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Automatic example queries for ad hoc databases

Published: 12 June 2011 Publication History

Abstract

Motivated by eScience applications, we explore automatic generation of example "starter" queries over unstructured collections of tables without relying on a schema, a query log, or prior input from users. Such example queries are demonstrably sufficient to have non-experts self-train and become productive using SQL, helping to increase the uptake of database technology among scientists.
Our method is to learn a model for each relational operator based on example queries from public databases, then assemble queries syntactically operator-by-operator. For example, the likelihood that a pair of attributes will be used as a join condition in an example query depends on the cardinality of their intersection, among other features. Our demonstration illustrates that datasets with different statistical properties lead to different sets of example queries with different properties.

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Cited By

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  • (2024)Guided SQL-Based Data Exploration with User Feedback2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00372(4884-4896)Online publication date: 13-May-2024
  • (2024)PyExplore 2.0: Explainable, Approximate and Combined Clustering Based SQL Query RecommendationsManagement of Digital EcoSystems10.1007/978-3-031-51643-6_7(88-102)Online publication date: 2-Feb-2024
  • (2023)DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data PreparationProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581509(1-18)Online publication date: 19-Apr-2023
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Information & Contributors

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Published In

cover image ACM Conferences
SIGMOD '11: Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
June 2011
1364 pages
ISBN:9781450306614
DOI:10.1145/1989323

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2011

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Author Tags

  1. dataspaces
  2. query recommendation
  3. scientific databases

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  • Demonstration

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SIGMOD/PODS '11
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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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View all
  • (2024)Guided SQL-Based Data Exploration with User Feedback2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00372(4884-4896)Online publication date: 13-May-2024
  • (2024)PyExplore 2.0: Explainable, Approximate and Combined Clustering Based SQL Query RecommendationsManagement of Digital EcoSystems10.1007/978-3-031-51643-6_7(88-102)Online publication date: 2-Feb-2024
  • (2023)DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data PreparationProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581509(1-18)Online publication date: 19-Apr-2023
  • (2022)INODEACM SIGMOD Record10.1145/3516431.351643650:4(23-29)Online publication date: 31-Jan-2022
  • (2016)Accelerating data-driven discovery with scientific asset management2016 IEEE 12th International Conference on e-Science (e-Science)10.1109/eScience.2016.7870883(31-40)Online publication date: Oct-2016
  • (2015)Query from examplesProceedings of the VLDB Endowment10.14778/2831360.28313698:13(2158-2169)Online publication date: 1-Sep-2015
  • (2014)UPnQ: An Architecture for Personal Information ExplorationDatabase and Expert Systems Applications10.1007/978-3-319-10073-9_20(257-264)Online publication date: 2014
  • (2013)Automatically synthesizing SQL queries from input-output examplesProceedings of the 28th IEEE/ACM International Conference on Automated Software Engineering10.1109/ASE.2013.6693082(224-234)Online publication date: 11-Nov-2013

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