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Query-Driven Indexing in Large-Scale Distributed Systems
Efficient query processing with distributed indexes
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Efficient and effective search in large-scale data§repositories requires complex indexing solutions§deployed on a large number of servers. Commercial Web§search engines already rely upon complex systems to§be able to return relevant query results and keep§processing times within the comfortable sub-second§limit. Nevertheless, the exponential growth of the§amount of content on the Web poses serious challenges§with respect to scalability. Coping with these§challenges requires novel indexing solutions that not§only remain scalable but also preserve the search§accuracy. In this work we introduce and explore the§concept of query-driven indexing - an index§construction strategy that uses caching techniques to§adapt to the querying patterns expressed by users. We§suggest to abandon the strict difference between§indexing and caching, and to build a distributed§indexing structure, or a distributed cache, such that§it is optimized for the current query load. Our§experimental and theoretical analysis shows that§employing query-driven indexing is especially§beneficial when the content is (geographically)§distributed in a Peer-to-Peer network.
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