Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | en_US |
| dc.contributor.advisor | Lo, Chi-lik Eric (COMP) | - |
| dc.creator | Wong, Chun Ho | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/8183 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Study on programming frameworks for big data analytics | en_US |
| dcterms.abstract | The phenomenon of explosion of data caused by the latest technology movements in recent years introduces the "Big Data" challenge, which means normal technology is not sufficient enough for users to obtain timely, cost-effective, and quality answers to data-driven questions. In order to properly address this challenge, specific infrastructures for data storage and management, and also programming framework for data analytics and knowledge discovery have been developed. The aim of this dissertation is to study there common open-source programming framework, namely Apache Hadoop MapReduce, Apache Giraph, and Apache GraphX for their working mechanisms. The PageRank experiment is conducted by executing the three programs implemented based on the three frameworks for calculating PageRank results for the selected Wikipedia articles. This experiment can examine the ability effectiveness of the three frameworks, specifically under the condition of extremely insufficient hardware resources. Discussions are to be made based on the performance of the three programs, and also the coding effort. | en_US |
| dcterms.extent | vii, 57 pages : illustrations (some color) | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2015 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Big data. | en_US |
| dcterms.LCSH | Programming (Mathematics) | en_US |
| dcterms.LCSH | Business intelligence. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b28252032.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 1.43 MB | Adobe PDF | View/Open |
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