Parallelizing user–defined functions in the ETL workflow using orchestration style sheets
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...
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| Vydáno v: | International journal of applied mathematics and computer science Ročník 29; číslo 1; s. 69 - 79 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Zielona Góra
Sciendo
01.03.2019
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services |
| Témata: | |
| ISSN: | 2083-8492, 1641-876X, 2083-8492 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Thiele, Maik Ali, Syed Muhammad Fawad Mey, Johannes |
| Author_xml | – sequence: 1 givenname: Syed Muhammad Fawad surname: Ali fullname: Ali, Syed Muhammad Fawad email: fawadali.ali@gmail.com organization: Data Engineering, trivago N.V. Leipzig, Bosestrasse 4, 04109, Leipzig, Germany – sequence: 2 givenname: Johannes surname: Mey fullname: Mey, Johannes organization: Faculty of Computer Science, Technical University of Dresden, Helmholtzstrasse 10, 01069, Dresden, Germany – sequence: 3 givenname: Maik surname: Thiele fullname: Thiele, Maik organization: Faculty of Computer Science, Technical University of Dresden, Helmholtzstrasse 10, 01069, Dresden, Germany |
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| SubjectTerms | Configuration management Configurations ETL workflow parallel algorithmic skeletons parallel ETL operators Parallel processing Task complexity user-defined functions Workflow |
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| Title | Parallelizing user–defined functions in the ETL workflow using orchestration style sheets |
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