Maximizing Page-Level Cache Hit Ratios in LargeWeb Services

Abstract

Large web services typically serve pages consisting of many individual objects. To improve the response times of page-requests, these services store a small set of popular objects in a fast caching layer. A page-request is not considered complete until all of its objects have either been found in the cache or retrieved from a backend system. Hence, caching only speeds up a page request if all of its objects are found in the cache. We seek caching policies that maximize the page-level hit ratio-the fraction of requests that find all of their objects in the cache. This work analyzes page requests served by a Microsoft production system.We find that in practice there is potential for improving the page-level hit ratio over existing caching strategies, but that analytically maximizing the page-level hit ratio is NP-hard.