TY - GEN
T1 - Selective materialization
T2 - 2nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 1998
AU - Han, Jiawei
AU - Stefanovic, Nebojsa
AU - Koperski, Krzysztof
PY - 1998
Y1 - 1998
N2 - On-line analytical processing (OLAP) has gained its popularity in database industry. With a huge amount of data stored in spatial databases and the introduction of spatial components to many relational or object-relational databases, it is important to study the methods for spatial data warehousing and on-line analytical processing of spatial data. In this paper, we study methods for spatial OLAP, by integration of nonspatial on-line analytical processing (OLAP) methods with spatial database implementation techniques. A spatial data warehouse model, which consists of both spatial and nonspatial dimensions and measures, is proposed. Methods for computation of spatial data cubes and analytical processing on such spatial data cubes are studied, with several strategies proposed, including approximation and partial materialization of the spatial objects resulted from spatial OLAP operations. Some techniques for selective materialization of the spatial computation results are worked out, and the performance study has demonstrated the effectiveness of these techniques.
AB - On-line analytical processing (OLAP) has gained its popularity in database industry. With a huge amount of data stored in spatial databases and the introduction of spatial components to many relational or object-relational databases, it is important to study the methods for spatial data warehousing and on-line analytical processing of spatial data. In this paper, we study methods for spatial OLAP, by integration of nonspatial on-line analytical processing (OLAP) methods with spatial database implementation techniques. A spatial data warehouse model, which consists of both spatial and nonspatial dimensions and measures, is proposed. Methods for computation of spatial data cubes and analytical processing on such spatial data cubes are studied, with several strategies proposed, including approximation and partial materialization of the spatial objects resulted from spatial OLAP operations. Some techniques for selective materialization of the spatial computation results are worked out, and the performance study has demonstrated the effectiveness of these techniques.
KW - Data mining
KW - Data warehouse
KW - On-line analytical processing (OLAP)
KW - Spatial OLAP
KW - Spatial data analysis
KW - Spatial databases
UR - http://www.scopus.com/inward/record.url?scp=84958957229&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84958957229&partnerID=8YFLogxK
U2 - 10.1007/3-540-64383-4_13
DO - 10.1007/3-540-64383-4_13
M3 - Conference contribution
AN - SCOPUS:84958957229
SN - 3540643834
SN - 9783540643838
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 144
EP - 158
BT - Research and Development in Knowledge Discovery and Data Mining - 2nd Pacific-Asia Conference, PAKDD 1998, Proceedings
A2 - Wu, Xindong
A2 - Kotagiri, Ramamohanarao
A2 - Korb, Kevin B.
PB - Springer
Y2 - 15 April 1998 through 17 April 1998
ER -