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authorRafael Garcia-Suarez <rgarciasuarez@gmail.com>2008-12-21 10:22:27 +0100
committerRafael Garcia-Suarez <rgarciasuarez@gmail.com>2008-12-21 10:22:27 +0100
commitda09661133f307d85bb4af54945611a44b1d907f (patch)
tree9570843da91ce8c2cbe55b8053efd4a4cdd9ca66 /pod/perlperf.pod
parentde8ca8af19546d4922bab4537a72c9b2b3354009 (diff)
downloadperl-da09661133f307d85bb4af54945611a44b1d907f.tar.gz
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+=head1 NAME
+
+perlperf - Perl Performance and Optimization Techniques
+
+=head1 DESCRIPTION
+
+This is an introduction to the use of performance and optimization techniques
+which can be used with particular reference to perl progams. 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.
+
+=head1 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 I<correctly> do something B<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.
+
+=head2 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
+C<Benchmark> or C<Devel::DProf> modules, or something similar, for this step,
+or perhaps the unix system C<time> utility, whichever is appropriate. See the
+base of this document for a longer list of benchmarking and profiling modules,
+and recommended further reading.
+
+=head2 ONE STEP FORWARD
+
+Next, having examined the program for I<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 C<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 B<really> was the slow bit.
+
+=head2 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 B<same task> in
+I<less time>. Save your work and repeat...
+
+=head1 GENERAL GUIDELINES
+
+The critical thing when considering performance is to remember there is no such
+thing as a C<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 I<alphabetic> C<cmp> and
+I<numeric> C<E<lt>=E<gt>> 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 the C<OM> (Orcish Maneuver) to cache the
+sort keys in advance. The cache lookup, while a good idea, can itself be a
+source of slowdown by enforcing a double pass over the data - once to setup the
+cache, and once to sort the data. Using C<pack()> to extract the required sort
+key into a consistent string can be an efficient way to build a single string
+to compare, instead of using multiple sort keys, which makes it possible to use
+the standard, written in C<c> and fast, perl C<sort()> function on the output,
+and is the basis of the C<GRT> (Guttman Rossler Transform). Some string
+combinations can slow the C<GRT> down, by just being too plain complex for it's
+own good.
+
+For applications using database backends, the standard C<DBIx> namespace has
+tries to help with keeping things nippy, not least because it tries to I<not>
+query the database until the latest possible moment, but always read the docs
+which come with your choice of libraries. Among the many issues facing
+developers dealing with databases should remain aware of is to always use
+C<SQL> placeholders and to consider pre-fetching data sets when this might
+prove advantageous. Splitting up a large file by assigning multiple processes
+to parsing a single file, using say C<POE>, C<threads> or C<fork> can also be a
+useful way of optimizing your usage of the available C<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.
+
+=head1 BENCHMARKS
+
+Here are a few examples to demonstrate usage of Perl's benchmarking tools.
+
+=head2 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 C<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 numerical average, otherwise each run will naturally
+fluctuate due to variations in the environment, to reduce the effect of
+contention for C<CPU> resources and network bandwidth for instance. Running
+the above code for one million iterations, we can take a look at the report
+output by the C<Benchmark> module, to see which approach is the most effective.
+
+ $> perl dereference
+
+ Benchmark: timing 1000000 iterations of dereference, direct...
+ dereference: 2 wallclock secs ( 1.59 usr + 0.00 sys = 1.59 CPU) @ 628930.82/s (n=1000000)
+ direct: 1 wallclock secs ( 1.20 usr + 0.00 sys = 1.20 CPU) @ 833333.33/s (n=1000000)
+
+The difference is clear to see and the dereferencing approach is slower. While
+it managed to execute an 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, miniscully faster. The question remains whether the minute gain is
+actually worth the eyestrain, or the loss of maintainability.
+
+=head2 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, C<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 C<tr> alternative might look like this:
+
+ $str =~ tr/aeiou/xxxxx/
+
+We can put that into a test file which we can run to check which approach is
+the fastest, using a global C<$STR> variable to assign to the C<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 C<tr> version is a clear winner. One solution is flexible, the other is
+fast - and it's appropriately the programmers choice which to use in the
+circumstances.
+
+Check the C<Benchmark> docs for further useful techniques.
+
+=head1 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
+C<wordmatch> program which parses a given input file and spews out a short
+report on the contents.
+
+# wordmatch
+
+ #!/usr/bin/perl
+
+ use strict;
+ use warnings;
+
+ =head1 NAME
+
+ filewords - word analysis of input file
+
+ =head1 SYNOPSIS
+
+ 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 {
+ my $i_wd = shift;
+ my $word = shift;
+ my $regex = shift;
+ my $has = 0;
+
+ if ( $word =~ /($regex)/ ) {
+ $has++ if $1;
+ }
+
+ debug("word: $i_wd ".($has ? 'matches' : 'does not match')." chars: /$regex/");
+
+ return $has;
+ }
+
+ 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;
+
+=head2 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 L<Devel::NYTProf> seems to be the
+weapon of choice - see below), we'll take a quick look at the output from
+L<Devel::DProf> first, to set a baseline for Perl profiling tools. Run the
+above program under the control of C<Devel::DProf> by using the C<-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
+ words with only capital letters: 1316
+ words with only vowels: 1701
+
+C<Devel::DProf> produces a special file, called F<tmon.out> by default, and
+this file is read by the C<dprofpp> program, which is already installed as part
+of the C<Devel::DProf> distribution. If you call C<dprofpp> with no options,
+it will read the F<tmon.out> file in the current directory and produce a human
+readable statistics report of the run of your program. Note that this may take
+a little time.
+
+ $> dprofpp
+
+ Total Elapsed Time = 2.951677 Seconds
+ User+System Time = 2.871677 Seconds
+ 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
+
+C<dprofpp> will produce some quite detailed reporting on the activity of the
+C<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 C<dprofpp> docs for details of the many options it supports.
+
+See also C<Apache::DProf> which hooks C<Devel::DProf> into C<mod_perl>.
+
+=head2 Devel::Profiler
+
+Let's take a look at the same program using a different profiler:
+C<Devel::Profiler>, a drop-in Perl-only replacement for C<Devel::DProf>. The
+usage is very slightly different in that instead of using the special C<-d:>
+flag, you pull C<Devel::Profiler> in directly as a module using C<-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
+
+
+C<Devel::Profiler> generates a tmon.out file which is compatible with the
+C<dprofpp> program, thus saving the construction of a dedicated statistics
+reader program. C<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
+ 0.25 0.049 0.049 1 0.0490 0.0490 main::report
+ 0.00 0.000 0.000 1 0.0000 0.0000 Getopt::Long::GetOptions
+ 0.00 0.000 0.000 2 0.0000 0.0000 Getopt::Long::ParseOptionSpec
+ 0.00 0.000 0.000 1 0.0000 0.0000 Getopt::Long::FindOption
+ 0.00 0.000 0.000 1 0.0000 0.0000 IO::File::new
+ 0.00 0.000 0.000 1 0.0000 0.0000 IO::Handle::new
+ 0.00 0.000 0.000 1 0.0000 0.0000 Symbol::gensym
+ 0.00 0.000 0.000 1 0.0000 0.0000 IO::File::open
+
+Interestingly we get slightly different results, which is mostly because the
+algorithm which generates the report is different, even though the output file
+format was allegedly identical. The elapsed, user and system times are clearly
+showing the time it took for C<Devel::Profiler> to execute it's own run, but
+the column listings feel more accurate somehow than the ones we had earlier
+from C<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 C<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 C<Devel::Apache::Profiler> which hooks C<Devel::Profiler> into C<mod_perl>.
+
+=head2 Devel::SmallProf
+
+The C<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
+C<-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
+
+C<Devel::SmallProf> writes it's output into a file called F<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} =
+ 50243 0.00644 0.89000 56: my $i_cons = matches($i_word, $word,
+ 50243 0.48837 0.88000 63: $count{$i_LINES}{caps} =
+ 50243 0.00516 0.88000 58: my $i_caps = matches($i_word, $word, '^[(A-
+ 50243 0.00631 0.81000 54: my $i_spec = matches($i_word, $word, '[^a-
+ 50243 0.00496 0.80000 57: my $i_vows = matches($i_word, $word,
+ 50243 0.00688 0.80000 53: $i_word++;
+ 50243 0.48469 0.79000 62: $count{$i_LINES}{only} =
+ 50243 0.48928 0.77000 60: $count{$i_LINES}{vows} =
+ 50243 0.00683 0.75000 55: my $i_only = matches($i_word, $word, '^[^a-
+
+You can immediately see a slightly different focus to the subroutine profiling
+modules, and we start to see exactly which line of code is taking the most
+time. That regex line is looking a bit suspicious, for example. 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 C<Apache::SmallProf> which hooks C<Devel::SmallProf> into C<mod_perl>.
+
+=head2 Devel::FastProf
+
+C<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
+C<Devel::SmallProf>, because it's written in C<C>. To use C<Devel::FastProf>,
+supply the C<-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
+
+C<Devel::FastProf> writes statistics to the file F<fastprof.out> in the current
+directory. The output file, which can be specified, can be interpreted by using
+the C<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 C<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, C<if ( $debug ) { > and C<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 L<DBIx::Profiler> which will profile database queries running
+under the C<DBIx::*> namespace.
+
+=head2 Devel::NYTProf
+
+C<Devel::NYTProf> is the B<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 I<line> profiler, a I<block> or a I<subroutine>
+profiler, all at once. It can also use sub-microsecond (100ns) resolution on
+systems which provide C<clock_gettime()>. It can be started and stopped even
+by the program being profiled. It's a one-line entry to profile C<mod_perl>
+applications. It's written in C<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 C<-d> switch to plug it in and run
+the code.
+
+ $> perl -d:NYTProf wordmatch -f perl5db.pl
+
+ wordmatch report for perl5db.pl:
+ lines in file: 9427
+ 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
+
+C<NYTProf> will generate a report database into the file F<nytprof.out> by
+default. Human readable reports can be generated from here by using the
+supplied C<nytprofhtml> (HTML output) and C<nytprofcsv> (CSV output) programs.
+We've used the unix sytem C<html2text> utility to convert the
+F<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 |
+ |198 |0.00085 |4e-06 |line . block . sub|warnings/register.pm|
+ |114 |0.00080 |7e-06 |line . block . sub|strict.pm |
+ |47 |0.00068 |0.00001|line . block . sub|warnings.pm |
+ |27 |0.00054 |0.00002|line . block . sub|overload.pm |
+ |9 |0.00047 |0.00005|line . block . sub|SelectSaver.pm |
+ |13 |0.00045 |0.00003|line . block . sub|File/Spec.pm |
+ |2701595|15.73869 | |Total |
+ |128647 |0.74946 | |Average |
+ | |0.00201 |0.00003|Median |
+ | |0.00121 |0.00003|Deviation |
+
+ Report produced by the NYTProf 2.03 Perl profiler, developed by Tim Bunce and
+ Adam Kaplan.
+
+At this point, if you're using the I<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 F<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 |
+ | | | | |sub matches { |
+ <...snip...>
+ |102 | | | | |
+ | | | | |# spent 2.71199s within main::debug which was |
+ | | | | |called 260642 times, avg 0.00001s/call: # |
+ | | | | |251215 times (2.61571+0s) by main::matches at |
+ |103 | | | |line 74 of wordmatch, avg 0.00001s/call # 9427 |
+ | | | | |times (0.09628+0s) at line 50 of wordmatch, avg|
+ | | | | |0.00001s/call |
+ | | | | |sub debug { |
+ |104 |260642|0.58496 |2e-06 |my $message = shift; |
+ |105 | | | | |
+ |106 |260642|1.09917 |4e-06 |if ( $debug ) { |
+ |107 | | | |print STDERR "DBG: $message\n"; |
+ |108 | | | |} |
+ |109 | | | |} |
+ |110 | | | | |
+ |111 |1 |0.01501 |0.01501|exit 0; |
+ |112 | | | | |
+
+Oodles of very useful information in there - this seems to be the way forward.
+
+See also C<Devel::NYTProf::Apache> which hooks C<Devel::NYTProf> into C<mod_perl>.
+
+=head1 SORTING
+
+Perl modules are not the only tools a performance analyst has at their
+disposal, system tools like C<time> should not be overlooked as the next
+example shows, where we take a quick look at sorting. Many books, theses and
+articles, have been written about efficient sorting algorithms, and this is not
+the place to repeat such work, there's several good sorting modules which
+deserve taking a look at too: C<Sort::Maker>, C<Sort::Key> spring to mind.
+However, it's still possible to make some observations on certain Perl specific
+interpretations on issues relating to sorting data sets and give an example or
+two with regard to how sorting large data volumes can effect performance.
+Firstly, an often overlooked point when sorting large amounts of data, one can
+attempt to reduce the data set to be dealt with and in many cases C<grep()> can
+be quite useful as a simple filter:
+
+ @data = sort grep { /$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 it's simplicity. The C<KISS> principle is too often
+overlooked - the next example uses the simple system C<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)"
+ livebot-207-46-98-57.search.live.com - - [08/Feb/2007:14:12:04 +0000] "GET /html/oracle.html HTTP/1.0" 404 214 "-" "msnbot/1.0 (+http://search.msn.com/msnbot.htm)"
+ dslb-088-064-005-154.pools.arcor-ip.net - - [08/Feb/2007:14:12:15 +0000] "GET / HTTP/1.1" 200 3309 "-" "www.clamav.net"
+ 196.201.92.41 - - [08/Feb/2007:14:15:01 +0000] "GET / HTTP/1.1" 200 3309 "-" "MOT-L7/08.B7.DCR MIB/2.2.1 Profile/MIDP-2.0 Configuration/CLDC-1.1"
+
+The specific task here is to sort the 286,525 lines of this file by Response
+Code, Query, Browser, Referring Url, and lastly Date. One solution might be to
+use the following code, which iterates over the files given on the
+command-line.
+
+# sort-apache-log
+
+ #!/usr/bin/perl -n
+
+ 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 C<STDOUT> so it is possible to check the
+output is correct from following test runs and use the system C<time> utility
+to check the overall runtime.
+
+ $> time ./sort-apache-log logfile > out-sort
+
+ real 0m17.371s
+ user 0m15.757s
+ sys 0m0.592s
+
+The program took just over 17 wallclock seconds to run. Note the different
+values C<time> outputs, it's important to always use the same one, and to not
+confuse what each one means.
+
+=over 4
+
+=item Elapsed Real Time
+
+The overall, or wallclock, time between when C<time> was called, and when it
+terminates. The elapsed time 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.
+
+=item 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.
+
+=item 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.
+
+=back
+
+Running this same process as a C<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;
+
+Run the new code against the same logfile, as above, to check the new time.
+
+ $> time ./sort-apache-log-schwarzian logfile > out-schwarz
+
+ real 0m9.664s
+ user 0m8.873s
+ sys 0m0.704s
+
+The time has been cut in half, which is a respectable speed improvement by any
+standard. Naturally, it is important to check the output is consistent with
+the first program run, this is where the unix system C<cksum> utility comes in.
+
+ $> 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...
+
+=head1 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 I<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: $$ INC: " . Dumper(\%INC) )
+
+The problem is that this code will always be parsed and executed, even when the
+debug level set in the logging configuration file is zero. Once the debug()
+subroutine has been entered, and the internal C<$debug> variable confirmed to
+be zero, for example, the message which has been sent in will be discarded and
+the program will continue. In the example given though, the \%INC hash will
+already have been dumped, and the message string constructed, all of which work
+could be bypassed by a debug variable at the statement level, like this:
+
+ logger->debug( "A logging message via process-id: $$ INC: " . Dumper(\%INC) ) if $DEBUG;
+
+This effect can be demonstrated by setting up a test script with both forms,
+including a C<debug()> subroutine to emulate typical C<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: $$" . Dumper(\%INC) )
+ },
+ 'ifdebug' => sub {
+ debug( "A $0 logging message via process-id: $$" . Dumper(\%INC) ) if $DEBUG
+ },
+ });
+
+Let's see what C<Benchmark> makes of this:
+
+ $> perl ifdebug
+ Benchmark: timing 100000 iterations of constant, sub...
+ ifdebug: 0 wallclock secs ( 0.01 usr + 0.00 sys = 0.01 CPU) @ 10000000.00/s (n=100000)
+ (warning: too few iterations for a reliable count)
+ debug: 14 wallclock secs (13.18 usr + 0.04 sys = 13.22 CPU) @ 7564.30/s (n=100000)
+
+In the one case the code, which does exactly the same thing as far as
+outputting any debugging information is concerned, in other words nothing,
+takes 14 seconds, and in the other case the code takes one hundredth of a
+second. Looks fairly definitive. Use a C<$DEBUG> variable BEFORE you call the
+subroutine, rather than relying on the smart functionality inside it.
+
+=head2 Logging if DEBUG (constant)
+
+It's possible to take the previous idea a little further, by using a compile
+time C<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:
+
+ $> perl ifdebug-constant
+ Benchmark: timing 100000 iterations of constant, sub...
+ constant: 0 wallclock secs (-0.00 usr + 0.00 sys = -0.00 CPU) @ -7205759403792793600000.00/s (n=100000)
+ (warning: too few iterations for a reliable count)
+ sub: 14 wallclock secs (13.09 usr + 0.00 sys = 13.09 CPU) @ 7639.42/s (n=100000)
+
+The C<DEBUG> constant wipes the floor with even the C<$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 C<B::Deparse> to inspect the new code:
+
+ $> perl -MO=Deparse ifdebug-constant
+
+ use Benchmark;
+ use Data::Dumper;
+ use constant ('DEBUG', 0);
+ sub debug {
+ use warnings;
+ use strict 'refs';
+ 0;
+ }
+ use warnings;
+ use strict 'refs';
+ timethese(100000, {'sub', sub {
+ debug "A $0 logging message via process-id: $$" . Dumper(\%INC);
+ }
+ , 'constant', sub {
+ 0;
+ }
+ });
+ ifdebug-constant syntax OK
+
+The output shows the constant() subroutine we're testing being replaced with
+the value of the C<DEBUG> constant: zero. The line to be tested has been
+completely optimized away, and you can't get much more efficient than that.
+
+=head1 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: I<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 C<p5p>.
+
+=head1 SEE ALSO
+
+Further reading can be found using the modules and links below.
+
+=head2 PERLDOCS
+
+For example: perldoc -f sort
+
+ L<perlfaq4>
+ L<perlfork>
+ L<perlfunc>
+ L<perlretut>
+ L<perlthrtut>
+ L<threads>
+
+=head2 MAN PAGES
+
+ L<time>
+
+=head2 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.
+
+ L<Apache::DProf>
+ L<Apache::SmallProf>
+ L<Benchmark>
+ L<DBIx::Profiler>
+ L<Devel::AutoProfiler>
+ L<Devel::DProf>
+ L<Devel::DProfLB>
+ L<Devel::FastProf>
+ L<Devel::GraphVizProf>
+ L<Devel::NYTProf>
+ L<Devel::NYTProf::Apache>
+ L<Devel::Profiler>
+ L<Devel::Profile>
+ L<Devel::Profit>
+ L<Devel::SmallProf>
+ L<Devel::WxProf>
+ L<POE::Devel::Profiler>
+ L<Sort::Key>
+ L<Sort::Maker>
+
+=head2 URLS
+
+Very useful online reference material:
+
+ http://www.ccl4.org/~nick/P/Fast_Enough/
+
+ 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
+
+ http://www.unix.org.ua/orelly/perl/prog/ch08_03.htm
+
+=head1 AUTHOR
+
+Richard Foley <richard.foley@rfi.net> Copyright (c) 2008
+
+=cut