KR-bluejay opened a new issue, #1316:
URL: https://github.com/apache/datafusion-ballista/issues/1316
**Is your feature request related to a problem or challenge? Please describe
what you are trying to do.**
There are several improvement points in the current job-data deletion flow:
1. *Duplication*
The executor has `clean_all_shuffle_data` alongside other ad-hoc removal
logic. These overlap in functionality, making the code harder to maintain and
reason about.
2. *Push-based broadcast*
When the scheduler initiates cleanup, it currently notifies all
executors. This is inefficient because only a subset of executors actually hold
the job’s data.
3. *Per-job deletion tasks*
In `clean_up_successful_job` / `clean_up_failed_job`, the scheduler
spawns a separate delayed task (`sleep`) for each job and calls
`state.remove_job(job_id)` individually. This results in many small tasks and
RPCs, which could be batched more efficiently.
**Describe the solution you'd like**
Unify cleanup behind a single, testable “deletion facility”:
1. *Deduplicate* logic with `clean_all_shuffle_data`; extract/keep a shared
async remover (e.g., `remove_job_dir`) with safety checks.
2. *Targeted push*: notify only executors that actually hold the job’s data
(no broadcast).
3. *Batching*: we already dispatch periodically; change each tick to send
one batched `remove_jobs(Vec<JobId>)` for all pending IDs rather than spawning
per-job sleeps and individual removals.
**Describe alternatives you've considered**
**Additional context**
Related: #1219 , #1314
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