As shown by the code below, Julia is twice slower than R (!) to sum elements of a Float64 vector with missing values, even with Julia 0.7. In R, missing values are encoded with sentinelle values. In Julia, they are encoded with different type. This difference of design makes it much slower to mani…

See the two last sections of my blog post . We get an incredibly high performance on recent git master for a manual sum over Vector{Int}, a similar performance as R for a manual sum over Vector{Float64}, but a somewhat poorer performance using skipmissing. I’ve filed this issue about it yesterday. A…

With Missings, Julia is slower than R

General Usage

StefanKarpinski June 21, 2018, 3:19am 2

Don’t benchmark in global scope (performance tips)
Use BenchmarkTools for benchmarking
The first run includes compile time

3 Likes

CSV Reading (rewrite in C?)

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With Missings, Julia is slower than R

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