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Perturbation analysis of database queries

Publication ,  Conference
Walenz, B; Yang, J
Published in: Proceedings of the VLDB Endowment
January 1, 2015
Published version (DOI)

We present a system, Perada, for parallel perturbation analysis of database queries. Perturbation analysis considers the results of a query evaluated with (a typically large number of) different parameter settings, to help discover leads and evaluate claims from data. Perada simplifies the development of general, ad hoc perturbation analysis by providing a flexible API to support a variety of optimizations such as grouping, memoization, and pruning; by automatically optimizing performance through run-time observation, learning, and adaptation; and by hiding the complexity of concurrency and failures from its developers. We demonstrate Perada's efficacy and efficiency with real workloads applying perturbation analysis to computational journalism.

Duke Scholars

Jun Yang
Author Jun Yang Computer Science
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Published In

Proceedings of the VLDB Endowment

DOI

10.14778/3007328.3007330

EISSN

2150-8097

Publication Date

January 1, 2015

Volume

9

Issue

14

Start / End Page

1635 / 1646

Related Subject Headings

  • 4605 Data management and data science
  • 0807 Library and Information Studies
  • 0806 Information Systems
  • 0802 Computation Theory and Mathematics
 

Citation

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Walenz, B., & Yang, J. (2015). Perturbation analysis of database queries. In Proceedings of the VLDB Endowment (Vol. 9, pp. 1635–1646). https://doi.org/10.14778/3007328.3007330
Walenz, B., and J. Yang. “Perturbation analysis of database queries.” In Proceedings of the VLDB Endowment, 9:1635–46, 2015. https://doi.org/10.14778/3007328.3007330.
Walenz B, Yang J. Perturbation analysis of database queries. In: Proceedings of the VLDB Endowment. 2015. p. 1635–46.
Walenz, B., and J. Yang. “Perturbation analysis of database queries.” Proceedings of the VLDB Endowment, vol. 9, no. 14, 2015, pp. 1635–46. Scopus, doi:10.14778/3007328.3007330.
Walenz B, Yang J. Perturbation analysis of database queries. Proceedings of the VLDB Endowment. 2015. p. 1635–1646.

Published In

Proceedings of the VLDB Endowment

DOI

10.14778/3007328.3007330

EISSN

2150-8097

Publication Date

January 1, 2015

Volume

9

Issue

14

Start / End Page

1635 / 1646

Related Subject Headings

  • 4605 Data management and data science
  • 0807 Library and Information Studies
  • 0806 Information Systems
  • 0802 Computation Theory and Mathematics