Efficient OLAP operations for spatial data using peano trees

Authors:
Baoying Wang;Fei Pan;Dongmei Ren;Yue Cui;Qiang Ding;William Perrizo
Affiliations:
North Dakota State University, Fargo, ND;North Dakota State University, Fargo, ND;North Dakota State University, Fargo, ND;North Dakota State University, Fargo, ND;North Dakota State University, Fargo, ND;North Dakota State University, Fargo, ND
Venue:
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Year:
2003

Citing 9
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Abstract

Online Analytical Processing (OLAP) is an important application of data warehouses. With more and more spatial data being collected, such as remotely sensed images, geographical information, digital sky survey data, efficient OLAP for spatial data is in great demand. In this paper, we build up a new data warehouse structure -- PD-cube, With PD-cube, OLAP operations and queries can be efficiently implemented. All these are accomplished based on the fast logical operations of Peano Trees (P-Trees*). One of the P-tree variations, Predicate P-tree, is used to efficiently reduce data accesses by filtering out "bit holes" consisting of consecutive 0's. Experiments show that OLAP operations can be executed much faster than with traditional OLAP methods.