Encyclopedia of Big Data Technologies

2019 Edition
| Editors: Sherif Sakr, Albert Y. Zomaya

Graph Processing Frameworks

  • Arturo Diaz-PerezEmail author
  • Alberto Garcia-Robledo
  • Jose-Luis Gonzalez-Compean
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-77525-8_283



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...

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

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