PERLPERF(1) Perl Programmers Reference Guide PERLPERF(1)
NAME
perlperf - Perl Performance and Optimization Techniques
DESCRIPTION
This is an introduction to the use of performance and optimization techniques which can be used with
particular reference to perl programs. While many perl developers have come from other languages, and can use
their prior knowledge where appropriate, there are many other people who might benefit from a few perl
specific pointers. If you want the condensed version, perhaps the best advice comes from the renowned
Japanese Samurai, Miyamoto Musashi, who said:
"Do Not Engage in Useless Activity"
in 1645.
OVERVIEW
Perhaps the most common mistake programmers make is to attempt to optimize their code before a program
actually does anything useful - this is a bad idea. There's no point in having an extremely fast program that
doesn't work. The first job is to get a program to correctly do something useful, (not to mention ensuring
the test suite is fully functional), and only then to consider optimizing it. Having decided to optimize
existing working code, there are several simple but essential steps to consider which are intrinsic to any
optimization process.
ONE STEP SIDEWAYS
Firstly, you need to establish a baseline time for the existing code, which timing needs to be reliable and
repeatable. You'll probably want to use the "Benchmark" or "Devel::NYTProf" modules, or something similar,
for this step, or perhaps the Unix system "time" utility, whichever is appropriate. See the base of this
document for a longer list of benchmarking and profiling modules, and recommended further reading.
ONE STEP FORWARD
Next, having examined the program for hot spots, (places where the code seems to run slowly), change the code
with the intention of making it run faster. Using version control software, like "subversion", will ensure no
changes are irreversible. It's too easy to fiddle here and fiddle there - don't change too much at any one
time or you might not discover which piece of code really was the slow bit.
ANOTHER STEP SIDEWAYS
It's not enough to say: "that will make it run faster", you have to check it. Rerun the code under control of
the benchmarking or profiling modules, from the first step above, and check that the new code executed the
same task in less time. Save your work and repeat...
GENERAL GUIDELINES
The critical thing when considering performance is to remember there is no such thing as a "Golden Bullet",
which is why there are no rules, only guidelines.
It is clear that inline code is going to be faster than subroutine or method calls, because there is less
overhead, but this approach has the disadvantage of being less maintainable and comes at the cost of greater
memory usage - there is no such thing as a free lunch. If you are searching for an element in a list, it can
be more efficient to store the data in a hash structure, and then simply look to see whether the key is
defined, rather than to loop through the entire array using grep() for instance. substr() may be (a lot)
faster than grep() but not as flexible, so you have another trade-off to access. Your code may contain a line
which takes 0.01 of a second to execute which if you call it 1,000 times, quite likely in a program parsing
even medium sized files for instance, you already have a 10 second delay, in just one single code location,
and if you call that line 100,000 times, your entire program will slow down to an unbearable crawl.
Using a subroutine as part of your sort is a powerful way to get exactly what you want, but will usually be
slower than the built-in alphabetic "cmp" and numeric "<=>" sort operators. It is possible to make multiple
passes over your data, building indices to make the upcoming sort more efficient, and to use what is known as
when this might prove advantageous. Splitting up a large file by assigning multiple processes to parsing a
single file, using say "POE", "threads" or "fork" can also be a useful way of optimizing your usage of the
available "CPU" resources, though this technique is fraught with concurrency issues and demands high attention
to detail.
Every case has a specific application and one or more exceptions, and there is no replacement for running a
few tests and finding out which method works best for your particular environment, this is why writing optimal
code is not an exact science, and why we love using Perl so much - TMTOWTDI.
BENCHMARKS
Here are a few examples to demonstrate usage of Perl's benchmarking tools.
Assigning and Dereferencing Variables.
I'm sure most of us have seen code which looks like, (or worse than), this:
if ( $obj->{_ref}->{_myscore} >= $obj->{_ref}->{_yourscore} ) {
...
This sort of code can be a real eyesore to read, as well as being very sensitive to typos, and it's much
clearer to dereference the variable explicitly. We're side-stepping the issue of working with object-oriented
programming techniques to encapsulate variable access via methods, only accessible through an object. Here
we're just discussing the technical implementation of choice, and whether this has an effect on performance.
We can see whether this dereferencing operation, has any overhead by putting comparative code in a file and
running a "Benchmark" test.
# dereference
#!/usr/bin/perl
use strict;
use warnings;
use Benchmark;
my $ref = {
'ref' => {
_myscore => '100 + 1',
_yourscore => '102 - 1',
},
};
timethese(1000000, {
'direct' => sub {
my $x = $ref->{ref}->{_myscore} . $ref->{ref}->{_yourscore} ;
},
'dereference' => sub {
my $ref = $ref->{ref};
my $myscore = $ref->{_myscore};
my $yourscore = $ref->{_yourscore};
my $x = $myscore . $yourscore;
},
});
It's essential to run any timing measurements a sufficient number of times so the numbers settle on a
average of 628,930 times a second during our test, the direct approach managed to run an additional 204,403
times, unfortunately. Unfortunately, because there are many examples of code written using the multiple layer
direct variable access, and it's usually horrible. It is, however, minusculy faster. The question remains
whether the minute gain is actually worth the eyestrain, or the loss of maintainability.
Search and replace or tr
If we have a string which needs to be modified, while a regex will almost always be much more flexible, "tr",
an oft underused tool, can still be a useful. One scenario might be replace all vowels with another
character. The regex solution might look like this:
$str =~ s/[aeiou]/x/g
The "tr" alternative might look like this:
$str =~ tr/aeiou/xxxxx/
We can put that into a test file which we can run to check which approach is the fastest, using a global $STR
variable to assign to the "my $str" variable so as to avoid perl trying to optimize any of the work away by
noticing it's assigned only the once.
# regex-transliterate
#!/usr/bin/perl
use strict;
use warnings;
use Benchmark;
my $STR = "$$-this and that";
timethese( 1000000, {
'sr' => sub { my $str = $STR; $str =~ s/[aeiou]/x/g; return $str; },
'tr' => sub { my $str = $STR; $str =~ tr/aeiou/xxxxx/; return $str; },
});
Running the code gives us our results:
$> perl regex-transliterate
Benchmark: timing 1000000 iterations of sr, tr...
sr: 2 wallclock secs ( 1.19 usr + 0.00 sys = 1.19 CPU) @ 840336.13/s (n=1000000)
tr: 0 wallclock secs ( 0.49 usr + 0.00 sys = 0.49 CPU) @ 2040816.33/s (n=1000000)
The "tr" version is a clear winner. One solution is flexible, the other is fast - and it's appropriately the
programmer's choice which to use.
Check the "Benchmark" docs for further useful techniques.
PROFILING TOOLS
A slightly larger piece of code will provide something on which a profiler can produce more extensive
reporting statistics. This example uses the simplistic "wordmatch" program which parses a given input file
and spews out a short report on the contents.
filewords -f inputfilename [-d]
=head1 DESCRIPTION
This program parses the given filename, specified with C<-f>, and displays a
simple analysis of the words found therein. Use the C<-d> switch to enable
debugging messages.
=cut
use FileHandle;
use Getopt::Long;
my $debug = 0;
my $file = '';
my $result = GetOptions (
'debug' => \$debug,
'file=s' => \$file,
);
die("invalid args") unless $result;
unless ( -f $file ) {
die("Usage: $0 -f filename [-d]");
}
my $FH = FileHandle->new("< $file") or die("unable to open file($file): $!");
my $i_LINES = 0;
my $i_WORDS = 0;
my %count = ();
my @lines = <$FH>;
foreach my $line ( @lines ) {
$i_LINES++;
$line =~ s/\n//;
my @words = split(/ +/, $line);
my $i_words = scalar(@words);
$i_WORDS = $i_WORDS + $i_words;
debug("line: $i_LINES supplying $i_words words: @words");
my $i_word = 0;
foreach my $word ( @words ) {
$i_word++;
$count{$i_LINES}{spec} += matches($i_word, $word, '[^a-zA-Z0-9]');
$count{$i_LINES}{only} += matches($i_word, $word, '^[^a-zA-Z0-9]+$');
$count{$i_LINES}{cons} += matches($i_word, $word, '^[(?i:bcdfghjklmnpqrstvwxyz)]+$');
$count{$i_LINES}{vows} += matches($i_word, $word, '^[(?i:aeiou)]+$');
$count{$i_LINES}{caps} += matches($i_word, $word, '^[(A-Z)]+$');
}
}
print report( %count );
sub matches {
}
sub report {
my %report = @_;
my %rep;
foreach my $line ( keys %report ) {
foreach my $key ( keys %{ $report{$line} } ) {
$rep{$key} += $report{$line}{$key};
}
}
my $report = qq|
$0 report for $file:
lines in file: $i_LINES
words in file: $i_WORDS
words with special (non-word) characters: $i_spec
words with only special (non-word) characters: $i_only
words with only consonants: $i_cons
words with only capital letters: $i_caps
words with only vowels: $i_vows
|;
return $report;
}
sub debug {
my $message = shift;
if ( $debug ) {
print STDERR "DBG: $message\n";
}
}
exit 0;
Devel::DProf
This venerable module has been the de-facto standard for Perl code profiling for more than a decade, but has
been replaced by a number of other modules which have brought us back to the 21st century. Although you're
recommended to evaluate your tool from the several mentioned here and from the CPAN list at the base of this
document, (and currently Devel::NYTProf seems to be the weapon of choice - see below), we'll take a quick look
at the output from Devel::DProf first, to set a baseline for Perl profiling tools. Run the above program
under the control of "Devel::DProf" by using the "-d" switch on the command-line.
$> perl -d:DProf wordmatch -f perl5db.pl
<...multiple lines snipped...>
wordmatch report for perl5db.pl:
lines in file: 9428
words in file: 50243
words with special (non-word) characters: 20480
words with only special (non-word) characters: 7790
words with only consonants: 4801
Exclusive Times
%Time ExclSec CumulS #Calls sec/call Csec/c Name
102. 2.945 3.003 251215 0.0000 0.0000 main::matches
2.40 0.069 0.069 260643 0.0000 0.0000 main::debug
1.74 0.050 0.050 1 0.0500 0.0500 main::report
1.04 0.030 0.049 4 0.0075 0.0123 main::BEGIN
0.35 0.010 0.010 3 0.0033 0.0033 Exporter::as_heavy
0.35 0.010 0.010 7 0.0014 0.0014 IO::File::BEGIN
0.00 - -0.000 1 - - Getopt::Long::FindOption
0.00 - -0.000 1 - - Symbol::BEGIN
0.00 - -0.000 1 - - Fcntl::BEGIN
0.00 - -0.000 1 - - Fcntl::bootstrap
0.00 - -0.000 1 - - warnings::BEGIN
0.00 - -0.000 1 - - IO::bootstrap
0.00 - -0.000 1 - - Getopt::Long::ConfigDefaults
0.00 - -0.000 1 - - Getopt::Long::Configure
0.00 - -0.000 1 - - Symbol::gensym
"dprofpp" will produce some quite detailed reporting on the activity of the "wordmatch" program. The
wallclock, user and system, times are at the top of the analysis, and after this are the main columns defining
which define the report. Check the "dprofpp" docs for details of the many options it supports.
See also "Apache::DProf" which hooks "Devel::DProf" into "mod_perl".
Devel::Profiler
Let's take a look at the same program using a different profiler: "Devel::Profiler", a drop-in Perl-only
replacement for "Devel::DProf". The usage is very slightly different in that instead of using the special
"-d:" flag, you pull "Devel::Profiler" in directly as a module using "-M".
$> perl -MDevel::Profiler wordmatch -f perl5db.pl
<...multiple lines snipped...>
wordmatch report for perl5db.pl:
lines in file: 9428
words in file: 50243
words with special (non-word) characters: 20480
words with only special (non-word) characters: 7790
words with only consonants: 4801
words with only capital letters: 1316
words with only vowels: 1701
"Devel::Profiler" generates a tmon.out file which is compatible with the "dprofpp" program, thus saving the
construction of a dedicated statistics reader program. "dprofpp" usage is therefore identical to the above
example.
$> dprofpp
Total Elapsed Time = 20.984 Seconds
User+System Time = 19.981 Seconds
Exclusive Times
%Time ExclSec CumulS #Calls sec/call Csec/c Name
49.0 9.792 14.509 251215 0.0000 0.0001 main::matches
24.4 4.887 4.887 260643 0.0000 0.0000 main::debug
listings feel more accurate somehow than the ones we had earlier from "Devel::DProf". The 102% figure has
disappeared, for example. This is where we have to use the tools at our disposal, and recognise their pros
and cons, before using them. Interestingly, the numbers of calls for each subroutine are identical in the two
reports, it's the percentages which differ. As the author of "Devel::Proviler" writes:
...running HTML::Template's test suite under Devel::DProf shows output()
taking NO time but Devel::Profiler shows around 10% of the time is in output().
I don't know which to trust but my gut tells me something is wrong with
Devel::DProf. HTML::Template::output() is a big routine that's called for
every test. Either way, something needs fixing.
YMMV.
See also "Devel::Apache::Profiler" which hooks "Devel::Profiler" into "mod_perl".
Devel::SmallProf
The "Devel::SmallProf" profiler examines the runtime of your Perl program and produces a line-by-line listing
to show how many times each line was called, and how long each line took to execute. It is called by
supplying the familiar "-d" flag to Perl at runtime.
$> perl -d:SmallProf wordmatch -f perl5db.pl
<...multiple lines snipped...>
wordmatch report for perl5db.pl:
lines in file: 9428
words in file: 50243
words with special (non-word) characters: 20480
words with only special (non-word) characters: 7790
words with only consonants: 4801
words with only capital letters: 1316
words with only vowels: 1701
"Devel::SmallProf" writes it's output into a file called smallprof.out, by default. The format of the file
looks like this:
<num> <time> <ctime> <line>:<text>
When the program has terminated, the output may be examined and sorted using any standard text filtering
utilities. Something like the following may be sufficient:
$> cat smallprof.out | grep \d*: | sort -k3 | tac | head -n20
251215 1.65674 7.68000 75: if ( $word =~ /($regex)/ ) {
251215 0.03264 4.40000 79: debug("word: $i_wd ".($has ? 'matches' :
251215 0.02693 4.10000 81: return $has;
260643 0.02841 4.07000 128: if ( $debug ) {
260643 0.02601 4.04000 126: my $message = shift;
251215 0.02641 3.91000 73: my $has = 0;
251215 0.03311 3.71000 70: my $i_wd = shift;
251215 0.02699 3.69000 72: my $regex = shift;
251215 0.02766 3.68000 71: my $word = shift;
50243 0.59726 1.00000 59: $count{$i_LINES}{cons} =
50243 0.48175 0.92000 61: $count{$i_LINES}{spec} =
Remember that these tools are supposed to be used together, there is no single best way to profile your code,
you need to use the best tools for the job.
See also "Apache::SmallProf" which hooks "Devel::SmallProf" into "mod_perl".
Devel::FastProf
"Devel::FastProf" is another Perl line profiler. This was written with a view to getting a faster line
profiler, than is possible with for example "Devel::SmallProf", because it's written in "C". To use
"Devel::FastProf", supply the "-d" argument to Perl:
$> perl -d:FastProf wordmatch -f perl5db.pl
<...multiple lines snipped...>
wordmatch report for perl5db.pl:
lines in file: 9428
words in file: 50243
words with special (non-word) characters: 20480
words with only special (non-word) characters: 7790
words with only consonants: 4801
words with only capital letters: 1316
words with only vowels: 1701
"Devel::FastProf" writes statistics to the file fastprof.out in the current directory. The output file, which
can be specified, can be interpreted by using the "fprofpp" command-line program.
$> fprofpp | head -n20
# fprofpp output format is:
# filename:line time count: source
wordmatch:75 3.93338 251215: if ( $word =~ /($regex)/ ) {
wordmatch:79 1.77774 251215: debug("word: $i_wd ".($has ? 'matches' : 'does not match')." chars: /$regex/");
wordmatch:81 1.47604 251215: return $has;
wordmatch:126 1.43441 260643: my $message = shift;
wordmatch:128 1.42156 260643: if ( $debug ) {
wordmatch:70 1.36824 251215: my $i_wd = shift;
wordmatch:71 1.36739 251215: my $word = shift;
wordmatch:72 1.35939 251215: my $regex = shift;
Straightaway we can see that the number of times each line has been called is identical to the
"Devel::SmallProf" output, and the sequence is only very slightly different based on the ordering of the
amount of time each line took to execute, "if ( $debug ) { " and "my $message = shift;", for example. The
differences in the actual times recorded might be in the algorithm used internally, or it could be due to
system resource limitations or contention.
See also the DBIx::Profile which will profile database queries running under the "DBIx::*" namespace.
Devel::NYTProf
"Devel::NYTProf" is the next generation of Perl code profiler, fixing many shortcomings in other tools and
implementing many cool features. First of all it can be used as either a line profiler, a block or a
subroutine profiler, all at once. It can also use sub-microsecond (100ns) resolution on systems which provide
"clock_gettime()". It can be started and stopped even by the program being profiled. It's a one-line entry
to profile "mod_perl" applications. It's written in "c" and is probably the fastest profiler available for
Perl. The list of coolness just goes on. Enough of that, let's see how to it works - just use the familiar
"NYTProf" will generate a report database into the file nytprof.out by default. Human readable reports can be
generated from here by using the supplied "nytprofhtml" (HTML output) and "nytprofcsv" (CSV output) programs.
We've used the Unix system "html2text" utility to convert the nytprof/index.html file for convenience here.
$> html2text nytprof/index.html
Performance Profile Index
For wordmatch
Run on Fri Sep 26 13:46:39 2008
Reported on Fri Sep 26 13:47:23 2008
Top 15 Subroutines -- ordered by exclusive time
|Calls |P |F |Inclusive|Exclusive|Subroutine |
| | | |Time |Time | |
|251215|5 |1 |13.09263 |10.47692 |main:: |matches |
|260642|2 |1 |2.71199 |2.71199 |main:: |debug |
|1 |1 |1 |0.21404 |0.21404 |main:: |report |
|2 |2 |2 |0.00511 |0.00511 |XSLoader:: |load (xsub) |
|14 |14|7 |0.00304 |0.00298 |Exporter:: |import |
|3 |1 |1 |0.00265 |0.00254 |Exporter:: |as_heavy |
|10 |10|4 |0.00140 |0.00140 |vars:: |import |
|13 |13|1 |0.00129 |0.00109 |constant:: |import |
|1 |1 |1 |0.00360 |0.00096 |FileHandle:: |import |
|3 |3 |3 |0.00086 |0.00074 |warnings::register::|import |
|9 |3 |1 |0.00036 |0.00036 |strict:: |bits |
|13 |13|13|0.00032 |0.00029 |strict:: |import |
|2 |2 |2 |0.00020 |0.00020 |warnings:: |import |
|2 |1 |1 |0.00020 |0.00020 |Getopt::Long:: |ParseOptionSpec|
|7 |7 |6 |0.00043 |0.00020 |strict:: |unimport |
For more information see the full list of 189 subroutines.
The first part of the report already shows the critical information regarding which subroutines are using the
most time. The next gives some statistics about the source files profiled.
Source Code Files -- ordered by exclusive time then name
|Stmts |Exclusive|Avg. |Reports |Source File |
| |Time | | | |
|2699761|15.66654 |6e-06 |line . block . sub|wordmatch |
|35 |0.02187 |0.00062|line . block . sub|IO/Handle.pm |
|274 |0.01525 |0.00006|line . block . sub|Getopt/Long.pm |
|20 |0.00585 |0.00029|line . block . sub|Fcntl.pm |
|128 |0.00340 |0.00003|line . block . sub|Exporter/Heavy.pm |
|42 |0.00332 |0.00008|line . block . sub|IO/File.pm |
|261 |0.00308 |0.00001|line . block . sub|Exporter.pm |
|323 |0.00248 |8e-06 |line . block . sub|constant.pm |
|12 |0.00246 |0.00021|line . block . sub|File/Spec/Unix.pm |
|191 |0.00240 |0.00001|line . block . sub|vars.pm |
|77 |0.00201 |0.00003|line . block . sub|FileHandle.pm |
|12 |0.00198 |0.00016|line . block . sub|Carp.pm |
|14 |0.00175 |0.00013|line . block . sub|Symbol.pm |
|15 |0.00130 |0.00009|line . block . sub|IO.pm |
|22 |0.00120 |0.00005|line . block . sub|IO/Seekable.pm |
Adam Kaplan.
At this point, if you're using the html report, you can click through the various links to bore down into each
subroutine and each line of code. Because we're using the text reporting here, and there's a whole directory
full of reports built for each source file, we'll just display a part of the corresponding wordmatch-line.html
file, sufficient to give an idea of the sort of output you can expect from this cool tool.
$> html2text nytprof/wordmatch-line.html
Performance Profile -- -block view-.-line view-.-sub view-
For wordmatch
Run on Fri Sep 26 13:46:39 2008
Reported on Fri Sep 26 13:47:22 2008
File wordmatch
Subroutines -- ordered by exclusive time
|Calls |P|F|Inclusive|Exclusive|Subroutine |
| | | |Time |Time | |
|251215|5|1|13.09263 |10.47692 |main::|matches|
|260642|2|1|2.71199 |2.71199 |main::|debug |
|1 |1|1|0.21404 |0.21404 |main::|report |
|0 |0|0|0 |0 |main::|BEGIN |
|Line|Stmts.|Exclusive|Avg. |Code |
| | |Time | | |
|1 | | | |#!/usr/bin/perl |
|2 | | | | |
| | | | |use strict; |
|3 |3 |0.00086 |0.00029|# spent 0.00003s making 1 calls to strict:: |
| | | | |import |
| | | | |use warnings; |
|4 |3 |0.01563 |0.00521|# spent 0.00012s making 1 calls to warnings:: |
| | | | |import |
|5 | | | | |
|6 | | | |=head1 NAME |
|7 | | | | |
|8 | | | |filewords - word analysis of input file |
<...snip...>
|62 |1 |0.00445 |0.00445|print report( %count ); |
| | | | |# spent 0.21404s making 1 calls to main::report|
|63 | | | | |
| | | | |# spent 23.56955s (10.47692+2.61571) within |
| | | | |main::matches which was called 251215 times, |
| | | | |avg 0.00005s/call: # 50243 times |
| | | | |(2.12134+0.51939s) at line 57 of wordmatch, avg|
| | | | |0.00005s/call # 50243 times (2.17735+0.54550s) |
|64 | | | |at line 56 of wordmatch, avg 0.00005s/call # |
| | | | |50243 times (2.10992+0.51797s) at line 58 of |
| | | | |wordmatch, avg 0.00005s/call # 50243 times |
| | | | |(2.12696+0.51598s) at line 55 of wordmatch, avg|
| | | | |0.00005s/call # 50243 times (1.94134+0.51687s) |
| | | | |at line 54 of wordmatch, avg 0.00005s/call |
|106 |260642|1.09917 |4e-06 |if ( $debug ) { |
|107 | | | |print STDERR "DBG: $message\n"; |
|108 | | | |} |
|109 | | | |} |
|110 | | | | |
|111 |1 |0.01501 |0.01501|exit 0; |
|112 | | | | |
Oodles of very useful information in there - this seems to be the way forward.
See also "Devel::NYTProf::Apache" which hooks "Devel::NYTProf" into "mod_perl".
SORTING
Perl modules are not the only tools a performance analyst has at their disposal, system tools like "time"
should not be overlooked as the next example shows, where we take a quick look at sorting. Many books, theses
and articles, have been written about efficient sorting algorithms, and this is not the place to repeat such
work, there's several good sorting modules which deserve taking a look at too: "Sort::Maker", "Sort::Key"
spring to mind. However, it's still possible to make some observations on certain Perl specific
interpretations on issues relating to sorting data sets and give an example or two with regard to how sorting
large data volumes can effect performance. Firstly, an often overlooked point when sorting large amounts of
data, one can attempt to reduce the data set to be dealt with and in many cases "grep()" can be quite useful
as a simple filter:
@data = sort grep { /$filter/ } @incoming
A command such as this can vastly reduce the volume of material to actually sort through in the first place,
and should not be too lightly disregarded purely on the basis of its simplicity. The "KISS" principle is too
often overlooked - the next example uses the simple system "time" utility to demonstrate. Let's take a look
at an actual example of sorting the contents of a large file, an apache logfile would do. This one has over a
quarter of a million lines, is 50M in size, and a snippet of it looks like this:
# logfile
188.209-65-87.adsl-dyn.isp.belgacom.be - - [08/Feb/2007:12:57:16 +0000] "GET /favicon.ico HTTP/1.1" 404 209 "-" "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)"
188.209-65-87.adsl-dyn.isp.belgacom.be - - [08/Feb/2007:12:57:16 +0000] "GET /favicon.ico HTTP/1.1" 404 209 "-" "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)"
151.56.71.198 - - [08/Feb/2007:12:57:41 +0000] "GET /suse-on-vaio.html HTTP/1.1" 200 2858 "http://www.linux-on-laptops.com/sony.html" "Mozilla/5.0 (Windows; U; Windows NT 5.2; en-US; rv:1.8.1.1) Gecko/20061204 Firefox/2.0.0.1"
151.56.71.198 - - [08/Feb/2007:12:57:42 +0000] "GET /data/css HTTP/1.1" 404 206 "http://www.rfi.net/suse-on-vaio.html" "Mozilla/5.0 (Windows; U; Windows NT 5.2; en-US; rv:1.8.1.1) Gecko/20061204 Firefox/2.0.0.1"
151.56.71.198 - - [08/Feb/2007:12:57:43 +0000] "GET /favicon.ico HTTP/1.1" 404 209 "-" "Mozilla/5.0 (Windows; U; Windows NT 5.2; en-US; rv:1.8.1.1) Gecko/20061204 Firefox/2.0.0.1"
217.113.68.60 - - [08/Feb/2007:13:02:15 +0000] "GET / HTTP/1.1" 304 - "-" "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)"
217.113.68.60 - - [08/Feb/2007:13:02:16 +0000] "GET /data/css HTTP/1.1" 404 206 "http://www.rfi.net/" "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)"
debora.to.isac.cnr.it - - [08/Feb/2007:13:03:58 +0000] "GET /suse-on-vaio.html HTTP/1.1" 200 2858 "http://www.linux-on-laptops.com/sony.html" "Mozilla/5.0 (compatible; Konqueror/3.4; Linux) KHTML/3.4.0 (like Gecko)"
debora.to.isac.cnr.it - - [08/Feb/2007:13:03:58 +0000] "GET /data/css HTTP/1.1" 404 206 "http://www.rfi.net/suse-on-vaio.html" "Mozilla/5.0 (compatible; Konqueror/3.4; Linux) KHTML/3.4.0 (like Gecko)"
debora.to.isac.cnr.it - - [08/Feb/2007:13:03:58 +0000] "GET /favicon.ico HTTP/1.1" 404 209 "-" "Mozilla/5.0 (compatible; Konqueror/3.4; Linux) KHTML/3.4.0 (like Gecko)"
195.24.196.99 - - [08/Feb/2007:13:26:48 +0000] "GET / HTTP/1.0" 200 3309 "-" "Mozilla/5.0 (Windows; U; Windows NT 5.1; fr; rv:1.8.0.9) Gecko/20061206 Firefox/1.5.0.9"
195.24.196.99 - - [08/Feb/2007:13:26:58 +0000] "GET /data/css HTTP/1.0" 404 206 "http://www.rfi.net/" "Mozilla/5.0 (Windows; U; Windows NT 5.1; fr; rv:1.8.0.9) Gecko/20061206 Firefox/1.5.0.9"
195.24.196.99 - - [08/Feb/2007:13:26:59 +0000] "GET /favicon.ico HTTP/1.0" 404 209 "-" "Mozilla/5.0 (Windows; U; Windows NT 5.1; fr; rv:1.8.0.9) Gecko/20061206 Firefox/1.5.0.9"
crawl1.cosmixcorp.com - - [08/Feb/2007:13:27:57 +0000] "GET /robots.txt HTTP/1.0" 200 179 "-" "voyager/1.0"
crawl1.cosmixcorp.com - - [08/Feb/2007:13:28:25 +0000] "GET /links.html HTTP/1.0" 200 3413 "-" "voyager/1.0"
fhm226.internetdsl.tpnet.pl - - [08/Feb/2007:13:37:32 +0000] "GET /suse-on-vaio.html HTTP/1.1" 200 2858 "http://www.linux-on-laptops.com/sony.html" "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)"
fhm226.internetdsl.tpnet.pl - - [08/Feb/2007:13:37:34 +0000] "GET /data/css HTTP/1.1" 404 206 "http://www.rfi.net/suse-on-vaio.html" "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)"
80.247.140.134 - - [08/Feb/2007:13:57:35 +0000] "GET / HTTP/1.1" 200 3309 "-" "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; .NET CLR 1.1.4322)"
80.247.140.134 - - [08/Feb/2007:13:57:37 +0000] "GET /data/css HTTP/1.1" 404 206 "http://www.rfi.net" "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; .NET CLR 1.1.4322)"
pop.compuscan.co.za - - [08/Feb/2007:14:10:43 +0000] "GET / HTTP/1.1" 200 3309 "-" "www.clamav.net"
livebot-207-46-98-57.search.live.com - - [08/Feb/2007:14:12:04 +0000] "GET /robots.txt HTTP/1.0" 200 179 "-" "msnbot/1.0 (+http://search.msn.com/msnbot.htm)"
use strict;
use warnings;
my @data;
LINE:
while ( <> ) {
my $line = $_;
if (
$line =~ m/^(
([\w\.\-]+) # client
\s*-\s*-\s*\[
([^]]+) # date
\]\s*"\w+\s*
(\S+) # query
[^"]+"\s*
(\d+) # status
\s+\S+\s+"[^"]*"\s+"
([^"]*) # browser
"
.*
)$/x
) {
my @chunks = split(/ +/, $line);
my $ip = $1;
my $date = $2;
my $query = $3;
my $status = $4;
my $browser = $5;
push(@data, [$ip, $date, $query, $status, $browser, $line]);
}
}
my @sorted = sort {
$a->[3] cmp $b->[3]
||
$a->[2] cmp $b->[2]
||
$a->[0] cmp $b->[0]
||
$a->[1] cmp $b->[1]
||
$a->[4] cmp $b->[4]
} @data;
foreach my $data ( @sorted ) {
print $data->[5];
}
exit 0;
When running this program, redirect "STDOUT" so it is possible to check the output is correct from following
test runs and use the system "time" utility to check the overall runtime.
includes both user and system times, and time spent waiting for other users and processes on the system.
Inevitably, this is the most approximate of the measurements given.
User CPU Time
The user time is the amount of time the entire process spent on behalf of the user on this system
executing this program.
System CPU Time
The system time is the amount of time the kernel itself spent executing routines, or system calls, on
behalf of this process user.
Running this same process as a "Schwarzian Transform" it is possible to eliminate the input and output arrays
for storing all the data, and work on the input directly as it arrives too. Otherwise, the code looks fairly
similar:
# sort-apache-log-schwarzian
#!/usr/bin/perl -n
use strict;
use warnings;
print
map $_->[0] =>
sort {
$a->[4] cmp $b->[4]
||
$a->[3] cmp $b->[3]
||
$a->[1] cmp $b->[1]
||
$a->[2] cmp $b->[2]
||
$a->[5] cmp $b->[5]
}
map [ $_, m/^(
([\w\.\-]+) # client
\s*-\s*-\s*\[
([^]]+) # date
\]\s*"\w+\s*
(\S+) # query
[^"]+"\s*
(\d+) # status
\s+\S+\s+"[^"]*"\s+"
([^"]*) # browser
"
.*
)$/xo ]
=> <>;
exit 0;
$> cksum out-sort out-schwarz
3044173777 52029194 out-sort
3044173777 52029194 out-schwarz
BTW. Beware too of pressure from managers who see you speed a program up by 50% of the runtime once, only to
get a request one month later to do the same again (true story) - you'll just have to point out your only
human, even if you are a Perl programmer, and you'll see what you can do...
LOGGING
An essential part of any good development process is appropriate error handling with appropriately informative
messages, however there exists a school of thought which suggests that log files should be chatty, as if the
chain of unbroken output somehow ensures the survival of the program. If speed is in any way an issue, this
approach is wrong.
A common sight is code which looks something like this:
logger->debug( "A logging message via process-id: $$ INC: " . Dumper(\%INC) )
The problem is that this code will always be parsed and executed, even when the debug level set in the logging
configuration file is zero. Once the debug() subroutine has been entered, and the internal $debug variable
confirmed to be zero, for example, the message which has been sent in will be discarded and the program will
continue. In the example given though, the \%INC hash will already have been dumped, and the message string
constructed, all of which work could be bypassed by a debug variable at the statement level, like this:
logger->debug( "A logging message via process-id: $$ INC: " . Dumper(\%INC) ) if $DEBUG;
This effect can be demonstrated by setting up a test script with both forms, including a "debug()" subroutine
to emulate typical "logger()" functionality.
# ifdebug
#!/usr/bin/perl
use strict;
use warnings;
use Benchmark;
use Data::Dumper;
my $DEBUG = 0;
sub debug {
my $msg = shift;
if ( $DEBUG ) {
print "DEBUG: $msg\n";
}
};
timethese(100000, {
'debug' => sub {
debug( "A $0 logging message via process-id: $$" . Dumper(\%INC) )
},
'ifdebug' => sub {
In the one case the code, which does exactly the same thing as far as outputting any debugging information is
concerned, in other words nothing, takes 14 seconds, and in the other case the code takes one hundredth of a
second. Looks fairly definitive. Use a $DEBUG variable BEFORE you call the subroutine, rather than relying
on the smart functionality inside it.
Logging if DEBUG (constant)
It's possible to take the previous idea a little further, by using a compile time "DEBUG" constant.
# ifdebug-constant
#!/usr/bin/perl
use strict;
use warnings;
use Benchmark;
use Data::Dumper;
use constant
DEBUG => 0
;
sub debug {
if ( DEBUG ) {
my $msg = shift;
print "DEBUG: $msg\n";
}
};
timethese(100000, {
'debug' => sub {
debug( "A $0 logging message via process-id: $$" . Dumper(\%INC) )
},
'constant' => sub {
debug( "A $0 logging message via process-id: $$" . Dumper(\%INC) ) if DEBUG
},
});
Running this program produces the following output:
$> perl ifdebug-constant
Benchmark: timing 100000 iterations of constant, sub...
constant: 0 wallclock secs (-0.00 usr + 0.00 sys = -0.00 CPU) @ -7205759403792793600000.00/s (n=100000)
(warning: too few iterations for a reliable count)
sub: 14 wallclock secs (13.09 usr + 0.00 sys = 13.09 CPU) @ 7639.42/s (n=100000)
The "DEBUG" constant wipes the floor with even the $debug variable, clocking in at minus zero seconds, and
generates a "warning: too few iterations for a reliable count" message into the bargain. To see what is
really going on, and why we had too few iterations when we thought we asked for 100000, we can use the very
useful "B::Deparse" to inspect the new code:
$> perl -MO=Deparse ifdebug-constant
use Benchmark;
use Data::Dumper;
0;
}
});
ifdebug-constant syntax OK
The output shows the constant() subroutine we're testing being replaced with the value of the "DEBUG"
constant: zero. The line to be tested has been completely optimized away, and you can't get much more
efficient than that.
POSTSCRIPT
This document has provided several way to go about identifying hot-spots, and checking whether any
modifications have improved the runtime of the code.
As a final thought, remember that it's not (at the time of writing) possible to produce a useful program which
will run in zero or negative time and this basic principle can be written as: useful programs are slow by
their very definition. It is of course possible to write a nearly instantaneous program, but it's not going
to do very much, here's a very efficient one:
$> perl -e 0
Optimizing that any further is a job for "p5p".
SEE ALSO
Further reading can be found using the modules and links below.
PERLDOCS
For example: "perldoc -f sort".
perlfaq4.
perlfork, perlfunc, perlretut, perlthrtut.
threads.
MAN PAGES
"time".
MODULES
It's not possible to individually showcase all the performance related code for Perl here, naturally, but
here's a short list of modules from the CPAN which deserve further attention.
Apache::DProf
Apache::SmallProf
Benchmark
DBIx::Profile
Devel::AutoProfiler
Devel::DProf
Devel::DProfLB
Devel::FastProf
Devel::GraphVizProf
Devel::NYTProf
Devel::NYTProf::Apache
Devel::Profiler
Devel::Profile
http://www-128.ibm.com/developerworks/library/l-optperl.html
http://perlbuzz.com/2007/11/bind-output-variables-in-dbi-for-speed-and-safety.html
http://en.wikipedia.org/wiki/Performance_analysis
http://apache.perl.org/docs/1.0/guide/performance.html
http://perlgolf.sourceforge.net/
http://www.sysarch.com/Perl/sort_paper.html
AUTHOR
Richard Foley <[email protected]> Copyright (c) 2008
perl v5.16.3 2013-03-04 PERLPERF(1)
Back to main site | Back to man page index