数据库操作加速：向量处理器的应用

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"这篇学术论文‘Acceleration of relational database operations on vector processors’由Shintaro Meki和Yahiko Kambayashi撰写，分别来自日本Okayama Prefectural University的计算机科学与系统工程学院和京都大学的工程研究生院。文章探讨了在数据库应用领域的扩展背景下，处理的数据量变得极其庞大，对更快的数据库系统的需要日益增强的问题。随着数据库应用领域的拓宽，处理数据的规模已经达到了巨大的程度，这使得对数据库系统速度的需求不断加剧。因此，许多研究工作致力于通过使用特殊硬件来更有效地执行数据库操作。然而，对于无法使用大规模集成电路（LSI）的情况，成本变得过高，人们开始寻求替代方案。近年来，具有强大流水线操作员和大容量主内存的向量处理器得到了迅速普及。论文提出了适合于向量处理器的、充分展现其特性的关系数据库操作算法。这种算法基于哈希方法，当主内存容量较大时，哈希方法能实现高效运行。论文展示了这种算法如何能够利用向量处理器的并行计算能力，以加速数据库操作，如查询和数据处理，从而提高整体性能。在数据库管理系统中，向量处理器的运用可以显著提升处理大量数据的速度。哈希方法是一种常用的数据查找技术，通过创建哈希表，能够在平均时间内快速定位数据。在大型数据集上，哈希方法与向量处理器的结合可以实现高效的数据检索和处理，这对于大数据分析、实时查询和事务处理等应用场景尤其重要。这篇论文为利用向量处理器优化数据库操作提供了新的思路，为解决数据库性能瓶颈问题提供了可能的解决方案，特别是在处理大规模数据和追求高速运算的场景下，这种方法有望成为一种经济高效的策略。"

Acceleration of Relational Database Operations on Vector

Processors

Shintaro Meki

Faculty of Computer Science & Systems Engineering, Okayama Prefectural University, Soja, Japan 719-1197

Yahiko Kambayashi

Graduate Faculty of Engineering, Kyoto University, Kyoto, Japan 606-8501

SUMMARY

With the expansion of the areas of database applica-

tions, the amount of data processed has become gigantic,

and the demand for faster database systems has increasingly

intensified. Thus, many efforts have been expended to

execute database operations more efficiently using special

hardware. However, for the cases in which mass-produced

LSI cannot be used, cost has become excessive, and replace-

ment methods have been sought. Vector processors have

powerful pipeline operators and large-capacity main

memories and have rapidly spread in recent years. In this

paper, algorithms for relational database operations suitable

for vector processors showing the characteristics of vector

processors sufficiently are presented. This algorithm is

based on the hash method, which is highly efficient when

the capacity of the main memory is large, and it is shown

that a rate of acceleration more than 10 times the average is

obtained for representative relational database operations

Scripta Technica, Syst Comp Jpn, 31(8): 7988, 2000

Key words: Vector processor; main memory data-

base; join algorithm; hash technique.

1. Introduction

The demand for high-speed database management

systems (DBMS) has increased each year due to the expan-

sion of areas of database applications in recent years. Thus,

special hardware for database operations has generally been

developed. However, since such trial systems have been

expensive and much time is required to design such LSI,

the hardware technology would become antiquated when

the hardware is completed. Two methods are comparatively

successful approaches regarding the development of

DBMS satisfying the cost requirements: (1) use of a com-

puter with a large-capacity main memory for executing a

main memory database and (2) use of many microproces-

sors for executing parallel database systems.

The cost of memory devices has decreased each year

with the advancement of the technology for large-scale

integrated circuits, and the capacity of the main memory for

a computer has become increasingly large. Thus, all major

parts of data can now be placed in the main memory, and

thus, high-speed DBMS with a decreased number of ac-

cesses to secondary memory devices have become possible.

In addition, with the advancement of hardware technology,

the capabilities of microprocessors have increased while the

cost has decreased, making economical realization of par-

allel database machines possible. Since these approaches

use mass-produced LSI chips, special LSI for database

Systems and Computers in Japan, Vol. 31, No. 8, 2000

Translated from Denshi Joho Tsushin Gakkai Ronbunshi, Vol. J81-D-I, No. 8, August 1998, pp. 976985

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数据库操作加速：向量处理器的应用

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