Publication Details

An Executable Sequential Specification for Spark Aggregation

LENGÁL, O.; HONG, C.; CHEN, Y.; MU, S.; SINHA, N.; WANG, B. An Executable Sequential Specification for Spark Aggregation. In Proceedings of NETYS'17. Lecture Notes in Computer Science. Heidelberg: Springer Verlag, 2017. p. 421-438. ISSN: 0302-9743.
Czech title
Spustitelná sekvenční specifikace pro agregaci v prostředí Spark
Type
conference paper
Language
English
Authors
Lengál Ondřej, Ing., Ph.D. (DITS)
Hong Chih-Duo
Chen Yu-Fang
Mu Shin-Cheng (FIT)
Sinha Nishant (FIT)
Wang Bow-Yaw (FIT)
Keywords

Data Parallel Computation, Functional Specification, Requirements, Verification, Spark

Abstract

Spark is a new promising platform for scalable data-parallel computation. It provides several high-level application programming interfaces (APIs) to perform parallel data aggregation. Since execution of parallel aggregation in Spark is inherently non-deterministic, a natural requirement for Spark programs is to give the same result for any execution on the same data set. We present PureSpark, an executable formal Haskell specification for Spark aggregate combinators. Our specification allows us to deduce the precise condition for deterministic outcomes from Spark aggregation. We report case studies analyzing deterministic outcomes and correctness of Spark programs.

Published
2017
Pages
421–438
Journal
Lecture Notes in Computer Science, no. 10299, ISSN 0302-9743
Proceedings
Proceedings of NETYS'17
Publisher
Springer Verlag
Place
Heidelberg
DOI
EID Scopus
BibTeX
@inproceedings{BUT146257,
  author="Ondřej {Lengál} and Chih-Duo {Hong} and Yu-Fang {Chen} and Shin-Cheng {Mu} and Nishant {Sinha} and Bow-Yaw {Wang}",
  title="An Executable Sequential Specification for Spark Aggregation",
  booktitle="Proceedings of NETYS'17",
  year="2017",
  journal="Lecture Notes in Computer Science",
  number="10299",
  pages="421--438",
  publisher="Springer Verlag",
  address="Heidelberg",
  doi="10.1007/978-3-319-59647-1\{_}31",
  issn="0302-9743",
  url="https://www.fit.vut.cz/research/publication/11330/"
}
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