CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
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CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
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Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#2Julia is a hidden gem Once ecosystem for web dev matures Julia will be the killer lang for building web apps
Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#3this is neat. that said, to me, this is like comparing car startup times. even if a tesla starts faster than a toyota, they're both fast enough to not notice 99.999% of the time. This isn't a factor in a purchasing decision -- i've never even thought of that before contriving this metaphor
Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#4this is neat. that said, to me, this is like comparing car startup times. even if a tesla starts faster than a toyota, they're both fast enough to not notice 99.999% of the time. This isn't a factor in a purchasing decision -- i've never even thought of that before contriving this metaphor
Maybe not a deciding factor, but definitely a factor in a purchasing decision, among many others.
Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#5Julia is a hidden gem Once ecosystem for web dev matures Julia will be the killer lang for building web apps
> Julia will be the killer lang for building web apps
That would be fun, but Julia's community aren't web devs. Julia spawned around very specific needs of scientific computing, which is characterised by a short-running daemon or a script-type interpreter. A web server is a long-running process. Not knowledgeable enough about Julia to tell how it lends itself to server uses, but heard hearsay that it's problematic.
Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#6EDIT: Be sure to read the reply from the author of the package.
I do think Julia has promise, but it is still early days.
In the last 2 months there have been problems with:
* Throwing rows away: https://github.com/JuliaData/CSV.jl/issues/720
* Incorrect float parsing: https://github.com/JuliaData/CSV.jl/issues/714
At there are unfixed issues to do with parsing large files ( https://github.com/JuliaData/CSV.jl/issues/749 , https://github.com/JuliaData/CSV.jl/issues/734 ).
While Julia has become much more stable than it used to be, it is still in many places an evolving system and you (in my limited experience) should be prepared to hit issues.
Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#7> The very first task in any data analysis workflow is simply reading the data, and this absolutely must be done quickly.
Lost me here. For what use-case of data analysis workflow does saving a minute or two make a difference? When will you tech bros learn to separate web dev from data science?
Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#8[deleted]
Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#9I’d really think all these languages would have the bottleneck of disk read speed. So how can Julia be that much faster? Are the others really that inefficient?
Re: CSV Reader Benchmarks: Julia Reads CSVs 10-20x Faster than Python and R
#10> The very first task in any data analysis workflow is simply reading the data, and this absolutely must be done quickly. Lost me here. For what use-case of data analysis workflow does saving a minute or two make a difference? When will you tech bros learn to separate web dev from data science?
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