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Virtuoso Sesame Provider

What is Sesame

Sesame is an open source Java framework for storing, querying, and reasoning with RDF and RDF Schema. It can be used as a database for RDF and RDF Schema, or as a Java library for applications that need to work with RDF internally. For example, suppose you need to read a big RDF file, find the relevant information for your application, and use that information. Sesame provides you with the necessary tools to parse, interpret, query, and store all this information, embedded in your own application if you want, or, if you prefer, in a separate database or even on a remote server. More generally: Sesame provides an application developer with a toolbox that contains useful hammers, screwdrivers, etc., for 'Do-It-Yourself' projects with RDF.

What is the Virtuoso Sesame Provider

The Virtuoso Sesame Provider is a fully operational Native Graph Model Storage Provider for the Sesame Framework, allowing users of Virtuoso to leverage the Sesame framework to modify, query, and reason with the Virtuoso quad store using the Java language. The Sesame Repository API offers a central access point for connecting to the Virtuoso quad store. Its purpose is to provides a Java-friendly access point to Virtuoso. It offers various methods for querying and updating the data, while abstracting the details of the underlying machinery. The Provider has been tested against the two latest currently available versions, Sesame 2.6.x and 2.7.x.

Fig. 1 Sesame Component Stack Sesame Component Stack

If you need more information about how to set up your environment for working with the Sesame APIs, take a look at Chapter 4 of the Sesame User Guide, Setting up to use the Sesame libraries.

Setup

Required Files

This tutorial assumes you have Virtuoso server installed and that the database is accessible at http://localhost:1111/. In addition, you will need the latest version of the Virtuoso Sesame Provider, and Sesame 2 or greater installed.

You should download the Virtuoso Sesame 2 Provider JAR archive for the version of Sesame being used, Virtuoso JDBC Driver, Sesame Framework and associated classes and sample programs from our download page. Note the version of the Sesame Provider (virt_sesame2.jar) can be determined with the command:

$ java -jar virt_sesame2.jar
OpenLink Virtuoso(TM) Provider for Sesame2(TM) Version 2.6.5 [Build 1.7]

Compiling Sesame 2 Sample Program

  1. Ensure that full paths to the following files, or equivalents for your version of Sesame, are all included in the active CLASSPATH setting --
    • openrdf-sesame-2.1.2-onejar.jar
    • slf4j-api-1.5.0.jar
    • slf4j-jdk14-1.5.0.jar
    • virtjdbc3.jar
    • virt_sesame2.jar
  2. Execute the following command --

    javac VirtuosoTest.java

    • Note: we recommend adding the following to the connect string, to use utf-8 and row-auto-commit:

      "/charset=UTF-8/log_enable=2"

      -- i.e., in VirtuosoTest.java, the line --

      Repository repository = new VirtuosoRepository("jdbc:virtuoso://" + sa[0] + ":" + sa[1], sa[2], sa[3]);

      -- should become --

      Repository repository = new VirtuosoRepository("jdbc:virtuoso://" + sa[0] + ":" + sa[1]+ "/charset=UTF-8/log_enable=2", sa[2], sa[3]);

Testing

  1. Ensure that full paths to the following files are all included in the active CLASSPATH setting (note the addition of virtuoso_driver, here) --
    • openrdf-sesame-2.1.2-onejar.jar
    • slf4j-api-1.5.0.jar
    • slf4j-jdk14-1.5.0.jar
    • virtjdbc3.jar
    • virt_sesame2.jar
    • virtuoso_driver
  2. Run the VirtuosoTest program to test the Sesame 2 Provider with the following command --

    java VirtuosoTest <hostname> <port> <uid> <pwd>

  3. The test run should look like this --

    $ java VirtuosoTest localhost 1111 dba dba == TEST 1: : Start Loading data from URL: http://www.openlinksw.com/dataspace/person/kidehen@openlinksw.com/foaf.rdf == TEST 1: : End PASSED: TEST 1 == TEST 2: : Start Clearing triple store == TEST 2: : End PASSED: TEST 2 == TEST 3: : Start Loading data from file: virtuoso_driver/data.nt == TEST 3: : End PASSED: TEST 3 == TEST 4: : Start Loading UNICODE single triple == TEST 4: : End PASSED: TEST 4 == TEST 5: : Start Loading single triple == TEST 5: : End PASSED: TEST 5 == TEST 6: : Start Casted value type == TEST 6: : End PASSED: TEST 6 == TEST 7: : Start Selecting property == TEST 7: : End PASSED: TEST 7 == TEST 8: : Start Statement does not exists == TEST 8: : End PASSED: TEST 8 == TEST 9: : Start Statement exists (by resultset size) == TEST 9: : End PASSED: TEST 9 == TEST 10: : Start Statement exists (by hasStatement()) == TEST 10: : End PASSED: TEST 10 == TEST 11: : Start Retrieving namespaces == TEST 11: : End PASSED: TEST 11 == TEST 12: : Start Retrieving statement (http://myopenlink.net/dataspace/person/kidehen http://myopenlink.net/foaf/name null) == TEST 12: : End PASSED: TEST 12 == TEST 13: : Start Writing the statements to file: (/Users/src/virtuoso-opensource/binsrc/sesame2/results.n3.txt) == TEST 13: : End PASSED: TEST 13 == TEST 14: : Start Retrieving graph ids == TEST 14: : End PASSED: TEST 14 == TEST 15: : Start Retrieving triple store size == TEST 15: : End PASSED: TEST 15 == TEST 16: : Start Sending ask query == TEST 16: : End PASSED: TEST 16 == TEST 17: : Start Sending construct query == TEST 17: : End PASSED: TEST 17 == TEST 18: : Start Sending describe query == TEST 18: : End PASSED: TEST 18 ============================ PASSED:18 FAILED:0

Getting Started

This section covers the essentials for connecting to and manipulating data stored in a Virtuoso repository using the Sesame API. More information on the Sesame Framework, including extended examples on how to use the API, can be found in Chapter 8 of the Sesame User's guide, the RepositoryConnection API.

The interfaces for the Repository API can be found in packages virtuoso.sesame2.driver and org.openrdf.repository. Several implementations for these interfaces exist in the Virtuoso Provider download package. The Javadoc reference for the Sesame API is available online and can also be found in the doc directory of the download.

Creating a Virtuoso Repository RDF object

The first step to connecting to Virtuoso through the Sesame API is to create a Repository for it. The Repository object operates on (stacks of) Sail object(s) for storage and retrieval of RDF data.

One of the simplest configurations is a repository that just stores RDF data in main memory, without applying any inference. This is also by far the fastest type of repository that can be used. The following code creates and initialize a non-inferencing main-memory repository:

import virtuoso.sesame2.driver.VirtuosoRepository;

Repository myRepository = VirtuosoRepository("jdbc:virtuoso://localhost:1111","dba","dba");

myRepository.initialize();

The constructor of the VirtuosoRepository class accepts the JDBC URL of the Virtuoso engine, and the username and password of an authorized user. Following this example, the repository needs to be initialized to prepare the Sail(s) that it operates on, which includes performing operations such as restoring previously stored data, setting up connections to a relational database, etc.

The repository that is created by the above code is volatile: its contents are lost when the object is garbage collected or when the program is shut down. This is fine for cases where, for example, the repository is used as a means for manipulating an RDF model in memory.

Creating a Virtuoso Repository Connection

Now that we have created a VirtuosoRepository object instance, we want to do something with it. This is achieved through the use of the VirtuosoRepositoryConnection class, which can be created by the VirtuosoRepository class.

A VirtuosoRepositoryConnection represents — as the name suggests — a connection to the actual Virtuoso quad store. We can issue operations over this connection, and close it when we are done to make sure we are not keeping resources unnecessarily occupied.

In the following sections, we will show some examples of basic operations using the Northwind dataset.

Adding RDF to Virtuoso

The Repository implements the Sesame Repository API, which offers various methods for adding data to a repository. Data can be added programmatically by specifying the location of a file that contains RDF data, and statements can be added individually or in collections.

We perform operations on the repository by requesting a RepositoryConnection from the repository, which returns a VirtuosoRepositoryConnection object. On this VirtuosoRepositoryConnection object we can perform the various operations, such as query evaluation; getting, adding, or removing statements; etc.

The following example code adds two files, one local and one located on the Web, to a repository:

import org.openrdf.repository.RepositoryException;

import org.openrdf.repository.Repository;

import org.openrdf.repository.RepositoryConnection;

import org.openrdf.rio.RDFFormat;

import java.io.File;

import java.net.URL;

File file = new File("/path/to/example.rdf");

String baseURI = "http://example.org/example/localRDF";

…
try {

   RepositoryConnection con = myRepository.getConnection();

   try {

      con.add(file, baseURI, RDFFormat.RDFXML);

      URL url = new URL("http://example.org/example/remoteRDF");

      con.add(url, url.toString(), RDFFormat.RDFXML);

   }

   finally {

      con.close();

   }

}

catch (RepositoryException rex) {

   // handle exception

}

catch (java.io.IOEXception e) {

   // handle io exception

}

More information on other available methods can be found in the javadoc reference of the RepositoryConnection interface.

Querying Virtuoso

The Repository API has a number of methods for creating and evaluating queries. Three types of queries are distinguished: tuple queries, graph queries, and Boolean queries. The query types differ in the type of results that they produce.

Select Query: The result of a select query is a set of tuples (or variable bindings), where each tuple represents a solution of the query. This type of query is commonly used to get specific values (URIs, blank nodes, literals) from the stored RDF data. The method QueryFactory.executeQuery() returns a Value [ ][ ] for SPARQL "SELECT" queries. The method QueryFactory.executeQuery() also calls the QueryFactory.setResult() which populates a set of tuples for SPARQL "SELECT" queries. The graph can be retrieved using QueryFactory.getBooleanResult().

Graph Query: The result of a graph query is an RDF graph (or set of statements). This type of query is very useful for extracting sub-graphs from the stored RDF data, which can then be queried further, serialized to an RDF document, etc. The method QueryFactory.executeQuery() calls the QueryFactory.setGraphResult() which populates a graph for SPARQL "DESCRIBE" and "CONSTRUCT" queries. The graph can be retrieved using QueryFactory.getGraphResult().

Boolean Query: The result of a Boolean query is a simple Boolean value, i.e., TRUE or FALSE. This type of query can be used to check if a repository contains specific information. The method QueryFactory.executeQuery() calls the QueryFactory.setBooleanResult() which sets a Boolean value for SPARQL "ASK" queries. The value can be retrieved using QueryFactory.getBooleanResult().

Note: Although Sesame 2 currently supports two query languages: SeRQL and SPARQL, the Virtuoso provider only supports the W3C SPARQL specification at this time.

Evaluating a SELECT Query

To evaluate a tuple query we simply do the following:

import java.util.List;

import org.openrdf.OpenRDFException;

import org.openrdf.repository.RepositoryConnection;

import org.openrdf.query.TupleQuery;

import org.openrdf.query.TupleQueryResult;

import org.openrdf.query.BindingSet;

import org.openrdf.query.QueryLanguage;
…

try {

   RepositoryConnection con = myRepository.getConnection();

   try {

      String queryString = "SELECT x, y FROM  WHERE {x} p {y}";

      TupleQuery tupleQuery = con.prepareTupleQuery(QueryLanguage.SPARQL, queryString);

      TupleQueryResult result = tupleQuery.evaluate();

      try {

         … // do something with the result

      }

      finally {

         result.close();

      }

   }

   finally {

      con.close();

   }

}

catch (RepositoryException e) {

   // handle exception

}

This evaluates a SPARQL query and returns a TupleQueryResult, which consists of a sequence of BindingSet objects. Each BindingSet contains a set of pairs called Binding objects. A Binding object represents a name/value pair for each variable in the query's projection.

We can use the TupleQueryResult to iterate over all results and get each individual result for x and y:

while (result.hasNext()) {

   BindingSet bindingSet = result.next();

   Value valueOfX = bindingSet.getValue("x");

   Value valueOfY = bindingSet.getValue("y");

   // do something interesting with the query variable values here…

}

As you can see, we retrieve values by name rather than by an index. The names used should be the names of variables as specified in your query. The TupleQueryResult.getBindingNames() method returns a list of binding names, in the order in which they were specified in the query. To process the bindings in each binding set in the order specified by the projection, you can do the following:

List bindingNames = result.getBindingNames();

while (result.hasNext()) {

   BindingSet bindingSet = result.next();

   Value firstValue = bindingSet.getValue(bindingNames.get(0));

   Value secondValue = bindingSet.getValue(bindingNames.get(1));

   // do something interesting with the values here…

}

It is important to invoke the close() operation on the TupleQueryResult, after we are done with it. A TupleQueryResult evaluates lazily and keeps resources (such as connections to the underlying database) open. Closing the TupleQueryResult frees up these resources. Do not forget that iterating over a result may cause exceptions! The best way to make sure no connections are kept open unnecessarily is to invoke close() in the finally clause.

An alternative to producing a TupleQueryResult is to supply an object that implements the TupleQueryResultHandler interface to the query's evaluate() method. The main difference is that when using a return object, the caller has control over when the next answer is retrieved, whereas with the use of a handler, the connection simply pushes answers to the handler object as soon as it has them available.

As an example we will use SPARQLResultsXMLWriter, which is a TupleQueryResultHandler implementation that writes SPARQL Results XML documents to an output stream or to a writer:

import org.openrdf.query.resultio.sparqlxml.SPARQLResultsXMLWriter;

…
FileOutputStream out = new FileOutputStream("/path/to/result.srx");

try {

   SPARQLResultsXMLWriter sparqlWriter = new SPARQLResultsXMLWriter(out);

   RepositoryConnection con = myRepository.getConnection();

   try {

      String queryString = "SELECT * FROM  WHERE {x} p {y}";

      TupleQuery tupleQuery = con.prepareTupleQuery(QueryLanguage.SPARQL, queryString);

      tupleQuery.evaluate(sparqlWriter);

   }

   finally {

      con.close();

   }

}

finally {

   out.close();

}

You can just as easily supply your own application-specific implementation of TupleQueryResultHandler, if desired.

Lastly, an important warning: as soon as you are done with the RepositoryConnection object, you should close it. Notice that during processing of the TupleQueryResult object (for example, when iterating over its contents), the RepositoryConnection should still be open. We can invoke con.close() after we have finished with the result.

Evaluating a CONSTRUCT query

The following code evaluates a graph query on a repository:

import org.openrdf.query.GraphQueryResult;

GraphQueryResult graphResult = con.prepareGraphQuery(

      QueryLanguage.SPARQL, "CONSTRUCT * FROM {x} p {y}").evaluate();

A GraphQueryResult is similar to TupleQueryResult in that it is an object that iterates over the query results. However, for graph queries the query results are RDF statements, so a GraphQueryResult iterates over Statement objects:

while (graphResult.hasNext()) {

   Statement st = graphResult.next();

   // … do something with the resulting statement here.

}

The TupleQueryResultHandler equivalent for graph queries is org.openrdf.rio.RDFHandler. Again, this is a generic interface; each object implementing it can process the reported RDF statements in any way it wants.

All writers from Rio (such as the RDFXMLWriter, TurtleWriter, TriXWriter, etc.) implement the RDFHandler interface. This allows them to be used in combination with querying quite easily. In the following example, we use a TurtleWriter to write the result of a SPARQL graph query to standard output in Turtle format:

import org.openrdf.rio.turtle.TurtleWriter;

…
RepositoryConnection con = myRepository.getConnection();

try {

   TurtleWriter turtleWriter = new TurtleWriter(System.out);

   con.prepareGraphQuery(QueryLanguage.SPARQL, "CONSTRUCT * FROM  WHERE {x} p {y}").evaluate(turtleWriter);

}

finally {

   con.close();

}

Again, note that as soon as we are done with the result of the query (either after iterating over the contents of the GraphQueryResult or after invoking the RDFHandler), we invoke con.close() to close the connection and free resources.

Javadoc API Documentation

Sesame Provider Javadoc API Documentation is available, covering the complete set of classes, interfaces, and methods implemented by the provider.

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