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https://issues.apache.org/jira/browse/JENA-624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15033731#comment-15033731
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A. Soroka commented on JENA-624:
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Ah, okay, now I understand your point. In fact, the current implementation will
_not_ suffer the problem you're outlining, because all of the relevant data in
all the machinery, all the way down, is segregated by thread. (In all impls of
{{TupleTable}}, particularly.) But a fresh impl might or might not have that
characteristic, so you're right that it could create a problem. I'll take in
your fix and add it to PR #103 with the test for which you asked above.
Can you expand your remark about {{isInTransaction}} in
{{DatasetGraphInMemory}}? It's a bit too gnomic for me. :)
> Develop a new in-memory RDF Dataset implementation
> --------------------------------------------------
>
> Key: JENA-624
> URL: https://issues.apache.org/jira/browse/JENA-624
> Project: Apache Jena
> Issue Type: Improvement
> Reporter: Andy Seaborne
> Assignee: A. Soroka
> Labels: java, linked_data, rdf
>
> The current (Jan 2014) Jena in-memory dataset uses a general purpose
> container that works for any storage technology for graphs together with
> in-memory graphs.
> This project would develop a new implementation design specifically for RDF
> datasets (triples and quads) and efficient SPARQL execution, for example,
> using multi-core parallel operations and/or multi-version concurrent
> datastructures to maximise true parallel operation.
> This is a system project suitable for someone interested in datatbase
> implementation, datastructure design and implementation, operating systems or
> distributed systems.
> Note that TDB can operate in-memory using a simulated disk with
> copy-in/copy-out semantics for disk-level operations. It is for faithful
> testing TDB infrastructure and is not designed performance, general in-memory
> use or use at scale. While lesson may be learnt from that system, TDB
> in-memory is not the answer here.
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