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Caching is a crucial performance component of large-scale web search engines, as it greatly helps reducing average query response times and query processing workloads on backend search clusters. In this paper, we describe a multi-level static cache architecture that stores five different item types: query results, precomputed scores, posting lists, precomputed intersections of posting lists, and documents. Moreover, we propose a greedy heuristic to prioritize items for caching, based on gainsdoi:10.1016/j.ipm.2010.12.007 fatcat:ozvshcjalzbq7jxxnkydw3fthu