Proposed javac argument processing performance improvement

[Jonathan Gibbons]

David,

Nice patch.  Thanks for submitting it.

-- Jon

On 06/11/2011 06:07 PM, David Schlosnagle wrote:
> I'd like to propose a minor change for javac to improve performance
> processing large numbers of filename arguments, especially on Windows.
> The main issue is that com.sun.tools.javac.main.Main currently uses a
> ListBuffer for the collection of filenames. Main.addFile calls
> ListBuffer.contains before calling ListBuffer.add, both of which are
> linear searches leading to O(N^2) performance. Additionally, the
> implementation of java.io.File.equals uses the underlying filesystem's
> compare method which on Windows requires an expensive case insensitive
> string comparison. For large numbers of files (I work with several
> modules of approximately 10,000 Java input files for a single javac
> invocation) so this is a big performance hit. The simple fix is to use
> a LinkedHashSet<File>  instead of ListBuffer<File>  for the filenames
> field in com.sun.tools.javac.main.Main (see attached patch).
>
> My preliminary tests show that execution time of
> com.sun.tools.javac.main.Main.processArgs method for 10,000 input
> files on my Windows machine went from around 15 seconds to around 300
> milliseconds with the patch. The performance improvement on
> case-sensitive filesystems isn't as good, but still seems to be an
> order of magnitude as seen in the following results on my main Mac OS
> X machine for com.sun.tools.javac.main.Main.processArgs method
> execution time.
>
> # files Before (ms) After (ms)  Delta (ms)
> ------- ----------- ----------  ----------
> 1       0.6         1.1         0.5
> 1000    39.4        39.7        0.3
> 2000    94.4        41.4        (53.1)
> 3000    184.8       61.4        (123.4)
> 4000    185.2       77.2        (108.0)
> 5000    257.9       89.1        (168.7)
> 6000    358.5       119.9       (238.6)
> 7000    422.1       126.7       (295.4)
> 8000    624.9       137.8       (487.2)
> 9000    620.1       139.8       (480.4)
> 10000   1,054.9     149.4       (905.5)
>
>
> Thanks,
> Dave