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Bitmap Index

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Encyclopedia of Database Systems

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Definition

An index on an attribute provides an efficient way to access data records associated with a given range of values for the indexed attribute. Typically, an index stores a list of RIDs (called a RID-list) of all the records associated with each distinct value v of the indexed attribute. In a bitmap index, each RID-list is represented in the form of a bit vector (i.e., bitmap) where the size of each bitmap is equal to the cardinality of the indexed relation, and the ith bit in each bitmap corresponds to the ith record in the indexed relation. The simplest bitmap index design is the Value-List index, which is illustrated in Fig. 1b for an attribute A of a 12-record relation R in Fig. 1a. In this bitmap index, there is one bitmap E v associated with each attribute value v ∈ [0,9] such that the ith bit of E v is set to 1 if and only if the ith record has a value v for the indexed attribute.

Bitmap Index. Figure 1
figure 1_749

Examples of bitmap indexes. (a) indexed attribute A(b)...

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Recommended Reading

  1. Amer-Yahia S. and Johnson T. Optimizing queries on compressed bitmaps. In Proc. 26th Int. Conf. on Very Large Data Bases, 2000, pp. 329–338.

    Google Scholar 

  2. Chan C.Y. and Ioannidis Y.E. Bitmap index design and evaluation. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1998, pp. 355–366.

    Google Scholar 

  3. Chan C.Y. and Ioannidis Y.E. An efficient bitmap encoding scheme for selection queries. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1999, pp. 215–226.

    Google Scholar 

  4. Knuth D.E. Retrieval on secondary keys. In The Art of Computer Programming: Sorting and Searching, vol. 3. Chap. 6. Addison-Wesley, Reading, Mass., 1973, pp. 550–567.

    Google Scholar 

  5. Koudas N. Space efficient bitmap indexing. In Proc. Int. Conf. on Information and Knowledge Management, 2000, pp. 194–201.

    Google Scholar 

  6. O’Neil P. and Graefe G. Multi-table joins through bitmapped join indices. ACM SIGMOD Record. September 1995, pp. 8–11.

    Google Scholar 

  7. O’Neil P. and Quass D. Improved query performance with variant indexes. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1997, pp. 38–49.

    Google Scholar 

  8. Reinfret D., O’Neil P., and O’Neil E. Bit-sliced index arithmetic. In Proc. ACM SIGMOD Int. Conf. on Management of Data. 2001, pp. 47–57.

    Google Scholar 

  9. Rotem D., Stockinger K., and Wu K. Optimizing candidate check cost for bitmap indices. In Proc. Int. Conf. on Information and Knowledge Management, 2005, pp. 648–655.

    Google Scholar 

  10. Sinha R. and Winslett M. Multi-resolution bitmap indexes for scientific data. ACM Trans. Database Syst., 32(3):1–39, 2007.

    Article  Google Scholar 

  11. Wong H.K.T., Liu H-F., Olken F., Rotem D., and Wong L. Bit transposed files. In Proc. 11th Int. Conf. on Very Large Data Bases, 1985, pp. 448–457.

    Google Scholar 

  12. Wu M.C. Query optimization for selections using nitmaps. In Proc. ACM SIGMOD Int. Conf. on Management of Data 1999, pp. 227–238, 1999.

    Google Scholar 

  13. Wu M.C. and Buchmann A.P. Encoded bitmap indexing for data warehouses. In Proc. 14th Int. Conf. on Data Engineering, 1998, pp. 220–230.

    Google Scholar 

  14. Wu K., Otoo E.J., and Shoshani A. Optimizing bitmap indices with efficient compression. ACM Trans. Database Syst., 31(1):1–38, 2006.

    Article  Google Scholar 

  15. Wu K.L. and Yu P.S. Range-based bitmap indexing for high cardinality attributes with skew. Technical report, IBM Watson Research Center, May 1996.

    Google Scholar 

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Author information

Authors and Affiliations

  1. National University of Singapore, Singapore, Singapore

    Chee Yong Chan

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  1. Chee Yong Chan
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Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU (Professor) (Professor)

  2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

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© 2009 Springer Science+Business Media, LLC

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Chan, C. (2009). Bitmap Index. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_749

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