Efficient implementation of data cubes via materialized views
Jeffrey David Ullman · Knowledge Discovery and Data Mining · 1996
Data cubes are specialized database management systems designed to support multidimensional data for such purposes as decision support and data mining. For a given mix of queries, we can optimize the implementation of a data cube by materializing some projections of the cube. A greedy approach turns out to be very effective; it is both polynomial-time as a function of the number of possible views to materialize and guaranteed to come close to the optimum choice of views. The work reported here is a summary of results appearing in the following two papers: V. Harinarayan, A. Rajaiaman, and J. D. Ullman, Implementing data cubes efficiently. To appear in 1996 SIGMOD. An extended version is available by anonymous ftp from db.stanford.edu as pub/harinarayan/1995/cube.ps. H. Gupta, V. Harinarayan, A. Rajaraman, and J. D. Ullman, Index selection for OLAP. Available by anonymous ftp from db.stanford.edu as pub/hgupta/1996/CubeIndex.ps.