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Query-Driven Indexing in Large-Scale Distributed Systems: Efficient query processing with distributed indexes (Paperback)

Gleb Skobeltsyn

ISBN 10: 3639150171 / ISBN 13: 9783639150179
Editorial: VDM Verlag, Germany, 2009
Nuevos Condición: New Encuadernación de tapa blanda
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Descripción

Language: English. Brand new Book. Efficient and effective search in large-scale datarepositories requires complex indexing solutionsdeployed on a large number of servers. Commercial Websearch engines already rely upon complex systems tobe able to return relevant query results and keepprocessing times within the comfortable sub-secondlimit. Nevertheless, the exponential growth of theamount of content on the Web poses serious challengeswith respect to scalability. Coping with thesechallenges requires novel indexing solutions that notonly remain scalable but also preserve the searchaccuracy. In this work we introduce and explore theconcept of query-driven indexing - an indexconstruction strategy that uses caching techniques toadapt to the querying patterns expressed by users. Wesuggest to abandon the strict difference betweenindexing and caching, and to build a distributedindexing structure, or a distributed cache, such thatit is optimized for the current query load. Ourexperimental and theoretical analysis shows thatemploying query-driven indexing is especiallybeneficial when the content is (geographically)distributed in a Peer-to-Peer network. N° de ref. de la librería KNV9783639150179

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Título: Query-Driven Indexing in Large-Scale ...

Editorial: VDM Verlag, Germany

Año de publicación: 2009

Encuadernación: Paperback

Condición del libro: New

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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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