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Detail publikačního výsledku
LENGÁL, O.; HONG, C.; CHEN, Y.; MU, S.; SINHA, N.; WANG, B.
Originální název
An Executable Sequential Specification for Spark Aggregation
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
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.
Anglický abstrakt
Klíčová slova
Data Parallel Computation, Functional Specification, Requirements, Verification, Spark
Klíčová slova v angličtině
Autoři
Rok RIV
2018
Vydáno
27.05.2017
Nakladatel
Springer Verlag
Místo
Heidelberg
Kniha
Proceedings of NETYS'17
ISSN
0302-9743
Periodikum
Lecture Notes in Computer Science
Číslo
10299
Stát
Spolková republika Německo
Strany od
421
Strany do
438
Strany počet
15
URL
https://www.fit.vut.cz/research/publication/11330/
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/" }
Dokumenty
netys17