Improving server performance on transaction processing workloads by enhanced data placement

Abstract

Modern servers access large volumes of data while running commercial workloads. The data is typically spread among several storage devices (e.g. disks). Carefully placing the data across the storage devices can minimize costly remote accesses and improve performance. We propose the use of simulated annealing to arrive at an effective layout of data on disk. The proposed technique considers the configuration of the system and the cost of data movement. An initial layout globally optimized across all queries, shows speedups of up to 13% for a group of DSS queries and up to 6% for selected OLTP queries. This technique can be re-applied at run-time to further improve performance beyond the initial, globally optimized data layout. This scheme monitors architecture parameters to prevent optimizations of multiple operations to conflict with each other. Such a dynamic reorganization results in speedups of up to 23% for the DSS queries and up to 10% for the OLTP queries.