[GitHub] jena pull request: Using ThreadLocal::remove to clean thread-speci...
Github user asfgit closed the pull request at: https://github.com/apache/jena/pull/104 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[jira] [Commented] (JENA-624) Develop a new in-memory RDF Dataset implementation
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https://issues.apache.org/jira/browse/JENA-624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15043441#comment-15043441
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A. Soroka commented on JENA-624:
Works for me. You know there are some minor refactorings for clarity and
concision I want to do when the time is right (e.g. bringing the {{find}}
methods up into {{TupleTable}} by using varargs) but I have nothing useful to
add to what's there now in terms of getting stuff in front of people.
> 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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[jira] [Commented] (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=15043426#comment-15043426
]
Andy Seaborne commented on JENA-624:
The PR looks right - getting stability for long-running code is important and
tricky. We can review in the light of experience - getting into 3.0.1 is the
start of that. From looking at the OpenJDK implementation,
{{ThreadLocal::remove}} is not normally expensive.
Suggestion: this ends development for 3.0.1. We resolve this as "done" and open
new JIRA as needed.
> 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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