Parallel data cube construction for high performance on-line analytical processing

Author

Goil, Sanjay ; Choudhary, Alok

Author_Institution

Dept. of Electr. & Comput. Sci., Northwestern Univ., Evanston, IL, USA

fYear

1997

fDate

18-21 Dec 1997

Firstpage

10

Lastpage

15

Abstract

Decision support systems use online analytical processing (OLAP) to analyze data by posing complex queries that require different views of data. Traditionally, a relational approach (ROLAP) has been taken to build such systems. More recently, multi-dimensional database techniques (MOLAP) have been applied to decision-support applications. Data is stored in multi-dimensional arrays, which is a natural way to express the multi-dimensionality of the enterprise and is more suited for analysis. Precomputed aggregate calculations in a data cube can provide efficient query processing for OLAP applications. In this paper, we present algorithms and results for in-memory data cube construction on distributed-memory machines

Keywords

arrays; data structures; decision support systems; distributed databases; distributed memory systems; hypercube networks; online operation; query processing; MOLAP; complex queries; data views; decision support systems; distributed-memory machines; high-performance online analytical processing; in-memory parallel data cube construction; multi-dimensional arrays; multi-dimensional database techniques; precomputed aggregate calculations; query processing; relational OLAP; Aggregates; Algorithm design and analysis; Concurrent computing; Data analysis; Decision support systems; Distributed computing; Memory management; Performance analysis; Query processing; Relational databases;

fLanguage

English

Publisher

ieee

Conference_Titel

High-Performance Computing, 1997. Proceedings. Fourth International Conference on

Conference_Location

Bangalore

Print_ISBN

0-8186-8067-9

Type

conf

DOI

10.1109/HIPC.1997.634462

Filename

634462