Kingsley Idehen's Blog Data Space

What?

A simple guide usable by any Perl developer seeking to exploit SPARQL without hassles.

Why?

SPARQL is a powerful query language, results serialization format, and an HTTP based data access protocol from the W3C. It provides a mechanism for accessing and integrating data across Deductive Database Systems (colloquially referred to as triple or quad stores in Semantic Web and Linked Data circles) -- database systems (or data spaces) that manage proposition oriented records in 3-tuple (triples) or 4-tuple (quads) form.

How?

SPARQL queries are actually HTTP payloads (typically). Thus, using a RESTful client-server interaction pattern, you can dispatch calls to a SPARQL compliant data server and receive a payload for local processing.

Steps:

1. Determine which SPARQL endpoint you want to access e.g. DBpedia or a local Virtuoso instance (typically: http://localhost:8890/sparql).
2. If using Virtuoso, and you want to populate its quad store using SPARQL, assign "SPARQL_SPONGE" privileges to user "SPARQL" (this is basic control, more sophisticated WebID based ACLs are available for controlling SPARQL access).

Script:

#
# Demonstrating use of a single query to populate a 
# Virtuoso Quad Store via Perl. 
#

# 
# HTTP URL is constructed accordingly with CSV query results format as the default via mime type.
#

use CGI qw/:standard/;
use LWP::UserAgent;
use Data::Dumper;
use Text::CSV_XS;

sub sparqlQuery(@args) {
  my $query=shift;
  my $baseURL=shift;
  my $format=shift;
	
	%params=(
		"default-graph" => "", "should-sponge" => "soft", "query" => $query,
		"debug" => "on", "timeout" => "", "format" => $format,
		"save" => "display", "fname" => ""
	);
	
	@fragments=();
	foreach $k (keys %params) {
		$fragment="$k=".CGI::escape($params{$k});
		push(@fragments,$fragment);
	}
	$query=join("&", @fragments);
	
	$sparqlURL="${baseURL}?$query";
	
	my $ua = LWP::UserAgent->new;
	$ua->agent("MyApp/0.1 ");
	my $req = HTTP::Request->new(GET => $sparqlURL);
	my $res = $ua->request($req);
	$str=$res->content;
	
	$csv = Text::CSV_XS->new();
	
	foreach $line ( split(/^/, $str) ) {
		$csv->parse($line);
		@bits=$csv->fields();
	  push(@rows, [ @bits ] );
	}
	return \@rows;
}


# Setting Data Source Name (DSN)

$dsn="http://dbpedia.org/resource/DBpedia";

# Virtuoso pragmas for instructing SPARQL engine to perform an HTTP GET using the IRI in
# FROM clause as Data Source URL en route to DBMS
# record Inserts.

$query="DEFINE get:soft \"replace\"\n

# Generic (non Virtuoso specific SPARQL
# Note: this will not add records to the 
# DBMS 

SELECT DISTINCT * FROM <$dsn> WHERE {?s ?p ?o}"; 

$data=sparqlQuery($query, "http://localhost:8890/sparql/", "text/csv");

print "Retrieved data:\n";
print Dumper($data);

Output

Retrieved data:
$VAR1 = [
          [
            's',
            'p',
            'o'
          ],
          [
            'http://dbpedia.org/resource/DBpedia',
            'http://www.w3.org/1999/02/22-rdf-syntax-ns#type',
            'http://www.w3.org/2002/07/owl#Thing'
          ],
          [
            'http://dbpedia.org/resource/DBpedia',
            'http://www.w3.org/1999/02/22-rdf-syntax-ns#type',
            'http://dbpedia.org/ontology/Work'
          ],
          [
            'http://dbpedia.org/resource/DBpedia',
            'http://www.w3.org/1999/02/22-rdf-syntax-ns#type',
            'http://dbpedia.org/class/yago/Software106566077'
          ],
...

Conclusion

CSV was chosen over XML (re. output format) since this is about a "no-brainer installation and utilization" guide for a Perl developer that already knows how to use Perl for HTTP based data access within HTML. SPARQL just provides an added bonus to URL dexterity (delivered via URI abstraction) with regards to constructing Data Source Names or Addresses.

Related

• RDF::Query::Client Guide
• SPARQL Guide for the Perl Developer
• SPARQL Guide for the PHP Developer
• SPARQL Guide for the Python Developer
• SPARQL Guide for the Ruby Developer
• Simple Guide for using SPARQL with Virtuoso
• General SPARQL Tutorial Collection
• Virtuoso Specific SPARQL Tutorial Collection
• The URI, URL, and Linked Data Meme's Generic HTTP URI.

What?

A simple guide usable by any Javascript developer seeking to exploit SPARQL without hassles.

Why?

SPARQL is a powerful query language, results serialization format, and an HTTP based data access protocol from the W3C. It provides a mechanism for accessing and integrating data across Deductive Database Systems (colloquially referred to as triple or quad stores in Semantic Web and Linked Data circles) -- database systems (or data spaces) that manage proposition oriented records in 3-tuple (triples) or 4-tuple (quads) form.

How?

SPARQL queries are actually HTTP payloads (typically). Thus, using a RESTful client-server interaction pattern, you can dispatch calls to a SPARQL compliant data server and receive a payload for local processing.

Steps:

1. Determine which SPARQL endpoint you want to access e.g. DBpedia or a local Virtuoso instance (typically: http://localhost:8890/sparql).
2. If using Virtuoso, and you want to populate its quad store using SPARQL, assign "SPARQL_SPONGE" privileges to user "SPARQL" (this is basic control, more sophisticated WebID based ACLs are available for controlling SPARQL access).

Script:

/*
Demonstrating use of a single query to populate a # Virtuoso Quad Store via Javascript. 
*/

/* 
HTTP URL is constructed accordingly with JSON query results format as the default via mime type.
*/

function sparqlQuery(query, baseURL, format) {
	if(!format)
		format="application/json";
	var params={
		"default-graph": "", "should-sponge": "soft", "query": query,
		"debug": "on", "timeout": "", "format": format,
		"save": "display", "fname": ""
	};
	
	var querypart="";
	for(var k in params) {
		querypart+=k+"="+encodeURIComponent(params[k])+"&";
	}
	var queryURL=baseURL + '?' + querypart;
	if (window.XMLHttpRequest) {
  	xmlhttp=new XMLHttpRequest();
  }
  else {
  	xmlhttp=new ActiveXObject("Microsoft.XMLHTTP");
  }
  xmlhttp.open("GET",queryURL,false);
  xmlhttp.send();
  return JSON.parse(xmlhttp.responseText);
}

/*
setting Data Source Name (DSN)
*/

var dsn="http://dbpedia.org/resource/DBpedia";

/*
Virtuoso pragma "DEFINE get:soft "replace" instructs Virtuoso SPARQL engine to perform an HTTP GET using the IRI in FROM clause as Data Source URL with regards to 
DBMS record inserts
*/

var query="DEFINE get:soft \"replace\"\nSELECT DISTINCT * FROM <"+dsn+"> WHERE {?s ?p ?o}"; 
var data=sparqlQuery(query, "/sparql/");

Output

Place the snippet above into the <script/> section of an HTML document to see the query result.

Conclusion

JSON was chosen over XML (re. output format) since this is about a "no-brainer installation and utilization" guide for a Javascript developer that already knows how to use Javascript for HTTP based data access within HTML. SPARQL just provides an added bonus to URL dexterity (delivered via URI abstraction) with regards to constructing Data Source Names or Addresses.

Related

• SPARQL Guide for the PHP Developer
• SPARQL Guide for the Python Developer
• SPARQL Guide for the Ruby Developer
• Simple Guide for using SPARQL with Virtuoso
• General SPARQL Tutorial Collection
• Virtuoso Specific SPARQL Tutorial Collection
• The URI, URL, and Linked Data Meme's Generic HTTP URI.

What?

A simple guide usable by any Javascript developer seeking to exploit SPARQL without hassles.

Why?

SPARQL is a powerful query language, results serialization format, and an HTTP based data access protocol from the W3C. It provides a mechanism for accessing and integrating data across Deductive Database Systems (colloquially referred to as triple or quad stores in Semantic Web and Linked Data circles) -- database systems (or data spaces) that manage proposition oriented records in 3-tuple (triples) or 4-tuple (quads) form.

How?

SPARQL queries are actually HTTP payloads (typically). Thus, using a RESTful client-server interaction pattern, you can dispatch calls to a SPARQL compliant data server and receive a payload for local processing.

Steps:

1. Determine which SPARQL endpoint you want to access e.g. DBpedia or a local Virtuoso instance (typically: http://localhost:8890/sparql).
2. If using Virtuoso, and you want to populate its quad store using SPARQL, assign "SPARQL_SPONGE" privileges to user "SPARQL" (this is basic control, more sophisticated WebID based ACLs are available for controlling SPARQL access).

Script:

/*
Demonstrating use of a single query to populate a # Virtuoso Quad Store via Javascript. 
*/

/* 
HTTP URL is constructed accordingly with JSON query results format as the default via mime type.
*/

function sparqlQuery(query, baseURL, format) {
	if(!format)
		format="application/json";
	var params={
		"default-graph": "", "should-sponge": "soft", "query": query,
		"debug": "on", "timeout": "", "format": format,
		"save": "display", "fname": ""
	};
	
	var querypart="";
	for(var k in params) {
		querypart+=k+"="+encodeURIComponent(params[k])+"&";
	}
	var queryURL=baseURL + '?' + querypart;
	if (window.XMLHttpRequest) {
  	xmlhttp=new XMLHttpRequest();
  }
  else {
  	xmlhttp=new ActiveXObject("Microsoft.XMLHTTP");
  }
  xmlhttp.open("GET",queryURL,false);
  xmlhttp.send();
  return JSON.parse(xmlhttp.responseText);
}

/*
setting Data Source Name (DSN)
*/

var dsn="http://dbpedia.org/resource/DBpedia";

/*
Virtuoso pragma "DEFINE get:soft "replace" instructs Virtuoso SPARQL engine to perform an HTTP GET using the IRI in FROM clause as Data Source URL with regards to 
DBMS record inserts
*/

var query="DEFINE get:soft \"replace\"\nSELECT DISTINCT * FROM <"+dsn+"> WHERE {?s ?p ?o}"; 
var data=sparqlQuery(query, "/sparql/");

Output

Place the snippet above into the <script/> section of an HTML document to see the query result.

Conclusion

JSON was chosen over XML (re. output format) since this is about a "no-brainer installation and utilization" guide for a Javascript developer that already knows how to use Javascript for HTTP based data access within HTML. SPARQL just provides an added bonus to URL dexterity (delivered via URI abstraction) with regards to constructing Data Source Names or Addresses.

Related

• SPARQL Guide for the PHP Developer
• SPARQL Guide for the Python Developer
• SPARQL Guide for the Ruby Developer
• Simple Guide for using SPARQL with Virtuoso
• General SPARQL Tutorial Collection
• Virtuoso Specific SPARQL Tutorial Collection
• The URI, URL, and Linked Data Meme's Generic HTTP URI.

What?

A simple guide usable by any PHP developer seeking to exploit SPARQL without hassles.

Why?

SPARQL is a powerful query language, results serialization format, and an HTTP based data access protocol from the W3C. It provides a mechanism for accessing and integrating data across Deductive Database Systems (colloquially referred to as triple or quad stores in Semantic Web and Linked Data circles) -- database systems (or data spaces) that manage proposition oriented records in 3-tuple (triples) or 4-tuple (quads) form.

How?

SPARQL queries are actually HTTP payloads (typically). Thus, using a RESTful client-server interaction pattern, you can dispatch calls to a SPARQL compliant data server and receive a payload for local processing e.g. local object binding re. PHP.

Steps:

1. From your command line execute: aptitude search '^PHP26', to verify PHP is in place
2. Determine which SPARQL endpoint you want to access e.g. DBpedia or a local Virtuoso instance (typically: http://localhost:8890/sparql).
3. If using Virtuoso, and you want to populate its quad store using SPARQL, assign "SPARQL_SPONGE" privileges to user "SPARQL" (this is basic control, more sophisticated WebID based ACLs are available for controlling SPARQL access).

Script:

#!/usr/bin/env php
<?php
#
# Demonstrating use of a single query to populate a # Virtuoso Quad Store via PHP. 
#

# HTTP URL is constructed accordingly with JSON query results format in mind.

function sparqlQuery($query, $baseURL, $format="application/json")

  {
	$params=array(
		"default-graph" =>  "",
		"should-sponge" =>  "soft",
		"query" =>  $query,
		"debug" =>  "on",
		"timeout" =>  "",
		"format" =>  $format,
		"save" =>  "display",
		"fname" =>  ""
	);

	$querypart="?";	
	foreach($params as $name => $value) 
  {
		$querypart=$querypart . $name . '=' . urlencode($value) . "&";
	}
	
	$sparqlURL=$baseURL . $querypart;
	
	return json_decode(file_get_contents($sparqlURL));
};



# Setting Data Source Name (DSN)
$dsn="http://dbpedia.org/resource/DBpedia";

#Virtuoso pragmas for instructing SPARQL engine to perform an HTTP GET
#using the IRI in FROM clause as Data Source URL

$query="DEFINE get:soft \"replace\"
SELECT DISTINCT * FROM <$dsn> WHERE {?s ?p ?o}"; 

$data=sparqlQuery($query, "http://localhost:8890/sparql/");

print "Retrieved data:\n" . json_encode($data);

?>

Output

Retrieved data:
  {"head":
  {"link":[],"vars":["s","p","o"]},
  "results":
		{"distinct":false,"ordered":true,
		"bindings":[
			{"s":
			{"type":"uri","value":"http:\/\/dbpedia.org\/resource\/DBpedia"},"p":
			{"type":"uri","value":"http:\/\/www.w3.org\/1999\/02\/22-rdf-syntax-ns#type"},"o":
			{"type":"uri","value":"http:\/\/www.w3.org\/2002\/07\/owl#Thing"}},
			{"s":
			{"type":"uri","value":"http:\/\/dbpedia.org\/resource\/DBpedia"},"p":
			{"type":"uri","value":"http:\/\/www.w3.org\/1999\/02\/22-rdf-syntax-ns#type"},"o":
			{"type":"uri","value":"http:\/\/dbpedia.org\/ontology\/Work"}},
			{"s":
			{"type":"uri","value":"http:\/\/dbpedia.org\/resource\/DBpedia"},"p":
			{"type":"uri","value":"http:\/\/www.w3.org\/1999\/02\/22-rdf-syntax-ns#type"},"o":
			{"type":"uri","value":"http:\/\/dbpedia.org\/class\/yago\/Software106566077"}},
...

Conclusion

JSON was chosen over XML (re. output format) since this is about a "no-brainer installation and utilization" guide for a PHP developer that already knows how to use PHP for HTTP based data access. SPARQL just provides an added bonus to URL dexterity (delivered via URI abstraction) with regards to constructing Data Source Names or Addresses.

Related

• SPARQL Guide for the Python Developer
• SPARQL Guide for the Ruby Developer
• Simple Guide for using SPARQL with Virtuoso
• General SPARQL Tutorial Collection
• Virtuoso Specific SPARQL Tutorial Collection
• The URI, URL, and Linked Data Meme's Generic HTTP URI.

What?

A simple guide usable by any Python developer seeking to exploit SPARQL without hassles.

Why?

SPARQL is a powerful query language, results serialization format, and an HTTP based data access protocol from the W3C. It provides a mechanism for accessing and integrating data across Deductive Database Systems (colloquially referred to as triple or quad stores in Semantic Web and Linked Data circles) -- database systems (or data spaces) that manage proposition oriented records in 3-tuple (triples) or 4-tuple (quads) form.

How?

SPARQL queries are actually HTTP payloads (typically). Thus, using a RESTful client-server interaction pattern, you can dispatch calls to a SPARQL compliant data server and receive a payload for local processing e.g. local object binding re. Python.

Steps:

1. From your command line execute: aptitude search '^python26', to verify Python is in place
2. Determine which SPARQL endpoint you want to access e.g. DBpedia or a local Virtuoso instance (typically: http://localhost:8890/sparql).
3. If using Virtuoso, and you want to populate its quad store using SPARQL, assign "SPARQL_SPONGE" privileges to user "SPARQL" (this is basic control, more sophisticated WebID based ACLs are available for controlling SPARQL access).

Script:

#!/usr/bin/env python
#
# Demonstrating use of a single query to populate a # Virtuoso Quad Store via Python. 
#

import urllib, json

# HTTP URL is constructed accordingly with JSON query results format in mind.

def sparqlQuery(query, baseURL, format="application/json"):
	params={
		"default-graph": "",
		"should-sponge": "soft",
		"query": query,
		"debug": "on",
		"timeout": "",
		"format": format,
		"save": "display",
		"fname": ""
	}
	querypart=urllib.urlencode(params)
	response = urllib.urlopen(baseURL,querypart).read()
	return json.loads(response)

# Setting Data Source Name (DSN)
dsn="http://dbpedia.org/resource/DBpedia"

# Virtuoso pragmas for instructing SPARQL engine to perform an HTTP GET
# using the IRI in FROM clause as Data Source URL

query="""DEFINE get:soft "replace"
SELECT DISTINCT * FROM <%s> WHERE {?s ?p ?o}""" % dsn 

data=sparqlQuery(query, "http://localhost:8890/sparql/")

print "Retrieved data:\n" + json.dumps(data, sort_keys=True, indent=4)

#
# End

Output

Retrieved data:
{
    "head": {
        "link": [], 
        "vars": [
            "s", 
            "p", 
            "o"
        ]
    }, 
    "results": {
        "bindings": [
            {
                "o": {
                    "type": "uri", 
                    "value": "http://www.w3.org/2002/07/owl#Thing"
                }, 
                "p": {
                    "type": "uri", 
                    "value": "http://www.w3.org/1999/02/22-rdf-syntax-ns#type"
                }, 
                "s": {
                    "type": "uri", 
                    "value": "http://dbpedia.org/resource/DBpedia"
                }
            }, 
...

Conclusion

JSON was chosen over XML (re. output format) since this is about a "no-brainer installation and utilization" guide for a Python developer that already knows how to use Python for HTTP based data access. SPARQL just provides an added bonus to URL dexterity (delivered via URI abstraction) with regards to constructing Data Source Names or Addresses.

Related

• SPARQL Guide for the Ruby Developer
• Simple Guide for using SPARQL with Virtuoso
• General SPARQL Tutorial Collection
• Virtuoso Specific SPARQL Tutorial Collection
• The URI, URL, and Linked Data Meme's Generic HTTP URI.

What?

A simple guide usable by any Python developer seeking to exploit SPARQL without hassles.

Why?

SPARQL is a powerful query language, results serialization format, and an HTTP based data access protocol from the W3C. It provides a mechanism for accessing and integrating data across Deductive Database Systems (colloquially referred to as triple or quad stores in Semantic Web and Linked Data circles) -- database systems (or data spaces) that manage proposition oriented records in 3-tuple (triples) or 4-tuple (quads) form.

How?

SPARQL queries are actually HTTP payloads (typically). Thus, using a RESTful client-server interaction pattern, you can dispatch calls to a SPARQL compliant data server and receive a payload for local processing e.g. local object binding re. Python.

Steps:

1. From your command line execute: aptitude search '^python26', to verify Python is in place
2. Determine which SPARQL endpoint you want to access e.g. DBpedia or a local Virtuoso instance (typically: http://localhost:8890/sparql).
3. If using Virtuoso, and you want to populate its quad store using SPARQL, assign "SPARQL_SPONGE" privileges to user "SPARQL" (this is basic control, more sophisticated WebID based ACLs are available for controlling SPARQL access).

Script:

#!/usr/bin/env python
#
# Demonstrating use of a single query to populate a # Virtuoso Quad Store via Python. 
#

import urllib, json

# HTTP URL is constructed accordingly with JSON query results format in mind.

def sparqlQuery(query, baseURL, format="application/json"):
	params={
		"default-graph": "",
		"should-sponge": "soft",
		"query": query,
		"debug": "on",
		"timeout": "",
		"format": format,
		"save": "display",
		"fname": ""
	}
	querypart=urllib.urlencode(params)
	response = urllib.urlopen(baseURL,querypart).read()
	return json.loads(response)

# Setting Data Source Name (DSN)
dsn="http://dbpedia.org/resource/DBpedia"

# Virtuoso pragmas for instructing SPARQL engine to perform an HTTP GET
# using the IRI in FROM clause as Data Source URL

query="""DEFINE get:soft "replace"
SELECT DISTINCT * FROM <%s> WHERE {?s ?p ?o}""" % dsn 

data=sparqlQuery(query, "http://localhost:8890/sparql/")

print "Retrieved data:\n" + json.dumps(data, sort_keys=True, indent=4)

#
# End

Output

Retrieved data:
{
    "head": {
        "link": [], 
        "vars": [
            "s", 
            "p", 
            "o"
        ]
    }, 
    "results": {
        "bindings": [
            {
                "o": {
                    "type": "uri", 
                    "value": "http://www.w3.org/2002/07/owl#Thing"
                }, 
                "p": {
                    "type": "uri", 
                    "value": "http://www.w3.org/1999/02/22-rdf-syntax-ns#type"
                }, 
                "s": {
                    "type": "uri", 
                    "value": "http://dbpedia.org/resource/DBpedia"
                }
            }, 
...

Conclusion

JSON was chosen over XML (re. output format) since this is about a "no-brainer installation and utilization" guide for a Python developer that already knows how to use Python for HTTP based data access. SPARQL just provides an added bonus to URL dexterity (delivered via URI abstraction) with regards to constructing Data Source Names or Addresses.

Related

• SPARQL Guide for the Ruby Developer
• Simple Guide for using SPARQL with Virtuoso
• General SPARQL Tutorial Collection
• Virtuoso Specific SPARQL Tutorial Collection
• The URI, URL, and Linked Data Meme's Generic HTTP URI.

- Produce RDF Linked Data from non RDF Data Sources (Heterogeneous SQL, XML, Web Services)

- Provide highly scalable RDF Data Management via a Quad Store (DBpedia is an example of a live demonstration)

- Sophisticated Deployment of Linked Data that exploits the power of SPARQL

- Powerful WebDAV innovations that simplify read-write mode interaction with Linked Data

- Use Web Data Virtualization to address the pain and frustration associated with Web Data Silos (e.g. OpenLink Data Spaces layer stop Virtuoso that delivers Personal Data Spaces / Unified Storage in the Clouds)

- Deliver a Linked Data development and deployment platform to .NET (VB, C#) , Java, PHP, Ruby, Perl, Python, 'C', C++, and other developers

- More...

Daniel lewis has penned a variation of post about Linked Data enabling PHP applications such as: Wordpress, phpBB3, MediaWiki etc.

Daniel simplifies my post by using diagrams to depict the different paths for PHP based applications exposing Linked Data - especially those that already provide a significant amount of the content that drives Web 2.0.

If all the content in Web 2.0 information resources are distillable into discrete data objects endowed with HTTP based IDs (URIs), with zero "RDF handcrafting Tax", what do we end up with? A Giant Global Graph of Linked Data; the Web as a Database.

So, what used to apply exclusively, within enterprise settings re. Oracle, DB2, Informix, Ingres, Sybase, Microsoft SQL Server, MySQL, PostrgeSQL, Progress Open Edge, Firebird, and others, now applies to the Web. The Web becomes the "Distributed Database Bus" that connects database records across disparate databases (or Data Spaces). These databases manage and expose records that are remotely accessible "by reference" via HTTP.

As I've stated at every opportunity in the past, Web 2.0 is the greatest thing that every happened to the Semantic Web vision :-) Without the "Web 2.0 Data Silo Conundrum" we wouldn't have the cry for "Data Portability" that brings a lot of clarity to some fundamental Web 2.0 limitations that end-users ultimately find unacceptable.

In the late '80s, the SQL Access Group (now part of X/Open) addressed a similar problem with RDBMS silos within the enterprise that lead to the SAG CLI which is exists today as Open Database Connectivity.

In a sense we now have WODBC (Web Open Database Connectivity), comprised of Web Services based CLIs and/or traditional back-end DBMS CLIs (ODBC, JDBC, ADO.NET, OLE-DB, or Native), Query Language (SPARQL Query Language), and a Wire Protocol (HTTP based SPARQL Protocol) delivering Web infrastructure equivalents of SQL and RDA, but much better, and with much broader scope for delivering profound value due to the Web's inherent openness. Today's PHP, Python, Ruby, Tcl, Perl, ASP.NET developer is the enterprise 4GL developer of yore, without enterprise confinement. We could even be talking about 5GL development once the Linked Data interaction is meshed with dynamic languages (delivering higher levels of abstraction at the language and data interaction levels). Even the underlying schemas and basic design will evolve from Closed World (solely) to a mesh of Closed & Open World view schemas.

SPARQL with SQL (Inline)

Virtuoso extends its SQL3 implementation with syntax for integrating SPARQL into queries and subqueries.Thus, as part of a SQL SELECT query or subquery, one can write the SPARQL keyword and a SPARQL query as part of query text processed by Virtuoso's SQL Query Processor.

Example 1 (basic) :

Using Virtuoso's Command line or the Web Based ISQL utility type in the following (note: "SQL>" is the command line prompt for the native ISQL utility):

SQL> sparql select distinct ?p where { graph ?g { ?s ?p ?o } };

Which will return the following:

	  p varchar
     ----------
     http://example.org/ns#b
     http://example.org/ns#d
     http://xmlns.com/foaf/0.1/name
     http://xmlns.com/foaf/0.1/mbox
     ...   

Example 2 (a subquery variation):

SQL> select distinct subseq (p, strchr (p, '#')) as fragment
 from (sparql select distinct ?p where { graph ?g { ?s ?p ?o } } ) as all_predicates
 where p like '%#%' ;

     fragment varchar
     ----------
     #query
     #data
     #name
     #comment
     ...

Parameterized Queries:

You can pass parameters to a SPARQL query using a Virtuoso-specific syntax extension. '??' or '$?' indicates a positional parameter similar to '?' in standard SQL. '??' can be used in graph patterns or anywhere else where a SPARQL variable is accepted. The value of a parameter should be passed in SQL form, i.e. this should be a number or an untyped string. An IRI ID can not be passed, but an absolute IRI can. Using this notation, a dynamic SQL capable client (ODBC, JDBC, ADO.NET, OLEDB, XMLA, or others) can execute parametrized SPARQL queries using parameter binding concepts that are common place in dynamic SQL. Which implies that existing SQL applications and development environments (PHP, Ruby, Python, Perl, VB, C#, Java, etc.) are capable of issuing SPARQL queries via their existing SQL bound data access channels against RDF Data stored in Virtuoso.

Note: This is the Virtuoso equivalent of a recently published example using Jena (a Java based RDF Triple Store).

Example:

Create a Virtuoso Function by execting the following:

SQL> create function param_passing_demo ();
 {
 	declare stat, msg varchar;
 	declare mdata, rset any;
 	exec ('sparql select ?s where { graph ?g { ?s ?? ?? }}',
 			stat, msg,
 			vector ('http://www.w3.org/2001/sw/DataAccess/tests/data/Sorting/sort-0#int1',
 		  		   4 ),	-- Vector of two parameters 
			10,			-- Max. result-set rows
			mdata, 		-- Variable for handling result-set metadata
 		 	rset   		-- Variable for handling query result-set
		 ); 
     return rset[0][0];
 }

SQL> select param_passing_demo ();

Which returns:

callret VARCHAR
 _______________________________________________________________________________

http://www.w3.org/2001/sw/DataAccess/tests/data/Sorting/sort-0#four

1 Rows. -- 00000 msec.

Using SPARQL in SQL Predicates:

A SPARQL ASK query can be used as an argument of the SQL EXISTS predicate.

create function sparql_ask_demo () returns varchar
  {
 		if (exists (sparql ask where { graph ?g { ?s ?p 4}})) return 'YES';
 		else return 'NO';
   };

Test by executing:

SQL> select sparql_ask_demo ();

Which returns:

_________________________
YES