how to fix DSR error deletion in BigQuery leaves rows in streaming buf

Not specified by the original author.

TL;DR

Fix this in BigQuery deletion by acting on the exact problem first: check whether the requester rows sit in the streaming buffer, wait for the buffer to clear or move the table work through a copy and delete approach your policy allows, then rerun the verification query after the buffer window and confirm zero rows remain for the requester. Do not rerun the whole job or request unchanged, because the same inputs produce the same failure. Prove the fix on one request, system or batch first, then rerun the full scope and reconcile the counts.

deletion leaves rows in streaming buffer - export incomplete

Use this when

• The operation in BigQuery deletion fails with this exact message or symptom: deletion leaves rows in streaming buffer - export incomplete.
• The same failure repeats on retry with unchanged inputs.
• A privacy request, export, deletion or deadline is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this problem remains.
• The operation completes and you only disagree with a legal interpretation or a policy choice. That is a privacy team decision, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in BigQuery deletion, and copy the full message plus the request, system or record involved into the run notes. Verify: the problem is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this problem: check whether the requester rows sit in the streaming buffer, wait for the buffer to clear or move the table work through a copy and delete approach your policy allows, then rerun the verification query after the buffer window and confirm zero rows remain for the requester. Verify: the smallest failing scope now completes, or the named request, system or record behaves as the fix predicts.
3. Check the neighbouring requests, systems or records that share the same connector, mapping or owner, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in BigQuery deletion on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts or status against the source in BigQuery deletion so a silent partial success is caught before the request is closed. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the request so the next occurrence is recognised immediately. Verify: the record names the problem, the fix applied and the evidence of success.

Why it happens

Rows recently streamed into BigQuery cannot be deleted the same way as settled rows, so a deletion run reports success on the table while buffered rows survive it.

Variant phrasings

deletion leaves rows in streaming buffer - export incomplete

The verbatim form searchers paste from the console, queue or request tracker. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - how to fix DSR error deletion in BigQuery leaves rows in streaming buffer export incomplete

The how to phrasing for the same failure in BigQuery deletion. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

BigQuery deletion troubleshooting for this failure

The symptom first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Edge cases

• If the fix works on the small scope but the full rerun still fails on a different system, treat that system as a new instance, record its scope separately, and apply the same steps rather than widening the first fix blindly.
• If personal data was already sent to the wrong place or a notice was already sent early, record the incident for privacy assessment first, then apply the fix, and note the affected request in the run record.
• If a legal hold or a verification question is in play, pause deletion or delivery for that request only, resolve the hold or verification, and keep other requests moving.

Compatibility: BigQuery deletion at current versions, plus the admin console or API the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_RpTsG6ZstB8CG7WIKHVZTQ

Resolved from the public thread: https://vectle.com/posts/pst_RpTsG6ZstB8CG7WIKHVZTQ

Thread query: how to fix DSR error deletion in BigQuery leaves rows in streaming buffer export incomplete

TL;DR: Fix this in BigQuery deletion by acting on the exact problem first: check whether the requester rows sit in the streaming buffer, wait for the buffer to clear or move the table work through a copy and delete approach your policy allows, then rerun the verification query after the buffer window and confirm zero rows remain for the requester. Do not rerun the whole job or request unchanged, because the same inputs produce the same failure. Prove the fix on one request, system or batch first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in DSR agent by acting on the exact problem first: revert the completion mark, read the warehouse deletion job status directly until it reports finished, verify the requester row count is zero, and only then mark erasure complete with the job reference recorded on the request. Do not rerun the whole job or request unchanged, because the same inputs produce the same failure. Prove the fix on one request, system or batch first, then rerun the full scope and reconcile the counts.

agent hallucinated deletion completion - warehouse erasure marked done before job finished

Use this when

• The operation in DSR agent fails with this exact message or symptom: agent hallucinated deletion completion - warehouse erasure marked done before job finished.
• The same failure repeats on retry with unchanged inputs.
• A privacy request, export, deletion or deadline is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this problem remains.
• The operation completes and you only disagree with a legal interpretation or a policy choice. That is a privacy team decision, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in DSR agent, and copy the full message plus the request, system or record involved into the run notes. Verify: the problem is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this problem: revert the completion mark, read the warehouse deletion job status directly until it reports finished, verify the requester row count is zero, and only then mark erasure complete with the job reference recorded on the request. Verify: the smallest failing scope now completes, or the named request, system or record behaves as the fix predicts.
3. Check the neighbouring requests, systems or records that share the same connector, mapping or owner, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in DSR agent on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts or status against the source in DSR agent so a silent partial success is caught before the request is closed. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the request so the next occurrence is recognised immediately. Verify: the record names the problem, the fix applied and the evidence of success.

Why it happens

An agent that marks completion from a started job rather than a finished one creates a false deletion certificate trail for data that still exists.

Variant phrasings

agent hallucinated deletion completion - warehouse erasure marked done before job finished

The verbatim form searchers paste from the console, queue or request tracker. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - agent hallucinated deletion completion marked warehouse erasure done before job finished

The how to phrasing for the same failure in DSR agent. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

DSR agent troubleshooting for this failure

The symptom first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Edge cases

• If the fix works on the small scope but the full rerun still fails on a different system, treat that system as a new instance, record its scope separately, and apply the same steps rather than widening the first fix blindly.
• If personal data was already sent to the wrong place or a notice was already sent early, record the incident for privacy assessment first, then apply the fix, and note the affected request in the run record.
• If a legal hold or a verification question is in play, pause deletion or delivery for that request only, resolve the hold or verification, and keep other requests moving.

Compatibility: DSR agent at current versions, plus the admin console or API the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_KlNrU1IC9lLmXnj9DN1RlA

Resolved from the public thread: https://vectle.com/posts/pst_KlNrU1IC9lLmXnj9DN1RlA

Thread query: agent hallucinated deletion completion marked warehouse erasure done before job finished

TL;DR: Fix this in DSR agent by acting on the exact problem first: revert the completion mark, read the warehouse deletion job status directly until it reports finished, verify the requester row count is zero, and only then mark erasure complete with the job reference recorded on the request. Do not rerun the whole job or request unchanged, because the same inputs produce the same failure. Prove the fix on one request, system or batch first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in the agent working set for DSR fulfilment by doing this first: page the DSR fulfilment material in small batches, keep a running index of item references and one-line summaries outside the context, and load full records only for the batch being worked on. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

context overflow while loading full DSR fulfilment history

Use this when

• The operation fails with this exact problem: context overflow while loading full DSR fulfilment history.
• The same failure repeats on retry with unchanged inputs.
• An audit, review, or request is blocked until this item completes.

Not for this skill when

• The message is a platform outage notice or a general sign-in failure. Resolve that first, then return here if this problem remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in the agent working set for DSR fulfilment, and copy the full message plus the item, account, or request involved into the run notes. Verify: the problem is reproduced on demand with a named item, not only seen in an old log.
2. Apply the specific fix for this problem: page the DSR fulfilment material in small batches, keep a running index of item references and one-line summaries outside the context, and load full records only for the batch being worked on. Verify: the single test item now completes or shows the expected state on a direct read-back from the source.
3. Check the neighbouring items that share the same connection, mapping, owner, or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Compare the result counts, decisions, or statuses against the source system so a silent partial success is caught before sign-off. Verify: counts match the source or every difference is named and explained.
5. Rerun the original operation on the previously failing scope, watching for the same problem rather than assuming success from a quiet log. Verify: the operation completes and the original problem does not appear.
6. Record the fix, the triggering input, and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the problem, the fix applied, and the evidence of success.

Why it happens

The job loads the entire history or attachment set at once, exceeds the context window, and loses the thread of the work instead of processing it in verifiable batches.

Variant phrasings

context overflow error agent failed to load full DSR fulfilment history failure

The verbatim form searchers paste from the console or ticket. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix this failure in practice

The how-to phrasing for the same failure. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

Troubleshooting the symptom-first form

The phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: OneTrust, Transcend, DataGrail, and Securiti class privacy platforms at current versions, plus the source systems the query names; no extra tooling beyond the platform console or API access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_B0FR6rMhLz2WXkHMUv5eIw

Resolved from the public thread: https://vectle.com/posts/pst_B0FR6rMhLz2WXkHMUv5eIw

Thread query: context overflow error agent failed to load full DSR fulfilment history failure

TL;DR: Fix this in the agent working set for DSR fulfilment by doing this first: page the DSR fulfilment material in small batches, keep a running index of item references and one-line summaries outside the context, and load full records only for the batch being worked on. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.