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master's thesis
Analiza velikih količina podataka korištenjem Apache Spark platforme
Zagreb: University of Zagreb, Faculty of Science, 2021. urn:nbn:hr:217:597888
Nevajdić, Vanja
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

Cite this document

Nevajdić, V. (2021). Analiza velikih količina podataka korištenjem Apache Spark platforme (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:597888

Nevajdić, Vanja. "Analiza velikih količina podataka korištenjem Apache Spark platforme." Master's thesis, University of Zagreb, Faculty of Science, 2021. https://urn.nsk.hr/urn:nbn:hr:217:597888

Nevajdić, Vanja. "Analiza velikih količina podataka korištenjem Apache Spark platforme." Master's thesis, University of Zagreb, Faculty of Science, 2021. https://urn.nsk.hr/urn:nbn:hr:217:597888

Nevajdić, V. (2021). 'Analiza velikih količina podataka korištenjem Apache Spark platforme', Master's thesis, University of Zagreb, Faculty of Science, accessed 16 June 2024, https://urn.nsk.hr/urn:nbn:hr:217:597888

Nevajdić V. Analiza velikih količina podataka korištenjem Apache Spark platforme [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2021 [cited 2024 June 16] Available at: https://urn.nsk.hr/urn:nbn:hr:217:597888

V. Nevajdić, "Analiza velikih količina podataka korištenjem Apache Spark platforme", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:217:597888

Metadata
TitleAnaliza velikih količina podataka korištenjem Apache Spark platforme
Title (english)Analysis of large amounts of data using the Apache Spark platform
AuthorVanja Nevajdić
MentorOgnjen Orel (mentor)
Committee memberOgnjen Orel (predsjednik povjerenstva)
Committee memberRobert Manger (član povjerenstva)
Committee memberMarko Tadić (član povjerenstva)
Committee memberFilip Najman (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2021-09-23, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
U današnjem digitalnom svijetu potrebno je analizirati ogromne količine podataka. Da bi to bilo moguće, najprije su se razvili distribuirani računalni sustavi i paralelno procesiranje podataka, a s vremenom i mnoštvo tehnologija za obradu i analizu podataka, jedna od kojih je Apache Spark. Apache Spark je platforma osmišljena za distribuirano procesiranje velike količine podataka. Ona se odlikuje svojom brzinom, širinom primjene i jednostavnosti korištenja. Brzina izvođenja ostvaruje se čuvanjem podataka u memoriji i internom optimizacijom koda. U Sparku se može raditi sa strukturiranim i graf podacima te tokovima podataka, a mogu se provoditi razne analize, uključujući strojno učenje. U praktičnom dijelu radu napravljena je analiza javno dostupnog skupa podataka Yelp platforme koristeći Apache Spark. Radi se o podacima o poduzećima, njihovim korisnicima i recenzijama koje oni ostavljaju. Analizirala se kvaliteta tih podataka tako što su se proučavale vremenske razlike između dvije uzastopne recenzije istog korisnika. Fokus analize bila je detekcija recenzija koje su napisane od strane robota.
Abstract (english)
In today’s digital world there is a need for analysing vast amounts of data. To achieve that, distributed computer systems and parallel processing were invented. In the following years, a number of technologies for processing and analysing data were created, with Apache Spark being one of them. Apache Spark is a platform designed for large-scale distributed data processing. Its main characteristics are speed, broad application and ease of use. Its speed is achieved with in-memory storage and code optimisation. Spark can be used on structured, graph and streaming data to perform different types of analyses, including machine learning. As part of this thesis, data quality analysis was performed on Yelp’s open dataset using Apache Spark. The data consisted of information about businesses, their customers and the reviews that they write. The focus of the analysis was on bot detection, which was performed by exploring the time between two consecutive reviews of a customer.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:597888
Study programmeTitle: Mathematical Statistics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2021-11-02 13:59:50