TY - GEN
T1 - An improved storage algorithm for multidimensional data cube
AU - He, Haitao
AU - Zhang, Yanpeng
AU - Ren, Jiadong
AU - Li, Lining
AU - Hu, Changzhen
PY - 2009
Y1 - 2009
N2 - There are 2n views in a n-dimensional data cube, the more the number of views, the more the maintenance time of data cube will be. According to the hierarchical feature of dimension in data cube, An Improved Storage Algorithm For Multidimensional Data Cube (ISMDC) is proposed in this paper. Dimensions are divided into association dimensions and no-association dimensions. The conception of Association Tree Cube is brought forward. On the no-association dimension, hierarchical B+ tree is used to remove redundancy and to form dimension hierarchical encoding. On the association dimension, encoding of the no-association dimension which is composed of dimension hierarchical encodings, is used for indexing. Thus, the value of aggregation will be searched out effectively. The experimental results show that ISMDC has reduced the storage requirement, maintenance time and improved the efficiency of data cube pattern update and the OLAP queries.
AB - There are 2n views in a n-dimensional data cube, the more the number of views, the more the maintenance time of data cube will be. According to the hierarchical feature of dimension in data cube, An Improved Storage Algorithm For Multidimensional Data Cube (ISMDC) is proposed in this paper. Dimensions are divided into association dimensions and no-association dimensions. The conception of Association Tree Cube is brought forward. On the no-association dimension, hierarchical B+ tree is used to remove redundancy and to form dimension hierarchical encoding. On the association dimension, encoding of the no-association dimension which is composed of dimension hierarchical encodings, is used for indexing. Thus, the value of aggregation will be searched out effectively. The experimental results show that ISMDC has reduced the storage requirement, maintenance time and improved the efficiency of data cube pattern update and the OLAP queries.
KW - Association tree cube
KW - Dimension hierarchical encoding
KW - Hierarchical B tree
KW - OLAP
UR - https://www.scopus.com/pages/publications/77951444075
U2 - 10.1109/ICICIC.2009.90
DO - 10.1109/ICICIC.2009.90
M3 - Conference contribution
AN - SCOPUS:77951444075
SN - 9780769538730
T3 - 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
SP - 841
EP - 844
BT - 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
T2 - 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
Y2 - 7 December 2009 through 9 December 2009
ER -