Space efficient bitmap indexing
Proceedings of the ninth international conference on Information and knowledge management
Strategies for processing ad hoc queries on large data warehouses
Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP
Model 204 Architecture and Performance
Proceedings of the 2nd International Workshop on High Performance Transaction Systems
Range-Based Bitmap Indexing for High Cardinality Attributes with Skew
COMPSAC '98 Proceedings of the 22nd International Computer Software and Applications Conference
Design and Implementation of Bitmap Indices for Scientific Data
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Optimizing candidate check costs for bitmap indices
Proceedings of the 14th ACM international conference on Information and knowledge management
Minimizing I/O Costs of Multi-Dimensional Queries with Bitmap Indices
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Optimizing i/o costs of multi-dimensional queries using bitmap indices
DEXA'05 Proceedings of the 16th international conference on Database and Expert Systems Applications
Column imprints: a secondary index structure
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
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Bitmap indices are the preferred indexing structures for read only & high dimensional data in data warehouses and scientific databases. High cardinality attributes pose a new challenge in terms of having space efficient bitmap indices. Binning is a common technique for reducing space requirements of bitmap indices. It is found that binning has an adverse affect on the query performance. A new efficient binning strategy is proposed for bitmap indices for high cardinality attributes. Exact bins are created based on query distribution. Exact bins are allowed to overlap. This gives a considerable performance advantage over the conventional non-overlapping bins at the expense of marginal increase in space overheads. Overlapping bins minimize the number of candidate-checks that need to be performed for a given set of queries. Algorithms are also presented for performing candidate checks more efficiently. Experimental results are presented in support of the new binning strategy.