tk3369
1
Is there any way to speed this up? I don’t think I’m the only one bothered by this…
julia> @time using DataFrames
28.351476 seconds (2.77 M allocations: 165.493 MiB, 2.67% gc time)
julia> versioninfo()
Julia Version 0.6.1
Commit 0d7248e (2017-10-24 22:15 UTC)
Platform Info:
OS: macOS (x86_64-apple-darwin14.5.0)
CPU: Intel(R) Core(TM) i5-4258U CPU @ 2.40GHz
WORD_SIZE: 64
BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)
LAPACK: libopenblas64_
LIBM: libopenlibm
LLVM: libLLVM-3.9.1 (ORCJIT, haswell)
juliohm
2
For reference, mine doesn’t take that long:
julia> @time using DataFrames
1.138097 seconds (1.20 M allocations: 66.721 MiB, 14.38% gc time)
julia> versioninfo()
Julia Version 0.6.1-pre.0
Commit dcf39a1dda* (2017-06-19 13:06 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-6500U CPU @ 2.50GHz
WORD_SIZE: 64
BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)
LAPACK: libopenblas64_
LIBM: libopenlibm
LLVM: libLLVM-3.9.1 (ORCJIT, skylake)
julia> Pkg.status("DataFrames")
- DataFrames 0.11.2
xiaodai
3
Are you using Juno? On my Windows PC, timing it in Juno is 9 seconds but in Julia REPL it is 1.7 seconds.
Sometimes Juno is only 4 seconds, so a bit of variability there.
Unless it’s the first time you are doing using DataFrames
after updating it or installing it for the first time.
tk3369
4
I am just using the REPL. In fact, every time I restart the REPL it takes just as long.
xiaodai
5
Probably a long shot but what is your Pkg.status("DataFrames")
. I suggest raising a performance bug in the DataFrames together with that information.
Perhaps you can try Pkg.checkout("DataFrames")
to install the latest version of DataFrames to help rule in/out if DataFrames is the issue.
tk3369
6
Strange but it works after removing and reinstalling all packages.
Thanks for the suggestions.
julia> @time using DataFrames
2.567160 seconds (2.89 M allocations: 164.181 MiB, 11.35% gc time)