TRAMP: Understanding the Behavior of Schema Mappings through Provenance

被引:16
|
作者
Glavic, Boris [1 ]
Alonso, Gustavo [2 ]
Miller, Renee J. [3 ]
Haas, Laura M. [4 ]
机构
[1] Univ Zurich, Zurich, Switzerland
[2] Swiss Fed Inst Technol, Zurich, Switzerland
[3] Univ Toronto, Toronto, ON, Canada
[4] IBM Almaden Res Ctr, San Jose, CA USA
来源
PROCEEDINGS OF THE VLDB ENDOWMENT | 2010年 / 3卷 / 01期
关键词
D O I
10.14778/1920841.1921003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Though partially automated, developing schema mappings remains a complex and potentially error-prone task. In this paper, we present TRAMP (TRAnsformation Mapping Provenance), an extensive suite of tools supporting the debugging and tracing of schema mappings and transformation queries. TRAMP combines and extends data provenance with two novel notions, transformation provenance and mapping provenance, to explain the relationship between transformed data and those transformations and mappings that produced that data. In addition we provide query support for transformations, data, and all forms of provenance. We formally define transformation and mapping provenance, present an efficient implementation of both forms of provenance, and evaluate the resulting system through extensive experiments.
引用
收藏
页码:1314 / 1325
页数:12
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