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A Minimal Attribute Set-oriented Data Provenance Method

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Published:20 December 2017Publication History

ABSTRACT

In view of data provenance in ETL, to improve the efficiency of provenance tracking, this paper analyzes the common transformation and attribute mapping of ETL, focuses on the key attributes in key attribute mapping, summarizes its characteristics, puts forward the concept of minimal attribute set, and designs the data provenance method based on minimal attribute set. In the reverse tracking, using this method construct the reverse transformation sequence whose input and output patterns are dynamically transformed, the number of attributes is decreasing, the space - time costs is reduced and the provenance efficiency is improved.

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  1. A Minimal Attribute Set-oriented Data Provenance Method

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    • Published in

      cover image ACM Other conferences
      BDIOT '17: Proceedings of the International Conference on Big Data and Internet of Thing
      December 2017
      251 pages
      ISBN:9781450354301
      DOI:10.1145/3175684

      Copyright © 2017 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 20 December 2017

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      Overall Acceptance Rate75of136submissions,55%

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