On 11/10/17 11:57, George News wrote:
Hi all,
The project I'm working in currently has a TDB with approximately 100M
triplets and the size is increasing quite quickly. When I make a typical
SPARQL query for getting data from the system, it takes ages, sometimes
more than 10-20 minutes. I think performance wise this is not really
user friendly. Therefore I need to know how I can increase the speed, etc.
I'm running the whole system on a machine with Intel Xeon E312xx with
32Gb RAM and many times I'm getting OutofMemory Exceptions and the
google.cache that Jena handles is the one that seems to be causing the
problem.
On uploading large amounts of data?
TDB1 will have trouble with 100M triple online uploads (if that is what
merging means).
TDB2 will do it but it is not in a release yet and will be settling down
for a release or two.
Are the figures I'm pointing normal (machine specs, response time,
etc.)? Is it too big/too small?
For the moment, we have decided to split the graph in pieces, that is,
generating a new named graph every now and then so the amount of
information stored in a "current" graph is smaller. Then restricting the
query to a set of graphs things work better.
Although this solution works, when we merge the graphs for historical
queries, we are facing the same problem as before. Then, how can we
increased the speed?
I cannot disclosed the dataset or part of it, but I will try to somehow
explain it.
- Ids for entities are approximately 255 random ASCII characters. Does
the size of the ids affect the speed of the SPARQL queries? If yes, can
I apply a Lucene index to the IDs in order to reduce the query time?
- The depth level of the graph or the information relationship is around
7-8 level at most, but most of the times it is required to link 3-4 levels.
- Most of the queries include several:
?x myont:hasattribute ?b.
?a rdf:type ?b.
Therefore checking the class and subclasses of entities. Is there anyway
to speed up the inference as if I'm asking for the parent class I will
get also the children ones defined in my ontology.
- I know the "." in a query acts as more or less like an AND logical
operation. Does the order of sentences have implications in the
performance? Should I start with the most restrictive ones? Should I
start with the simplest ones, i.e. checking number values, etc.?
- Some of the queries uses spatial and time filtering? Is is worth
implementing the support for spatial searches with SPARQL? Is there any
kind of index for time searches?
Any help is more than welcome.
Regards,
Jorge
