Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
An efficient bitmap encoding scheme for selection queries
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Communications of the ACM
Integrating parallel file I/O and database support for high-performance scientific data management
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Model 204 Architecture and Performance
Proceedings of the 2nd International Workshop on High Performance Transaction Systems
Design and Implementation of Bitmap Indices for Scientific Data
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Data Management for Large-Scale Scientific Computations in High Performance Distributed Systems
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Active Management of Scientific Data
IEEE Internet Computing
On the performance of bitmap indices for high cardinality attributes
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Supporting ranking and clustering as generalized order-by and group-by
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Multi-resolution bitmap indexes for scientific data
ACM Transactions on Database Systems (TODS)
Failure-tolerant distributed storage with compressed (1 out-of N) codes
Journal of Systems Architecture: the EUROMICRO Journal
HOBI: Hierarchically Organized Bitmap Index for Indexing Dimensional Data
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Time-HOBI: indexing dimension hierarchies by means of hierarchically organized bitmaps
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
Time-HOBI: Index for optimizing star queries
Information Systems
Data structures for multiversion data warehouse
ADBIS'09 Proceedings of the 13th East European conference on Advances in Databases and Information Systems
On contextual ranking queries in databases
Information Systems
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The data used by today's scientific applications are often very high in dimensionality and staggering in size. These characteristics necessitate the use of a good multidimensional indexing strategy to provide efficient access to the data. Researchers have previously proposed the use of bitmap indexes for high-dimension scientific data as a way of overcoming the drawbacks of traditional multidimensional indexes such as R-trees and KD-trees, which are bulky and whose performance does not scale well as the number of dimensions increases. However, the techniques proposed in previous work on bitmap indexes are not sufficient to address all problems that arise in practice. In experiments with real datasets, we experienced problems with index size and query performance. To overcome these shortcomings, we propose the use of adaptive, multilevel, multiresolution bitmap indexes, and evaluate their performance in two scientific domains. Our preliminary experiments with a parallel query processor and index creator also show that it is very easy to parallelize a bitmap index.