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I concur with rhesa's method. I've used this before with considerable success.

I just untarred a test structure containing a million files distributed this way using 3 levels of subdirectory to give an average of ~250 file per directory. I then ran a quick test of opening and reading 10,000 files at random and got an average time to locate, open, read and close each file of 12ms.

#! perl -slw use strict; use Math::Random::MT qw[ rand ]; use Digest::MD5 qw[ md5_hex ]; use Benchmark::Timer; our $SAMPLE ||= 1000; my $T = new Benchmark::Timer; for my $i ( 1 .. $SAMPLE ) { $T->start( 'encode/open/read/close' ); my $md5 = md5_hex( int( rand 1e6 ) ); my( $a, $b, $c ) = unpack 'AAA', $md5 ; $T->start( 'open' ); open my $fh, '<', "fs/$a/$b/$c/$md5.dat" or warn "fs/$a/$b/$c/$md5 + : $!"; $T->stop( 'open' ); $T->start( 'read' ); my $data = do{ local $/; <$fh> }; $T->stop( 'read' ); $T->start( 'close' ); close $fh; $T->stop( 'close' ); $T->stop( 'encode/open/read/close' ); } $T->report; __END__ c:\test>612729-r -SAMPLE=10000 10000 trials of encode/open/read/close (112.397s total), 11.240ms/tria +l 10000 trials of open (110.562s total), 11.056ms/trial 10000 trials of read (158.554ms total), 15us/trial 10000 trials of close (365.520ms total), 36us/trial

The files in this case are all 4k, but that doesn't affect your seek time. If you envisage needing to deal with much more than 1 million files, moving to 4 levels of hierarchy woudl distribute the million files at just 15 per directory.


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In reply to Re^3: Perl solution for storage of large number of small files by BrowserUk
in thread Perl solution for storage of large number of small files by isync

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