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Distributed Graph Analytics (DGA) is a compendium of graph analytics written for Bulk-Synchronous-Parallel (BSP) processing frameworks such as Giraph and GraphX. The analytics included are High Betweenness Set Extraction, Weakly Connected Components, Page Rank, Leaf Compression, and Louvain Modularity.

License: Apache License 2.0

distributed-graph-analytics's Introduction

distributed-graph-analytics

Distributed Graph Analytics (DGA) is a compendium of graph analytics written for Bulk-Synchronous-Parallel (BSP) processing frameworks such as Giraph and GraphX.

Currently, DGA supports the following analytics:

Giraph
  • Weakly Connected Components
  • Leaf Compression
  • Page Rank
  • High Betweenness Set Extraction
  • Louvain
GraphX
  • Louvain Modularity (initial stage)

Eventually, the following analytics will be supported:

  • Weakly Connected Components
  • High Betweenness Set Extraction
  • Leaf Compression
  • Page Rank
dga-giraph

dga-giraph is the project that contains our Giraph implementation of DGA. For more information, go here: dga-giraph README.md

distributed-graph-analytics's People

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