Online Balancing of aR-Tree Indexed Distributed Spatial Data Warehouse

  • Marcin Gorawski
  • Robert Chechelski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3911)


One of the key requirements of data warehouses is query response time. Amongst all methods of improving query performance, parallel processing (especially in shared nothing class) is one of the giving practically unlimited system’s scaling possibility. The complexity of data warehouse systems is very high with respect to system structure, data model and many mechanisms used, which have a strong influence on the overall performance. The main problem in a parallel data warehouse balancing is data allocation between system nodes. The problem is growing when nodes have different computational characteristics. In this paper we present an algorithm of balancing distributed data warehouse built on shared nothing architecture. Balancing is realized by iterative setting dataset size stored in each node. We employ some well known data allocation schemes using space filling curves: Hilbert and Peano. We provide a collection of system tests results and its analysis that confirm the possibility of a balancing algorithm realization in a proposed way.


Data Warehouse Range Query Query Execution Fact Table System Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Marcin Gorawski
    • 1
  • Robert Chechelski
    • 1
  1. 1.Institute of Computer ScienceSilesian University of TechnologyGliwicePoland

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