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https://issues.apache.org/jira/browse/JENA-624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15010731#comment-15010731
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ASF GitHub Bot commented on JENA-624:
-------------------------------------
GitHub user afs opened a pull request:
https://github.com/apache/jena/pull/100
Rename in-memory dataset test classes.
To help navigate tests, this is a reorganisation of the tests created for
JENA-624 into the same naming style and organization as the other tests in ARQ.
The main reason for reorganizing is so that there is one style, not that one
is better than another.
* Files with tests are `Test*` (Junit3 legacy naming!)
* Test frameworks using abstract classes are `AbstractTest*`
* Files `TS_` for test suites, usually `@RunWith(Suite.class)`
* Each `TS_*` is in a test collection file - `TC_General` in this case.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/afs/jena j624-tests-reorg
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/jena/pull/100.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #100
----
commit 3a7d1fc0dbf8b814ba8451b3e6ee58dec7ed9104
Author: Andy Seaborne <[email protected]>
Date: 2015-11-18T10:23:19Z
Rename test classes and put tests into top level classes.
JENA-624
AbstractTest* for the abstract test classes.
TS_ for the test suites.
Collect each TS_* into test suite collection TC_General
----
> 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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