TY - CHAP U1 - Konferenzveröffentlichung A1 - Astrova, Irina A1 - Koschel, Arne A1 - Heine, Felix A1 - Kalja, Ahto T1 - Moving Hadoop to the cloud for big data analytics T2 - Databases and Information Systems X - Selected Papers from the Thirteenth International Baltic Conference, DB&IS 2018, Trakai, Lithuania, July 1-4, 2018 N2 - Hadoop is a Java-based open source programming framework, which supports the processing and storage of large volumes of data sets in a distributed computing environment. On the other hand, an overwhelming majority of organizations are moving their big data processing and storing to the cloud to take advantage of cost reduction – the cloud eliminates the need for investing heavily in infrastructures, which may or may not be used by organizations. This paper shows how organizations can alleviate some of the obstacles faced when trying to make Hadoop run in the cloud. KW - Big Data Analytics KW - Education KW - OpenStack KW - Hadoop KW - Big Data KW - Cloud Computing KW - MapReduce KW - Pregel KW - Word Counting KW - Shortest Path KW - PageRank Y1 - 2019 UN - https://nbn-resolving.org/urn:nbn:de:bsz:960-opus4-15559 U6 - https://doi.org/10.25968/opus-1555 DO - https://doi.org/10.25968/opus-1555 SP - 195 EP - 209 ER -