20.500.12556/DKUM-73144 Procesiranje finančnih transakcij s programskim ogrodjem Hadoop Financial transaction processing with Hadoop 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. 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. Hadoop HDFS MapReduce finančna avtorizacija ISO8583 Hadoop HDFS MapReduce financial authorization ISO8583 true true false D. Pandel Slovenski jezik Angleški jezik Magistrsko delo/naloga 2019-02-19 22:20:21 2019-03-27 07:21:31 2022-08-01 23:59:43 2019-07-11 19:46:20 2019 0 [Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.94:004.83(043.2) 22237974 URN:SI:UM:DK:LUQXHOFI MAG_Pandel_David_2019.pdf MAG_Pandel_David_2019.pdf 1 7ACED07B4CF1D0C68A3FAF28EB900ED8 6c45003e61eb2ec5c07cd1a718d10239386e92bc09f1e680e5b35c61dfb249d0 9c28af1b-7c10-11eb-bb7a-00155d0001ca 20.500.12556/dkum/a928904f-764b-441a-983f-106137ad4add https://dk.um.si/Dokument.php?lang=slv&id=132697 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0