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From "Mark Hindess" <mark.hind...@googlemail.com>
Subject Optimizing jars
Date Fri, 01 Oct 2010 15:43:38 GMT

Our modular structure means we have many jars that need to be read at
startup, this is always going to give us a disadvantage in terms of
startup time compared to implementations with fewer jars.

I was reading:


and wondered if perhaps some of these techniques could be employed to
help us reduce the disadvantage a little.

So I took a federated build and tried:

  target/hdk/jdk/jre/bin/java -verbose:class -cp ~/hy/java HelloWorld \
    >trace.log 2>&1

  # create one log file per jar in trace subdir, one class filename per line
  class-load-by-jar trace.log

  cp -pr target target.new

  python optimizejars.py --optimize trace \

  python optimizejars.py --optimize trace \

so now new contains optimised versions of the jars need to run HelloWorld.

I then obtained some timing data.

The figures I get back weren't really conclusive - on one machine it
showed improvement but not on another.  I tried the same experiment
with a j9 vm but the zip implementation is obviously more fragile as
it crashed complaining about not finding java.lang.Object.  Ironically
given what I started thinking about, I suspect that the one big jar case
(e.g. the RI) will probably see more benefit than the multiple jar case.[1]

Anyway, I was just experimenting but I thought I'd write down what I
found in case anyone had similar/better ideas.


[1] Since you can't really reduce the disk seeks between multiple jars but
    you can within a single big jar.

class-load-by-jar is:

use strict;
use warnings;

my %fh;
mkdir 'trace', 0755;
while (<>) {
  my ($class, $jar) =
    m!(?:Loaded|class load:) (\S+) from:? .*\/([^\/\.]+\.jar)! or next;
  my $fh = file_handle($2);
  print $fh $class, ".class\n";
close $_ foreach (keys %fh);

sub file_handle {
  my $jar = shift;
  return $fh{$jar} if (exists $fh{$jar});
  open $fh{$jar}, '>', 'trace/'.$jar.'.log'
    or die "Failed to open $jar.log: $!\n";

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