A comparative analysis of fragmentation selection algorithms for data warehouse partitioning

Enterprise data warehouse system maintains large amounts of data for enabling business analysis. The queries imposed on such system involves complex joins, aggregation and filter operations. Hence in order to enhance query performance the data warehouse needs to be tuned by optimization techniques such as partitioning. Referential horizontal partitioning performs better for data warehouse where the fact table is partitioned based on the dimension table. The number of fragments or partitions that is generated by horizontal partitioning might be very large to be managed in the underlying database. In literature few fragmentation selection algorithms have been proposed in order to choose optimal set of fragments. In this paper we provide a summary of different fragmentation selection algorithms and provide comparative analysis between them.