Out of curiosity, does performance differ with defusedxml in there? (RDF)XML parser complexity really is unnecessary compared to e.g. N3, JSONLD, or RDFHDT.
Does performance differ after transforming to a non-XML format? defusedxml should probably be an install_requires dependency because of the XML parser vulnerabilities that it patches: https://pypi.org/project/defusedxml/ On Fri, Jan 7, 2022, 9:58 AM Brendan McMahon <brendan.mcma...@tempus.com> wrote: > Hi Nick, thanks for the response! Yes, the idea you mention is what I was > considering trying next, but I thought I'd ask in here to see if there were > any other ideas about handling this with what the library has built in. I > will report back here with what I do if it works out! Also, the file is > about half a gig. It takes ~25 minutes to parse. > > Thanks, > Brendan > > On Friday, January 7, 2022 at 6:38:43 AM UTC-5 > nichol...@surroundaustralia.com wrote: > >> Hi Brendan, >> >> This is an interesting issue! No I haven't encountered it, but then I >> never use large RDF/XMl graphs. How large is your graph by the way? >> >> If you really think the issue is the getting or testing of elements in >> the RDF DefinedNamespace, couldn't you just clone rdfxml.py and replace all >> references to the RDF DefinedNamespace with references to a hard-coded set >> of URIRefs? You could try using that in place of the current rdfxml.py and >> see if there is a speedup. the file's only ~600 lines long, so a find 'n >> replace shouldn't be too impossible. >> >> I would love to know how you go with this, if you try it. If it overcomes >> the problem, we may consider doing such a replacement within internal >> RDFlib files to improve performance and then providing the >> DefinedNamespaces for external use only, i.e. when people define RDFlib >> grapes with g.add() and use FOAF.givenName to represent URIs. >> >> Cheers, >> >> Nick >> >> On Thu, Dec 23, 2021 at 3:32 AM Brendan McMahon <brendan...@tempus.com> >> wrote: >> >>> Dear rdflib contributors and maintainers, >>> >>> I have recently been trying to update rdflib to version 6 from 4.2.2. >>> Upon doing so, a process I normally run, which uses rdflib to load a large >>> xml RDF file into a graph, has a significantly larger memory profile and >>> latency (for my large file, parsing is taking about 1.5x as much time). >>> >>> I've traced the issue back to the graph.parse method. More specifically, >>> by profiling the graph.parse with versions 6.1.1 and 4.2.2, I can see that >>> calls to access members of the RDF class (mostly occurring in the >>> node_element_start >>> method here >>> <https://github.com/RDFLib/rdflib/blob/master/rdflib/plugins/parsers/rdfxml.py#L299> >>> as >>> well as the property_element_start method) seem to be taking up a >>> significantly longer time, as they the class is now a DefinedNamespace with >>> overridden __getitem__ and __contains >>> <https://github.com/RDFLib/rdflib/blob/2011a6dd85518642e0800b2ee010a5565e16e5cc/rdflib/namespace/__init__.py#L190> >>> methods with added string checks. >>> >>> Has anyone else experienced this issue? I have been trying to find ways >>> to work around/with the library to lower the latency, but haven't been able >>> to find anything yet. >>> >>> Thanks, >>> Brendan >>> >>> ------------------------------ >>> This email and any attachments may contain confidential and/or >>> privileged information. 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