An overview of data warehousing and OLAP technology
ACM SIGMOD Record
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
Multidimensional access methods
ACM Computing Surveys (CSUR)
An efficient bitmap encoding scheme for selection queries
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
ACM Computing Surveys (CSUR)
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
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
The Universal B-Tree for Multidimensional Indexing: general Concepts
WWCA '97 Proceedings of the International Conference on Worldwide Computing and Its Applications
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
Optimizing bitmap indices with efficient compression
ACM Transactions on Database Systems (TODS)
Optimal Synchronization Policies for Data Warehouses
INFORMS Journal on Computing
High performance multivariate visual data exploration for extremely large data
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Histogram-aware sorting for enhanced word-aligned compression in bitmap indexes
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
Investigating design choices between Bitmap index and B-tree index for a large data warehouse system
ACS'08 Proceedings of the 8th conference on Applied computer scince
New binning strategy for bitmap indices on high cardinality attributes
Proceedings of the 2nd Bangalore Annual Compute Conference
Sorting improves word-aligned bitmap indexes
Data & Knowledge Engineering
Analyses of multi-level and multi-component compressed bitmap indexes
ACM Transactions on Database Systems (TODS)
Indexing RFID data using the VG-curve
ADC '12 Proceedings of the Twenty-Third Australasian Database Conference - Volume 124
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As data warehousing applications grow in size, existing data organizations and access strategies, such as relational tables and B-tree indexes, are becoming increasingly ineffective. The two primary reasons for this are that these datasets involve many attributes and the queries on the data usually involve conditions on small subsets of the attributes. Two strategies are known to address these difficulties well, namely vertical partitioning and bitmap indexes. In this paper, we summarize our experience of implementing a number of bitmap index schemes on vertically partitioned data tables. One important observation is that simply scanning the vertically partitioned data tables is often more efficient than using B-tree based indexes to answer ad hoc range queries on static datasets. For these range queries, compressed bitmap indexes are in most cases more efficient than scanning vertically partitioned tables. We evaluate the performance of two different compression schemes for bitmap indexes stored is various ways. Using the compression scheme called Word-Aligned Hybrid Code (WAH) to store the bitmaps in plain files shows the best overall performance for bitmap indexes. Tests indicate that our bitmap index strategy based on WAH is not only efficient for attributes of low cardinality, say,