This HTML5 document contains 33 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Subject Item

n9:this

foaf:made

n2:VOSSQLSPARQL

Subject Item

n5:this

sioc:creator_of

n2:VOSSQLSPARQL

Subject Item

n7:item

n6:services_of

n2:VOSSQLSPARQL

Subject Item

n14:this

sioc:creator_of

n2:VOSSQLSPARQL

Subject Item

n12:VOS

sioc:container_of

n2:VOSSQLSPARQL

atom:entry

n2:VOSSQLSPARQL

atom:contains

n2:VOSSQLSPARQL

Subject Item

n2:VOSRDF

sioc:links_to

n2:VOSSQLSPARQL

Subject Item

n2:VOSSQLSPARQL

rdf:type

atom:Entry sioct:Comment

dcterms:created

2017-06-13T05:41:28.125283

dcterms:modified

2017-06-13T05:41:28.125283

rdfs:label

VOSSQLSPARQL

foaf:maker

n9:this n19:this

dc:title

VOSSQLSPARQL

opl:isDescribedUsing

n11:rdf

sioc:has_creator

n14:this n5:this

sioc:content

%VOSWARNING% %META:TOPICINFO{author="DeeGerhardt" date="1144081525" format="1.1" version="1.1"}% %META:TOPICPARENT{name="VOSRDF"}% %VOSNAV% ---+ SPARQL Support in Virtuoso SQL ---+++ Data Types SPARQL needs to differentiate between names of nodes and any other data. To natively facilitate this, Virtuoso introduces a distinct SQL IRI data type. This is the unique id of a resource IRI, not to be confused with numbers, strings or other data. By making the IRI a first class citizen of SQL, Virtuoso avoids many of the problems traditionally found when mapping RDF to SQL, where special additional type flags are often used. Since Virtuoso SQL has always been typed at run time and has always featured an ANY data type, mapping operations on heterogeneous data from SPARQL to SQL is made easier and the inefficiency of extra type checking in SQL is avoided. Furthermore, Virtuoso has a SPARQL mode where automatic type casting is modified so as not to generate errors when regular SQL semantics require a cast failure to be signaled but SPARQL expects a silent failure. ---+++ SQL Compiler RDF querying is specially join intensive. Virtuoso recognizes joins between S and S and S and O where a merging AND of indices can be used instead of a loop join. This frequently converts random access to sequential access, for example when there is an AND of patterns where the S is a shared unknown and the P and O of the triples are given. Similar join order and loop invariant considerations apply to SPARQL as to SQL, thus the SPARQL implementation directly benefits from all the work done on SQL. There are additional plans to adjust the SQL cost model to specially sample the RDF data at compile time to better sense the cardinality of triple patterns, as standard SQL compiler statistics do not provide the requisite level of detail. Additionally, many specialized SQL constructs will be introduced for speeding up bulk load and such operations. %VOSCOPY% CategoryWebSite CategoryVirtuoso CategoryOpenSource

sioc:id

77bdd6f8df5cba7f06402c7a3fae3f18

sioc:link

n2:VOSSQLSPARQL

sioc:has_container

n12:VOS

n6:has_services

n7:item

atom:title

VOSSQLSPARQL

sioc:links_to

n2:CategoryVirtuoso n2:CategoryOpenSource n16:CategoryWebSite

atom:source

n12:VOS

atom:author

n9:this

atom:published

2017-06-13T05:41:28Z

atom:updated

2017-06-13T05:41:28Z

sioc:topic

n12:VOS