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Lethe: A Tunable Delete-Aware LSM Engine

  • Boston University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Data-intensive applications fueled the evolution of log structured merge (LSM) based key-value engines that employ the out-of-place paradigm to support high ingestion rates with low read/write interference. These benefits, however, come at the cost of treating deletes as a second-class citizen. A delete inserts a tombstone that invalidates older instances of the deleted key. State-of-the-art LSM engines do not provide guarantees as to how fast a tombstone will propagate to persist the deletion. Further, LSM engines only support deletion on the sort key. To delete on another attribute (e.g., timestamp), the entire tree is read and re-written. We highlight that fast persistent deletion without affecting read performance is key to support: (i) streaming systems operating on a window of data, (ii) privacy with latency guarantees on the right-to-be-forgotten, and (iii) en masse cloud deployment of data systems that makes storage a precious resource. To address these challenges, in this paper, we build a new key-value storage engine, Lethe, that uses a very small amount of additional metadata, a set of new delete-aware compaction policies, and a new physical data layout that weaves the sort and the delete key order. We show that Lethe supports any user-defined threshold for the delete persistence latency offering higher read throughput (1.17-1.4x) and lower space amplification (2.1-9.8x), with a modest increase in write amplification (between 4% and 25%). In addition, Lethe supports efficient range deletes on a secondary delete key by dropping entire data pages without sacrificing read performance nor employing a costly full tree merge.

Original languageEnglish
Title of host publicationSIGMOD 2020 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages893-908
Number of pages16
ISBN (Electronic)9781450367356
DOIs
StatePublished - Jun 14 2020
Externally publishedYes
Event2020 ACM SIGMOD International Conference on Management of Data, SIGMOD 2020 - Portland, United States
Duration: Jun 14 2020 → Jun 19 2020

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

Conference2020 ACM SIGMOD International Conference on Management of Data, SIGMOD 2020
Country/TerritoryUnited States
CityPortland
Period6/14/20 → 6/19/20

ASJC Scopus Subject Areas

  • Software
  • Information Systems

Keywords

  • compaction
  • compaction policy
  • compaction trigger
  • delete key
  • delete persistence
  • delete persistence latency
  • delete persistence threshold
  • fade
  • interweaved storage layout
  • kiwi
  • lethe
  • LSM-trees
  • out-of-place deletes
  • sort key
  • TTL-driven compaction

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