Implementing relational database operations in a cube-connected multicomputer system

1987 IEEE Third International Conference on Data Engineering Pub Date : 1987-02-03 DOI:10.1109/ICDE.1987.7272354

C. Baru, O. Frieder

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引用次数: 54

Abstract

Parallel architectures for database processing should incorporate parallel CPU as well as parallel I/O (disk access) capability. The need to support parallel I/O gives rise to two important issues - data combination and non-uniform data distribution. Strategies for performing database operations in a cube-connected multicomputer system with parallel I/O are presented in this paper. The cube interconnection subsumes many other structures such as the tree, ring, etc. This property is exploited to efficiently support database operations such as Select, Aggregate, Join, and Project. The strategies presented here are unique in that they account for the non-uniform distribution of data across parallel paths by incorporating data redistribution steps as part of the overall algorithm. The two main data redistribution operations used are tuple balancing and merging. A simple analysis of the join and project operations is carried out assuming non-uniform data distributions. A more detailed simulation and study of issues related to query processing will be carried out as part of the future work.

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在多维数据集连接的多计算机系统中实现关系数据库操作

用于数据库处理的并行体系结构应该包含并行CPU和并行I/O(磁盘访问)功能。支持并行I/O的需求产生了两个重要的问题——数据组合和不统一的数据分布。本文提出了在具有并行I/O的立方体连接多计算机系统中执行数据库操作的策略。立方体互连包含许多其他结构，如树、环等。此属性用于有效地支持数据库操作，如选择、聚合、连接和项目。这里提出的策略是独特的，因为它们通过将数据重新分配步骤作为整个算法的一部分来考虑数据在并行路径上的不均匀分布。使用的两个主要数据重新分配操作是元组平衡和合并。假设数据分布不均匀，对连接和项目操作进行简单分析。对查询处理相关问题的更详细的模拟和研究将作为未来工作的一部分进行。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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1987 IEEE Third International Conference on Data Engineering

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