Read as needed: Building WiSER, a Flash-optimized search engine

Jun He, Kan Wu, Sudarsun Kannan, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We describe WiSER, a clean-slate search engine designed to exploit high-performance SSDs with the philosophy "read as needed". WiSER utilizes many techniques to deliver high throughput and low latency with a relatively small amount of main memory; the techniques include an optimized data layout, a novel two-way cost-aware Bloom filter, adaptive prefetching, and space-time trade-offs. In a system with memory that is significantly smaller than the working set, these techniques increase storage space usage (up to 50%), but reduce read amplification by up to 3x, increase query throughput by up to 2.7x, and reduce latency by 16x when compared to the state-of-the-art Elasticsearch. We believe that the philosophy of "read as needed" can be applied to more applications as the read performance of storage devices keeps improving.

Original languageEnglish (US)
Title of host publicationProceedings of the 18th USENIX Conference on File and Storage Technologies, FAST 2020
PublisherUSENIX Association
Pages59-73
Number of pages15
ISBN (Electronic)9781939133120
StatePublished - 2020
Event18th USENIX Conference on File and Storage Technologies, FAST 2020 - Santa Clara, United States
Duration: Feb 25 2020Feb 27 2020

Publication series

NameProceedings of the 18th USENIX Conference on File and Storage Technologies, FAST 2020

Conference

Conference18th USENIX Conference on File and Storage Technologies, FAST 2020
Country/TerritoryUnited States
CitySanta Clara
Period2/25/202/27/20

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software
  • Computer Networks and Communications

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