Query execution for large relations on functional disk system

Abstract

The second version of FDS-R (functional disk system with relational database engine), FDS-RII, which is designed to handle large relations efficiently, is discussed. On FDS-RII, the processing algorithm is selected at run time from two algorithms (nested loop algorithms, grace hash algorithm) by comparing their estimated I/O costs. The processing strategy is discussed in detail. The I/O cost formula is examined by measuring the execution time of a join query on the FDS-RII. With the expanded version of Wisconsin Benchmark, the performance of FDS-RII is measured. FDS-RII attained a high performance level for large relations as compared to other large database systems such as Gamma and Teradata. While FDS uses just one disk and three MC68020s, Teradata uses 40 disks and 20 AMPs and Gamma requires eight disks and 17 VAX 11/750s.<>