A functional disk system for relational database processing: Design and performance evaluation

Abstract

This paper considers a relational database processing system and proposes a new high-performance secondary memory system and a functional disk system aiming at the high-speed processing. The traditional commercial relational DBMS employs the simple nest-loop and sort-merge as processing methods for relational algebra operations. However, the proposed functional disk system employs the dynamic clustering algorithm so that the processing load is reduced drastically. Such processes as the hash operation, the cluster management mechanism, the record extraction from the physical block and on-the-fly operation, which takes time by the software, are implemented by hardware. The clustering following the data transfer from the disk is then realized. The performance is improved further by using several processors so that the generated clusters are processed in parallel. Usually, the performance is deteriorated greatly due to the mismatch between OS and DBMS constructed on OS. To solve this problem, the dedicated input/output driver and the buffer management routine were developed in the functional disk system by optimizing the dynamic clustering technique. The functional disk system aims at the drastic performance improvement by introducing the database processing mechanism into the secondary memory system. To verify the effectiveness of this idea, an experimental system was constructed. In spite of the simple structure composed of a disk and 4 MC68020, the experimental system achieved a much higher performance than the existing commercial relational database system in the performance evaluation using the Wisconsin benchmark. Thus, the effectiveness of the functional disk system is verified.