Read as Needed: Building WiSER, a Flash-Optimized Search Engine
Read as Needed: Building WiSER, a Flash-Optimized Search Engine
复制标题
DOI：
--
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Jun He;Kan Wu;Sudarsun Kannan;Andrea C. Arpaci-Dusseau;Remzi H. Arpaci-Dusseau
中科院分区：
文献类型：
--
作者：
Jun He;Kan Wu;Sudarsun Kannan;Andrea C. Arpaci-Dusseau;Remzi H. Arpaci-Dusseau
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.
