Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Bitmap index design and evaluation
SIGMOD '98 Proceedings of the 1998 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
Query optimization for selections using bitmaps
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Space efficient bitmap indexing
Proceedings of the ninth international conference on Information and knowledge management
Vector approximation based indexing for non-uniform high dimensional data sets
Proceedings of the ninth international conference on Information and knowledge management
A performance comparison of bitmap indexes
Proceedings of the tenth international conference on Information and knowledge management
Model 204 Architecture and Performance
Proceedings of the 2nd International Workshop on High Performance Transaction Systems
Fast High-Dimensional Data Search in Incomplete Databases
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Performance Measurements of Compressed Bitmap Indices
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Optimizing Queries on Compressed Bitmaps
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Compressing Bitmap Indexes for Faster Search Operations
SSDBM '02 Proceedings of the 14th International Conference on Scientific and Statistical Database Management
Bitmap Indices for Speeding Up High-Dimensional Data Analysis
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Query processing and optimization in Oracle Rdb
The VLDB Journal — The International Journal on Very Large Data Bases
Byte-aligned bitmap compression
DCC '95 Proceedings of the Conference on Data Compression
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Incomplete databases, that is, databases that are missing data, are present in many research domains. It is important to derive techniques to access these databases efficiently. We first show that known indexing techniques for multi-dimensional data search break down in terms of performance when indexed attributes contain missing data. This paper utilizes two popularly employed indexing techniques, bitmaps and quantization, to correctly and efficiently answer queries in the presence of missing data. Query execution and interval evaluation are formalized for the indexing structures based on whether missing data is considered to be a query match or not. The performance of Bitmap indexes and quantization based indexes is evaluated and compared over a variety of analysis parameters for real and synthetic data sets. Insights into the conditions for which to use each technique are provided.