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Dynamic Graphs

Yogesh Simmhan edited this page Aug 13, 2016 · 8 revisions

Dynamic Graphs

Kineograph

  • Presented by Ravikant
  • Updates only to graph structure, not metadata/properties. Add/remove vertices/edges.
  • Ingest nodes convert input data into transactions, with a unique sequence no. assigned to the subset of transactions applied to a data node. Once a transaction is completed, a progress table maintains the latest seq no. that has been completed (including all prior transactions) for that ingest node.
  • Ordering of sequence nos across ingest is not considered.
  • Creation of snapshots commits a particular seq no for each ingest node at each data node.
  • Snapshots are taken periodically. Applications operate on the snapshots.
  • After creating a snapshot, each partition decides if each of its vertex was changed (a lot) or not, and based on that calls the compute method on that vertex.
  • Vertex centric algo, with both push (message passing) and pull (async).
  • Incremental execution of algo when each new snapshot is created.
  • Desiderata:
  • Is this similar to "creating" timeseries graphs rather than being a dynamic graph?
  • Topo update
  • Property update
  • Distributed update
  • Consistent temporal snapshots
  • Incremental algorithms
  • TODO
  • Additional Reading: Time evolving graphs [RD], dynamic graphs [RD], incremental algorithms [DK]

iGraph

  • Presented by Diptanshu
  • Graphs partitioned into different machines
  • Topo and attribute updates attrive as a stream
  • Multiple apps running at the same time
  • To be Continued...
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