On 26/08/2020 08:36, Andy Seaborne wrote:
Thanks for the report.
I don't have access to the paper.
https://t.co/ivcVMnPGEr
via
https://twitter.com/alphaverda/status/1276836317100421121
Unfortunately, the evaluation is a custom app for each database. Without
seeing the app, it's opaque.
I was hoping to see which features of SHACL they used in their shapes.
While Jena covers a all of core and SPARQL, the more obscure ones are
maybe slow. But if they are comparing across databases, maybe they went
for an implemented subset.
Where are the shapes they used?
Andy
"18 GB of heap memory" ... on a 16G machine. Hmm.
I don't see a reference to TopQuadrant SHACL in the references.
On 26/08/2020 07:23, Lorenz B. wrote:
Hi all,
as usual when I see something regarding Jena in recent publications:
"Benchmark for Performance Evaluation of SHACL Implementations in Graph
Databases" [1]
As the title indicates, it's a benchmark about SHACL validation
performance. The benchmark comprise 58 SHACL shapes tested on I guess 1
million triples. Jena got second place close to Stardog - which I think
is a success.
Especially for something that isn't in the slightest optimized other
than the fact it compiles the shapes to an execution tree. Incremental
validation for transactions is "work in progress".
Some other metrics like memory consumption might be something to
investigate - not sure if those numbers make sense, but according to the
paper Jena needs 14GB of RAM? RDF4J even 16GB, but Stardog only 1.2GB.
Sounds suspect to me for one million triples. A TDB database on disk is
likely less than 1G bytes.
Of course, Jena uses the Java heap and that just grows until a GC
happens but it's not all in use.
(Stardog does a lot outside the heap)
A weak point of Jena was "lack of documentation".
That's fixable - what were they looking for? A hands on-guide to SHACL?
Again, thanks
Andy
Anyways, good job Andy (and contributors).
Happy to see comments and thoughts from your side.
Cheers,
Lorenz
[1] https://link.springer.com/chapter/10.1007/978-3-030-57977-7_6
