This research is supported in part by NUS Grant R-252-000-512-112 and by a Shaw Foundation Visiting Professorship
Proceedings of the VLDB Endowment
SQL (Computer program language), Database searching
In this paper, we propose a new approach, called Query from Examples (QFE), to help non-expert database users construct SQL queries. Our approach, which is designed for users who might be unfamiliar with SQL, only requires that the user is able to determine whether a given output table is the result of his or her intended query on a given input database. To kick-start the construction of a target query Q, the user first provides a pair of inputs: a sample database D and an output table R which is the result of Q on D. As there will be many candidate queries that transform D to R, QFE winnows this collection by presenting the user with new database-result pairs that distinguish these candidates. Unlike previous approaches that use synthetic data for such pairs, QFE strives to make these distinguishing pairs as close to the original (D, R) pair as possible. By doing so, it seeks to minimize the effort needed by a user to determine if a new database-result pair is consistent with his or her desired query. We demonstrate the effectiveness and efficiency of our approach using real datasets from SQLShare, a cloudbased platform designed to help scientists utilize RDBMS technology for data analysis.
Li, H., Chan, C. and Maier, D. (2015). Query From Examples: An Iterative, Data-Driven Approach to Query Construction. Proceedings of the VLDB Endowment, Vol. 8, No. 13, p. 2158-2169.