Andrey Antukh ba78ccb8c9
✨ Harden file data offload job with lock, summary and metrics (#12403)
Take the file row with FOR UPDATE SKIP LOCKED when the offload job
starts and skip the run when the row is locked or gone, so the job
never runs while the file is being edited. Every live hot-storage
row of the file moves to cold storage inside one all-or-nothing
transaction, and the handler answers a summary map with the
offloaded rows, bytes and per-type stats.

Add bounded metrics for the job: rows and bytes counters labeled by
row type on successful runs only, and a timing histogram with the
ok, skip and error outcomes. The job definition now requires
metrics, the recorders live in app.jobs.metrics, and the existing
ephemeral job timing histogram pins its buckets.

Cover the job with a new test namespace: the happy path, the locked
row, missing and deleted files, the rows and bytes summary with its
no-op rerun, the whole-file abort on storage failure, the metric
definitions and emissions, and the submit-time params validation.
An end-to-end suite reads, snapshots, writes, exports, imports and
deletes offloaded files; concurrency tests pin the stale-revn skip,
the blocked-edit retry and the reclaimable orphans of a partial
failure. The file-gc scheduler test pins one job per eligible file,
and the scheduler private helper drops its bang.

Document the lock invariant, the deliberate no-pacing decision and
the metric label sets in the backend storage memory and the
configuration guide.

Related to #12398.

AI-assisted-by: muse-spark-1.3-contributor
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