A transient failure makes automatic reduction skip a run for good

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
25/100
Tipo de issue
Nueva funcionalidad
Claridad
Necesita aclaración
Estado de actividad
Activo
Stack tecnológico
python
Área
backend, data-engineering

Línea de trabajo

Read rules.py at TriggerLoop._requests, automatic-reduction.md under “The trigger loop,” and the linked requirements question in docs/requirements/data.md. Compare the failure cases and prior art in docs/developer/prior-art/; the issue leaves three design questions open. Done requires a decided approach for distinguishing or retrying failures and dataset readiness, with the related behavior and documentation specified.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

The trigger loop counts any record under a rule's label as handled, including a failed one (TriggerLoop._requests in rules.py; automatic-reduction.md, "The trigger loop"). That avoids retrying a dataset that fails at every step. But failed covers three cases that a driver cannot tell apart, since a failed record holds only str(error):

  • the workflow raised, or reported a failure;
  • the framework could not run it: a dataset could not be read, or a write failed;
  • the process died without a Python exception (out-of-memory kill, segfault), which the service must capture from the console and the batch system.

So a transient failure loses a run for good: a slow or missing /ess mount, or a dataset source that lists a run before its file is complete. Mantid's reflectometry autoprocessing hit exactly the second case in 2024 (mantidproject/mantid#36860); they fixed it by listing only runs already in the data cache, not by retrying.

Prior art, in docs/developer/prior-art/ (#67):

  • AiiDA ends a process Finished with a declared exit code, Excepted, or Killed; restart handlers key on exit codes. Transient transport failures are retried with backoff and then paused for a person, not failed.
  • Snakemake on Slurm takes OUT_OF_MEMORY, TIMEOUT, and NODE_FAIL from the batch system, not from the job.
  • Mantid never retries failed rows automatically; a user selects them and processes again.

Questions:

  1. Should a failed record say which kind of failure it was, so that an application can decide retries (relevant to #33, where rules move into applications)?
  2. Should the service retry framework failures, such as an unreadable dataset, before it fails a record (#27)?
  3. Should the dataset source promise to list a dataset only once its file is complete? This ties to the Open question in docs/requirements/data.md on how long after the file writer finishes the catalogue lists a run.
Lenguaje dominante
Python
Estrellas
0
Forks
1
Merge medio
9 h 23 min
PR fusionados (30 d)
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