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Is graphFromEdges too lazy?

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#917 5 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
30/100
Issue type
Refactor
Clarity
Mostly clear
Activity status
Stale
Tech stack
haskell
Domain
data

Research direction

Start in containers/src/Data/Graph.hs at the linked graphFromEdges construction and compare its evaluation behavior with buildG. Review the existing discussion and benchmark results before deciding whether strict construction preserves useful laziness; done means a maintainer-approved decision, with any resulting change validated by measurements.

Written by the indexing model from the issue text.

Description

Graph major-release performance

graphFromEdges is one way to construct a Graph in Data.Graph, and the line in it which actually constructs the graph looks like

https://github.com/haskell/containers/blob/d8d163a8baa43a7c8ba9b6f4198ee1e398e730d6/containers/src/Data/Graph.hs#L450

This is very lazy. The elements of the array (lists of vertices) are lazy, and the lists themselves would be lazily generated when required. I doubt building up all these thunks is good for us. So I checked out if construction times improve if we are strict, and it does, from 371 ms ± 18 ms, 107 MB allocated to 323 ms ± 30 ms, 77 MB allocated on the largest graph.

Now I've tried to think of situations where lazily constructing a graph is useful.
The only case I can think of is if the user constructs a large graph through graphFromEdges, then runs dfs on a subset of the graph the user already knows is not connected to the rest of the graph. Then they avoid paying the cost of constructing the full graph. But this seems far-fetched.
All other functions like dff, topSort, scc, bcc will always evaluate the full graph.

So, is there any other scenario where lazily constructing a graph is useful?

And if not, should we make it strict?
This would improve the times and also make it consistent with buildG, the other way in Data.Graph to build a graph. The second reason alone might be good reason to do this.

Dominant language
Haskell
Stars
355
Forks
194
Avg merge
2d 12h
Merged PRs (30d)
6

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