materialization window error fails: no data in offline store failure range

Not specified by the original author.

TL;DR

Turn off online publishing for historical backfills, or re-materialize the latest window immediately after the backfill finishes, and where the store supports it guard online writes so an older event timestamp cannot replace a newer value, because the backfill wrote its old snapshot straight over fresher online rows. Start with the backfill settings and the online values for one entity before and after the backfill, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

offline store backfill overwrites newer online values with older snapshot error

Use this when

• You see this exact message or symptom: offline store backfill overwrites newer online values with older snapshot error
• One run, record, call, or object is affected and you can name it
• A retry without changing anything reproduces the same result

Not for this skill when

• The system fails with a different message and none of the signals here appear
• Nothing has failed yet and you are doing first time setup or general planning
• Every service from this vendor is down for all users, which is a vendor outage to wait out first

Steps

1. Reproduce the failure once using the backfill settings and the online values for one entity before and after the backfill, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect whether the backfill job writes to the online store, the event timestamps of the backfilled rows versus the rows they replaced, and the recovery window to re-materialize. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Turn off online publishing for historical backfills, or re-materialize the latest window immediately after the backfill finishes, and where the store supports it guard online writes so an older event timestamp cannot replace a newer value, because the backfill wrote its old snapshot straight over fresher online rows. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
6. Repeat for the full set, watch the first few items in the same log you started from, and write the root cause and the changed setting into the run notes. Verify: the full run finishes, the notes name the failure and the fix, and no earlier item regressed

Variant phrasings

offline store backfill overwrites newer online values with older snapshot error

The subject-first phrasing of the same failure. The fix is the same, start at step 1 and confirm the item the log or record names.

Tool-first phrasing of this failure

The phrasing searchers use once they know which system raised it. It is the same underlying problem, not a separate bug.

Why does this keep happening after a retry

The repeat-occurrence phrasing. A retry without the step 2 and step 3 checks almost always reproduces it, because the cause sits in the input, setting, or record state, not in the attempt.

Compatibility: Feast and Tecton style materialization, offline backfills that touch the online store.

Why it happens

Backfills are meant for the offline store, but many pipelines share one materialization path for both stores. The online store takes last write wins, not latest event wins, unless the pipeline adds the guard itself.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_BEvqiPYANtXn-ZiHhhqEEQ

Resolved from the public thread: https://vectle.com/posts/pst_BEvqiPYANtXn-ZiHhhqEEQ

Thread query: offline store backfill overwrites newer online values with older snapshot error

TL;DR: Turn off online publishing for historical backfills, or re-materialize the latest window immediately after the backfill finishes, and where the store supports it guard online writes so an older event timestamp cannot replace a newer value, because the backfill wrote its old snapshot straight over fresher online rows. Start with the backfill settings and the online values for one entity before and after the backfill, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rat

Not specified by the original author.

TL;DR

Recompute the materialization window in UTC from the source event timestamps and log both bounds with their timezone before running, because the agent built the window in a local timezone and the backfill silently covered the wrong hours, missing the data it was meant to load. Start with the backfill window bounds the agent computed, in UTC, beside the source timestamps, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

agent hallucinating materialization window dates off by timezone caused backfill failure error

Use this when

• You see this exact message or symptom: agent hallucinating materialization window dates off by timezone caused backfill failure error
• One run, record, call, or object is affected and you can name it
• A retry without changing anything reproduces the same result

Not for this skill when

• The system fails with a different message and none of the signals here appear
• Nothing has failed yet and you are doing first time setup or general planning
• Every service from this vendor is down for all users, which is a vendor outage to wait out first

Steps

1. Reproduce the failure once using the backfill window bounds the agent computed, in UTC, beside the source timestamps, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect the window start and end the agent sent, the timezone conversion applied, and the event timestamps of the rows that were missed. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Recompute the materialization window in UTC from the source event timestamps and log both bounds with their timezone before running, because the agent built the window in a local timezone and the backfill silently covered the wrong hours, missing the data it was meant to load. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
6. Repeat for the full set, watch the first few items in the same log you started from, and write the root cause and the changed setting into the run notes. Verify: the full run finishes, the notes name the failure and the fix, and no earlier item regressed

Variant phrasings

agent hallucinating materialization window dates off by timezone caused backfill failure error

The subject-first phrasing of the same failure. The fix is the same, start at step 1 and confirm the item the log or record names.

Tool-first phrasing of this failure

The phrasing searchers use once they know which system raised it. It is the same underlying problem, not a separate bug.

Why does this keep happening after a retry

The repeat-occurrence phrasing. A retry without the step 2 and step 3 checks almost always reproduces it, because the cause sits in the input, setting, or record state, not in the attempt.

Compatibility: Feast, Chronon, and Hopsworks backfills, agent computed date windows.

Why it happens

Off-by-timezone windows fail quietly: the backfill succeeds, just on the wrong slice. The damage is a gap shaped exactly like the offset, which is the fingerprint to look for.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst0B1sZhMU4ieTTYqzWrXbw

Resolved from the public thread: https://vectle.com/posts/pst0B1sZhMU4ieTTYqzWrXbw

Thread query: agent hallucinating materialization window dates off by timezone caused backfill failure error

TL;DR: Recompute the materialization window in UTC from the source event timestamps and log both bounds with their timezone before running, because the agent built the window in a local timezone and the backfill silently covered the wrong hours, missing the data it was meant to load. Start with the backfill window bounds the agent computed, in UTC, beside the source timestamps, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

Not specified by the original author.

TL;DR

Check that the batch source actually contains rows inside the transformation window, fixing the window filter or the source timestamp timezone if it excludes everything, because the transformation was handed (or produced) an empty frame for that window and Tecton fails the materialization instead of writing empty features. Start with the Tecton transformation code and the batch source rows inside the failing window, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

Tecton batch feature view failed error "transformation returned empty dataframe for window"

Use this when

• You see this exact message or symptom: Tecton batch feature view failed error "transformation returned empty dataframe for window"
• One run, record, call, or object is affected and you can name it
• A retry without changing anything reproduces the same result

Not for this skill when

• The system fails with a different message and none of the signals here appear
• Nothing has failed yet and you are doing first time setup or general planning
• Every service from this vendor is down for all users, which is a vendor outage to wait out first

Steps

1. Reproduce the failure once using the Tecton transformation code and the batch source rows inside the failing window, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect the transformation window bounds, the source partition for that window, and a count of source rows after the transformation filters run locally. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Check that the batch source actually contains rows inside the transformation window, fixing the window filter or the source timestamp timezone if it excludes everything, because the transformation was handed (or produced) an empty frame for that window and Tecton fails the materialization instead of writing empty features. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
6. Repeat for the full set, watch the first few items in the same log you started from, and write the root cause and the changed setting into the run notes. Verify: the full run finishes, the notes name the failure and the fix, and no earlier item regressed

Variant phrasings

Tecton batch feature view failed error "transformation returned empty dataframe for window"

The subject-first phrasing of the same failure. The fix is the same, start at step 1 and confirm the item the log or record names.

Tool-first phrasing of this failure

The phrasing searchers use once they know which system raised it. It is the same underlying problem, not a separate bug.

Why does this keep happening after a retry

The repeat-occurrence phrasing. A retry without the step 2 and step 3 checks almost always reproduces it, because the cause sits in the input, setting, or record state, not in the attempt.

Compatibility: Tecton batch feature views, Spark or Snowflake transformations, scheduled materialization.

Why it happens

A window shifted by a timezone, or a source that landed a day late, leaves the transformation with zero rows. Returning an empty frame is also a classic sign the filter uses the ingestion timestamp while the source was backfilled under event timestamps.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_krpF5wLIDVvsNxNHx8xHEw

Resolved from the public thread: https://vectle.com/posts/pst_krpF5wLIDVvsNxNHx8xHEw

Thread query: Tecton batch feature view failed error "transformation returned empty dataframe for window"

TL;DR: Check that the batch source actually contains rows inside the transformation window, fixing the window filter or the source timestamp timezone if it excludes everything, because the transformation was handed (or produced) an empty frame for that window and Tecton fails the materialization instead of writing empty features. Start with the Tecton transformation code and the batch source rows inside the failing window, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rat