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- From: xml <firstname.lastname@example.org>
- To: email@example.com
- Date: Wed, 14 Apr 1999 11:43:51 -0700
Being a Java Virtual Machine guy, I can tell you definitively that string
processing is something that Java tends to be slow at, especially if you're
talking large datasets. That being said, if you're going to do Java and
XML, it's smart to put Java wrappers around C/C++ code and let the compiled
code do all of the storage-related functions. If you're someone like Sun,
that's no big deal because the compiled code is hidden away. Indeed this
is the case with many elements of the standard Java JDK/JRE from Sun.
To the best of my knowledge though, the string handling classes are
pure Java in their frameworks, which can make processing of collections
of text pretty slow.
Again if you're running server-side Java, usually all this means is that
you have to play with your network and add more servers or processors.
Doing client-side Java/XML is a different can of worms tho', since you
can't just plop another processor into your average box at home.
My XML parser is C with java wrappers on top of it for this reason as the
target customer is a desktop computer or smaller. Of course, given a
Solaris machine in a server role, the C code would perform that much
better than the machine next to it running pure Java.
The Java incarnation where I work is heavily dependent on SQL servers,
a typical situation which externalizes a lot of C-based data handling
(a la a Sybase or Oracle SQL server) and uses Java mainly to orchestrate
how the data is processed instead of actually processing it much itself.
For this reason, the performance _can_ be pretty good and Java/SQL can
be a pretty nice match.
XML presents a different set of performance considerations since the
frameworks are often totally written in Java and rely on code that is
also pure Java.
It would be interesting to know if the collection classes in Java 2.0
and associated string classes may be moved to C and wrapped in Java.
Using this in a Java/XML framework could minimize the performance problems.
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