The performance of disk arrays in shared-memory database machines

Abstract

Disk arrays and shared-memory multiprocessors are new technologies that are rapidly becoming pervasive. They are complementary because disk arrays naturally balance the I/O workload by interleaving data across all disks while a shared-memory multiprocessor balances the processing workload across multiple processors. In this paper, we examine how disk arrays and shared memory multiprocessors lead to an effective method for constructing database machines for general-purpose complex query processing. We show that disk arrays can lead to cost-effective storage systems if they are configured from suitably small formfactor disk drives. We introduce the storage system metricdata temperature (IO/s/Gbyte) as a way to evaluate how well a disk configuration can sustain its workload, and we show that disk arrays can sustain the same data temperature as a more expensive mirrored-disk configuration. We use the metric to evaluate the performance of disk arrays in XPRS, an operational shared-memory multiprocessor database system being developed at the University of California, Berkeley.