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GeezerVison is showing github.com — fix: Normalize Dask timestamps to UTC without a row-wise apply by Daksha1611 · Pull Request #6818 · feast-dev/feast Conversation
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What this PR does / why we need it:
A zero-row While fixing this I found the same mismatch on a second path: a column carrying a Both applies are replaced with Which issue(s) this PR fixes:Fixes #6817 Checks
Testing Strategy
New Verified end to end as well:
MiscPoint-in-time correctness is unaffected — I re-ran the
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There was an error while loading. Please reload this page. All reactions_normalize_timestamp made timestamp columns tz-aware with a row-wise apply
declaring meta="datetime64[ns, UTC]". meta only declares the dtype; the
partition gets whatever the lambda returns. With zero rows the lambda never
runs, so the computed column stayed tz-naive while meta claimed UTC, and the
tz-aware comparison in _filter_ttl then raised:
TypeError: Invalid comparison between dtype=datetime64[ns] and DatetimeArray
A zero-row entity_df is a normal case in batch scoring, when the upstream
query matched nothing for that run, so get_historical_features crashed rather
than returning an empty result.
A column carrying a non-UTC timezone diverged from the declared meta the same
way, because the lambda returned any value that already had tzinfo untouched.
Replace both applies with dd.to_datetime(..., utc=True), which localizes
tz-naive values, converts tz-aware ones, and yields the correct dtype for an
empty frame. It is also vectorized, so it avoids a Python-level call per row
on non-empty frames.
Signed-off-by: Daksha1611 <[email protected]>
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There was an error while loading. Please reload this page. AssigneesNo one assignedLabelsProjectsMilestoneNo milestoneDevelopmentSuccessfully merging this pull request may close these issues. get_historical_features raises TypeError on a zero-row entity_df (Dask/file offline store)Uh oh!
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