Interactive and deterministic data cleaning: A tossed stone raises a thousand ripples

Jian He, Enzo Veltri, Donatello Santoro, Guoliang Li, Giansalvatore Mecca, Paolo Papotti, Nan Tang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

56 Scopus citations

Abstract

We present Falcon, an interactive, deterministic, and declarative data cleaning system, which uses SQL update queries as the language to repair data. Falcon does not rely on the existence of a set of pre-defined data quality rules. On the contrary, it encourages users to explore the data, identify possible problems, and make updates to fix them. Bootstrapped by one user update, Falcon guesses a set of possible SQL update queries that can be used to repair the data. The main technical challenge addressed in this paper consists in finding a set of SQL update queries that is minimal in size and at the same time fixes the largest number of errors in the data. We formalize this problem as a search in a lattice-shaped space. To guarantee that the chosen updates are semantically correct, Falcon navigates the lattice by interacting with users to gradually validate the set of SQL update queries. Besides using traditional one-hop based traverse algorithms (e.g., BFS or DFS), we describe novel multi-hop search algorithms such that Falcon can dive over the lattice and conduct the search efficiently. Our novel search strategy is coupled with a number of optimization techniques to further prune the search space and efficiently maintain the lattice. We have conducted extensive experiments using both real-world and synthetic datasets to show that Falcon can effectively communicate with users in data repairing.

Original languageEnglish (US)
Title of host publicationSIGMOD 2016 - Proceedings of the 2016 International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages893-907
Number of pages15
ISBN (Electronic)9781450335317
DOIs
StatePublished - Jun 26 2016
Event2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016 - San Francisco, United States
Duration: Jun 26 2016Jul 1 2016

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
Volume26-June-2016
ISSN (Print)0730-8078

Conference

Conference2016 ACM SIGMOD International Conference on Management of Data, SIGMOD 2016
Country/TerritoryUnited States
CitySan Francisco
Period6/26/167/1/16

Keywords

  • Data cleaning
  • Declarative
  • Deterministic
  • Interactive

ASJC Scopus subject areas

  • Software
  • Information Systems

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