Renovating Database Queries with Query AutoAwesome

被引：0

作者：

Suryavanshi, Chetna ^{[1
]}

Dyreson, Curtis ^{[2
]}

Adams, Jonathan ^{[2
]}

机构：

[1] Micron, Boise, ID 83707 USA

[2] Dept Comp Sci, Logan, UT USA

来源：

2019 IEEE 20TH INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION FOR DATA SCIENCE (IRI 2019) | 2019年

关键词：

D O I：

10.1109/IRI.2019.00048

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 replacing 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.

引用

页码：253 / 260

页数：8

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