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Hello
I have observed a 10x difference when loading the iris dataset in 2 different machines.
Loading times are a bit unreasonable, is there anything I can do to speed this up?
ulia> using RDatasets
julia> @time iris = dataset("datasets", "iris"); # a DataFrame
100.068931 seconds (75.23 M allocations: 4.053 GiB, 3.19% gc time)
julia> 102.497734 seconds (75.35 M allocations: 4.062 GiB, 3.33% gc time)
(v1.2) pkg> status RDatasets
Status `~/.julia/environments/v1.2/Project.toml`
[a93c6f00] DataFrames v0.19.4
[ce6b1742] RDatasets v0.6.4
julia> versioninfo()
Julia Version 1.2.0
Commit c6da87ff4b (2019-08-20 00:03 UTC)
Platform Info:
OS: macOS (x86_64-apple-darwin18.6.0)
CPU: Intel(R) Core(TM) i5-4278U CPU @ 2.60GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-6.0.1 (ORCJIT, haswell)
Environment:
JULIA_EDITOR = subl
(v1.2) pkg> status RDatasets
Status `~/.julia/environments/v1.2/Project.toml`
[336ed68f] CSV v0.5.14
[a93c6f00] DataFrames v0.19.4
[ce6b1742] RDatasets v0.6.4
In the other machine I get:
julia> using RDatasets
[ Info: Recompiling stale cache file /home/david/.julia/compiled/v1.1/RDatasets/JyIbx.ji for RDatasets [ce6b1742-4840-55fa-b093-852dadbb1d8b]
julia> @time iris = dataset("datasets", "iris");
10.544570 seconds (37.27 M allocations: 1.767 GiB, 8.98% gc time)
julia> versioninfo()
Julia Version 1.1.0
Commit 80516ca202 (2019-01-21 21:24 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-4600U CPU @ 2.10GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-6.0.1 (ORCJIT, haswell)
(v1.1) pkg> status RDatasets
Status `~/.julia/environments/v1.1/Project.toml`
[336ed68f] CSV v0.5.14
[a93c6f00] DataFrames v0.18.4
[ce6b1742] RDatasets v0.6.1
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