@inproceedings{AstrovaKoschelHeineetal.2019,
  author    = {Irina Astrova and Arne Koschel and Felix Heine and Ahto Kalja},
  title     = {Moving Hadoop to the cloud for big data analytics},
  series = {Databases and Information Systems X - Selected Papers from the Thirteenth International Baltic Conference, DB\&IS 2018, Trakai, Lithuania, July 1-4, 2018},
  doi       = {10.25968/opus-1555},
  url       = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus4-15559},
  pages     = {195 -- 209},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}