Encyclopedia of Big Data Technologies

Living Edition
| Editors: Sherif Sakr, Albert Zomaya

Graph Processing Frameworks

  • Arturo Diaz-Perez
  • Alberto Garcia-Robledo
  • Jose-Luis Gonzalez-Compean
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-63962-8_283-1

Synonyms

Definition

A graph processing framework (GPF) is a set of tools oriented to process graphs. Graph vertices are used to model data and edges model relationships between vertices. Typically, a GPF includes an input data stream, an execution model, and an application programming interface (API) having a set of functions implementing specific graph algorithms. In addition, some GPFs provide support for vertices and edges annotated with arbitrary properties of any kind and number.

Graphs are being used for modeling large phenomena and their relationships in different application domains such as social network analysis (SNA), biological network analysis, and link analysis for fraud/cybercrime detection. Since real graphs can be large, complex, and dynamic, GPFs have to deal with the three challenges of data growth: volume, velocity, and variety.

The programming API of GPFs is simple enough...

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References

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Arturo Diaz-Perez
    • 1
  • Alberto Garcia-Robledo
    • 2
  • Jose-Luis Gonzalez-Compean
    • 1
  1. 1.Cinvestav TamaulipasVictoriaMexico
  2. 2.Universidad Politecnica de VictoriaVictoriaMexico

Section editors and affiliations

  • Rodrigo N. Calheiros
    • 1
  • Marcos Dias de Assuncao
    • 2
  1. 1.School of Computing, Engineering and MathematicsWestern Sydney UniversityPenrithAustralia
  2. 2.Inria, LIP, ENS LyonLyonFrance