- From: Damyan Ognyanoff <damyan@sirma.bg>
- Date: Thu, 25 May 2006 13:57:31 +0300
- To: <sekt@aifb.uni-karlsruhe.de>
- Cc: <interested-in-OWLIM@ontotext.com>, <sesame-interest@lists.sourceforge.net>, <dip-all@lists.deri.org>, <seweb-list@lists.deri.org>, <everyone@sirma.bg>, <www-rdf-interest@w3.org>, <semantic-web@w3.org>, <tripcom@lists.deri.org>, <tao@dcs.shef.ac.uk>, <consortium@infrawebs.org>, <mediacampaign@iis-list.joanneum.ac.at>, <all@semantic-gov.org>, <internal@ist-world.org>
(*** We apologize if you receive multiple copies of this announcement ***) BigOWLIM successfully passed the threshold of 1 billion (10^9) statements of OWL/RDF - it loaded an 8000-university dataset of the LUBM benchmark (http://swat.cse.lehigh.edu/projects/lubm/) and answered the evaluation queries correctly. Evaluation setup and statistics: - Hardware: 2 x Opteron 270, 16GB of RAM, RAID 10; assembly cost < 5000 EURO - OS: Suse 10.0 Linux, x86_64, Kernel 2.6.13-15-smp; 64-bit JDK 1.5 -Xmx12000m - Loading, inference, and storage took 69 hours and 51 min - LUBM(8000,0) contains 1.06 billions of explicit statements -- The "inferred closure" contains about 786M statements -- BigOWLIM had to manage over 1.85 billions of statements in total - 92GB RDF/XML files; 95 GB binary storage files - Average Speed: 4 538 statements/sec. OWLIM (http://www.ontotext.com/owlim/) is a high-performance semantic repository, packaged as a Storage and Inference Layer (SAIL) for the Sesame RDF database (v.1.2.1-1.2.4). OWLIM uses TRREE (Triple Reasoning and Rule Entailment Engine) to perform RDFS, OWL DLP, and OWL Horst/Tiny reasoning. The most expressive language supported is a combination of unconstrained RDFS and limited OWL Lite. BigOWLIM (http://www.ontotext.com/owlim/big/) is a new and even more scalable version of the OWLIM semantic repository. A pre-release of BigOWLIM (ver. 0.9-beta) is already available. The "standard" OWLIM version, which performs reasoning and query evaluation in-memory, is referred now as SwiftOWLIM. The major distinctive features of BigOWLIM are: - The storage, inference and query evaluation are performed directly against binary files; it does not need to maintain all the contents of the repository in the main memory; this allows instant startup and initialization of large repositories; - BigOWLIM performs database-like query optimizations; re-ordering of the constraints in the query has no impact on the execution time; - BigOWLIM features special handling of owl:sameAs, so that processing of large "classes" of equivalent resources, does not cause excessive generation of inferred statements; - It has much lower memory requirements: LUBM(50,0) can be handled in 26 min on a desktop machine, giving Java (-Xmx) 192MB of RAM; LUBM(1000,0), which includes over 130 M statements, is handled in 11h on the same machine, given 1.6GB of RAM. We also take the opportunity to announce the release of ver. 2.8.3 of SwiftOWLIM (the in-memory version), which features several improvements and better configurability. The major changes in version 2.8.3, with respect to 2.8.2, are: - Improved concurrency: several fixes took place to allow swift handling of hundreds of simultaneous users; - Stack-safe mode: a new parameter (stackSafe) allows switching the engine in a slower mode, which prevents stack overflows that could happen for some datasets and ontologies in the standard mode; - eLUBM: in stack-safe mode, SwiftOWLIM passes the Lite-1, Lite-5, DL-1, and DL-5 tests of the eLUBM benchmark on a desktop machine given 512MB. eLUBM is an extended version of the LUBM test: "Towards a Complete OWL Ontology Benchmark", [Li Ma et al], ESWC2006; OWLIM will be presented today (25th of May, 14:00 GMT) in the Developers Track of WWW2006, http://www2006.org/programme/ . Damyan Ognyanoff, Ontotext Lab, Sirma Group Corp. http://www.ontotext.com
Received on Thursday, 25 May 2006 10:59:26 UTC