Most of the time is spent in building a node adjacency list, but there might be ways around it. Which OS and python environment are you using?
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I added a program to benchmark graph I/O to the repo, it is now in test/readgraph.py. It creates a graph using a preferential attachment and then performs graph I/O with different methods. The graph file size is about 6GB.
Here are the reading times for an undirected graph with 120M nodes and 360M edges:
- 350s, reading an edge list via LoadEdgeList()
- 512s, reading an adjacency list via LoadConnList()
- 29s, reading a binary graph via Load()
- 250s, reading a table via LoadSS() and then running ToGraph()
The best option is to build the graph once, save it in a binary format and then use that to load it at a later time.
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