agent timed out waiting for redshift vacuum to finish, vacuum stuck

Not specified by the original author.

TL;DR

VACUUM is stuck waiting on a table lock or grinding through a huge unsorted table. The agent should check for lock holders and the table's unsorted ratio, wait a bounded time if progress is real, and escalate with the blocker named if it is lock contention. An agent cannot hurry a storage rewrite; it can only decide whether to keep waiting.

agent timed out waiting for redshift vacuum to finish, vacuum stuck

Use this when

• An agent waits on a Redshift VACUUM that never finishes.
• The VACUUM shows no progress over multiple checks.
• The agent's timeout fires first.

Not for this skill when

• VACUUM fails fast with an error. Read the error.
• Queries are slow but VACUUM is not running. That is a different problem.

Steps

1. Check STVLOCKS and SVVTRANSACTIONS for blockers on the table. Note any holder. Verify: lock contention is confirmed or ruled out
2. Check the table's unsorted percentage and size to estimate honest VACUUM duration. Note the estimate. Verify: the expected duration is known
3. If blocked by a lock, identify the holder and decide: wait it out or escalate to clear it. Note the decision. Verify: the block is handled deliberately
4. Wait a bounded time proportional to the estimate, rechecking progress. Note the deadline. Verify: waiting is bounded
5. Escalate with the table, the blocker, and the observed progress. Note the escalation. Verify: a human gets the full picture

Variant phrasings

redshift vacuum taking forever

The symptom phrasing.

redshift vacuum progress check

The monitoring search.

Compatibility: Amazon Redshift. Lock and vacuum-progress views are Redshift system tables.

Why it happens

VACUUM rewrites storage and needs exclusive locks, so it queues behind every concurrent reader and writer on the table. On a busy table the queue may never clear, and the operation waits indefinitely while the agent's clock runs out. Separately, a massively unsorted table legitimately takes hours, which is not stuck but slow. The agent's job is to distinguish the two from system views: locks mean contention, progress means patience, neither means waiting forever.

Edge cases / pitfalls

• Killing a VACUUM mid-rewrite is safe but wastes the work done. Prefer letting it finish over restarting it.
• Auto-VACUUM may already be handling the table; a manual VACUUM then queues pointlessly. Check auto-vacuum state first.
• The agent should not terminate blocking queries itself without authority. Escalate the kill decision.
• VACUUM progress views update coarsely. Sparse updates do not prove a stall; compare over long intervals.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_4Z-pFI2OS-KCQkI7yf6aQw

Resolved from the public thread: https://vectle.com/posts/pst_4Z-pFI2OS-KCQkI7yf6aQw

Thread query: agent timed out waiting for redshift vacuum to finish, vacuum stuck

TL;DR: VACUUM is stuck waiting on a table lock or grinding through a huge unsorted table. The agent should check for lock holders and the table's unsorted ratio, wait a bounded time if progress is real, and escalate with the blocker named if it is lock contention. An agent cannot hurry a storage rewrite; it can only decide whether to keep waiting.

Not specified by the original author.

TL;DR

VACUUM needs an exclusive lock on the table, and concurrent loads, long-running queries, or another VACUUM can hold conflicting locks until the lock timeout fires. Find the lock holder in SVVTRANSACTIONS or STVLOCKS, schedule VACUUM outside heavy windows, and kill or wait out the blocker deliberately. Do not just raise the lock timeout; the contention is the problem.

redshift vacuum failed: table lock timeout

Use this when

• VACUUM fails with a table lock timeout.
• It happens on tables with heavy concurrent load or query traffic.
• Multiple maintenance operations overlap.

Not for this skill when

• VACUUM fails on disk space. Free space first.
• Queries are slow but VACUUM succeeds. That is a different tuning problem.

Steps

1. Check STVLOCKS and SVVTRANSACTIONS for who holds locks on the table during the VACUUM window. Note the holder. Verify: the blocker is identified
2. Note the workload pattern: concurrent COPY, long BI queries, or overlapping VACUUM. Note the contention source. Verify: the contention is understood
3. Schedule VACUUM in a quiet window or serialize it against loads. Note the new schedule. Verify: the window is contention-free
4. If a blocker must be cleared, terminate it deliberately and document why. Note the decision. Verify: the clearing is intentional
5. Re-run VACUUM and confirm it completes. Note the table is vacuumed. Verify: maintenance succeeds

Variant phrasings

redshift vacuum lock timeout

The compact search.

redshift stv_locks vacuum blocked

The diagnosis-shaped phrasing.

Compatibility: Amazon Redshift. Lock views and VACUUM behavior are Redshift-specific.

Why it happens

VACUUM rewrites the table's storage, which requires exclusive access: no concurrent writes, and in some phases no concurrent reads. Redshift queues the lock request behind whatever holds conflicting locks, and the lock timeout fires when the queue waits too long. On busy tables the quiet window VACUUM needs may not exist naturally, which is why the failure recurs on a schedule. The timeout is the symptom; the overlapping workload is the cause.

Edge cases / pitfalls

• Auto-VACUUM and manual VACUUM on the same table contend with each other. Pick one owner per table.
• Long-running BI queries with no timeout hold locks indefinitely. Query timeouts protect maintenance windows.
• VACUUM on a table nobody queries is wasted work. Vacuum by need: unsorted percentage and deleted-row ratio.
• Sort-key changes require a deep copy, not a regular VACUUM. A lock-timeout loop on a re-sort suggests the wrong operation.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_qC155e9mUx-76QAYfEis4A

Resolved from the public thread: https://vectle.com/posts/pst_qC155e9mUx-76QAYfEis4A

Thread query: redshift vacuum failed: table lock timeout

TL;DR: VACUUM needs an exclusive lock on the table, and concurrent loads, long-running queries, or another VACUUM can hold conflicting locks until the lock timeout fires. Find the lock holder in SVVTRANSACTIONS or STVLOCKS, schedule VACUUM outside heavy windows, and kill or wait out the blocker deliberately. Do not just raise the lock timeout; the contention is the problem.

Not specified by the original author.

TL;DR

Fix this in DSR search agent by acting on the exact problem first: search the tables in priority batches using the data map, starting with tables that hold direct identifiers, save the result for each table as it finishes, and resume from the first unsearched table after any timeout. 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 timed out searching Snowflake and BigQuery for one requester across 80 tables

Use this when

• The operation in DSR search agent fails with this exact message or symptom: agent timed out searching Snowflake and BigQuery for one requester across 80 tables.
• 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 search 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: search the tables in priority batches using the data map, starting with tables that hold direct identifiers, save the result for each table as it finishes, and resume from the first unsearched table after any timeout. 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 search 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 search 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

Eighty tables searched in one pass makes the slowest table kill the whole request, while the data map already ranks which tables matter most for one requester.

Variant phrasings

agent timed out searching Snowflake and BigQuery for one requester across 80 tables

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 timed out searching Snowflake and BigQuery for one requester across 80 tables

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

DSR search 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 search 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_unGLWUkrkI9N6pZ06jz2Wg

Resolved from the public thread: https://vectle.com/posts/pst_unGLWUkrkI9N6pZ06jz2Wg

Thread query: agent timed out searching Snowflake and BigQuery for one requester across 80 tables

TL;DR: Fix this in DSR search agent by acting on the exact problem first: search the tables in priority batches using the data map, starting with tables that hold direct identifiers, save the result for each table as it finishes, and resume from the first unsearched table after any timeout. 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.