Data mining on an OLTP system (nearly) for free

This paper proposes a scheme for scheduling disk requests that takes advant age of the ability of high-level functions to operate directly at individua l disk drives. We show that such a scheme makes it possible to support a Da ta Mining workload on an OLTP system almost for free: there is only a small impact on the throughput and response time of the existing workload. Speci fically, we show that an OLTP system has the disk resources to consistently provide one third of its sequential bandwidth to a background Data Mining task with close to zero impact on OLTP throughput and response time at high transaction loads. At low transaction loads, we show much lower impact tha n observed in previous work. This means that a production OLTP system can b e used for Data Mining tasks without the expense of a second dedicated syst em. Our scheme takes advantage of close interaction with the on-disk schedu ler by reading blocks for the Data Mining workload as the disk head "passes over" them while satisfying demand blocks from the OLTP request stream. We show that this scheme provides a consistent level of throughput for the ba ckground workload even at very high foreground loads. Such a scheme is of m ost:benefit in combination with an Active Disk environment that allows the background Data Mining application to also take advantage of the processing power and memory available directly on the disk drives.