Performance comparison: counting words in Python, Go, C++, C, AWK, Forth, and Rust

• countwords

  43 209 5.9 Rust

  Discontinued Playing with counting word frequencies (and performance) in various languages.

My favorite one is the "bonus" submission. It intentionally ignores the constraints of the benchmark and tries to be a bit more "correct" by using Unicode's word segmentation. The code is still almost as simple as the other "simple" variants and nearly as fast! https://github.com/benhoyt/countwords/blob/8553c8f600c40a4626e966bc7e7e804097e6e2f4/rust/bonus/main.rs

• coreutils

  112 4,036 9.3 C

  upstream mirror (by coreutils)

  

You only had to look at the code (https://github.com/coreutils/coreutils/blob/master/src/wc.c) to know whether or not that was really true.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• vowpal_wabbit

  11 8,409 8.1 C++

  Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

  

You're likely correct, but I do recall attending a lecture by John Langford of https://vowpalwabbit.org/ running some form of an N-gram C++ based NLP model, including summary statistics on performance, in less time than wc -l took on the same data. Must have some neat hashing tricks, but still was cool

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