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Interactive Query Synthesis from Input-Output Examples

Authors:

Chenglong Wang,

Alvin Cheung,

Rastislav BodikAuthors Info & Claims

SIGMOD '17: Proceedings of the 2017 ACM International Conference on Management of Data

Pages 1631 - 1634

https://doi.org/10.1145/3035918.3058738

Published: 09 May 2017 Publication History

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Abstract

This demo showcases Scythe, a novel query-by-example system that can synthesize expressive SQL queries from input-output examples. Scythe is designed to help end-users program SQL and explore data simply using input-output examples. From a web-browser, users can obtain SQL queries with Scythe in an automated, interactive fashion: from a provided example, Scythe synthesizes SQL queries and resolves ambiguities via conversations with the users.

In this demo, we first show Scythe how end users can formulate queries using Scythe; we then switch to the perspective of an algorithm designer to show how Scythe can scale up to handle complex SQL features, like outer joins and subqueries.

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Cited By

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Brucato MSiddiqui TWu WNarasayya VChaudhuri S(2024)Wred: Workload Reduction for Scalable Index TuningProceedings of the ACM on Management of Data10.1145/36393052:1(1-26)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639305
Dou QWang HTang HPan HZhang S(2024)Query Reverse Engineering of Pre-deleted Uncorrelated OperatorsData Mining and Big Data10.1007/978-981-97-0844-4_4(45-58)Online publication date: 22-Feb-2024
https://doi.org/10.1007/978-981-97-0844-4_4
Liu HDou QWang H(2024)AL-SQUARES: SQL Synthesis System with the Addition of ReducerData Mining and Big Data10.1007/978-981-97-0844-4_3(33-44)Online publication date: 22-Feb-2024
https://doi.org/10.1007/978-981-97-0844-4_3
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Index Terms

Interactive Query Synthesis from Input-Output Examples
1. Information systems
  1. Data management systems
    1. Query languages
      1. Relational database query languages
        Structured Query Language

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Information & Contributors

Information

Published In

SIGMOD '17: Proceedings of the 2017 ACM International Conference on Management of Data

May 2017

1810 pages

ISBN:9781450341974

DOI:10.1145/3035918

General Chairs:
Rada Chirkova
North Carolina State University, USA
,
Jun Yang
Duke University, USA
,
Program Chair:
Dan Suciu
University of Washington, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 May 2017

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Short-paper

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SIGMOD/PODS'17

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SIGMOD

SIGMOD/PODS'17: International Conference on Management of Data

May 14 - 19, 2017

Illinois, Chicago, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

View all

Brucato MSiddiqui TWu WNarasayya VChaudhuri S(2024)Wred: Workload Reduction for Scalable Index TuningProceedings of the ACM on Management of Data10.1145/36393052:1(1-26)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639305
Dou QWang HTang HPan HZhang S(2024)Query Reverse Engineering of Pre-deleted Uncorrelated OperatorsData Mining and Big Data10.1007/978-981-97-0844-4_4(45-58)Online publication date: 22-Feb-2024
https://doi.org/10.1007/978-981-97-0844-4_4
Liu HDou QWang H(2024)AL-SQUARES: SQL Synthesis System with the Addition of ReducerData Mining and Big Data10.1007/978-981-97-0844-4_3(33-44)Online publication date: 22-Feb-2024
https://doi.org/10.1007/978-981-97-0844-4_3
Brancas RTerra-Neves MVentura MManquinho VMartins R(2024)Towards Reliable SQL Synthesis: Fuzzing-Based Evaluation and DisambiguationFundamental Approaches to Software Engineering10.1007/978-3-031-57259-3_11(232-254)Online publication date: 6-Apr-2024
https://dl.acm.org/doi/10.1007/978-3-031-57259-3_11
Naik AThakkar AStein AAlur RNaik M(2023)Relational Query Synthesis ⋈ Decision Tree LearningProceedings of the VLDB Endowment10.14778/3626292.362630617:2(250-263)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.14778/3626292.3626306
Cheung AAhmad MHaynes BKittivorawong CLaddad SLiu XWang CYan C(2023)Towards Auto-Generated Data SystemsProceedings of the VLDB Endowment10.14778/3611540.361163516:12(4116-4129)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.14778/3611540.3611635
Wang HDou QTang HZhang SPan H(2023)A SQL Synthesis System with Operator HandlerProceedings of the 2023 7th International Conference on Computer Science and Artificial Intelligence10.1145/3638584.3638654(132-136)Online publication date: 8-Dec-2023
https://dl.acm.org/doi/10.1145/3638584.3638654
Thakkar ASands NPetrou GAlur RNaik MRaghothaman M(2023)Mobius: Synthesizing Relational Queries with Recursive and Invented PredicatesProceedings of the ACM on Programming Languages10.1145/36228477:OOPSLA2(1394-1417)Online publication date: 16-Oct-2023
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Ji RKong CXiong YHu Z(2023)Improving Oracle-Guided Inductive Synthesis by Efficient Question SelectionProceedings of the ACM on Programming Languages10.1145/35860557:OOPSLA1(819-847)Online publication date: 6-Apr-2023
https://dl.acm.org/doi/10.1145/3586055
Zhang SDou Q(2023)DeepQRE: A QRE System Based on Deep Learning2023 9th International Conference on Mechatronics and Robotics Engineering (ICMRE)10.1109/ICMRE56789.2023.10106580(240-244)Online publication date: 10-Feb-2023
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