Renovating Database Queries with Query AutoAwesome

Chetna Suryavanshi, C. Dyreson, Jonathan Adams
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Abstract

Querying is an important database activity, typically occurring more frequently than update. Programmers invest time and effort into developing a set of queries. We propose reusing these queries with Query AutoAwesome (QAA). QAA is a system to automatically enhance queries. QAA was inspired by Google's Auto Awesome tool, which provides automatic enhancements of photos. QAA ingests a query, the database schema, and the data to enhance a query. QAA can reuse a query in several ways, such as re-placing a literal with a choice of alternatives. From among the pool of potential enhancements it is important to choose the top-k generated queries. To do so we introduce objective functions to measure the enhancement and rank potential queries.
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使用Query AutoAwesome更新数据库查询
查询是一项重要的数据库活动,通常比更新发生得更频繁。程序员投入时间和精力开发一组查询。我们建议使用Query AutoAwesome (QAA)来重用这些查询。QAA是一个自动增强查询的系统。QAA的灵感来自谷歌的Auto Awesome工具,该工具可以自动增强照片。QAA摄取查询、数据库模式和数据以增强查询。QAA可以通过几种方式重用查询,例如用替代选项替换文字。从潜在的增强池中选择top-k生成的查询是很重要的。为此,我们引入目标函数来衡量增强并对潜在查询进行排序。
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