Performance Modeling in the Age of Big Data - Some Reflections on Current Limitations
R. Heinrich, H. Eichelberger, und K. Schmid. 3rd International Workshop on Interplay of Model-Driven and Component-Based Software Engineering (ModComp '16),, Seite 37-38. (Oktober 2016)
Zusammenfassung
Big Data aims at the efficient processing of massive amounts of data. Performance modeling is often used to optimize performance of systems under development. Based on experiences from modeling Big Data solutions, we describe some problems in applying performance modeling and discuss potential solution approaches.
%0 Conference Paper
%1 heinrich2016performance
%A Heinrich, Robert
%A Eichelberger, Holger
%A Schmid, Klaus
%B 3rd International Workshop on Interplay of Model-Driven and Component-Based Software Engineering (ModComp '16),
%D 2016
%E Ciccozzi, Federico
%E Malavolta, Ivano
%K myown qualimaster
%P 37-38
%T Performance Modeling in the Age of Big Data - Some Reflections on Current Limitations
%U http://ceur-ws.org/Vol-1723/6.pdf
%X Big Data aims at the efficient processing of massive amounts of data. Performance modeling is often used to optimize performance of systems under development. Based on experiences from modeling Big Data solutions, we describe some problems in applying performance modeling and discuss potential solution approaches.
@inproceedings{heinrich2016performance,
abstract = {Big Data aims at the efficient processing of massive amounts of data. Performance modeling is often used to optimize performance of systems under development. Based on experiences from modeling Big Data solutions, we describe some problems in applying performance modeling and discuss potential solution approaches.},
added-at = {2016-10-12T11:38:52.000+0200},
author = {Heinrich, Robert and Eichelberger, Holger and Schmid, Klaus},
biburl = {https://www.bibsonomy.org/bibtex/2397f3c2e0942978e6707c0b1db381ae0/eichelbe},
booktitle = {3rd International Workshop on Interplay of Model-Driven and Component-Based Software Engineering (ModComp '16),},
editor = {Ciccozzi, Federico and Malavolta, Ivano},
interhash = {5a8852c8ea6f8dcfe0c409475e0e548f},
intrahash = {397f3c2e0942978e6707c0b1db381ae0},
keywords = {myown qualimaster},
month = {October},
pages = {37-38},
timestamp = {2016-11-18T10:29:33.000+0100},
title = {Performance Modeling in the Age of Big Data - Some Reflections on Current Limitations},
url = {http://ceur-ws.org/Vol-1723/6.pdf},
year = 2016
}