Analyzing data-centric applications: Why, what-if, and how-to

Pierre Bourhis, Daniel Deutch, Yuval Moskovitch

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider in this paper the analysis of complex applications that query and update an underlying database in their operation. We focus on three classes of analytical questions that are important for application owners and users alike: Why was a result generated? What would be the result if the application logic or database is modified in a particular way? How can one interact with the application to achieve a particular goal? Answering these questions efficiently is a fundamental step towards optimizing the application and its use. Noting that provenance was a key component in answering similar questions in the context of database queries, we develop a provenance-based model and efficient algorithms for these problems in the context of data-centric applications. Novel challenges here include the dynamic update of data, combined with the possibly complex workflows allowed by applications. We nevertheless achieve theoretical guarantees for the algorithms performance, and experimentally show their efficiency and usefulness, even in presence of complex applications and large-scale data.

Original languageEnglish
Title of host publication2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages779-790
Number of pages12
ISBN (Electronic)9781509020195
DOIs
StatePublished - 22 Jun 2016
Event32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland
Duration: 16 May 201620 May 2016

Publication series

Name2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016

Conference

Conference32nd IEEE International Conference on Data Engineering, ICDE 2016
Country/TerritoryFinland
CityHelsinki
Period16/05/1620/05/16

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