Summary: I describe a simple interview problem (counting frequencies of unique words), solve it in various languages, and compare performance across them. For each language, I’ve included a simple, idiomatic solution as well as a more optimized approach via profiling…
Language Simple Optimized Notes grep
0.04 0.04 grep
baseline; optimized setsLC_ALL=C
wc -w
0.29 0.20 wc
baseline; optimized setsLC_ALL=C
Zig 0.54 by ifreund and matu3ba Nim 0.76 0.58 by csterritt and euantorano C 0.97 0.23 Go 1.14 0.39 Crystal 1.29 by Andrea Manzini PHP 1.36 by Max Semenik Rust 1.43 0.38 by Andrew Gallant C# 1.51 0.82 by J Taylor, Y Ostapenko, O Turan OCaml 1.72 by Nate Dobbins and Pavlo Khrystenko C++ 1.73 0.42 optimized by Jussi Pakkanen Perl 1.81 by Charles Randall F# 1.82 1.59 by Yuriy Ostapenko Kotlin 1.86 by Kazik Pogoda Python 2.07 1.30 Lua 2.50 1.97 by themadsens; runs under luajit JavaScript 2.52 1.90 by Dani Biro and Flo Hinze Ruby 3.13 2.43 by Bill Mill AWK 3.55 1.13 optimized uses mawk
D 4.16 1.01 by Ross Lonstein Swift 4.23 by Daniel Muellenborn Forth 4.26 1.46 Shell 14.60 1.85 optimized does LC_ALL=C sort -S 2G
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