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Speed up persisting large number of outliers #16649
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erikjohnston
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clokep
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| @@ -135,3 +135,54 @@ def sorted_topologically( | |||
| degree_map[edge] -= 1 | |||
| if degree_map[edge] == 0: | |||
| heapq.heappush(zero_degree, edge) | |||
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| def sorted_topologically_batched( | |||
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FWIW I think sorted_topologically could become
def sorted_topologically(nodes, graph):
for batch in sorted_topologically_batched(nodes, graph):
yield from batchIt would probably create a bunch of intermediate lists and such though, which is unnecessary.
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Yes, ish. I think sorted_topologically gives a lexicographical topological sort, which could return a slightly different order (though I don't think we really rely on that fact anywhere, so)
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Recalculating the roots tuple every iteration could be very expensive, so instead let's do a topological sort.
(Note that
sorted_topologically_batchedis basically a slightly modifiedsorted_topologically, and the tests are more or less a copy and paste)