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https://issues.apache.org/jira/browse/JENA-901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14371574#comment-14371574
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Stian Soiland-Reyes commented on JENA-901:
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There seemed to be a leak of activeInterpreters even when closing the iterator
returned from find - but that was because I never called it.hasNext() - which
of course would be a bit odd. With that fixed I can't see any memory leaks on
my branch with the BoundedMap.
I tested my branch now with JProfiler and a max of 1024*1024 - which consumes
25 MB for the TriplePatterns - this is because it keeps those 1024*1024 URIs as
string[] referenced from within the cache. So a good number is probably
somewhere around that scale - if not smaller.
Pull request with suggested fix: https://github.com/apache/jena/pull/44
Changing to Guava might longer-term be a better option - but I think this fix
should suffice now.
> Make the cache of LPBRuleEngine bounded to avoid out-of-memory
> --------------------------------------------------------------
>
> Key: JENA-901
> URL: https://issues.apache.org/jira/browse/JENA-901
> Project: Apache Jena
> Issue Type: Improvement
> Components: Reasoners
> Affects Versions: Jena 2.12.1
> Reporter: Jan De Beer
>
> The class "com.hp.hpl.jena.reasoner.rulesys.impl.LPBRuleEngine" uses an
> in-memory cache named "tabledGoals", which has no limit as to the size/number
> of entries stored.
> {noformat}
> /** Table mapping tabled goals to generators for those goals.
> * This is here so that partial goal state can be shared across multiple
> queries. */
> protected HashMap<TriplePattern, Generator> tabledGoals = new HashMap<>();
> {noformat}
> We have experienced out-of-memory issues because of the cache being filled
> with millions of entries in just a few days under normal query usage
> conditions and a heap memory set to 3GB.
> In our setup, we have a dataset containing multiple graphs, some of them are
> actual data graphs (backed by TDB), and then there are two which are ontology
> models using a "TransitiveReasoner" and an "OWLMicroFBRuleReasoner",
> respectively. A typical query may run over all the graphs in the dataset,
> including the ontology ones (see below for a query template). Eventhough the
> ontology graphs would not yield any additional results for data queries
> (which is fine), the above mentioned cache would still fill up with new
> entries.
> {noformat}
> SELECT ?p ?o
> WHERE {
> GRAPH ?g {
> <some resource of interest> ?p ?o .
> }
> }
> {noformat}
> As there is no upper bound to the cache, soon or later all available heap
> memory will be consumed by the cache, giving rise to an out-of-memory
> criticial error.
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