Workfile disk management for concurrent mergesorts in a multiprocessor database system

This paper studies workfile disk management for concurrent mergesorts in a multiprocessor database system. Specifically we examine the impacts of workfile disk allocation and data striping on the average mergesort response time. Concurrent mergesorts in a multiprocessor system can create severe I/O interference in which a large number of sequential write requests are continuously issued to the same workfile disk and block other read requests for a long period of time. We examine through detailed simulations a logical partitioning approach to workfile disk management and evaluate the effectiveness of data striping. The results show that (1) without data striping, the best performance is achieved by using the entire workfile disks as a single partition if there are abundant workfile disks (or system workload is light); (2) however, if there are limited workfile disks (or system workload is heavy), the workfile disks should be partitioned into multiple groups and the optimal partition size is workload dependent; (3) data striping is beneficial only if the striping unit size is properly chosen; and (4) with a proper striping size, the best performance is generally achieved by using the entire disks as a single logical partition.