Automating physical database design in a parallel database

Physical database design is important for query performance in a shared-nothing parallel database system, in which data is horizontally partitioned among multiple independent nodes. We seek to automate the process of data partitioning. Given a workload of SQL statements, we seek to determine automatically how to partition the base data across multiple nodes to achieve overall optimal or close to optimal performance for that workload. Previous attempts use heuristic rules to make those decisions. These approaches fail to consider all of the interdependent aspects of query performance typically modeled by today's sophisticated query optimizers. We present a comprehensive solution to the problem that has been tightly integrated with the optimizer of a commercial shared-nothing parallel database system. Our approach uses the query optimizer itself both to recommend candidate partitions for each table that will bene t each query in the workload, and to evaluate various combinations of...

• Type: Conference
• Year: 2002
• Where: SIGMOD
• Authors: Jun Rao, Chun Zhang, Nimrod Megiddo, Guy M. Lohman
• Keywords: Database, Query Optimizer, Query Performance, SIGMOD 2002, Sophisticated Query Optimizers