@masterthesis{Scharlau2016,
  type      = {Bachelor Thesis},
  author    = {Scharlau, Lukas},
  title     = {Multi-part Nanocubes},
  publisher = {FH M{\"u}nster},
  doi       = {10.25974/fhms-950},
  url       = {http://nbn-resolving.de/urn:nbn:de:hbz:836-opus-9500},
  school      = {FH M{\"u}nster - University of Applied Sciences},
  year      = {2016},
  abstract  = {This thesis describes the development of Multi-part Nanocubes. It is a further development of Nanocubes, an in-memory data structure for spatiotemporal data cubes. "Nanocubes provides you with real-time visualization of large datasets. Slice and dice your data with respect to space, time, or some of your data attributes, and view the results in real-time on a web browser over heatmaps, bar charts, and histograms." Partitioning the structure to parallelize the build process as well as merging query results is the principal part of this document. Furthermore, a new memory management (slab allocation with offset pointers) was implemented to enable 32-bit support and faster load times of already built nanocubes. Porting the project to Windows and implementing on-the-fly compression and decompression of nanocube files is also described.},
  subject      = {Massendaten},
  language  = {en}
}