Any time you derefernce to get to a value pointed to by a reference, it's called a layer of indirection.
Every layer of indirection adds some overhead, so if you are acccessing data deep inside a complex data
structure, it adds up. Normally this is negligable, but if you are doing so inside loops you can gain
more speed by removing as many layers of indirecion as possible.
Take the following code sample. The structure '$data' is two levels deep, and the subs 'foo' and 'bar'
both loop thru and access all the data at the deepest level. 'foo' uses a naive aproach of multiple
layers of indirection at the deepest level 'my $val = $data->{$key1}->{$key2}', while 'bar' reduces
the indirection by assigning the inner data struct to a variable 'my $data2 = $data->{$key1}' and
looping over it, accessing that data with 'my $val = $data2->{$key2}'.
results:
Benchmark: timing 100000 iterations of multiple_indirection, reduced_indirection...
multiple_indirection: 29 wallclock secs (28.08 usr + 0.00 sys = 28.08 CPU) @ 3561.25/s (n=100000)
reduced_indirection: 25 wallclock secs (24.19 usr + 0.00 sys = 24.19 CPU) @ 4133.94/s (n=100000)
Rate multiple_indirection reduced_indirection
multiple_indirection 3561/s -- -14%
reduced_indirection 4134/s 16% --
code:
#!/usr/bin/perl
my %innerdata;
@innerdata{a..z} = a..z;
my $data = {
foo => {
%innerdata
},
bar => {
%innerdata
}
};
sub foo {
my $data = $_[0];
for $key1 (keys %$data) {
for $key2 (keys %{$data->{$key1}}) {
my $val = $data->{$key1}->{$key2};
# process $val;
# print $val;
}
}
}
sub bar {
my $data = $_[0];
for $key1 (keys %$data) {
my $data2 = $data->{$key1};
for $key2 (keys %$data2) {
my $val = $data2->{$key2};
# process $val;
# print $val;
}
}
}
use Benchmark qw(cmpthese);
cmpthese(
100000,
{
multiple_indirection => sub { foo($data) },
reduced_indirection => sub { bar($data) },
}
)
-- O thievish Night, Why should'st thou, but for some felonious end, In thy dark lantern thus close up the stars? --Milton | [reply]
[d/l] |