QueryBooster的演示:支持基于中间件的SQL查询重写服务

IF 2.6 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Qiushi Bai, Sadeem Alsudais, Chen Li
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引用次数: 0

摘要

查询重写是优化数据库中SQL性能的一项重要技术。随着商业智能系统和对象关系映射框架的广泛使用,数据库内部现有的重写功能不足以优化机器生成的查询。在本文中,我们提出了一个名为“QueryBooster”的新系统,将SQL查询重写作为云服务来支持。它为用户提供了一个功能强大且易于使用的Web界面,使用户可以通过一种语言制定重写规则,或者通过提供示例查询对来表达重写意图。它允许多个用户共享重写知识,并自动为用户推荐共享的重写规则。它不需要对应用程序或数据库进行修改或安装插件。在这个演示中,我们使用真实的应用程序和数据集来展示QueryBooster的用户体验,以重写他们的应用程序查询并共享重写知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Demo of QueryBooster: Supporting Middleware-Based SQL Query Rewriting as a Service
Query rewriting is an important technique to optimize SQL performance in databases. With the prevalent use of business intelligence systems and object-relational mapping frameworks, existing rewriting capabilities inside databases are insufficient to optimize machine-generated queries. In this paper, we propose a novel system called "QueryBooster," to support SQL query rewriting as a cloud service. It provides a powerful and easy-to-use Web interface for users to formulate rewriting rules via a language or express rewriting intentions by providing example query pairs. It allows multiple users to share rewriting knowledge and automatically suggests shared rewriting rules for users. It requires no modifications or plugin installations to applications or databases. In this demonstration, we use real-world applications and datasets to show the user experience of QueryBooster to rewrite their application queries and share rewriting knowledge.
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来源期刊
Proceedings of the Vldb Endowment
Proceedings of the Vldb Endowment Computer Science-General Computer Science
CiteScore
7.70
自引率
0.00%
发文量
95
期刊介绍: The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.
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