Analyzing and Improving the Scalability of In-Memory Indices for Managed Search Engines
Aditya Chilukuri, Shoaib Akram · 2023
Managed search engines, such as Apache Solr and Elastic- search, host huge inverted indices in main memory to offer fast response times. This practice faces two challenges. First, limited DRAM capacity necessitates search engines aggres- sively compress indices to reduce their storage footprint. Unfortunately, our analysis with a popular search library shows that compression slows down queries (on average) by up to 1.7× due to high decompression latency. Despite their performance advantage, uncompressed indices require 10× more memory capacity, making them impractical. Second, indices today reside off-heap, encouraging unsafe memory accesses and risking eviction from the page cache.