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feat: Offline Store historical features retrieval based on datetime range in Ray by aniketpalu · Pull Request #5738 · feast-dev/feast · GitHub
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feat: Offline Store historical features retrieval based on datetime range in Ray #5738

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Merged
ntkathole merged 5 commits into from
Dec 30, 2025
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feat: Offline Store historical features retrieval based on datetime range in Ray #5738

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1b5aebe
feat: Offline Store historical features retrieval based on datetime r…
aniketpalu Nov 25, 2025
de8b2c5
Reforamatted code to fix lint issues
aniketpalu Nov 25, 2025
c25280c
preserve event_timestamp in non-entity mode for correct point-in-time…
aniketpalu Dec 26, 2025
0c20ac0
Minor lint changes
aniketpalu Dec 26, 2025
f589956
Added test cases for datetime range based feature retrieval in Ray
aniketpalu Dec 29, 2025
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Minor lint changes 
Signed-off-by: Aniket Paluskar <apaluska@redhat.com>
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@aniketpalu @ntkathole
aniketpalu authored and ntkathole committed Dec 30, 2025
commit 0c20ac078adb25d2dedd251e22581d772cd1d4c4
4 changes: 1 addition & 3 deletions sdk/python/feast/infra/offline_stores/contrib/ray_offline_store/ray.py
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Expand Up @@ -1237,9 +1237,7 @@ def _filter_range(batch: pd.DataFrame) -> pd.Series:
return _filter_range


def _make_select_distinct_entity_timestamps(
join_keys: List[str], timestamp_field: str
):
def _make_select_distinct_entity_timestamps(join_keys: List[str], timestamp_field: str):
# Why: factory function for distinct (entity_keys, event_timestamp) projection in Ray map_batches
# This preserves multiple transactions per entity ID with different timestamps for proper PIT joins
def _select_distinct_entity_timestamps(batch: pd.DataFrame) -> pd.DataFrame:
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