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Title:Procesiranje finančnih transakcij s programskim ogrodjem Hadoop
Authors:ID Pandel, David (Author)
ID Ojsteršek, Milan (Mentor) More about this mentor... New window
Files:.pdf MAG_Pandel_David_2019.pdf (19,34 MB)
MD5: 7ACED07B4CF1D0C68A3FAF28EB900ED8
PID: 20.500.12556/dkum/a928904f-764b-441a-983f-106137ad4add
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V okviru magistrskega dela je bila izdelana aplikacija, ki omogoča paralelno procesiranje masovnih kartičnih transakcij, t.i. avtorizacij. Programska rešitev temelji na odprtokodnem ogrodju Apache Hadoop, ki je namenjeno obdelovanju velikih količin podatkov (angl. big data). S pristopom Hadoop razbijemo vhodne podatke na več manjših delov, ki se paralelno procesirajo. Hadoop je sestavljen iz dveh glavnih komponent. MapReduce vhodni niz podatkov razdeli na med seboj neodvisne dele, ki se obdelajo paralelno. Datotečni sistem HDFS (angl. Hadoop distributed file system) je bil razvit v programskem jeziku Java in je implementiran za zagotavljanje prilagodljivega in zanesljivega shranjevanja podatkov na več med seboj povezanih računalnikih (angl. clusters of commodity servers). Glavna prednost uporabe Hadoopa je v porazdeljenem sistemu, sestavljenem iz več manj zmogljivih računalnikov in ne le enega zelo zmogljivega. Računalniki se lahko nahajajo na različnih lokacijah, zato ne potrebujemo dodatnega redundantnega sistema, ki služi za samo vzpostavitev sistema v primeru naravne katastrofe.
Keywords:Hadoop, HDFS, MapReduce, finančna avtorizacija, ISO8583
Place of publishing:[Maribor
Publisher:D. Pandel
Year of publishing:2019
PID:20.500.12556/DKUM-73144 New window
UDC:004.94:004.83(043.2)
COBISS.SI-ID:22237974 New window
NUK URN:URN:SI:UM:DK:LUQXHOFI
Publication date in DKUM:27.03.2019
Views:1263
Downloads:206
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:19.02.2019

Secondary language

Language:English
Title:Financial transaction processing with Hadoop
Abstract:Within the scope of this master thesis an application was developed, which enables parallel processing of large financial transactions or authorizations. The software solution is based on the Apache Hadoop open source framework, which is designed to handle big data as input. With the Hadoop approach, input data is broken down into several smaller parts and processed in parallel. The Hadoop framework contains two main components. MapReduce divides the input dataset into independent parts, processed in parallel. The Hadoop distributed file system (HDFS) was developed in the Java programming language and was implemented to provide a flexible and reliable way to store data on multiple clusters of commodity servers. The main advantage of using the Hadoop framework is in its distributed system approach which consists of several less powerful computers working in sync and not only one very powerful computer. Computers can be located in different locations, thus rendering the use of other redundant systems in the case of a natural disaster unnecessary.
Keywords:Hadoop, HDFS, MapReduce, financial authorization, ISO8583


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