在功能磁盘系统上执行大型关系的查询

M. Kitsuregawa, M. Nakano, M. Takagi
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引用次数: 24

摘要

讨论了基于关系数据库引擎的功能磁盘系统(functional disk system with relational database engine, FDS-RII)的第二版——FDS-RII。在FDS-RII上,通过比较估计的I/O成本,在运行时从两种算法(嵌套循环算法、grace哈希算法)中选择处理算法。详细讨论了加工策略。通过测量FDS-RII上连接查询的执行时间来检查I/O成本公式。通过威斯康星基准的扩展版本,对FDS-RII的性能进行了测量。与Gamma和Teradata等其他大型数据库系统相比,FDS-RII在处理大型关系方面达到了很高的性能水平。FDS只需要一个磁盘和三个mc68020, Teradata需要40个磁盘和20个amp, Gamma需要8个磁盘和17个VAX 11/750。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Query execution for large relations on functional disk system
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.<>
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