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Unexpectedly endless pathfinding from the nth size.

Abierto
#72 2 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
35/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Estancado
Stack tecnológico
elixir
Área
performance

Línea de trabajo

Start with the Graph.get_paths/3 call shown in the report and reproduce the timing at 10,000 and 11,000 relationships using the supplied Elixir, OTP, and libgraph versions. Compare pathfinding behavior with the reported graph construction pattern and check whether an existing benchmark covers graphs of this size. Done means explaining the scaling behavior and, if appropriate, adding a benchmark that captures it.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

Machine: Intel Core i5-8250U (1.60GHz), 16gb RAM
OS: Ubuntu 22.04
Elixir version: Elixir 1.15.0-rc.0
OTP version: 25.0
libgraph version: 0.16.0

I use graph to accumulate pages while I crawl. The crawler is a stream of pages: above page (previous) and sub page (current). Such relationship I have to record to find paths between pages later.

I noticed that from nth node it becomes impossible to compute paths. Literally, when my crawler reached a goal and needed to collect paths from A to B pages, it took all night and there was no calculation result (the calculation was definitely still going on, judging by the load).

I decided to log every thousandth relationship recorded and try to find all paths from the starting page to the current page (I record page to subpage relationship).

The results are as follows (relation a sub page to the above page -> time to find all paths from the first page to the sub page):

  • 1000 -> 99µ
  • 2000 -> 179µ
  • 3000 -> 306µ
  • 4000 -> 302µ
  • 5000 -> 745µ
  • 6000 -> 834µ
  • 7000 -> 3018µ
  • 8000 -> 3059µ
  • 9000 -> 6092µ
  • 10000 -> 66057µ
  • 11000 -> infinity

I used this to record relationship:

graph
|> Graph.add_vertex(abv_ref, abv)
|> Graph.add_vertex(sub_ref, sub)
|> Graph.add_edge(abv_ref, sub_ref)

Where abv and sub are structs, abv_ref and sub_ref are strings.

Tested like this:

IO.puts("Task now: #{x}")
if rem(x, 1000) === 0 do
  IO.puts("Trying to get all paths from the start to current urls...")

  {d, result} = :timer.tc(fn ->
    Graph.get_paths(graph, start_ref, sub_ref)
  end)

  IO.puts("Got result in #{d}µ (#{div(d, 1_000_000)}s): #{inspect(result)}")
end

Where result is a list of strings, start_ref is string as well.


I don't know if my problem is unique or if it's a general property of the library graph. Is there a benchmark that tests such a large amount of relations? Send links if available. If not, my suggestion is to make one.

Lenguaje dominante
Elixir
Estrellas
571
Forks
76
Métricas de merge de PR
Sin PR fusionados en 30 d

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