A general solution of the n-dimensional B-tree problem
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
The pyramid-technique: towards breaking the curse of dimensionality
SIGMOD '98 Proceedings of the 1998 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
Query optimization for selections using bitmaps
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Encoded Bitmap Indexing for Data Warehouses
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Multidimensional Indexing and Query Coordination for Tertiary Storage Management
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Automatic Reclustering of Objects in Very Large Databases for High Energy Physics
IDEAS '98 Proceedings of the 1998 International Symposium on Database Engineering & Applications
Bitmap Indices for Speeding Up High-Dimensional Data Analysis
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
On multidimensional data and modern disks
FAST'05 Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4
Breaking the Curse of Cardinality on Bitmap Indexes
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
Effective bitmap indexing for non-metric similarities
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
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Bitmap indices are popular multi-dimensional data structures for accessing read-mostly data such as data warehouse (DW) applications, decision support systems (DSS) and on-line analytical processing (OLAP). One of their main strengths is that they provide good performance characteristics for complex adhoc queries and an efficient combination of multiple index dimensions in one query. Considerable research work has been done in the area of finite (and low) attribute cardinalities. However, additional complexity is imposed on the design of bitmap indices for high cardinality or even non-discrete attributes, where different optimisation techniques than the ones proposed so far have to be applied. In this paper we discuss the design and implementation of bitmap indices for High-Energy Physics (HEP) analysis, where the potential search space consists of hundreds of independent dimensions. A single HEP query typically covers 10 to 100 dimensions out of the whole search space. In this context we evaluated two different bitmap encoding techniques, namely equality encoding and range encoding. For both methods the number of bit slices (or bitmap vectors) per attribute is a central optimisation parameter. The paper presents some (first) results for choosing the optimal number of bit slices for multi-dimensional indices with attributes of different value distribution and query selectivity. We believe that this discussion is not only applicable to HEP but also to DW, DSS and OLAP type problems in general.