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LSM Management on Computational Storage

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 17:1-17:3 (4 pages)

Publication milestones

  • Published - 2019

Publication status

Published - 2019

Publisher

Association for Computing Machinery, United States
978-1-4503-6801-8

Publication IDs

  • Scopus: 85074449516

Host publication title

Proceedings of the 15th International Workshop on Data Management on New Hardware, DaMoN 2019, Amsterdam, The Netherlands, 1 July 2019

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.

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