Proceedings of the ninth international conference on Information and knowledge management
Some issues in design of data warehousing systems
Data warehousing and web engineering
Journal of Computer Science and Technology
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Automatic physical database tuning: a relaxation-based approach
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Database tuning advisor for microsoft SQL server 2005: demo
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
To tune or not to tune?: a lightweight physical design alerter
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more
Physical design refinement: The ‘merge-reduce’ approach
ACM Transactions on Database Systems (TODS)
Self-tuning database systems: a decade of progress
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient use of the query optimizer for automated physical design
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Constrained physical design tuning
Proceedings of the VLDB Endowment
Constrained physical design tuning
The VLDB Journal — The International Journal on Very Large Data Bases
Saving space and time using index merging
Data & Knowledge Engineering
CORADD: correlation aware database designer for materialized views and indexes
Proceedings of the VLDB Endowment
Physical design refinement: the "merge-reduce" approach
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
An automatic physical design tool for clustered column-stores
Proceedings of the 16th International Conference on Extending Database Technology
Intelligent Decision Technologies
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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.