FEAT-#7117: Support building range-partitioning from an index level #7120
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…index level Signed-off-by: Dmitry Chigarev <dmitry.chigarev@intel.com>
Signed-off-by: Dmitry Chigarev <dmitry.chigarev@intel.com>
Signed-off-by: Dmitry Chigarev <dmitry.chigarev@intel.com>
dchigarev
commented
Mar 28, 2024
| if RangePartitioningGroupby.get(): | ||
| return tuple(df.sort_index() for df in dfs) |
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previously, the function was only sorting by index, however in case of the low amount of unique values in the index this approach may not work well, so sorting on column values as it appears to be more stable for dataframes
dchigarev
commented
Mar 28, 2024
| @@ -2453,7 +2454,7 @@ def _apply_func_to_range_partitioning( | |||
| Parameters | |||
| ---------- | |||
| key_columns : list of hashables | |||
| Columns to build the range partitioning for. | |||
| Columns to build the range partitioning for. Can't be specified along with `level`. | |||
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pandas.groupby.level doc says: "Do not specify both by and level.", so we're putting the same restriction
dchigarev
commented
Mar 28, 2024
| @@ -1726,7 +1746,7 @@ def test_groupby_getitem_preserves_key_order_issue_6154(): | |||
| ], | |||
| ) | |||
| def test_groupby_multiindex(groupby_kwargs): | |||
| frame_data = np.random.randint(0, 100, size=(2**6, 2**4)) | |||
| frame_data = np.random.randint(0, 100, size=(2**6, 2**6)) | |||
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increased the number from 16 to 64 to use multiple partitions
dchigarev
requested review from
devin-petersohn,
mvashishtha,
RehanSD,
YarShev,
vnlitvinov,
anmyachev and
a team
as code owners
7 tasks
YarShev
approved these changes
Apr 2, 2024
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What do these changes do?
Adds support for building range-partitioning based on an index level(s) and enables range-partitioning support for
df.groupby(level=...)cases.flake8 modin/ asv_bench/benchmarks scripts/doc_checker.pyblack --check modin/ asv_bench/benchmarks scripts/doc_checker.pygit commit -sdocs/development/architecture.rstis up-to-date