Optimal Semijoins for Distributed Database Systems
IEEE Transactions on Software Engineering
Join processing in relational databases
ACM Computing Surveys (CSUR)
Parameterised compression for sparse bitmaps
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
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
Summary cache: a scalable wide-area web cache sharing protocol
IEEE/ACM Transactions on Networking (TON)
Space efficient bitmap indexing
Proceedings of the ninth international conference on Information and knowledge management
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
A performance comparison of bitmap indexes
Proceedings of the tenth international conference on Information and knowledge management
IEEE/ACM Transactions on Networking (TON)
Informed content delivery across adaptive overlay networks
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Model 204 Architecture and Performance
Proceedings of the 2nd International Workshop on High Performance Transaction Systems
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
Multidimensional Indexing and Query Coordination for Tertiary Storage Management
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Byte-aligned bitmap compression
DCC '95 Proceedings of the Conference on Data Compression
Space-code bloom filter for efficient traffic flow measurement
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Compressing Bitmap Indices by Data Reorganization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
SSDBM'2005 Proceedings of the 17th international conference on Scientific and statistical database management
Optimizing bitmap indices with efficient compression
ACM Transactions on Database Systems (TODS)
Compressing large boolean matrices using reordering techniques
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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
RLH: bitmap compression technique based on run-length and huffman encoding
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
Brighthouse: an analytic data warehouse for ad-hoc queries
Proceedings of the VLDB Endowment
Dynamic data organization for bitmap indices
Proceedings of the 3rd international conference on Scalable information systems
RLH: Bitmap compression technique based on run-length and Huffman encoding
Information Systems
Secondary indexing in one dimension: beyond b-trees and bitmap indexes
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Finding Regions of Interest in Large Scientific Datasets
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Inverted indexes vs. bitmap indexes in decision support systems
Proceedings of the 18th ACM conference on Information and knowledge management
Correlation maps: a compressed access method for exploiting soft functional dependencies
Proceedings of the VLDB Endowment
Position list word aligned hybrid: optimizing space and performance for compressed bitmaps
Proceedings of the 13th International Conference on Extending Database Technology
Space-efficient structures for detecting port scans
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
Approximation trade-offs in a Markovian stream warehouse: An empirical study
Information Systems
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Bitmap indices have been widely and successfully used in scientific and commercial databases. Compression techniques based on run-length encoding are used to improve the storage performance. However, these techniques introduce significant overheads in query processing even when only a few rows are queried. We propose a new bitmap encoding scheme based on multiple hashing, where the bitmap is kept in a compressed form, and can be directly accessed without decompression. Any subset of rows and/or columns can be retrieved efficiently by reconstructing and processing only the necessary subset of the bitmap. The proposed scheme provides approximate results with a trade-off between the amount of space and the accuracy. False misses are guaranteed not to occur, and the false positive rate can be estimated and controlled. We show that query execution is significantly faster than WAH-compressed bitmaps, which have been previously shown to achieve the fastest query response times. The proposed scheme achieves accurate results (90%-100%) and improves the speed of query processing from 1 to 3 orders of magnitude compared to WAH.