Large-Scale Graph Processing Using Apache Giraph by Sherif Sakr Faisal Moeen Orakzai Ibrahim Abdelaziz & Zuhair Khayyat

Author:Sherif Sakr, Faisal Moeen Orakzai, Ibrahim Abdelaziz & Zuhair Khayyat
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

The following methods of the Computation interface are generally not required to be implemented as Giraph comes with a class AbstractComputation which has this method already implemented. You just have to extend this class for writing your computation after which you can call these methods whenever needed.

\hskip-1.6pc{\small\sffamily Fig. 3.3Social graph

3.2 Vertex Similarity Algorithm

Let us use the knowledge gained in the previous sections to write a simple vertex similarity algorithm for finding friends’ similarity in terms of their common friends. Figure 3.3 shows a simple social graph. Each vertex in the figure represents a person and the edges represent friendship. We want to assign a weight to each edge, representing the similarity between the persons it connects together. The weight of an edge will be higher if the persons it connects, have more common friends. Thus the weight an edge between two persons shows the similarity between the two persons. We use Jaccard Index as the similarity measure which is used for finding similarity between two sets. If A and B are two sets, Jaccard Index can be written as the size of the intersection between A & B divided by the size of the union of A & B:

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