Comments (2)
One thing we'll have decide here is whether GraphStream will internally be represented as a DataStream of Edges and a DataStream of Vertices or something else.
I would say let's go for this solution initially and try to figure out how to create these streams in the cases mentioned above, i.e. random edge streams, incidence streams and mutation events.
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I think we've settled for random edge streams with duplicates for now.
from gelly-streaming.
Related Issues (20)
- Add stream graph partitioning algorithms HOT 1
- Exact global and local triangle count
- Degree distribution example
- Adding data-parallel window graph aggregation HOT 7
- [Discuss] Decouple SimpleEdgeStream and GraphWindowStream from neighbor stream keying
- [Feature] Min-cut / Max-flow HOT 1
- Introduce Interfacing for Customly Purging Aggregation State
- Introduce Alternative (Binary) Tree Parallel Aggregation Strategy
- Make window aggregation state fault tolerant
- How to use GellyStream API in Scala code HOT 1
- The result of ExactTriangleCount HOT 2
- How to run GellyStream on Flink HOT 2
- Why run IterativeConnectedComponents is similar to the death cycle HOT 2
- How to develop PageRank algorithm on GellyStream HOT 1
- Last window never triggers in snapshot iterations
- Allow initialState() to access the vertex context
- Clarification of gelly-stream features HOT 5
- Can we run ConnectedComponents algorithm in production using this library? HOT 3
- BroadcastTriangleCount HOT 1
- Scala version
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