Efficient binning for bitmap indices on high-cardinality attributes

PDF Version Also Available for Download.

Description

Bitmap indexing is a common technique for indexing high-dimensional data in data warehouses and scientific applications. Though efficient for low-cardinality attributes, query processing can be rather costly for high-cardinality attributes due to the large storage requirements for the bitmap indices. Binning is a common technique for reducing storage costs of bitmap indices. This technique partitions the attribute values into a number of ranges, called bins, and uses bitmap vectors to represent bins (attribute ranges) rather than distinct values. Although binning may reduce storage costs, it may increase the access costs of queries that do not fall on exact bin boundaries ... continued below

Physical Description

vp.

Creation Information

Rotem, Doron; Stockinger, Kurt & Wu, Kesheng November 17, 2004.

Context

This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 41 times . More information about this report can be viewed below.

Who

People and organizations associated with either the creation of this report or its content.

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this report. Follow the links below to find similar items on the Digital Library.

Description

Bitmap indexing is a common technique for indexing high-dimensional data in data warehouses and scientific applications. Though efficient for low-cardinality attributes, query processing can be rather costly for high-cardinality attributes due to the large storage requirements for the bitmap indices. Binning is a common technique for reducing storage costs of bitmap indices. This technique partitions the attribute values into a number of ranges, called bins, and uses bitmap vectors to represent bins (attribute ranges) rather than distinct values. Although binning may reduce storage costs, it may increase the access costs of queries that do not fall on exact bin boundaries (edge bins). For this kind of queries the original data values associated with edge bins must be accessed, in order to check them against the query constraints.In this paper we study the problem of finding optimal locations for the bin boundaries in order to minimize these access costs subject to storage constraints. We propose a dynamic programming algorithm for optimal partitioning of attribute values into bins that takes into account query access patterns as well as data distribution statistics. Mathematical analysis and experiments on real life data sets show that the optimal partitioning achieved by this algorithm can lead to a significant improvement in the access costs of bitmap indexing systems for high-cardinality attributes.

Physical Description

vp.

Notes

OSTI as DE00841113

Source

  • Other Information: PBD: 17 Nov 2004

Language

Item Type

Identifier

Unique identifying numbers for this report in the Digital Library or other systems.

  • Report No.: LBNL--56936
  • Grant Number: AC03-76SF00098
  • DOI: 10.2172/841113 | External Link
  • Office of Scientific & Technical Information Report Number: 841113
  • Archival Resource Key: ark:/67531/metadc785154

Collections

This report is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this report?

When

Dates and time periods associated with this report.

Creation Date

  • November 17, 2004

Added to The UNT Digital Library

  • Dec. 3, 2015, 9:30 a.m.

Description Last Updated

  • April 4, 2016, 12:48 p.m.

Usage Statistics

When was this report last used?

Yesterday: 0
Past 30 days: 1
Total Uses: 41

Interact With This Report

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Rotem, Doron; Stockinger, Kurt & Wu, Kesheng. Efficient binning for bitmap indices on high-cardinality attributes, report, November 17, 2004; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc785154/: accessed October 23, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.