prikaz prve stranice dokumenta Analiza tokova podataka u Big Data okruženju
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master's thesis
Analiza tokova podataka u Big Data okruženju
2017. urn:nbn:hr:168:845944
Borotić, Jelena
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Borotić, J. (2017). Analiza tokova podataka u Big Data okruženju (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:845944

Borotić, Jelena. "Analiza tokova podataka u Big Data okruženju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:845944

Borotić, Jelena. "Analiza tokova podataka u Big Data okruženju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:845944

Borotić, J. (2017). 'Analiza tokova podataka u Big Data okruženju', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:845944

Borotić J. Analiza tokova podataka u Big Data okruženju [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2017 [cited 2024 December 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:845944

J. Borotić, "Analiza tokova podataka u Big Data okruženju", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:168:845944

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Metadata
TitleAnaliza tokova podataka u Big Data okruženju
Title (english)Data Stream Analysis in Big Data Environments
AuthorJelena Borotić
MentorDamir Pintar (mentor)
Committee memberDamir Pintar (predsjednik povjerenstva)
Committee memberZoran Skočir (član povjerenstva)
Committee memberBoris Vrdoljak (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2017-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj ovoga rada bio je istražiti postojeće tehnologije za obradu tokova podataka, s naglaskom na Apache Spark Streaming. Na početku rada opisane su tehnologije koje su od najvećeg značaja za ovaj rad, Apcahe Spark i Apache Kafka. U sklopu Sparka opisan je Spark Streaming koji je bio glavna tema ovog rada. Nakon toga opisane su neke specifikacije grozda računala na kojemu je ovaj diplomski rađen. Spark Streaming isproban je problemu detekcije anomalija, a na početku praktičnog dijela prvo je dana teorijska pozadina vezana za anomalije, a nakon toga je opisan i postupak rješavanja problema. Na kraju je dana usporedba Apache Storma sa Spark Streamingom.
Abstract (english)
The main goal of this thesis was to explore current streaming technologies with main focus on Apache Spark Streaming. At the beginning are describen main technologies used in this thesis. After that are given specifications of cluster used in this thesis. For practical part is chosen anomaly detection problem. At the beginning of practical part are explained anomalies and why are they usefull, and afterwards is describen problem solution. At the end are compared Apache Storm and Apache Spark Streaming.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:845944
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2019-03-13 19:12:59