Manual physical snapshots start additional snapshot and retention schedulers

Aberta
  • Algo errado?
#403 0 comentários 0 reações 0 responsáveis Ver no GitHub

Ninguém assumiu esta issue ainda.

Avaliação

Dificuldade
4/5
Tempo estimado
3-5 dias
Facilidade para iniciantes
45/100
Tipo de issue
Bug
Clareza
Claramente especificada
Status de atividade
Ativa
Stack de tecnologia
go, postgresql
Domínio
backend, databases

Direção de pesquisa

Read engine/internal/srv/routes.go and engine/internal/retrieval/retrieval.go around the named createSnapshot and SnapshotData paths, then inspect engine/internal/retrieval/engine/postgres/snapshot/physical.go for scheduler startup and lifecycle. Reproduce the reported sequence of startup followed by four manual requests and observe scheduled callbacks. Done means manual snapshots do not add recurring schedulers, and snapshot and retention jobs run once per pool with operations coordinated.

Escrita pelo modelo de indexação a partir do texto da issue.

Descrição

While testing physical snapshots on DBLab Engine v4.2.0, I noticed that each manual POST /snapshot request starts another recurring scheduler. After four manual snapshots, the scheduled snapshot and retention jobs run five times instead of once.

I also reproduced the scheduler behavior against the v4.2.2 retrieval code in an isolated Go test. That test skipped storage operations; it was not a full v4.2.2 database restore test.

Steps to reproduce

  1. Start an engine with a ZFS pool and physicalRestore / physicalSnapshot configured.

  2. Enable scheduled snapshots and retention. For example, this is the relevant configuration section:

    retrieval:
  jobs: [physicalRestore, physicalSnapshot]
  spec:
    physicalSnapshot:
      options:
        scheduler:
          snapshot:
            timetable: "0 * * * *"
          retention:
            timetable: "30 * * * *"
            limit: 2

  3. Wait for initialization to finish, then request four manual snapshots sequentially, letting each request finish before starting the next. For a pool named test_pool:

    curl --fail-with-body --request POST \
  --header 'Verification-Token: <token>' \
  --header 'Content-Type: application/json' \
  --data '{"poolName":"test_pool"}' \
  http://127.0.0.1:2345/snapshot

  4. Check the logs at the next scheduled snapshot and retention times.

Actual behavior

  • Startup logs Snapshot scheduler has been started once. Each manual request adds another occurrence, without stopping the previous scheduler.
  • After four manual requests, five snapshot jobs start at the scheduled time. One succeeds; the others collide with it and report that the dataset already exists.
  • The retention callbacks also run concurrently against the same targets. I observed dataset is busy errors during these overlapping cleanup attempts.

The isolated test exercised the real SnapshotData and scheduler startup path. The number of active schedulers increased from 1 -> 2 -> 3 -> 4 -> 5, and callbacks from all five fired. Cancelling the startup context stopped only the first scheduler; the four created with context.Background() continued running. The test explicitly stopped all schedulers afterward.

Expected behavior

A manual snapshot should take one snapshot without adding another recurring schedule. Scheduled snapshot creation and retention should continue running once per pool, with manual and scheduled operations coordinated.

Relevant code

  • createSnapshot calls SnapshotData(context.Background(), poolName).
  • SnapshotData constructs new jobs and replaces statefulJobs without stopping the previous jobs.
  • PhysicalInitial.Run starts a scheduler on return. Each instance registers both snapshot and retention callbacks and has its own mutex, so the instances do not serialize their operations with each other.

Workaround

Restarting the engine clears the extra schedulers. Avoiding manual POST /snapshot requests afterward prevents them from accumulating again.

Linguagem predominante
Go
Estrelas
2.8k
Forks
90
Nenhum PR com merge em 30d

Preparar o ambiente

Primeiros passos

  1. Leia a issue inteira e depois o guia de contribuição do projeto.
  2. Comente na issue dizendo que vai assumir — evita que duas pessoas façam o mesmo trabalho.
  3. Faça um fork do repositório e trabalhe em uma branch.
  4. Abra um pull request que referencie o número da issue.

Mais de postgres-ai/database-lab-engine

Todas as issues de postgres-ai/database-lab-engine

Issues semelhantes

Mais issues de Go

Receba novas issues na sua caixa de entrada

Um resumo curto de issues do GitHub para quem está começando.