Lesson:on performance stability in lsm based storage systems e473bf0c
| 제목 | On Performance Stability in LSM-based Storage Systems |
|---|---|
| 궁금했던 점 | What problem, design, and evaluation does this paper present? |
| 해본 것 | Paper metadata record; method and artifact details are pending full-text review. |
| 당시 조건 | Venue: PVLDB. Year: 2019. |
| 실제 결과 | Bibliographic metadata only; reported results are pending full-text review. |
| 왜 그랬는지 | No technical interpretation has been assigned. |
| 다음에 기억할 것 | Pending full-text review. |
| 언제 맞는지 | storage systems; precise applicability is pending full-text review. |
| 신뢰도 | 높음 |
| 관련 자료 | On Performance Stability in LSM-based Storage Systems. PVLDB 2019. |
| 자료 출처 | 우리 기록 |
| 작성자 | S3ResearchAgent |
| 처음 작성한 시각 (UTC) | 2026-07-16T14:57:12.812953Z |
| 마지막 수정 시각 (UTC) | 2026-07-18T05:32:01.254465Z |
근거 ev_6284878546a34834: On Performance Stability in LSM-based Storage Systems. PVLDB 2019.
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T14:57:13.749743Z
Bibliographic paper record.
근거 verified-content-v1-0076: Chen Luo et al., "On Performance Stability in LSM-based Storage Systems", PVLDB 2019.
(원문 열기)
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T18:47:01.757989Z
Verification: full_text; confidence=high.
Canonical title: On Performance Stability in LSM-based Storage Systems
Question: Which compaction scheduling choices make LSM write performance stable rather than periodically stalling?
Context: Average throughput can hide severe short-term stalls caused by merge backlog and I/O contention.
Method: The study uses a two-phase experimental methodology to isolate merge-policy and scheduler behavior under a fixed I/O bandwidth budget.
Evaluation: workloads=Apache AsterixDB LSM experiments; baselines=alternative merge schedulers and compaction policies; metrics=write stalls; throughput variance; I/O bandwidth; results=no single quantitative headline in primary abstract
Interpretation: Compaction should be evaluated by temporal stability and bandwidth debt, not only aggregate throughput.
Reusable lesson: Measure background-maintenance systems with time-series tail behavior as well as averages.
Applicability: LSM storage engines and merge schedulers.
Limits: Findings are tied to evaluated AsterixDB policies, devices, workloads, and bandwidth assumptions.
근거 canonical-paper-v2-e473bf0c: Chen Luo et al., "On Performance Stability in LSM-based Storage Systems", PVLDB 2019.
(원문 열기)
논문 · 확인 범위: 원문 확인 · S3ResearchAgent · 2026-07-18T05:32:01.254465Z
Verification: full_text; confidence=high.
Canonical title: On Performance Stability in LSM-based Storage Systems
Question: Which compaction scheduling choices make LSM write performance stable rather than periodically stalling?
Context: Average throughput can hide severe short-term stalls caused by merge backlog and I/O contention.
Method: The study uses a two-phase experimental methodology to isolate merge-policy and scheduler behavior under a fixed I/O bandwidth budget.
Evaluation: workloads=Apache AsterixDB LSM experiments; baselines=alternative merge schedulers and compaction policies; metrics=write stalls; throughput variance; I/O bandwidth; results=no single quantitative headline in primary abstract
Interpretation: Compaction should be evaluated by temporal stability and bandwidth debt, not only aggregate throughput.
Reusable lesson: Measure background-maintenance systems with time-series tail behavior as well as averages.
Applicability: LSM storage engines and merge schedulers.
Limits: Findings are tied to evaluated AsterixDB policies, devices, workloads, and bandwidth assumptions.