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ASF GitHub Bot commented on JENA-624: ------------------------------------- GitHub user ajs6f opened a pull request: https://github.com/apache/jena/pull/103 JENA-624: Correction to transaction begin for DatasetGraphInMemory Correction to transaction begin for DatasetGraphInMemory to include default graph as well as quad table. You can merge this pull request into a Git repository by running: $ git pull https://github.com/ajs6f/jena CorrectionToDatasetGraphInMemory Alternatively you can review and apply these changes as the patch at: https://github.com/apache/jena/pull/103.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 #103 ---- commit c9b292293d307de305700981adb3d2d6d424d732 Author: ajs6f <aj...@virginia.edu> Date: 2015-11-30T18:23:34Z Correction to transaction begin for DatasetGraphInMemory to include default graph as well as quad table. ---- > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332)