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性能 – 在Perl中快速加载大型哈希表

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我有大约30个带有结构的文本文件 wordleft1|wordright1wordleft2|wordright2wordleft3|wordright3... 文件的总大小约为1 GB,大约有3200万行字组合. 我尝试了一些方法来尽快加载它们并将组合存储在哈希中
我有大约30个带有结构的文本文件

wordleft1|wordright1
wordleft2|wordright2
wordleft3|wordright3
...

文件的总大小约为1 GB,大约有3200万行字组合.

我尝试了一些方法来尽快加载它们并将组合存储在哈希中

$hash{$wordleft} = $wordright

逐个文件打开文件并逐行阅读大约需要42秒.然后我用Storable模块存储哈希值

store \%hash, $filename

再次加载数据

$hashref = retrieve $filename

将时间缩短到大约28秒.我使用快速SSD驱动器和快速CPU,并有足够的RAM来容纳所有数据(大约需要7 GB).

我正在寻找一种更快的方法将这些数据加载到RAM中(由于某些原因,我无法将其保留在那里).

您可以尝试使用Dan Bernstein的CDB文件格式使用绑定哈希,这将需要最少的代码更改.您可能需要安装 CDB_File.在我的笔记本电脑上,cdb文件打开得非常快,我每秒可以进行大约200-250k的查找.以下是创建/使用/基准测试cdb的示例脚本:

test_cdb.pl

#!/usr/bin/env perl

use warnings;
use strict;

use Benchmark qw(:all) ;
use CDB_File 'create';
use Time::HiRes qw( gettimeofday tv_interval );

scalar @ARGV or die "usage: $0 number_of_keys seconds_to_benchmark\n";
my ($size)    = $ARGV[0] || 1000;
my ($seconds) = $ARGV[1] || 10;

my $t0;
tic();

# Create CDB
my ($file, %data);

%data = map { $_ => 'something' } (1..$size);
print "Created $size element hash in memory\n";
toc();

$file = 'data.cdb';
create %data, $file, "$file.$$";
my $bytes = -s $file;
print "Created data.cdb [ $size keys and values, $bytes bytes]\n";
toc();

# Read from CDB
my $c = tie my %h, 'CDB_File', 'data.cdb' or die "tie failed: $!\n";
print "Opened data.cdb as a tied hash.\n";
toc();

timethese( -1 * $seconds, {
          'Pick Random Key'    => sub { int rand $size },
          'Fetch Random Value' => sub { $h{ int rand $size }; },
});

tic();
print "Fetching Every Value\n";
for (0..$size) {
    no warnings; # Useless use of hash element
    $h{ $_ };
}
toc();

sub tic {
    $t0 = [gettimeofday];    
}

sub toc {
    my $t1 = [gettimeofday];
    my $elapsed = tv_interval ( $t0, $t1);
    $t0 = $t1;
    print "==> took $elapsed seconds\n";
}

输出(100万键,10秒以上测试)

./test_cdb.pl 1000000 10

Created 1000000 element hash in memory
==> took 2.882813 seconds
Created data.cdb [ 1000000 keys and values, 38890944 bytes]
==> took 2.333624 seconds
Opened data.cdb as a tied hash.
==> took 0.00015 seconds
Benchmark: running Fetch Random Value, Pick Random Key for at least 10 CPU seconds...
Fetch Random Value: 10 wallclock secs (10.46 usr +  0.01 sys = 10.47 CPU) @ 236984.72/s (n=2481230)
Pick Random Key:  9 wallclock secs (10.11 usr +  0.02 sys = 10.13 CPU) @ 3117208.98/s (n=31577327)
Fetching Every Value
==> took 3.514183 seconds

输出(1000万键,经过10秒测试)

./test_cdb.pl 10000000 10

Created 10000000 element hash in memory
==> took 44.72331 seconds
Created data.cdb [ 10000000 keys and values, 398890945 bytes] 
==> took 25.729652 seconds
Opened data.cdb as a tied hash.
==> took 0.000222 seconds
Benchmark: running Fetch Random Value, Pick Random Key for at least 10 CPU seconds...
Fetch Random Value: 14 wallclock secs ( 9.65 usr +  0.35 sys = 10.00 CPU) @ 209811.20/s (n=2098112)
Pick Random Key: 12 wallclock secs (10.40 usr +  0.02 sys = 10.42 CPU) @ 2865335.22/s (n=29856793)
Fetching Every Value
==> took 38.274356 seconds
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