Access restricted to students and staff of home institution
master's thesis
3   2
Map Reduce as a Processing Technique for Large Quantities of Semi-structured Data
Mario Nikolaus (2015)
University of Zagreb
Faculty of Organization and Informatics Varaždin
Department of Theoretical and Applied Foundations of Information Sciences
Metadata
TitleMap Reduce kao tehnika za obradu velikih količina polustrukturiranih podataka
AuthorMario Nikolaus
Mentor(s)Markus Schatten (thesis advisor)
Abstract

Ovaj diplomski rad opisuje polustrukturirani model podataka i tehniku MapReduce kroz implementaciju aplikacije napisane u Node.js i MongoDB tehnologijama. Aplikacija prikuplja i analizira podatke iz Twitter API-a i u oblik nadzorne ploče prikazuje izvedene analize.
Parallel title (English)Map Reduce as a Processing Technique for Large Quantities of Semi-structured Data
Committee MembersMiroslav Bača
GranterUniversity of Zagreb
Faculty of Organization and Informatics Varaždin
Lower level organizational unitsDepartment of Theoretical and Applied Foundations of Information Sciences
PlaceVaraždin
StateCroatia
Scientific field, discipline, subdisciplineSOCIAL SCIENCES
Information and Communication Sciences
Organization and Informatics
Study programme typeuniversity
Study levelgraduate
Study programmeDatabase and Knowledge Base Studies
Academic title abbreviationmag.inf.
Genremaster's thesis
Language Croatian
Defense date2015-09-23
Parallel keywords (Croatian)polustrukturirani podaci couchdb mongodb existdb mapreduce xquery baza podataka
Resource typetext
Access conditionAccess restricted to students and staff of home institution
Terms of usehttp://rightsstatements.org/vocab/InC/1.0/
URN:NBNhttps://urn.nsk.hr/urn:nbn:hr:211:489885
CommitterMarinko Kokotec