# CSV.read very slow when number of threads changed

**URL:** <https://discourse.julialang.org/t/csv-read-very-slow-when-number-of-threads-changed/103991>\
**Category:** General Usage\
**Tags:** multithreading, csv\
**Created:** [September 18, 2023, 3:01pm UTC](https://discourse.julialang.org/t/csv-read-very-slow-when-number-of-threads-changed/103991 "2023-09-18T15:01:56Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![pascal](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/pascal/32/207922_2.png) [@pascal](https://discourse.julialang.org/u/pascal)\
**Post date:** [September 18, 2023, 3:01pm UTC](https://discourse.julialang.org/t/csv-read-very-slow-when-number-of-threads-changed/103991/1 "2023-09-18T15:01:56Z")

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I want to read in a csv file with ~5000 lines which is usually very fast. But when I start Julia with `--threads=10` or `--threads=auto` waiting times for `CSV.read` are going through the roof.  
So, how can I have both, fast `CSV.read` and multithreading that deserves the name?

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<div class="post-metadata">

**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [September 18, 2023, 3:16pm UTC](https://discourse.julialang.org/t/csv-read-very-slow-when-number-of-threads-changed/103991/2 "2023-09-18T15:16:35Z")

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Could you clarify what “going through the roof” means?

For me on 1.10beta2 with one thread:

```julia
julia> using CSV, DataFrames

julia> CSV.write("test.csv", DataFrame(rand(5_000, 30), :auto));

julia> @time CSV.read("test.csv", DataFrame);
  0.700708 seconds (359.52 k allocations: 25.033 MiB, 3.32% gc time, 97.74% compilation time: 95% of which was recompilation)

julia> @time CSV.read("test.csv", DataFrame);
  0.017480 seconds (11.53 k allocations: 1.492 MiB)

```

and with `--threads=auto` (which means 8 for my machine):

```julia
julia> using CSV, DataFrames

julia> @time CSV.read("test.csv", DataFrame);
  2.103722 seconds (3.27 M allocations: 227.861 MiB, 3.96% gc time, 682.92% compilation time: 6% of which was recompilation)

julia> @time CSV.read("test.csv", DataFrame);
  0.008714 seconds (17.77 k allocations: 1.722 MiB)

```

so 0.7 → 2.1 seconds for the first run, and about a 50% speedup for the second (I guess the file is too small to benefit more from 8 threads).

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<div class="post-metadata">

**Author:** ![pascal](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/pascal/32/207922_2.png) [@pascal](https://discourse.julialang.org/u/pascal)\
**Post date:** [September 18, 2023, 3:53pm UTC](https://discourse.julialang.org/t/csv-read-very-slow-when-number-of-threads-changed/103991/3 "2023-09-18T15:53:22Z")

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Hm, I’ve repeated your inputs and got quite similar results, when I’m calling Julia in a separate terminal.  
I suspect the problem now to be with Pumas for Desktop. Because these long loading times only occur when I’m using Julia and `CSV.read` in VSCode which is linked to `Pumas-2.4.1.app`. Maybe I need to ask over at discourse.pumas.ai.