PIN: A partitioning and indexing optimization method for OLAP

Authors

Abstract

Optimizing the performance of OLAP queries in relational data warehouses (DW) has always been a major research issue. There are various techniques that can be used to achieve its goals, such as data partitioning, indexing, data aggregation, data sampling, redefinition of database (DB) schemas, among others. In this paper we present a simple and easy to implement method which links partitioning and indexing based on the features present in predefined major decision making queries to efficiently optimize a data warehouse’s performance. The evaluation of this method is also presented using the TPC-H benchmark, comparing it with standard partitioning and indexing techniques, demonstrating its efficiency with single and multiple simultaneous user scenarios.

Keywords

Performance Optimization, Partitioning, Indexing, Data warehousing

Subject

Query optimization

Conference

ICEIS 2007 - International Conference on Enterprise Information Systems, June 2007

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