Multidimensional data clustering

Multidimensional data clustering is flexible, continuous, and automatic clustering of data along multiple dimensions. With multidimensional data clustering, you will see significant improvement in the performance of queries, as well as significant reduction in the overhead of data maintenance operations, such as reorganization and index maintenance operations during insert, update, and delete operations. Multidimensional data clustering is primarily intended for data warehousing and large database environments, and it can also be used in online transaction processing (OLTP) environments.

Multidimensional data clustering enables a table to be physically clustered on more than one key (or dimension) simultaneously. Before version 8.1, DB2 supported only single-dimensional data clustering of data, through clustering indexes. Using a clustering index, DB2 attempts to maintain the physical order of data on pages in the key order of the index, as records are inserted and updated in the table. Clustering indexes greatly improve the performance of range queries that have predicates containing one or more keys of the clustering index. With good clustering, only a portion of the table needs to be accessed and, when the pages are sequential, more efficient prefetching can be performed.