skip to main content
10.1145/253260.253268acmconferencesArticle/Chapter ViewAbstractPublication PagesmodConference Proceedingsconference-collections
Article
Free Access

Improved query performance with variant indexes

Authors Info & Claims
Published:01 June 1997Publication History

ABSTRACT

The read-mostly environment of data warehousing makes it possible to use more complex indexes to speed up queries than in situations where concurrent updates are present. The current paper presents a short review of current indexing technology, including row-set representation by Bitmaps, and then introduces two approaches we call Bit-Sliced indexing and Projection indexing. A Projection index materializes all values of a column in RID order, and a Bit-Sliced index essentially takes an orthogonal bit-by-bit view of the same data. While some of these concepts started with the MODEL 204 product, and both Bit-Sliced and Projection indexing are now fully realized in Sybase IQ, this is the first rigorous examination of such indexing capabilities in the literature. We compare algorithms that become feasible with these variant index types against algorithms using more conventional indexes. The analysis demonstrates important performance advantages for variant indexes in some types of SQL aggregation, predicate evaluation, and grouping. The paper concludes by introducing a new method whereby multi-dimensional group-by queries, reminiscent of OLAP/Datacube queries but with more flexibility, can be very efficiently performed.

References

  1. COMER79.Comer, D. The Ubiquitous B-tree. Comput. Surv. 11 (1979), pp. 121-137. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. EDEL95.Herb Edelstein. Faster Data Warehouses. Information Week, Dec. 4, 1995, pp. 77-88. Give title and author on http://www.techweb.com/search/advsearch.html.Google ScholarGoogle Scholar
  3. FREN95.Clark D. French. "One Size Fits All" Database Architectures Do Not Work for DSS. Proceedings of the 1995 ACM SIGMOD Conference, pp. 449-450. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. GBLP96.Jim Gray, Adam Bosworth, Andrew Layman, and Hamid Pirahesh. Data Cube: A Relational Operator Generalizing Group-By, Cross-Tab, and Sub-Totals. Proc. 12th Int. Conf. on Data Eng., pp. 152-159, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. GP87.Jim Gray and Franco Putzolu. The Five Minute Rule for Trading Memory for Disk Accesses and The 10 Byte Rule for Trading Memory for CPU Time. Proc. 1987 ACM SIGMOD, pp. 395-398. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. HRU96.Venky Harinarayan, Anand Rajaraman, and Jeffrey D. Ullman. Implementing Data Cubes Efficiently. Proc. 1996 ACM SIGMOD, pp. 205-216. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. KIMB96.Ralph Kimball. The Data Warehouse Toolkit. John Wiley & Sons, 1996.Google ScholarGoogle Scholar
  8. M204.MODEL 204 File Manager's Guide, Version 2, Release 1.0, April 1989, Computer Corporation of America.Google ScholarGoogle Scholar
  9. O'NEI87.Patrick O'Neil. Model 204 Architecture and Performance. Springer-Verlag Lecture Notes in Computer Science 359, 2nd Int. Workshop on High Performance Transactions Systems (HPTS), Asilomar, CA, 1987, pp. 40-59. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. O'NEI91.Patrick O'Neil. The Set Query Benchmark. The Benchmark Handbook for Database and Transaction Processing Systems, Jim Gray (Ed.), Morgan Kaufmann, 2nd Ed. 1993, pp. 359-395.Google ScholarGoogle Scholar
  11. O'NEI96.Patrick O'Neil. Database: Principles, Programming, and Performance. Morgan Kaufmann, 3rd printing, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. O'NGG95.Patrick O'Neil and Goetz Graefe. Multi-Table Joins Through Bitmapped Join Indices. SIGMOD Record, September, 1995, pp. 8-11, Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. O'NQUA.Patrick O'Neil and Dallan Quass. Improved Query Performance with Variant Indexes. Extended paper, available on h ttp :/www. c s. umb. edu/--po nei I/v ari nde xx. psGoogle ScholarGoogle Scholar
  14. PH96.D. A. Patterson and J. L. Hennessy. Computer Architecture, A Quantitative Approach. Morgan Kaufmann, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. STG95.Stanford Technology Group, Inc., An INFORMIX Co. Designing the Data Warehouse on Relational Databases. lnformix White Paper, 1995, http://www.informix.com.Google ScholarGoogle Scholar
  16. TPC.TPC Home Page. Descriptions and results of TPC benchmarks, including the TPC-C and TPC-D benchmarks. http://www.tpc.org.Google ScholarGoogle Scholar

Index Terms

  1. Improved query performance with variant indexes

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in
            • Published in

              cover image ACM Conferences
              SIGMOD '97: Proceedings of the 1997 ACM SIGMOD international conference on Management of data
              June 1997
              594 pages
              ISBN:0897919114
              DOI:10.1145/253260

              Copyright © 1997 ACM

              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 1 June 1997

              Permissions

              Request permissions about this article.

              Request Permissions

              Check for updates

              Qualifiers

              • Article

              Acceptance Rates

              SIGMOD '97 Paper Acceptance Rate42of202submissions,21%Overall Acceptance Rate785of4,003submissions,20%

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader