如何通过其中一个哈希值对哈希引用数组进行排序?

时间:2009-10-28 22:05:51

标签: perl sorting bugzilla

首先,请原谅我生锈的Perl。我正在尝试修改Bugzilla的“whine.pl”以生成按严重性排序的错误列表。

所以它给了我一个哈希引用数组。每个哈希都包含一系列有关特定错误(id,受让人,严重性等)的信息。我想按严重程度对数组进行排序。最好的方法是什么?

我想出了几个可能性。一种是创建五个数组(每个严重级别一个),然后遍历数组并将哈希引用推送到适当的严重性级别数组。在此之后,我可以重新组装它们并用已排序的数组替换原始数组。

我的朋友提出的另一种方法是将严重性级别(存储为散列中的文本)分配给某些nubmers,然后cmp它们。也许是这样的?

sub getVal {
    my $entry = $_[0];
    %lookup = ( "critical" => 0, ... );
    return $lookup(entry("bug_severity"));
}
@sorted = sort { getVal($a) <=> getVal($b) } @unsorted;

4 个答案:

答案 0 :(得分:7)

为了避免多次调用getVal,可以使用“decorate,sort,undecorate”。装饰正在获取您真正关心的信息:

my @decorated = map { [ $_, getVal($_) ] } @unsorted;

然后对装饰列表进行排序:

my @sortedDecorate = sort { $a->[1] <=> $b->[1] } @decorated;

然后获取原始信息(undecorate):

my @sorted = map { $_->[0] } @sortedDecorate;

或更多的Perl-ish方法:

@sorted = map { $_->[0] }
          sort { $a->[1] <=> $b->[1] }
          map { [ $_, getVal($_) ] } @unsorted;

答案 1 :(得分:4)

您可以使用Schwartzian Transform

my @sorted = map  { $_->[1] }
             sort { $a->[0] <=> $b->[0] }
             map  { [ $lookup{$_->{bug_severity}, $_ ] } 
             @unsorted;

说明:

map  { [ $lookup{$_->{bug_severity}, $_ ] } @unsorted;

将每个错误映射到数组引用,其第一个元素是查找表中的数字错误严重性。使用Schwartzian变换,您只需查看@unsorted 中每个错误的值一次。

然后,

sort { $a->[0] <=> $b->[0] }

按第一个元素对该数组进行排序。最后,

@sorted = map  { $_->[1] }

sort返回的数组中提取原始错误。

getval所做的只是哈希查找时,确实没有必要。

为了自动生成高效的分拣机,CPAN模块Sort::Maker非常出色:

use strict; use warnings;

use Sort::Maker;

my @bugs = (
    { name => 'bar', bug_severity => 'severe' },
    { name => 'baz', bug_severity => 'noncritical' },
    { name => 'foo', bug_severity => 'critical' },
);

my $sorter = make_sorter('ST',
    name      => 'severity_sorter',
    init_code => 'my %lookup = (
                     critical => 0,
                     severe => 1,
                     noncritical => -1 );',
    number    => [ code => '$lookup{$_->{bug_severity}}' ],
);

use Data::Dumper;
print Dumper $_ for severity_sorter( @bugs );

输出:

$VAR1 = {
          'name' => 'baz',
          'bug_severity' => 'noncritical'
        };
$VAR1 = {
          'name' => 'foo',
          'bug_severity' => 'critical'
        };
$VAR1 = {
          'name' => 'bar',
          'bug_severity' => 'severe'
        };

请注意,使用朴素方法时需要进行的查找次数取决于@unsorted中的元素数量。我们可以使用简单的程序来计算它们:

#!/usr/bin/perl

use strict;
use warnings;

my ($n_elements) = @ARGV;

my @keys = qw(a b c);
my %lookup = map { $keys[$_-1] => $_ } 1 .. @keys;

my @unsorted = map { $keys[rand 3] } 1 .. $n_elements;

my $n_lookups;

my @sorted = sort {
    $n_lookups += 2;
    $lookup{$a} <=> $lookup{$b}
} @unsorted;

print "It took $n_lookups lookups to sort $n_elements elements\n";

输出:

C:\Temp> tzt 10
It took 38 lookups to sort 10 elements

C:\Temp> tzt 100
It took 978 lookups to sort 100 elements

C:\Temp> tzt 1000
It took 10916 lookups to sort 1000 elements

C:\Temp> tzt 10000
It took 113000 lookups to sort 10000 elements

因此,需要更多信息来确定天真排序或使用Schwartzian变换是否是合适的解决方案。

这是一个简单的基准测试,似乎与@Ether的论点一致:

#!/usr/bin/perl

use strict;
use warnings;

use Benchmark qw( cmpthese );

my ($n_elements) = @ARGV;

my @keys = qw(foo bar baz);
my %lookup = map { $keys[$_] => $_ } 0 .. $#keys;

my @unsorted = map { {v => $keys[rand 3]} } 1 .. $n_elements;

cmpthese(-1, {
    naive => sub {
        my @sorted = sort {
            $lookup{$a->{v}} <=> $lookup{$b->{v}}
        } @unsorted;
    },
    schwartzian => sub {
        my @sorted = map  { $_->[1] }
                     sort { $a->[0] <=> $b->[0] }
                     map  { [$lookup{$_->{v}}, $_] }
                     @unsorted;
    }
});

输出:

C:\Temp> tzt 10
               Rate schwartzian       naive
schwartzian 18842/s          --        -29%
naive       26357/s         40%          --

C:\Temp> tzt 100
              Rate       naive schwartzian
naive       1365/s          --        -11%
schwartzian 1532/s         12%          --

C:\Temp> tzt 1000
             Rate       naive schwartzian
naive       121/s          --        -11%
schwartzian 135/s         12%          --

答案 2 :(得分:3)

我喜欢你提出的解决方案:

my %sevs = (critical => 0, high => 1, ...);
my @sorted = sort { $sevs{$a->{bug_severity}} <=> $sevs{$b->{bug_severity}} } @unsorted

答案 3 :(得分:0)

您可以使用查找表来确定bugzilla严重性的排序,如下所示(使用示例数据来说明):

use strict; use warnings;
use Data::Dumper;

my @bugInfo = (
                { id => 1,
                  assignee => 'Bob',
                  severity => 'HIGH'
                },
                { id => 2,
                  assignee => 'Anna',
                  severity => 'LOW'
                },
                { id => 3,
                  assignee => 'Carl',
                  severity => 'EXTREME'
                },
              );
my %severity_ordering = (
    EXTREME => 0,
    HIGH => 1,
    MEDIUM => 2,
    LOW => 3,
);
sub byseverity
{
    $severity_ordering{$a->{severity}} <=> $severity_ordering{$b->{severity}}
}

my @sortedBugs = sort byseverity @bugInfo;
print Dumper(\@sortedBugs);

的产率:

$VAR1 = [
          {
            'assignee' => 'Carl',
            'id' => 3,
            'severity' => 'EXTREME'
          },
          {
            'assignee' => 'Bob',
            'id' => 1,
            'severity' => 'HIGH'
          },
          {
            'assignee' => 'Anna',
            'id' => 2,
            'severity' => 'LOW'
          }
        ];
相关问题