Free Tool for Efficient XML Data Compression

[Hartmut Liefke]

We would like to announce the release of XMill, a compressor for XML
data.  XMill typically compresses twice as good as gzip, at about the
same speed.

XMill is written in C++, and its distribution site is:

   http://www.research.att.com/sw/tools/xmill


TECHNICAL SUMMARY. The idea in XMill is that XML data items are
grouped according to their tags, then each group is compressed
separately with gzip.  This is XMill's default behavior, and already
results in better compression than gzip.

Furthermore, users can select particular semantic compressors (such as
for integers, IP addresses, state names, ...) to be applied to certain
data items, or can override the way data items are grouped: this
further improves the compression rate.

In complex applications where XML files contain highly specialized
datatypes, such as images or DNA sequences, XMill can be extended with
user-defined compressors for those data types.  XMill defines a C++
Semantic Compressor API (SCAPI) for such extensions.


PAPER.  A technical paper describing XMill is included in the
distribution package, and is also available directly from:

   http://www.cis.upenn.edu/~liefke/papers/xmill.ps.gz


HIGHLIGHT. It is known that XML files tend to be larger than files in
application specific data formats.  With XMill however, it becomes
more economical to choose XML over application specific data formats,
because the XML file is compressed with XMill better (up to half the
size) than the application specific file compressed with gzip.  We
discovered this surprising fact by converting several application
specific data formats to XML (including weblog data, protein meta
data, linguistic data), then compressing the original file with gzip,
and the XML file with XMill: the compressed XML file was always
smaller, up to a factor of two. Details are included in the
distribution at the Web site above.

MAILING LIST.  For updates on XMill, please subscribe to
xmill at research.att.com, by sending an email to
majordomo at research.att.com, with the body "subscribe xmill".


Regards,

   Hartmut Liefke  -- University of Pennsylvania, liefke at seas.upenn.edu
   Dan Suciu       -- AT&T Labs, suciu at research.att.com

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