're considering it.
from dask.
shuffle for me is just very unspecific, could be a bool or something else. shuffle_method expresses the intent of the option very clearly. It's inconsistent with the config option as well
Note that the shuffle
keyword can be a bool
for groupby-aggregates:
dask/dask/dataframe/groupby.py
Lines 1332 to 1341 in 2d8f6d5
In light of this, renaming shuffle
to shuffle_method
for all the cases where only a method is accepted is even more relevant to highlight the distinction.
We may also want to reconsider dumping all kinds of things into shuffle
for groupby-aggregates.
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Related Issues (20)
- Docs build failing
- DEPR: pandas 3.0 deprecations and the migration to dask-expr
- Unexpected Results Caused by BigInt ID in numpy linspace HOT 1
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- Unstable grouping result when calling groupby apply on merged dask dataframes with missing values HOT 3
- `isinstance(Future, Future)` evaluates to `False` HOT 1
- linalg.solve has unexpected TypeError with cupy HOT 3
- Applying `functools.partial()` to a `@delayed`-decorated function changes the execution behavior
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- `read_parquet` doesn't handle nested objects (dicts, arrays) HOT 1
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- `test_split_adaptive_aggregate_files` failing on main HOT 4
- Deprecate fastparquet engine for read_parquet to enable switch to dask-expr HOT 1
- Boolean logic with shift seems broken
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- Breaking of concurrency when calling `dask.delayed` inside a `@dask.delayed`-decorated function HOT 5
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from dask.