[Feature] Add query-scoped planning limits and cooperative cancellation
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Avaliação
- Dificuldade
- 5/5
- Tempo estimado
- Mais de uma semana
- Facilidade para iniciantes
- 8/100
- Tipo de issue
- Funcionalidade
- Clareza
- Precisa de esclarecimento
- Status de atividade
- Ativa
- Stack de tecnologia
- cpp
- Domínio
- data-engineering
Direção de pesquisa
This is design work, so start by reading the API surfaces in include/paimon/scan_context.h and include/paimon/table/source/table_scan.h, then the limit ordering in src/paimon/core/table/source/data_table_batch_scan.cpp and the manifest fan-out in src/paimon/core/operation/file_store_scan.cpp (ReadFileEntries). The first step is agreeing the API shape with maintainers on this thread. Done means an approved contract plus tests that inject allocation, I/O and submission failures.
Escrita pelo modelo de indexação a partir do texto da issue.
Descrição
Parent integration: sirius-db/sirius#2181. Consumer bridge tracking: polardb/duckdb-paimon#139.
Need
A database embedding paimon-cpp needs to admit planning work before materializing an arbitrarily large native plan, and stop submitting work after cooperative cancellation. This is a feature request, not a claim that existing standalone planning is incorrect.
The integration pins 53f9c86d45aabb0a6f1a379271da07d7a9f27a3d. The following API gap also remains in inspected main 242decffdfdefef01dcd0e52e48c9a1e69792479:
ScanContextBuilder::WithMemoryPoolroutes pool-backed allocations, but does not bound ordinary STL planning containers or their transitive metadata allocations.TableScan::CreatePlan()returns a complete plan; it exposes no planning cancellation/budget contract.SetLimitis a row-result pushdown, not a planning-memory quota:DataTableBatchScan::CreatePlancallsstarting_scanner_->ScanbeforeApplyPushDownLimit.FileStoreScan::ReadFileEntriesbuilds a vector of futures for all supplied manifest metadata, then collects complete per-manifest entry vectors. A custom serial executor can prevent concurrent task execution, but does not itself bound those retained containers/results.
Source references at the inspected main:
Proposed Contract To Discuss
Provide optional query-scoped planning controls, preserving existing unlimited behavior by default. The API shape should be agreed with maintainers; a post-plan split-count check is not sufficient.
- Check conservative manifest/entry/split/retained-metadata quotas before the corresponding allocation or task submission; identify which allocations are covered and what remains outside the guarantee.
- Bound outstanding manifest work and retained results, including ordinary containers, rather than only pool-backed buffers.
- Check a cooperative cancellation token before I/O/submission and inside substantial decode/merge loops. Do not promise interruption of an arbitrary blocking filesystem call unless the filesystem supports it.
- Return a distinguishable resource-refusal/cancellation status, never partial success or EOF. Stop new submissions and drain accepted work before returning, including exceptions and submission failure.
- Avoid changing process-global executors, Arrow thread capacity, or allocation resources.
Acceptance tests should use many small manifests and injected allocation/I/O/submission failures. Assert the limit is enforced before excess work is accepted, accepted jobs are drained on every terminal path, and cancellation cannot return a partial successful plan. Include serial/nested executor configurations to guard against deadlock. Keep row LIMIT semantics separate.
This issue does not request another Arrow batch-lifetime implementation; that work already exists in #259/#260. No hard whole-process-memory bound or prompt cancellation of uninterruptible I/O is claimed by the current integration.
- Linguagem predominante
- C++
- Estrelas
- 68
- Forks
- 34
- Merge médio
- 3d 18h
- PRs com merge (30d)
- 44
Preparar o ambiente
- Sem Dockerfile nem arquivo Docker Compose
- Tem um modelo de pull request
- Ler o guia de contribuição
Primeiros passos
- Leia a issue inteira e depois o guia de contribuição do projeto.
- Comente na issue dizendo que vai assumir — evita que duas pessoas façam o mesmo trabalho.
- Faça um fork do repositório e trabalhe em uma branch.
- Abra um pull request que referencie o número da issue.
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