Diversified caching for replicated web search engines

Commercial web search engines adopt parallel and replicated architecture in order to support high query throughput. In this paper, we investigate the effect of caching on the throughput in such a setting. A simple scheme, called uniform caching, would replicate the cache content to all servers. Unfortunately, it does not exploit the variations among queries, thus wasting memory space on caching the same cache content redundantly on multiple servers. To tackle this limitation, we propose a diversified caching problem, which aims to diversify the types of queries served by different servers, and maximize the sharing of terms among queries assigned to the same server. We show that it is NP-hard to find the optimal diversified caching scheme, and identify intuitive properties to seek good solutions. Then we present a framework with a suite of techniques and heuristics for diversified caching. Finally, we evaluate the proposed solution with competitors by using a real dataset and a real query log.