International Conference on Database and Expert Systems Applications

DEXA 2015: Database and Expert Systems Applications pp 285-299 | Cite as

Workload-Aware Self-Tuning Histograms of String Data

  • Nickolas Zoulis
  • Effrosyni Mavroudi
  • Anna Lykoura
  • Angelos Charalambidis
  • Stasinos Konstantopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9261)

Abstract

In this paper we extend STHoles, a very successful algorithm that uses query results to build and maintain multi-dimensional histograms of numerical data. Our contribution is the formal definition of extensions of all relevant concepts; such that they are independent of the domain of the data, but subsume STHoles concepts as their numerical specialization. At the same time, we also derive specializations for the string domain and implement these into a prototype that we use to empirically validate our approach. Our current implementation uses string prefixes as the machinery for describing string ranges. Although weaker than regular expressions, prefixes can be very efficiently applied and can capture interesting ranges in hierarchically structured string domains, such as those of filesystem pathnames and URIs. In fact, we base the empirical validation of the approach on existing, publicly available Semantic Web data where we demonstrate convergence to accurate and efficient histograms.

Keywords

Resource Description Framework Query Result Query Execution Resource Description Framework Data Resource Description Framework Triple 
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.

Notes

Acknowledgements

The work described here was partially carried out at the 2014 edition of the International Research-Centred Summer School, held at NCSR ‘Demokritos’, Athens, Greece, 3–30 July 2014. For more details please see http://irss.iit.demokritos.gr

The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 318497. More details at http://www.semagrow.eu.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nickolas Zoulis
    • 1
  • Effrosyni Mavroudi
    • 2
  • Anna Lykoura
    • 3
  • Angelos Charalambidis
    • 4
  • Stasinos Konstantopoulos
    • 4
  1. 1.Computer ScienceAthens University of Economics and BusinessAthensGreece
  2. 2.Electrical and Computer EngineeringNational Technical University of AthensKesarianiGreece
  3. 3.Applied Mathematical and Physical ScienceNational Technical University of AthensKesarianiGreece
  4. 4.Institute of Informatics and TelecommunicationsNCSR ‘Demokritos’AthensGreece

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