LSM Management on Computational Storage

Ivan Luiz Picoli, Philippe Bonnet, Pinar Tözün

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

LSM-trees have emerged as the write-optimized index of choice for key-value stores and relational database systems. LSM-trees typically rely on a storage manager on top of a file system for storing data on Solid-State Drives (SSDs). The I/O path thus comprises four layers, each independently managing similar indirection, journaling, and garbage collection mechanisms. Such overhead is
increasingly problematic. First, the advent of microsecond-scale SSDs makes it necessary to streamline the I/O software stack. Second, the increasing performance gap between storage and CPU makes it necessary to reduce CPU storage overhead. A solution is to collapse LSM, file system, and SSD management layers into a single software layer embedded on computational storage. Specific commercial solutions are already available. In this short paper, we describe the design space for LSM management on computational storage.
Original languageEnglish
Title of host publicationProceedings of the 15th International Workshop on Data Management on New Hardware, DaMoN 2019, Amsterdam, The Netherlands, 1 July 2019
Number of pages4
PublisherAssociation for Computing Machinery
Publication date2019
Pages17:1-17:3
ISBN (Print)978-1-4503-6801-8
DOIs
Publication statusPublished - 2019

Keywords

  • LSM-trees
  • Key-value stores
  • Relational database systems
  • Solid-State Drives (SSDs)
  • I/O path optimization
  • Computational storage
  • Microsecond-scale SSDs
  • Storage overhead
  • CPU performance
  • Storage management layers

Fingerprint

Dive into the research topics of 'LSM Management on Computational Storage'. Together they form a unique fingerprint.

Cite this