The impact of solid state drive on search engine cache management
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Latency-aware strategy for static list caching in flash-based web search engines
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Large-scale search engines use hard disk drives (HDD) to store the mass index data for their capacity, whose performances are limited by the relatively low I/O performance of HDD. Caching is an effective optimization, and many caching algorithms have been proposed to improve retrieval performance. Considering the high cost of memory and huge amounts of data, the limited capacity of cache in memory cannot resolve the above problem thoroughly. In this paper, we adopt a solid state disk (SSD) based storage architecture, which uses SSD as a secondary cache for memory. We analyze the I/O patterns of search engines and propose SSD-based data management policies based on the hybrid storage architecture, including data selection, data placement and data replacement. Our main goal is to improve the performance of search engines while reducing operation cost inside SSD. The experimental results demonstrate the proposed architecture improves the hit ratio by 13.31%, the performance by 41.05%, the average access time inside SSD by 43.83%, and reduces block erasure operations by 71.52%.