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Faster Querying for Database Integration and Virtualization with Distributed Semi-Joins

机译:更快地查询数据库集成和虚拟化与分布式半连接

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Data integration and virtualization is commonly used to combine data for data analytics and reporting. A major challenge is handling large data sizes ("Big Data") as moving data across a network is extremely expensive and limits query processing. Business intelligence and data visualization software require rapid response times for users, and data virtualization is often limited for use cases involving joins across systems. The contribution of this work is a semi-join based approach to data virtualization joins that minimizes data movement and utilizes the extensive resources available in the database systems rather than performing query processing in the virtualization engine. The result is significantly less data movement which translates into faster query times and higher performance. Experimental results demonstrate that performance can be increased by an order of magnitude. A unique feature of the approach is that it does not require any special software installed above the database servers such as mediators and works directly using SQL queries.
机译:数据集成和虚拟化通常用于组合数据分析和报告的数据。主要挑战是处理大数据尺寸(“大数据”),因为网络上的移动数据非常昂贵并限制查询处理。商业智能和数据可视化软件需要对用户的快速响应时间,并且数据虚拟化通常有限于涉及跨系统的连接。这项工作的贡献是基于半加入的数据虚拟化联接方法,其最小化数据移动,并利用数据库系统中可用的广泛资源而不是在虚拟化引擎中执行查询处理。结果显着较低,数据移动转化为更快的查询时间和更高的性能。实验结果表明,性能可以增加一个数量级。该方法的一个独特功能是它不需要安装在数据库服务器上方的任何特殊软件,例如Mediators,并直接使用SQL查询。

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