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1 © 2008 OpenLink Software, All rights reserved. SPARQL for Business Intelligence Orri Erling - Program Manager, Virtuoso 1
2 © 2008 OpenLink Software, All rights reserved. For The Data Web to Deliver Promise of limitless integration and analysis Existing SQL workloads should naturally fall within SPARQLs scope Surfing and joining between relational data and RDF should be seamless 2
3 © 2008 OpenLink Software, All rights reserved. What Is Missing? Aggregation Nested Queries Expressions 3
4 © 2008 OpenLink Software, All rights reserved. Mapped vs. Physical RDF Predicates are unspecified Combining lots off different data sources Lots of A-box inference (SameAs, Transitivity) Mapped is better, if: Can push all to RDBMS - about 10x faster Data is time-sensitive, frequently changing, very large Physical is better, if:
5 © 2008 OpenLink Software, All rights reserved. When defining mappings... Be careful when many tables make one entity - you may get lots of unions Make explicit IRI scheme to limit pointless joining Know what the mapper and SQL can and cannot optimize 5
6 © 2008 OpenLink Software, All rights reserved. Some Present Work Refining generated SQL There is no reason why SPARQL mapped should not equal SQL in performance, when going to single DBMS
7 © 2008 OpenLink Software, All rights reserved. Joining Between Mapped and Physical Special SQL logic is needed when joining IRI IDs of physical quads with IRI strings of virtual triples SameAs requires special attention 7
8 © 2008 OpenLink Software, All rights reserved. Use Cases OpenLink MIS All accounts, CRM, products, emails, support cases have URIs MusicBrainz OpenLink Data Spaces PHPbb, Mediawiki, Drupal, etc. 8
9 © 2008 OpenLink Software, All rights reserved. OpenLink Software Thank You! http://virtuoso.openlinksw.com
On The Evolution of Terms
The Basics of Efficient SQL Written for myself –Writing doesnt make you rich Proof of what works –and what doesnt Three parts: –Data Model Tuning –SQL.
© 2007 OpenLink Software, All rights reserved OpenLink Virtuoso - SQL & RDF RDF Views of SQL Data (Exposing SQL Data as RDF) Orri Erling Program Manager.
Virtuoso Product Family
© 2008 OpenLink Software, All rights reserved Open Conceptual Data Models Making the Conceptual Layer Real via HTTP based Linked Data (aka. Linked Data)
August 6, 2009 Joint Ontolog-OOR Panel 1 Ontology Repository Research Issues Joint Ontolog-OOR Panel Discussion Ken Baclawski August 6, 2009.
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Digital Repositories – Linked Open Data – the possible Role of D4Science Workshop, December 2010, FAO use cases A tool to create Linked Data providers.
Advanced SQL (part 1) CS263 Lecture 7.
Tuning Oracle SQL The Basics of Efficient SQLThe Basics of Efficient SQL Common Sense Indexing The Optimizer –Making SQL Efficient Finding Problem Queries.
RDF and RDB 1 Some slides adapted from a presentation by Ivan Herman at the Semantic Technology & Business Conference, 2012.
© 2007 OpenLink Software, All rights reserved Virtuoso Sponger Extracting RDF Structured Data from Non-RDF Sources.
© 2006 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice Use Case: Populating Business Objects.
Natural Data Clustering: Why Nested Loops Win So Often May, 2008 ©2008 Dan Tow, All rights reserved SingingSQL.
Store RDF Triples In A Scalable Way Liu Long & Liu Chunqiu.
Knowledge Graph: Connecting Big Data Semantics
Building and Analyzing Social Networks Web Data and Semantics in Social Network Applications Dr. Bhavani Thuraisingham February 15, 2013.
Michael Povolotsky CMSC491s/691s. What is Virtuoso? Virtuoso, known as Virtuoso Universal Server, is a multi-protocol RDBMS Includes an object-relational.
Chapter 14 An Overview of Query Optimization. Copyright © 2005 Pearson Addison-Wesley. All rights reserved Figure 14.1 Typical architecture for.
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