Cache and retention controls: delete, time limits, per-tenant budgets

Aperta
#103 0 commenti 0 reazioni 0 assegnatari Vedi su GitHub

I maintainer di solito rispondono entro 1 giorno

Nessuno ha ancora preso questa issue.

Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
35/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
python

Direzione di ricerca

Start by reading the API and cache management entry points for dataset contexts, uploads, and GPU, host, and spill storage; the issue does not name specific files or tests. Map how contexts are admitted and evicted before working through delete, expiry, tenant budgets, and listing. Done means the stated deletion, expiry, and per-tenant eviction criteria pass, with a retention page documenting storage and restart behavior.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

area/api area/memory enhancement P1 roadmap

Users can't control or see how long their data stays on the server. Today a context lives until LRU eviction, can sit in the spill tier on disk, and nothing in the API removes it. Hospitals, banks and similar users need this answered before they deploy. Prior Labs documents none of it.

Add

  • Delete: DELETE /v1/tabctx/datasets/{id} removes a context from GPU, host and spill, along with its uploaded table.
  • Time limits: a server-wide maximum age for contexts and uploads, and an optional per-fit ttl_s that can only be shorter.
  • Per-tenant budgets: a cap on cache bytes per tenant, so one tenant can't evict everyone else's contexts.
  • List: GET /v1/tabctx/datasets shows a tenant's contexts with their size, age, expiry and where each one is held (GPU, host or disk).
  • Docs: a short retention page covering what's stored, where, for how long, and what a restart does.

Accept

  • After a delete or an expiry, nothing about that context is left on GPU, in memory or on disk (tested).
  • A tenant over its budget evicts its own contexts first.

Part of #6, which also covers persistent contexts and a catalog.

Lingua principale
Python
Stelle
1
Fork
1
Merge medio
6h 45m
PR unite (30g)
66

Preparare l'ambiente

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Altre issue di VectorInstitute/tabctx

Tutte le issue di VectorInstitute/tabctx

Issue simili

Altre issue su Python

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.