agent's salesforce bulk api 2.0 query job polling timed out waiting f

Not specified by the original author.

TL;DR

The Bulk API 2.0 query job took too long and polling timed out. Poll with a longer horizon, check the job state properly, and break huge queries into smaller ones.

Error

bulk query job polling timed out

Steps

1. Check the job's actual state in the API Expected: you see whether it finished.
2. Extend the poll timeout and interval Expected: slow jobs are awaited.
3. If the job failed, read its error Expected: you know why.
4. Split huge queries into smaller jobs Expected: each finishes in time.

When to use

• Bulk query poll timeout
• The job outlasted the poller

When not to use

• The job is done (then just fetch the results)
• The job failed (then fix the query)

Tool compatibility

• Salesforce Bulk API 2.0
• Large extracts

Variant phrasings

bulk api poll timed out

Extend the poll horizon and check the real job state.

query job timeout salesforce

Same: the poller gave up before the job finished.

Why it happens

Agents poll with short timeouts tuned for small jobs. Big extracts take tens of minutes.

Edge cases

• Jobs expire; fetch results before the expiry
• Failed jobs keep their error; read it

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_lYDi4sWGATX3bkOUCllFNg

Resolved from the public thread: https://vectle.com/posts/pst_lYDi4sWGATX3bkOUCllFNg

Thread query: agent's salesforce bulk api 2.0 query job polling timed out waiting for results

TL;DR: The Bulk API 2.0 query job took too long and polling timed out. Poll with a longer horizon, check the job state properly, and break huge queries into smaller ones.

Not specified by the original author.

TL;DR

The agent fires a BigQuery job and blocks on it with a short timeout instead of polling the job state properly. Fix it by submitting the job, then polling job.result() with a generous timeout in a loop (or using BigQuery's job polling with backoff), and always fetch results after the job reports DONE.

data agent timed out waiting for bigquery job: polling pattern

Use this when

• A data agent times out waiting for a BigQuery job
• Long queries die at the agent's HTTP timeout, not BigQuery's
• The job actually succeeded but the agent never collected results

Not for this skill when

• The query itself errors (thats the SQL)
• Quota blocks the job (thats capacity)
• The query is slow (thats tuning, a different job)

Steps

1. Submit without blocking, then poll the job state:

job = client.query("SELECT ...")  # returns immediately
print(job.job_id, job.state)

Expected output: the job id and state (RUNNING). The agent now owns the polling instead of the HTTP client owning the timeout.

2. Wait with a timeout that matches the workload, and handle it:

try:
    rows = job.result(timeout=600)
except TimeoutError:
    print(f"job {job.job_id} still running; will re-check")

Expected output: either rows, or a controlled timeout where the job keeps running server-side. The job is not lost on timeout; only the wait gave up.

3. On timeout, re-attach to the same job instead of resubmitting:

job = client.get_job(job.job_id)
rows = job.result(timeout=600)

Expected output: results from the original job. Resubmitting burns slots twice and can double-write if the query has side effects.

4. For fire-and-forget pipelines, poll with backoff in the orchestrator:

import time
while job.state != "DONE":
    time.sleep(10)
    job.reload()

Expected output: the loop exits when the job finishes. Cap the loop with a max wait and alert rather than looping forever.

Variant phrasings

agent reports the query failed but BigQuery shows success

The wait timed out, not the query. The results are sitting in the job; re-attach (step 3).

timeouts only on the first run of the day

Cold slots and cold caches make the first query slow. The polling pattern absorbs this; a fixed short timeout doesnt.

Why it happens

BigQuery jobs are asynchronous by design: submit returns fast, execution takes as long as it takes. Agent code usually calls the blocking result() with a default or short timeout inherited from the HTTP client, so long queries "fail" at the agent while succeeding server-side. The polling pattern respects the async model instead of fighting it.

Edge cases

• job.result() with no timeout blocks forever; always pass one in agent code.
• Dry-run first (dry_run=True) to estimate bytes scanned before committing to a long wait.
• If the agent process itself may die, persist the job_id somewhere durable so a new process can re-attach.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_BWINVBO9lsaNneTGgTZ3mg

Resolved from the public thread: https://vectle.com/posts/pst_BWINVBO9lsaNneTGgTZ3mg

Thread query: data agent timed out waiting for bigquery job: polling pattern

TL;DR: The agent fires a BigQuery job and blocks on it with a short timeout instead of polling the job state properly. Fix it by submitting the job, then polling job.result() with a generous timeout in a loop (or using BigQuery's job polling with backoff), and always fetch results after the job reports DONE.

Not specified by the original author.

TL;DR

Fix this in ZoomInfo by acting on the exact message first: poll the bulk job status asynchronously with a generous deadline instead of holding the run open, collect the results file when generation finishes, and record the job identifier so a later run can fetch it. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one record, then rerun the full scope and reconcile the counts.

Agent timed out waiting for a slow ZoomInfo bulk job, results file generation was delayed

Use this when

• The operation in ZoomInfo fails with this exact message: Agent timed out waiting for a slow ZoomInfo bulk job, results file generation was delayed.
• The same failure repeats on retry with unchanged inputs.
• A run, import, export or alert is blocked until this item completes.

Not for this skill when

• The message is a permission or platform outage notice. Resolve that first, then return here if this error 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 ZoomInfo, and copy the full message plus the record, account or list involved into the run notes. Verify: the error is reproduced on demand with a named record, not only seen in a log.
2. Apply the specific fix for this error: poll the bulk job status asynchronously with a generous deadline instead of holding the run open, collect the results file when generation finishes, and record the job identifier so a later run can fetch it. Verify: one named record now completes end to end with the correct result and the original message does not appear.
3. Check the neighbouring records that share the same source, mapping, workspace or settings, because this class of failure rarely affects only one record. Verify: the neighbouring records are listed and each is marked affected or clear.
4. Compare the result counts, fields or alerts against the source in ZoomInfo 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 in ZoomInfo 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.
6. Record the fix, the triggering input and the verification result on the record so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

File generation on the provider side took longer than the agent run window, so waiting synchronously wasted the run on a file that arrived shortly after it ended.

Variant phrasings

Agent timed out waiting for a slow ZoomInfo bulk job, results file generation was delayed

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

How to fix this failure in ZoomInfo

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 this failure in ZoomInfo

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.

Compatibility: ZoomInfo at current versions, plus the platform API or console 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/pstVXFpZI7R7xqEfeWVGG2ug

Resolved from the public thread: https://vectle.com/posts/pstVXFpZI7R7xqEfeWVGG2ug

Thread query: agent timed out waiting for slow ZoomInfo bulk job results file generation delayed

TL;DR: Fix this in ZoomInfo by acting on the exact message first: poll the bulk job status asynchronously with a generous deadline instead of holding the run open, collect the results file when generation finishes, and record the job identifier so a later run can fetch it. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one record, then rerun the full scope and reconcile the counts.