- From: Bryan Thompson <bryan@systap.com>
- Date: Tue, 5 Jul 2011 12:26:16 -0500
- To: "bigdata-developers@lists.sourceforge.net" <bigdata-developers@lists.sourceforge.net>
This is a bigdata (R) release. This release is capable of loading 1B triples in under one hour on a 15 node cluster. JDK 1.6 is required. Bigdata(R) is a horizontally scaled open source architecture for indexed data with an emphasis on semantic web data architectures. Bigdata operates in both a single machine mode (Journal) and a cluster mode (Federation). The Journal provides fast scalable ACID indexed storage for very large data sets. The federation provides fast scalable shard-wise parallel indexed storage using dynamic sharding and shard-wise ACID updates. Both platforms support fully concurrent readers with snapshot isolation. Distributed processing offers greater throughput but does not reduce query or update latency. Choose the Journal when the anticipated scale and throughput requirements permit. Choose the Federation when the administrative and machine overhead associated with operating a cluster is an acceptable tradeoff to have essentially unlimited data scaling and throughput. See [1,2,8] for instructions on installing bigdata(R), [4] for the javadoc, and [3,5,6] for news, questions, and the latest developments. For more information about SYSTAP, LLC and bigdata, see [7]. Starting with this release, we offer a WAR artifact [8] for easy installation of the Journal mode database. For custom development and cluster installations we recommend checking out the code from SVN using the tag for this release. The code will build automatically under eclipse. You can also build the code using the ant script. The cluster installer requires the use of the ant script. You can checkout this release from the following URL: https://bigdata.svn.sourceforge.net/svnroot/bigdata/branches/BIGDATA_RELEASE_1_0_0 New features: - Single machine data storage to ~50B triples/quads (RWStore); - Simple embedded and/or webapp deployment (NanoSparqlServer); - Fast 100% native SPARQL 1.0 evaluation with lots of query optimizations; Feature summary: - Triples, quads, or triples with provenance (SIDs); - Fast RDFS+ inference and truth maintenance; - Clustered data storage is essentially unlimited; - Fast statement level provenance mode (SIDs). The road map [3] for the next releases includes: - High-volume analytic query and SPARQL 1.1 query, including aggregations; - Simplified deployment, configuration, and administration for clusters; and - High availability for the journal and the cluster. For more information, please see the following links: [1] https://sourceforge.net/apps/mediawiki/bigdata/index.php?title=Main_Page [2] https://sourceforge.net/apps/mediawiki/bigdata/index.php?title=GettingStarted [3] https://sourceforge.net/apps/mediawiki/bigdata/index.php?title=Roadmap [4] http://www.bigdata.com/bigdata/docs/api/ [5] http://sourceforge.net/projects/bigdata/ [6] http://www.bigdata.com/blog [7] http://www.systap.com/bigdata.htm [8] https://sourceforge.net/projects/bigdata/files/bigdata/ About bigdata: Bigdata(r) is a horizontally-scaled, general purpose storage and computing fabric for ordered data (B+Trees), designed to operate on either a single server or a cluster of commodity hardware. Bigdata(r) uses dynamically partitioned key-range shards in order to remove any realistic scaling limits - in principle, bigdata(r) may be deployed on 10s, 100s, or even thousands of machines and new capacity may be added incrementally without requiring the full reload of all data. The bigdata(r) RDF database supports RDFS and OWL Lite reasoning, high-level query (SPARQL), and datum level provenance.
Received on Friday, 8 July 2011 13:40:23 UTC