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https://issues.apache.org/jira/browse/JENA-624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14957460#comment-14957460
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ASF GitHub Bot commented on JENA-624:
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Github user afs commented on the pull request:
https://github.com/apache/jena/pull/94#issuecomment-148144899
Really good to see this.
If you could squash commits that would be great.
It will probably take some while and some discussion.
If it is meaningful to split into parts that can be considered separately,
that might also help but I would not be surprised if that is not natural to the
PR.
> 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
> Labels: gsoc, gsoc2015, 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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