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Improved Query Performance with Variant Indexes

O'Neil, P. and Quass, D. (1996) Improved Query Performance with Variant Indexes. Technical Report. Stanford InfoLab. (Publication Note: SIGMOD'97)




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 basically 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 or Datacube queries but withmore flexibility, can be very efficiently performed.

Item Type:Techreport (Technical Report)
Uncontrolled Keywords:indexes, indexing, bitmap, data warehousing, olap
Subjects:Computer Science > Query Processing
Related URLs:Project Homepage
ID Code:137
Deposited By:Import Account
Deposited On:25 Feb 2000 16:00
Last Modified:09 Dec 2008 09:14

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