Index merging

Index merging (1999)

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by Surajit Chaudhuri , Vivek Narasayya

Venue:	In Proceedings of the International Conference on Data Engineering (ICDE
Citations:	19 - 4 self

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Datum	Value	Source
TITLE	Index merging	INFERENCE
AUTHOR NAME	Surajit Chaudhuri	SVM HeaderParse 0.2
AUTHOR AFFIL	Microsoft Research, Redmond	SVM HeaderParse 0.2
AUTHOR NAME	Vivek Narasayya	SVM HeaderParse 0.2
AUTHOR AFFIL	Microsoft Research, Redmond	SVM HeaderParse 0.2
ABSTRACT	Indexes play a vital role in decision support systems by reducing the cost of answering complex queries. A popular methodology for choosing indexes that is adopted by database administrators as well as automatic tools is: (a) Consider poorly performing queries in the workload. (b) For each query, propose a set of candidate indexes that potentially benefits the query. (c) Choose a subset from the candidate indexes in (b). Unfortunately, such a strategy can result in significant storage and index maintenance cost. In this paper, we present a novel technique called index merging to address the above shortcoming. Index merging can take an existing set of indexes (perhaps optimized for individual queries in the workload), and produce a new set of indexes with significantly lower storage and maintenance overhead, while retaining almost all the querying benefits of the initial set of indexes. We present an efficient algorithm for index merging, and demonstrate significant savings in index storage and maintenance by virtue of index merging, through experiments on Microsoft SQL Server 7.0. 1.	SVM HeaderParse 0.2
YEAR	1999	INFERENCE
VENUE	In Proceedings of the International Conference on Data Engineering (ICDE	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
CITATIONS	16 found	ParsCit 1.0