Performance Study of Rollout for Multi Dimensional Clustered Tables in DB2

In data warehousing applications, the ability to efficiently delete large chunks of data from a table is very important. This feature is also known as Rollout. Rollout is generally carried out periodically and is often done on more than one dimension or attribute. DB2 UDB V8.1 introduced a new physical clustering scheme called Multi Dimensional Clustering (MDC) which allows users to cluster data in a table on multiple attributes or dimensions. This is very useful for query processing and maintenance activities including deletes. Subsequently, an enhancement was incorporated which allowed for more efficient rollout of data on dimensional boundaries. This paper details a performance study of MDC rollout and delete and compares it against the conventional delete mechanism of a regular DB2 table. We discuss some of the key points noticed and the lessons learnt. Categories and Subject Descriptors H.2.4 [Systems]: Relational databases General Terms Algorithms, Measurement, Performance, Desi...

• Type: Conference
• Year: 2006
• Where: EXPDB
• Authors: Bishwaranjan Bhattacharjee
• Keywords: Efficient Rollout, EXPDB 2006, Information Management, MDC Rollout, Multi Dimensional Clustering