Incremental Maintenance of Data Cubes
Dong Jin, Tatsuo Tsuji, Ken Higuchi
Abstract
Dong Jin, Tatsuo Tsuji, Ken Higuchi
Abstract
Data cube construction is a commonly used operation in data warehouses. Because of the volume of data stored and analyzed in a data warehouse and the amount of computation involved in data cube construction, incremental maintenance of data cube is really effective. To maintain a data cube incrementally, previous methods were mainly for relational databases. In this paper, we employ an extendible multidimensional array model to maintain data cubes. Such an array enables incremental cube maintenance without relocating any data dumped at an earlier time, while computing the data cube efficiently by utilizing the fast random accessing capability of arrays. Our data cube scheme and related maintenance methods are presented in this paper, and cost analysis on our approach is shown and compared with existing methods. Keyword Data warehouse,Data cube,Incremental maintenance,Extendible array
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Data cube construction is a commonly used operation in data warehouses. Because of the volume of data stored and analyzed in a data warehouse and the amount of computation involved in data cube construction, incremental maintenance of data cube is really effective. To maintain a data cube incrementally, previous methods were mainly for relational databases. In this paper, we employ an extendible multidimensional array model to maintain data cubes. Such an array enables incremental cube maintenance without relocating any data dumped at an earlier time, while computing the data cube efficiently by utilizing the fast random accessing capability of arrays. Our data cube scheme and related maintenance methods are presented in this paper, and cost analysis on our approach is shown and compared with existing methods. Keyword Data warehouse,Data cube,Incremental maintenance,Extendible array
Key concepts: Data cube, Data warehouse, Cube (algebra), Computer science, Online analytical processing, Database, Volume (thermodynamics), Data mining