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A Database Optimization Strategy for Massive Data Based Information System

机译:基于海量数据的信息系统数据库优化策略

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With the rapid arrival of the information explosion era, the amount of data stored in a single table of an enterprise information management system is getting more and more common. Therefore, efficiency optimization of SQL based on the massive data is an essential task to break the bottleneck in current enterprise information management systems. This paper proposes single table optimization methods for massive database. These methods including: physical optimization, index optimization and query statement optimization. Each optimization method is integrated into the database design process, and a set of optimization programs for the massive database design process is proposed. In the test environment, the size of the databases file is over 200G and single table records is over 80 million, the proposed optimization methods break the bottleneck of query efficiency and improve the database query efficiency of tens of times.
机译:随着信息爆炸时代的快速到来,企业信息管理系统中单个表中存储的数据量越来越普遍。因此,在海量数据的基础上对SQL进行效率优化,是突破当前企业信息管理系统瓶颈的重要任务。本文针对海量数据库提出了单表优化方法。这些方法包括:物理优化、索引优化和查询语句优化。将各种优化方法集成到数据库设计过程中,提出了一套大规模数据库设计过程的优化方案。在测试环境中,数据库文件大小超过200G,单表记录超过8000万条,提出的优化方法突破了查询效率的瓶颈,将数据库查询效率提高了数十倍。

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