Change search
CiteExportLink to record
Permanent link

Direct link
Cite
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
Improvement of a big data statistic system: using multi-level mid-tier caching
University West, Department of Engineering Science, Division of Computer, Electrical and Surveying Engineering.
University West, Department of Engineering Science, Division of Computer, Electrical and Surveying Engineering.
2015 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This work presents the improvement and optimization of a statistic system containing big data. Both the performance and the visual presentation of the system are addressed but the main focus is against the performance part of the problem.

Baseline benchmarks of the performance and analysis regarding the visual presentation of the system are conducted. Multiple solutions are discussed, evaluated and critically analyzed to find the right key for this problem.

The technique of implementing a Multi-Level Mid-Tier cache with an "Update on Event" trigger is proposed as a solution to the performance issues in the system. By implementing a hierarchical structure to a mid-tier cache, the idea is to provide a highly dynamic, configu-rable and responsive system without compromises. The Multi-Level Mid-Tier cache is in this implementation consisting of two levels; one static and one dynamic.

The creation of a multi-platform compatible user interface is proposed as a solution to the visual presentation. This is done by revising the front end of the system by implementing API; s such as JQMobile and DataTables.

Benchmarks of the improved system are performed. Both the loading time of the system and the derivative of the increase of loading time are tested in the same way as for the base-line results. Comparing these results with the baseline results lead towards the conclusion which confirms the sterling functionality of the Multi-Level Mid-Tier Cache.

The Multi-Level Mid-Tier cache eliminated the performance problems of the MyMo statis-tic system. The loading time at 10 000 reports is decreased by 96,45% and the derivative at the same point is decreased by 98,40% without the any compromises to the accessible data.

Place, publisher, year, edition, pages
2015. , 40 p.
Keyword [en]
Big Data, Mid-Tier Cache, Optimization, Statistics
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hv:diva-8329Local ID: EXD500OAI: oai:DiVA.org:hv-8329DiVA: diva2:858078
Subject / course
Computer enigeering
Educational program
Datateknisk systemutveckling
Supervisors
Examiners
Available from: 2015-10-02 Created: 2015-10-01 Last updated: 2015-10-02Bibliographically approved

Open Access in DiVA

No full text

By organisation
Division of Computer, Electrical and Surveying Engineering
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 16 hits
CiteExportLink to record
Permanent link

Direct link
Cite
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