Implementing data cubes efficiently

Implementing data cubes efficiently (1996)

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by Venky Harinarayan , Anand Rajaraman , Jeffrey D. Ulman

Venue:	In SIGMOD
Citations:	425 - 1 self

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Datum	Value	Source
TITLE	Implementing data cubes efficiently	INFERENCE
AUTHOR NAME	Venky Harinarayan	SVM HeaderParse 0.2
AUTHOR AFFIL	Stanford University Stanford University Stanford IJniversity	SVM HeaderParse 0.2
AUTHOR NAME	Anand Rajaraman	SVM HeaderParse 0.2
AUTHOR AFFIL	Stanford University Stanford University Stanford IJniversity	SVM HeaderParse 0.2
AUTHOR NAME	Jeffrey D. Ulman	SVM HeaderParse 0.2
AUTHOR AFFIL	Stanford University Stanford University Stanford IJniversity	SVM HeaderParse 0.2
ABSTRACT	Decision support applications involve complex queries on very large databases. Since response times should be small, query optimization is critical. Users typically view the data as multidimensional data cubes. Each cell of the data cube is a view consisting of an aggregation of interest, like total sales. The values of many of these cells are dependent on the values of other cells in the data cube..A common and powerful query optimization technique is to materialize some or all of these cells rather than compute them from raw data each time. Commercial systems differ mainly in their approach to materializing the data cube. In this paper, we investigate the issue of which cells (views) to materialize when it is too expensive to materialize all views. A lattice framework is used to express dependencies among views. We present greedy algorithms that work off this lattice and determine a good set of views to materialize. The greedy algorithm performs within a small constant factor of optimal under a variety of models. We then consider the most common case of the hypercube lattice and examine the choice of materialized views for hypercubes in detail, giving some good tradeoffs between the space used and the average time to answer a query. 1	SVM HeaderParse 0.2
YEAR	1996	INFERENCE
VENUE	In SIGMOD	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
CITATIONS	14 found	ParsCit 1.0