Implement groupby by multiple columns in Spark DataFrame API #501
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miracvbasaran
approved these changes
Oct 31, 2023
| max_groups_contributed: int, | ||
| max_contributions_per_group: int, | ||
| public_keys: Optional[Iterable[Any]] = None, | ||
| column: Optional[str] = None # deprecated |
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When will we remove this deprecated parameter?
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I'd say in a ~month (to be sure that everybody who uses this parameter migrate)
dvadym
commented
Nov 3, 2023
| max_groups_contributed: int, | ||
| max_contributions_per_group: int, | ||
| public_keys: Optional[Iterable[Any]] = None, | ||
| column: Optional[str] = None # deprecated |
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I'd say in a ~month (to be sure that everybody who uses this parameter migrate)
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DataFrame API allows to perform DP on DataFrames (now only Spark DataFrames are supported). In DataFrame API privacy_key, partition_key and values are specified by column names. Currently
partition_key(aka group by key) can be specified only by 1 column. This PR implements possibility to have multiple columns aspartition_key.