Efficient distributed selective search

Abstract

Simulation and analysis have shown that selective search can reduce the cost of large-scale distributed information retrieval. By partitioning the collection into small topical shards, and then using a resource ranking algorithm to choose a subset of shards to search for each query, fewer postings are evaluated. In this paper we extend the study of selective search into new areas using a fine-grained simulation, examining the difference in efficiency when term-based and sample-based resource selection algorithms are used; measuring the effect of two policies for assigning index shards to machines; and exploring the benefits of index-spreading and mirroring as the number of deployed machines ..