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Posted to dev@jena.apache.org by "A. Soroka (JIRA)" <ji...@apache.org> on 2015/12/01 15:41:11 UTC

[jira] [Comment Edited] (JENA-624) Develop a new in-memory RDF Dataset implementation

    [ https://issues.apache.org/jira/browse/JENA-624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15033739#comment-15033739 ] 

A. Soroka edited comment on JENA-624 at 12/1/15 2:40 PM:
---------------------------------------------------------

Re: lock exposure: 

Okay, no prob. I did it the way it is (using the dataset lock) because I thought it was intentional to offer that lock publicly, so that other components could inspect it, but I have no problem using an internal, private lock. If I do that, what should the public lock actually _be_? Would it be an independent MR+SW lock?

Yeah, {{DatasetGraphInMemory}} would be pretty helpless in the fact of multi-thread transactions. That's a whole new frontier! :)


was (Author: ajs6f):
Re: lock exposure: 

Okay, no prob. I did it the way it is (using the dataset lock) because I thought it was intentional to offer that lock publicly, so that other components could inspect it, but I have no problem using an internal, private lock. If I do that, what should the public lock actually _be_? 

Yeah, {{DatasetGraphInMemory}} would be pretty helpless in the fact of multi-thread transactions. That's a whole new frontier! :)

> 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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