Rahul, Thanks for reviving this topic.
Tuning Xerces is going to be an iterative process. We need some test data that everyone can use, and we need a test driver that everyone can use. I'm fine with the metrics and characterization of test data that you are proposing in your message. I think it's a great start I'd also like to propose that all the people working on this check the test data and the test classes into the build, so that anyone can run the performance timings for themselves. (I'd like to see this for the full test suite as well, but that's another message). I have some time that I can contribute towards this effort. Ted On Fri, 2002-05-03 at 14:03, Rahul Srivastava wrote: > > Hi folks, > > It has been long talking about improving the performance of Xerces2. There has > been some benchmarking done earlier, for instance the one done by Dennis > Sosnoski, see: http://www.sosnoski.com/opensrc/xmlbench/index.html . These > results are important to know how fast/slow xerces is as compared to other > parsers. But, we need to identify areas of improvement in xerces. We need to > calculate the time taken by each individual component in the pipeline and figure > out which component swallows how much time for various events and then we can > actually concentrate on improving performance for those areas. So, here is what > we plan to do: > > + sax parsing > - time taken > + dom parsing > - dom construction time > - dom traversal time > - memory consumed > - considering the feature deferred-dom as true/false for all of above > + DTD validation > - one time parse, time taken > - multiple times parse using same instance, time taken for second parse onwards > + Schema validation > - one time parse, time taken > - multiple times parse using same instance, time taken for second parse onwards > + optimising the pipeline > - calculate pipeline/component initialization time. > - calculating the time each component in the pipeline takes to propagate > the event. > - Using configurations to set up an optimised pipeline for various cases > such as novalidation, DTD validation only, etc. and calculate the > time taken. > > Apart from this should we consider the existing grammar caching framework to > evaluate the performance of the parser? > > We have classified the inputs to be used for this testing as follows: > > + instance docs used > - tag centric (more tags and small content say 10-50 bytes) > Type Tags# > ------------------- > * small 5-50 > * medium 50-500 > * large >500 > > - content centric (less tags say 5-10 and huge content) > Type content b/w a pair of tag > ------------------------------------- > * small 500 kb > * medium 500-5000 kb > * large >5000 kb > > We can also have depth of the tags as a criteria for the above cases. > > Actually speaking, there can be enormous combinations and different figures in > the above table that reflect the real word instance docs used. I would like to > know the view of the community here. Is this data enough to evaluate the > performance of the parser. Is there any data which is publicly available and can > be used for performance evaluation?. > > + DTD's used > - should use different types of entities > > + XMLSchema's used > - should use most of the elements and datatypes > > Will it really help in any way? > > Any comments or suggestions appreciated. > > Thanks, > Rahul. > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [EMAIL PROTECTED] > For additional commands, e-mail: [EMAIL PROTECTED] --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
