下面是一个使用python和生成器表达式的解决方案。在我破旧的笔记本电脑上测试了无数个数字。

time python -c "import sys; print sum((float(l) for l in sys.stdin))" < file

real    0m0.619s
user    0m0.512s
sys     0m0.028s

Perl 6

say sum lines

~$ perl6 -e '.say for 0..1000000' > test.in

~$ perl6 -e 'say sum lines' < test.in
500000500000

运行R脚本

我写了一个R脚本来获取文件名的参数并对行进行求和。

#! /usr/local/bin/R
file=commandArgs(trailingOnly=TRUE)[1]
sum(as.numeric(readLines(file)))

这可以通过“数据”来加快。表”或“vroom”软件包如下:

#! /usr/local/bin/R
file=commandArgs(trailingOnly=TRUE)[1]
sum(data.table::fread(file))

#! /usr/local/bin/R
file=commandArgs(trailingOnly=TRUE)[1]
sum(vroom::vroom(file))

基准测试

与@glenn jackman相同的基准测试数据。

for ((i=0; i<1000000; i++)) ; do echo $RANDOM; done > random_numbers

与上面的R调用相比，作为脚本运行R 3.5.0与其他方法(在相同的Linux Debian服务器上)相当。

$ time R -e 'sum(scan("random_numbers"))'  
 0.37s user
 0.04s system
 86% cpu
 0.478 total

R脚本与readLines

$ time Rscript sum.R random_numbers
  0.53s user
  0.04s system
  84% cpu
  0.679 total

R脚本data.table

$ time Rscript sum.R random_numbers     
 0.30s user
 0.05s system
 77% cpu
 0.453 total

R脚本与vroom

$ time Rscript sum.R random_numbers     
  0.54s user 
  0.11s system
  93% cpu
  0.696 total

与其他语言的比较

此处作为参考，建议在相同硬件上使用其他一些方法

Python 2 (2.7.13)

$ time python2 -c "import sys; print sum((float(l) for l in sys.stdin))" < random_numbers 
 0.27s user 0.00s system 89% cpu 0.298 total

Python 3 (3.6.8)

$ time python3 -c "import sys; print(sum((float(l) for l in sys.stdin)))" < random_number
0.37s user 0.02s system 98% cpu 0.393 total

Ruby (2.3.3)

$  time ruby -e 'sum = 0; File.foreach(ARGV.shift) {|line| sum+=line.to_i}; puts sum' random_numbers
 0.42s user
 0.03s system
 72% cpu
 0.625 total

Perl (5.24.1)

$ time perl -nle '$sum += $_ } END { print $sum' random_numbers
 0.24s user
 0.01s system
 99% cpu
 0.249 total

awk （4.1.4）

$ time awk '{ sum += $0 } END { print sum }' random_numbers
 0.26s user
 0.01s system
 99% cpu
 0.265 total
$ time awk '{ sum += $1 } END { print sum }' random_numbers
 0.34s user
 0.01s system
 99% cpu
 0.354 total

C (clang版本3.3;gcc (Debian 6.3.0-18)

 $ gcc sum.c -o sum && time ./sum < random_numbers   
 0.10s user
 0.00s system
 96% cpu
 0.108 total

使用其他语言更新

获取 （5.3.5）

$ time lua -e 'sum=0; for line in io.lines() do sum=sum+line end; print(sum)' < random_numbers 
 0.30s user 
 0.01s system
 98% cpu
 0.312 total

Tr(8.26)必须在bash中计时，不兼容ZSH

$time { { tr "\n" + < random_numbers ; echo 0; } | bc; }
real    0m0.494s
user    0m0.488s
sys 0m0.044s

Sed(4.4)必须在bash中计时，与ZSH不兼容

$  time { head -n 10000 random_numbers | sed ':a;N;s/\n/+/;ta' |bc; }
real    0m0.631s
user    0m0.628s
sys     0m0.008s
$  time { head -n 100000 random_numbers | sed ':a;N;s/\n/+/;ta' |bc; }
real    1m2.593s
user    1m2.588s
sys     0m0.012s

注意:sed调用似乎在有更多可用内存的系统上工作得更快(注意用于sed基准测试的数据集更小)

茱莉亚(0.5.0)

$ time julia -e 'print(sum(readdlm("random_numbers")))'
 3.00s user 
 1.39s system 
 136% cpu 
 3.204 total
$  time julia -e 'print(sum(readtable("random_numbers")))'
 0.63s user 
 0.96s system 
 248% cpu 
 0.638 total

注意，在R中，文件I/O方法具有不同的性能。

这是直接的Bash:

sum=0
while read -r line
do
    (( sum += line ))
done < file
echo $sum

tcl中的一个:

#!/usr/bin/env tclsh
set sum 0
while {[gets stdin num] >= 0} { incr sum $num }
puts $sum

sed ':a;N;s/\n/+/;ta' file|bc