Experiences with the Model-based Generation of Big Data Pipelines
| dc.contributor.author | Eichelberger, Holger | |
| dc.contributor.author | Qin, Cui | |
| dc.contributor.author | Schmid, Klaus | |
| dc.contributor.editor | Mitschang, Bernhard | |
| dc.contributor.editor | Nicklas, Daniela | |
| dc.contributor.editor | Leymann, Frank | |
| dc.contributor.editor | Schöning, Harald | |
| dc.contributor.editor | Herschel, Melanie | |
| dc.contributor.editor | Teubner, Jens | |
| dc.contributor.editor | Härder, Theo | |
| dc.contributor.editor | Kopp, Oliver | |
| dc.contributor.editor | Wieland, Matthias | |
| dc.date.accessioned | 2017-06-21T11:24:44Z | |
| dc.date.available | 2017-06-21T11:24:44Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | Developing Big Data applications implies a lot of schematic or complex structural tasks, which can easily lead to implementation errors and incorrect analysis results. In this paper, we present a model-based approach that supports the automatic generation of code to handle these repetitive tasks, enabling data engineers to focus on the functional aspects without being distracted by technical issues. In order to identify a solution, we analyzed different Big Data stream-processing frameworks, extracted a common graph-based model for Big Data streaming applications and de- veloped a tool to graphically design and generate such applications in a model-based fashion (in this work for Apache Storm). Here, we discuss the concepts of the approach, the tooling and, in particular, experiences with the approach based on feedback of our partners. | en |
| dc.identifier.isbn | 978-3-88579-660-2 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-266 | |
| dc.subject | Big Data | |
| dc.subject | stream-processing | |
| dc.subject | model-based development | |
| dc.subject | code generation | |
| dc.subject | Apache Storm | |
| dc.title | Experiences with the Model-based Generation of Big Data Pipelines | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 56 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 49 | |
| gi.conference.date | 6.-10. März 2017 | |
| gi.conference.location | Stuttgart | |
| gi.conference.sessiontitle | Workshop Big Data Management Systems in Business and Industrial Applications (BigBIA17) |
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