Parallelizing user-defined functions in the ETL workflow using orchestration style sheets

• Autorzy: Ali Syed Muhammad Fawad , Mey Johannes , Thiele Maik

Identyfikatory

DOI

10.2478/amcs-2019-0005

• Języki publikacji: EN

Abstrakty

EN

Today’s ETL tools provide capabilities to develop custom code as user-defined functions (UDFs) to extend the expressiveness of the standard ETL operators. However, while this allows us to easily add new functionalities, it also comes with the risk that the custom code is not intended to be optimized, e.g., by parallelism, and for this reason, it performs poorly for data-intensive ETL workflows. In this paper we present a novel framework, which allows the ETL developer to choose a design pattern in order to write parallelizable code and generates a configuration for the UDFs to be executed in a distributed environment. This enables ETL developers with minimum expertise in distributed and parallel computing to develop UDFs without taking care of parallelization configurations and complexities. We perform experiments on large-scale datasets based on TPC-DS and BigBench. The results show that our approach significantly reduces the effort of ETL developers and at the same time generates efficient parallel configurations to support complex and data-intensive ETL tasks.

Słowa kluczowe

EN

ETL workflow; parallel ETL operator; parallel algorithmic skeleton; user defined function

PL

workflow ETL; równoległy szkielet algorytmiczny; funkcja zdefiniowana przez użytkownika

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2019
• Tom: Vol. 29, no. 1
• Strony: 69--79
• Opis fizyczny: Bibliogr. 27 poz., rys., wykr.

Twórcy

autor

Ali Syed Muhammad Fawad

• Faculty of Computing, Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland; Data Engineering, trivago N.V. Leipzig, Bosestrasse 4, 04109, Leipzig, Germany

autor

Mey Johannes

• Faculty of Computer Science, Technical University of Dresden, Helmholtzstrasse 10, 01069, Dresden, Germany

autor

Thiele Maik

• Faculty of Computer Science, Technical University of Dresden, Helmholtzstrasse 10, 01069, Dresden, Germany

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).