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Performance assessment of Apache Spark applications
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
2019 (English)Independent thesis Basic level (degree of Bachelor), 180 HE creditsStudent thesis
Abstract [en]

This thesis addresses the challenges of large software and data-intensive systems. We will discuss a Big Data software that consists of quite a bit of Linux configuration, some Scala coding and a set of frameworks that work together to achieve the smooth performance of the system. Moreover, the thesis focuses on the Apache Spark framework and the challenging of measuring the lazy evaluation of the transformation operations of Spark. Investigating the challenges are essential for the performance engineers to increase their ability to study how the system behaves and take decisions in early design iteration. Thus, we made some experiments and measurements to achieve this goal. In addition to that, and after analyzing the result we could create a formula that will be useful for the engineers to predict the performance of the system in production.

Place, publisher, year, edition, pages
2019. , p. 33
Keywords [en]
Big Data, Apache Spark, BigBlu, Lazy evaluation of Spark
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-80181OAI: oai:DiVA.org:lnu-80181DiVA, id: diva2:1285270
Subject / course
Computer Science
Educational program
Software Technology Programme, 180 credits
Presentation
2018-09-21, Växjö, 09:00 (English)
Supervisors
Examiners
Available from: 2019-02-04 Created: 2019-02-04 Last updated: 2019-02-04Bibliographically approved

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fulltext(1117 kB)37 downloads
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Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf