3 comments

  • chrisweekly5 minutes ago
    &gt; &quot;I can compute PageRank on a directed graph with one billion edges (graph500-26 from the Graphalytics dataset) using 5 GB of memory. Alternatively, I can identify all the weakly connected components in a graph with two billion edges (twitter_mpi from the same dataset collection) using 10 GB of memory. Neither NetworkX nor Igraph can do this; most existing graph algorithms require the graph to fit into memory. Previously, I thought you needed Apache Spark and GraphFrames for billion-scale graph analytics. Now, however, I think all you need is a laptop. I have completely changed my old opinion about using Apache DataFusion for graph analytics.&quot;<p>Impressive!
  • esafak0 minutes ago
    Does it support out-of-core or multi-processor processing?
  • slopblast58 minutes ago
    Really cool visualization, amazing how it resembles a neural network.