Feast BigQuery offline store failed error "NotFound: table was not found in location US"

Not specified by the original author.

TL;DR

Point the source at the dataset and table that exist, in the location they actually live in, by setting the BigQuery dataset location in the offline store config to match (for example a regional dataset instead of US), because BigQuery refuses a table lookup when the query location and the dataset location differ. Start with the Feast BigQuery source config and the dataset location in the BigQuery console, 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.

Feast BigQuery offline store failed error "NotFound: table was not found in location US"

Use this when

• You see this exact message or symptom: Feast BigQuery offline store failed error "NotFound: table was not found in location US"
• 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 Feast BigQuery source config and the dataset location in the BigQuery console, 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 fully qualified table name in the data source, the dataset location shown in BigQuery, and the location value in the offline store config. 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: Point the source at the dataset and table that exist, in the location they actually live in, by setting the BigQuery dataset location in the offline store config to match (for example a regional dataset instead of US), because BigQuery refuses a table lookup when the query location and the dataset location differ. 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

Feast BigQuery offline store failed error "NotFound: table was not found in location US"

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 0.36 or later, BigQuery offline store, datasets in US, EU, or single regions.

Why it happens

Datasets created outside the console often land in a region while Feast defaults to the US multi-region. BigQuery treats a location mismatch as not found rather than as a location error, which sends people hunting for a deleted table that still exists.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstDDkuExmqgVfN3sqkjBjpg

Resolved from the public thread: https://vectle.com/posts/pstDDkuExmqgVfN3sqkjBjpg

Thread query: Feast BigQuery offline store failed error "NotFound: table was not found in location US"

TL;DR: Point the source at the dataset and table that exist, in the location they actually live in, by setting the BigQuery dataset location in the offline store config to match (for example a regional dataset instead of US), because BigQuery refuses a table lookup when the query location and the dataset location differ. Start with the Feast BigQuery source config and the dataset location in the BigQuery console, 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 r

Not specified by the original author.

TL;DR

Grant the identity that runs materialization read and write access on the offline bucket named in the error, and confirm the bucket name and project in the FileSource or BigQuery source config match the bucket the policy was set on, because the job cannot even list objects to start the load. Start with the Feast materialization job identity and the GCS offline bucket policy, 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.

Feast materialize failed error "PermissionError: cannot list objects in GCS offline bucket"

Use this when

• You see this exact message or symptom: Feast materialize failed error "PermissionError: cannot list objects in GCS offline bucket"
• 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 Feast materialization job identity and the GCS offline bucket policy, 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 service account the materialization job runs as, the bucket IAM policy, and the bucket path in feature_store.yaml and the data source definition. 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: Grant the identity that runs materialization read and write access on the offline bucket named in the error, and confirm the bucket name and project in the FileSource or BigQuery source config match the bucket the policy was set on, because the job cannot even list objects to start the 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

Feast materialize failed error "PermissionError: cannot list objects in GCS offline bucket"

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 0.36 or later, GCS offline store, materialization from Cloud Run, Airflow, or a VM job.

Why it happens

Feast itself runs fine locally where your own credentials apply, which hides the problem until a scheduled job runs under a different, narrower identity. A list denial is the first call the job makes, so nothing partial is written.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_Nn-3e9VIdhprrlhuN7fVcw

Resolved from the public thread: https://vectle.com/posts/pst_Nn-3e9VIdhprrlhuN7fVcw

Thread query: Feast materialize failed error "PermissionError: cannot list objects in GCS offline bucket"

TL;DR: Grant the identity that runs materialization read and write access on the offline bucket named in the error, and confirm the bucket name and project in the FileSource or BigQuery source config match the bucket the policy was set on, because the job cannot even list objects to start the load. Start with the Feast materialization job identity and the GCS offline bucket policy, 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

Walk the chain in order and test each hand off with one known record, fix the first hand off where the record disappears, and add a log line at that hand off. Start in the Feast registry and the materialization job log, work on one affected item, and prove the fix there before running the full set. Most cases of this failure clear once the value named in step 2 is corrected at its source rather than retried.

feast materialize failed with error: no feature views found in registry

Use this when

• You see this exact message or symptom in Feast: feast materialize failed with error: no feature views found in registry
• One run, record, build, or object is affected and you can name it
• A retry without changing anything reproduces the same text

Not for this skill when

• Feast 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 in the Feast registry and the materialization job log and search the log or history for the exact text in the block above, recording the time, the workspace or project, and the one object it names. Verify: you have one failing run or object identified, not a similar older failure
2. Inspect feature_store.yaml, the feature view definition, the entity definition, and the TTL on the view, and check the hand off where the test record stopped, the condition or field it failed, and the log line added there. Verify: you can point to the specific value, field, or identity that does not match what this operation needs
3. Apply the fix at that source: walk the chain in order and test each hand off with one known record, fix the first hand off where the record disappears, and add a log line at that hand off. Verify: the corrected value or setting is visible in Feast itself, not only in a local config file
4. Re-run the original operation on the single affected item first: run feast apply, then feast materialize for a short window covering only the affected feature view. Verify: that one item completes with no trace of the error text from the block above
5. Check the downstream result a user or the next job would see: an online retrieval for one known entity and a gethistoricalfeatures call for the same entity and timestamp. Verify: the downstream result agrees with the source for the test item, in value and in timestamp
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 error and the changed setting, and no earlier item regressed

Variant phrasings

feast materialize failed with error: no feature views found in registry

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

Feast version of this failure

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

Why does feast materialize failed with error: no feature views found in registry 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 object state, not in the attempt.

Compatibility: Feast 0.36 or later, Python feature definitions, Redis or DynamoDB online store, Parquet or warehouse offline store. The steps assume you can read the job or build log and change the named object in Feast.

Why it happens

In Feast, this failure usually means one step in the chain checks a condition or a field that the earlier steps no longer produce, so the chain stops silently at that check. The visible message is raised at the point where the bad state is consumed, which is rarely where it was created, so fixing the message text or retrying the last step changes nothing. Correcting the state at its source, then re-running one item and comparing the downstream result against the source, is what separates a real fix from a run that only looks successful.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_Ff311dQtiHmyfBXcsp6v0g

Resolved from the public thread: https://vectle.com/posts/pst_Ff311dQtiHmyfBXcsp6v0g

Thread query: feast materialize failed with error: no feature views found in registry

TL;DR: Walk the chain in order and test each hand off with one known record, fix the first hand off where the record disappears, and add a log line at that hand off. Start in the Feast registry and the materialization job log, work on one affected item, and prove the fix there before running the full set. Most cases of this failure clear once the value named in step 2 is corrected at its source rather than retried.