Please refer to the errata for this document, which may include some normative corrections.
See also translations.
Copyright © 2013 W3C® (MIT, ERCIM, Keio, Beihang), All Rights Reserved. W3C liability, trademark and document use rules apply.
RDF is a directed, labeled graph data format for representing information in the Web. This specification defines the syntax and semantics of the SPARQL query language for RDF. SPARQL can be used to express queries across diverse data sources, whether the data is stored natively as RDF or viewed as RDF via middleware. SPARQL contains capabilities for querying required and optional graph patterns along with their conjunctions and disjunctions. SPARQL also supports aggregation, subqueries, negation, creating values by expressions, extensible value testing, and constraining queries by source RDF graph. The results of SPARQL queries can be result sets or RDF graphs.
This section describes the status of this document at the time of its publication. Other documents may supersede this document. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at http://www.w3.org/TR/.
This document is one of eleven SPARQL 1.1 Recommendations produced by the SPARQL Working Group:
There have been no substantive changes to this document since the previous version. Minor editorial changes, if any, are detailed in the change log and visible in the color-coded diff.
Please send any comments to public-rdf-dawg-comments@w3.org (public archive). Although work on this document by the SPARQL Working Group is complete, comments may be addressed in the errata or in future revisions. Open discussion is welcome at public-sparql-dev@w3.org (public archive).
This document has been reviewed by W3C Members, by software developers, and by other W3C groups and interested parties, and is endorsed by the Director as a W3C Recommendation. It is a stable document and may be used as reference material or cited from another document. W3C's role in making the Recommendation is to draw attention to the specification and to promote its widespread deployment. This enhances the functionality and interoperability of the Web.
This document was produced by a group operating under the 5 February 2004 W3C Patent Policy. W3C maintains a public list of any patent disclosures made in connection with the deliverables of the group; that page also includes instructions for disclosing a patent. An individual who has actual knowledge of a patent which the individual believes contains Essential Claim(s) must disclose the information in accordance with section 6 of the W3C Patent Policy.
1 Introduction
1.1 Document Outline
1.2 Document Conventions
1.2.1 Namespaces
1.2.2 Data Descriptions
1.2.3 Result Descriptions
1.2.4 Terminology
2 Making Simple Queries (Informative)
2.1 Writing a Simple Query
2.2 Multiple Matches
2.3 Matching RDF Literals
2.3.1 Matching Literals with Language Tags
2.3.2 Matching Literals with Numeric Types
2.3.3 Matching Literals with Arbitrary Datatypes
2.4 Blank Node Labels in Query Results
2.5 Creating Values with Expressions
2.6 Building RDF Graphs
3 RDF Term Constraints (Informative)
3.1 Restricting the Value of Strings
3.2 Restricting Numeric Values
3.3 Other Term Constraints
4 SPARQL Syntax
4.1 RDF Term Syntax
4.1.1 Syntax for IRIs
4.1.1.1 Prefixed Names
4.1.1.2 Relative IRIs
4.1.2 Syntax for Literals
4.1.3 Syntax for Query Variables
4.1.4 Syntax for Blank Nodes
4.2 Syntax for Triple Patterns
4.2.1 Predicate-Object Lists
4.2.2 Object Lists
4.2.3 RDF Collections
4.2.4 rdf:type
5 Graph Patterns
5.1 Basic Graph Patterns
5.1.1 Blank Node Labels
5.1.2 Extending Basic Graph Pattern Matching
5.2 Group Graph Patterns
5.2.1 Empty Group Pattern
5.2.2 Scope of Filters
5.2.3 Group Graph Pattern Examples
6 Including Optional Values
6.1 Optional Pattern Matching
6.2 Constraints
in Optional Pattern Matching
6.3 Multiple Optional Graph
Patterns
7 Matching Alternatives
8 Negation
8.1 Filtering Using Graph Patterns
8.1.1 Testing For the Absence of a Pattern
8.1.2 Testing For the Presence of a Pattern
8.2 Removing Possible Solutions
8.3 Relationship and differences between NOT EXISTS and MINUS
8.3.1 Example: Sharing of variables
8.3.2 Example: Fixed pattern
8.3.3 Example: Inner FILTERs
9 Property Paths
9.1 Property Path Syntax
9.2 Examples
9.3 Property Paths and Equivalent Patterns
9.4 Arbitrary Length Path Matching
10 Assignment
10.1 BIND: Assigning to Variables
10.2 VALUES: Providing inline data
10.2.1 VALUES syntax
10.2.2 VALUES Examples
11 Aggregates
11.1 Aggregate Example
11.2 GROUP BY
11.3 HAVING
11.4 Aggregate Projection Restrictions
11.5 Aggregate Example (with errors)
12 Subqueries
13 RDF Dataset
13.1 Examples of RDF Datasets
13.2 Specifying RDF Datasets
13.2.1 Specifying the Default Graph
13.2.2 Specifying Named Graphs
13.2.3 Combining FROM and FROM NAMED
13.3 Querying the Dataset
13.3.1 Accessing Graph Names
13.3.2 Restricting by Graph
IRI
13.3.3 Restricting Possible Graph IRIs
13.3.4 Named and Default
Graphs
14 Basic Federated Query
15 Solution Sequences and Modifiers
15.1 ORDER BY
15.2 Projection
15.3 Duplicate Solutions
15.4 OFFSET
15.5 LIMIT
16 Query Forms
16.1 SELECT
16.1.1 Projection
16.1.2 SELECT Expressions
16.2 CONSTRUCT
16.2.1 Templates with Blank Nodes
16.2.2 Accessing Graphs in the RDF Dataset
16.2.3 Solution Modifiers and CONSTRUCT
16.2.4 CONSTRUCT WHERE
16.3 ASK
16.4 DESCRIBE (Informative)
16.4.1 Explicit IRIs
16.4.2 Identifying Resources
16.4.3 Descriptions of Resources
17 Expressions and Testing Values
17.1 Operand Data Types
17.2 Filter Evaluation
17.2.1 Invocation
17.2.2 Effective Boolean Value (EBV)
17.3 Operator Mapping
17.3.1 Operator Extensibility
17.4 Function Definitions
17.4.1 Functional Forms
17.4.1.1 bound
17.4.1.2 IF
17.4.1.3 COALESCE
17.4.1.4 NOT EXISTS and EXISTS
17.4.1.5 logical-or
17.4.1.6 logical-and
17.4.1.7 RDFterm-equal
17.4.1.8 sameTerm
17.4.1.9 IN
17.4.1.10 NOT IN
17.4.2 Functions on RDF Terms
17.4.2.1 isIRI
17.4.2.2 isBlank
17.4.2.3 isLiteral
17.4.2.4 isNumeric
17.4.2.5 str
17.4.2.6 lang
17.4.2.7 datatype
17.4.2.8 IRI
17.4.2.9 BNODE
17.4.2.10 STRDT
17.4.2.11 STRLANG
17.4.2.12 UUID
17.4.2.13 STRUUID
17.4.3 Functions on Strings
17.4.3.1 Strings in SPARQL Functions
17.4.3.1.1 String arguments
17.4.3.1.2 Argument Compatibility Rules
17.4.3.1.3 String Literal Return Type
17.4.3.2 STRLEN
17.4.3.3 SUBSTR
17.4.3.4 UCASE
17.4.3.5 LCASE
17.4.3.6 STRSTARTS
17.4.3.7 STRENDS
17.4.3.8 CONTAINS
17.4.3.9 STRBEFORE
17.4.3.10 STRAFTER
17.4.3.11 ENCODE_FOR_URI
17.4.3.12 CONCAT
17.4.3.13 langMatches
17.4.3.14 REGEX
17.4.3.15 REPLACE
17.4.4 Functions on Numerics
17.4.4.1 abs
17.4.4.2 round
17.4.4.3 ceil
17.4.4.4 floor
17.4.4.5 RAND
17.4.5 Functions on Dates and Times
17.4.5.1 now
17.4.5.2 year
17.4.5.3 month
17.4.5.4 day
17.4.5.5 hours
17.4.5.6 minutes
17.4.5.7 seconds
17.4.5.8 timezone
17.4.5.9 tz
17.4.6 Hash Functions
17.4.6.1 MD5
17.4.6.2 SHA1
17.4.6.3 SHA256
17.4.6.4 SHA384
17.4.6.5 SHA512
17.5 XPath Constructor Functions
17.6 Extensible Value Testing
18 Definition of SPARQL
18.1 Initial Definitions
18.1.1 RDF Terms
18.1.2 Simple Literal
18.1.3 RDF Dataset
18.1.4 Query Variables
18.1.5 Triple Patterns
18.1.6 Basic Graph Patterns
18.1.7 Property Path Patterns
18.1.8 Solution Mapping
18.1.9 Solution Sequence Modifiers
18.1.10 SPARQL Query
18.2 Translation to the SPARQL Algebra
18.2.1 Variable Scope
18.2.2 Converting Graph Patterns
18.2.2.1 Expand Syntax Forms
18.2.2.2 Collect FILTER Elements
18.2.2.3 Translate Property Path Expressions
18.2.2.4 Translate Property Path Patterns
18.2.2.5 Translate Basic Graph Patterns
18.2.2.6 Translate Graph Patterns
18.2.2.7 Filters of Group
18.2.2.8 Simplification step
18.2.3 Examples of Mapped Graph Patterns
18.2.4 Converting Groups, Aggregates, HAVING, final VALUES clause and SELECT Expressions
18.2.4.1 Grouping and Aggregation
18.2.4.2 HAVING
18.2.4.3 VALUES
18.2.4.4 SELECT Expressions
18.2.5 Converting Solution Modifiers
18.2.5.1 ORDER BY
18.2.5.2 Projection
18.2.5.3 DISTINCT
18.2.5.4 REDUCED
18.2.5.5 OFFSET and LIMIT
18.2.5.6 Final Algebra Expression
18.3 Basic Graph Patterns
18.3.1 SPARQL Basic Graph Pattern Matching
18.3.2 Treatment of Blank Nodes
18.4 Property Path Patterns
18.5 SPARQL Algebra
18.5.1 Aggregate Algebra
18.5.1.1 Set Functions
18.5.1.2 Count
18.5.1.3 Sum
18.5.1.4 Avg
18.5.1.5 Min
18.5.1.6 Max
18.5.1.7 GroupConcat
18.5.1.8 Sample
18.6 Evaluation Semantics
18.7 Extending SPARQL Basic Graph Matching
18.7.1 Notes
19 SPARQL Grammar
19.1 SPARQL Request String
19.2 Codepoint Escape Sequences
19.3 White Space
19.4 Comments
19.5 IRI References
19.6 Blank Nodes and Blank Node Labels
19.7 Escape sequences in strings
19.8 Grammar
20 Conformance
21 Security Considerations (Informative)
22 Internet Media Type, File Extension and Macintosh File Type
A References
A.1 Normative References
A.2 Other References
RDF is a directed, labeled graph data format for representing information in the Web. RDF is often used to represent, among other things, personal information, social networks, metadata about digital artifacts, as well as to provide a means of integration over disparate sources of information. This specification defines the syntax and semantics of the SPARQL query language for RDF.
The SPARQL query language for RDF is designed to meet the use cases and requirements identified by the RDF Data Access Working Group in RDF Data Access Use Cases and Requirements [UCNR] and SPARQL New Features and Rationale [UCNR2].
Unless otherwise noted in the section heading, all sections and appendices in this document are normative.
This section of the document, section 1, introduces the SPARQL query language specification. It presents the organization of this specification document and the conventions used throughout the specification.
Section 2 of the specification introduces the SPARQL query language itself via a series of example queries and query results. Section 3 continues the introduction of the SPARQL query language with more examples that demonstrate SPARQL's ability to express constraints on the RDF terms that appear in a query's results.
Section 4 presents details of the SPARQL query language's syntax. It is a companion to the full grammar of the language and defines how grammatical constructs represent IRIs, blank nodes, literals, and variables. Section 4 also defines the meaning of several grammatical constructs that serve as syntactic sugar for more verbose expressions.
Section 5 introduces basic graph patterns and group graph patterns, the building blocks from which more complex SPARQL query patterns are constructed. Sections 6, 7, and 8 present constructs that combine SPARQL graph patterns into larger graph patterns. In particular, Section 6 introduces the ability to make portions of a query optional; Section 7 introduces the ability to express the disjunction of alternative graph patterns; and Section 8 introduces patterns to test for the absense of information.
Section 9 adds property paths to graph pattern matching, giving a compact representation of queries and also the ability to match arbitrary length paths in the graph.
Section 10 describes the forms of assignment possible in SPARQL.
Sections 11 introduces the mechanism to group and aggregate results, which can be incorporated as subqueries as described in Section 12.
Section 13 introduces the ability to constrain portions of a query to particular source graphs. Section 13 also presents SPARQL's mechanism for defining the source graphs for a query.
Section 14 refers to the separate document SPARQL 1.1 Federated Query.
Section 15 defines the constructs that affect the solutions of a query by ordering, slicing, projecting, limiting, and removing duplicates from a sequence of solutions.
Section 16 defines the four types of SPARQL queries that produce results in different forms.
Section 17 defines SPARQL's extensible value testing and expression framework. It presents the functions and operators that can be used to constrain the values that appear in a query's results and also calculate new values to be returned by a query.
Section 18 is a formal definition of the evaluation of SPARQL graph patterns and solution modifiers.
Section 19 contains the normative definition of the syntax for the SPARQL query and SPARQL update languages, as given by a grammar expressed in EBNF notation.
In this document, examples assume the following namespace prefix bindings unless otherwise stated:
| Prefix | IRI |
|---|---|
rdf: | http://www.w3.org/1999/02/22-rdf-syntax-ns# |
rdfs: | http://www.w3.org/2000/01/rdf-schema# |
xsd: | http://www.w3.org/2001/XMLSchema# |
fn: | http://www.w3.org/2005/xpath-functions# |
sfn: | http://www.w3.org/ns/sparql# |
This document uses the Turtle [TURTLE] data format to show each triple explicitly. Turtle allows IRIs to be abbreviated with prefixes:
@prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix : <http://example.org/book/> . :book1 dc:title "SPARQL Tutorial" .
Result sets are illustrated in tabular form.
A 'binding' is a pair (variable,
RDF term). In this result set, there are three
variables:
x, y and z (shown as column headers). Each
solution is shown as one row in the body of the table. Here, there is a single
solution, in which variable x is bound to "Alice", variable
y is bound to <http://example/a>, and variable z
is not bound to an RDF term. Variables are not required to be bound in a
solution.
The SPARQL language includes IRIs, a subset of RDF URI References that omits spaces. Note that all IRIs in SPARQL queries are absolute; they may or may not include a fragment identifier [RFC3987, section 3.1]. IRIs include URIs [RFC3986] and URLs. The abbreviated forms (relative IRIs and prefixed names) in the SPARQL syntax are resolved to produce absolute IRIs.
The following terms are defined in RDF Concepts and Abstract Syntax [CONCEPTS] and used in SPARQL:
RDF URI reference")datatype URI")In addition, we define the following terms:
Most forms of SPARQL query contain a set of triple patterns called a basic graph pattern. Triple patterns are like RDF triples except that each of the subject, predicate and object may be a variable. A basic graph pattern matches a subgraph of the RDF data when RDF terms from that subgraph may be substituted for the variables and the result is RDF graph equivalent to the subgraph.
The example below shows a SPARQL query to find the title of a book from the
given data graph. The query consists of two parts:
the SELECT clause identifies
the variables to appear in the query results, and the WHERE clause
provides the basic graph pattern to match against the data graph. The basic graph pattern in this example
consists of a single triple pattern with a single variable (?title) in the object position.
The result of a query is a solution sequence, corresponding to the ways in which the query's graph pattern matches the data. There may be zero, one or multiple solutions to a query.
Data:
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Johnny Lee Outlaw" . _:a foaf:mbox <mailto:jlow@example.com> . _:b foaf:name "Peter Goodguy" . _:b foaf:mbox <mailto:peter@example.org> . _:c foaf:mbox <mailto:carol@example.org> .
Query:
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE
{ ?x foaf:name ?name .
?x foaf:mbox ?mbox }Query Result:
| name | mbox |
|---|---|
| "Johnny Lee Outlaw" | <mailto:jlow@example.com> |
| "Peter Goodguy" | <mailto:peter@example.org> |
Each solution gives one way in which the selected variables can be bound to RDF terms so that the query pattern matches the data. The result set gives all the possible solutions. In the above example, the following two subsets of the data provided the two matches.
_:a foaf:name "Johnny Lee Outlaw" . _:a foaf:box <mailto:jlow@example.com> .
_:b foaf:name "Peter Goodguy" . _:b foaf:box <mailto:peter@example.org> .
This is a basic graph pattern match; all the variables used in the query pattern must be bound in every solution.
The data below contains three RDF literals:
@prefix dt: <http://example.org/datatype#> .
@prefix ns: <http://example.org/ns#> .
@prefix : <http://example.org/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
:x ns:p "cat"@en .
:y ns:p "42"^^xsd:integer .
:z ns:p "abc"^^dt:specialDatatype .Note that, in Turtle, "cat"@en is an RDF literal with a lexical form "cat" and a language tag "en"; "42"^^xsd:integer is a typed literal with the datatype http://www.w3.org/2001/XMLSchema#integer; and "abc"^^dt:specialDatatype is a typed literal with the datatype http://example.org/datatype#specialDatatype.
This RDF data is the data graph for the query examples in sections 2.3.1–2.3.3.
Language tags in SPARQL are expressed using @ and the
language tag, as defined in Best Common Practice 47 [BCP47].
This following query has no solution because "cat" is not the
same RDF literal as "cat"@en:
SELECT ?v WHERE { ?v ?p "cat" }| v |
|---|
but the query below will find a solution where variable v is bound to
:x because the language tag is specified and matches the given data:
SELECT ?v WHERE { ?v ?p "cat"@en }
| v |
|---|
| <http://example.org/ns#x> |
Integers in a SPARQL query indicate an RDF typed literal with the datatype
xsd:integer. For example: 42 is a shortened form
of "42"^^<http://www.w3.org/2001/XMLSchema#integer>.
The pattern in the following query has a solution with variable v
bound to :y.
Section 4.1.2 defines SPARQL shortened forms for xsd:float and xsd:double.
Query results can contain blank nodes. Blank nodes in the example result sets in this document are written in the form "_:" followed by a blank node label.
Blank node labels are scoped to a result set (see
"SPARQL
Query Results XML Format" and
"SPARQL 1.1 Query Results JSON Format")
or, for the CONSTRUCT query
form, the result graph.
Use of the same label within a
result set indicates the same blank node.
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:b foaf:name "Bob" .
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?x ?name
WHERE { ?x foaf:name ?name }
The results above could equally be given with different blank node labels because the labels in the results only indicate whether RDF terms in the solutions are the same or different.
These two results have the same information: the blank nodes used to match the
query are different in the two solutions. There need not be any relation between a
label
_:a in the result set and a blank node in the data graph
with the same label.
An application writer should not expect blank node labels in a query to refer to a particular blank node in the data.
SPARQL 1.1 allows to create values from complex expressions.
The queries below show how to the CONCAT function
can be used to concatenate first names and last names from foaf data, then assign
the value using an expression in the SELECT clause
and also assign the value by using the BIND form.
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
_:a foaf:givenName "John" .
_:a foaf:surname "Doe" .SPARQL has several query forms.
The SELECT query form
returns variable bindings. The CONSTRUCT query form
returns an RDF graph. The graph is built based on a template
which is used to generate RDF triples based on the results of matching
the graph pattern of the query.
Data:
@prefix org: <http://example.com/ns#> . _:a org:employeeName "Alice" . _:a org:employeeId 12345 . _:b org:employeeName "Bob" . _:b org:employeeId 67890 .
Query:
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX org: <http://example.com/ns#>
CONSTRUCT { ?x foaf:name ?name }
WHERE { ?x org:employeeName ?name }Results:
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
_:x foaf:name "Alice" .
_:y foaf:name "Bob" .which can be serialized in RDF/XML as:
<rdf:RDF
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
>
<rdf:Description>
<foaf:name>Alice</foaf:name>
</rdf:Description>
<rdf:Description>
<foaf:name>Bob</foaf:name>
</rdf:Description>
</rdf:RDF>Graph pattern matching produces a solution sequence, where each solution has a set of bindings of variables to RDF terms. SPARQL FILTERs
restrict solutions to those for which the filter expression evaluates to TRUE.
This section provides an informal introduction to SPARQL FILTERs; their semantics are defined in section 'Expressions and Testing Values' where there is a comprehensive function library. The examples in this section share one input graph:
@prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix : <http://example.org/book/> . @prefix ns: <http://example.org/ns#> . :book1 dc:title "SPARQL Tutorial" . :book1 ns:price 42 . :book2 dc:title "The Semantic Web" . :book2 ns:price 23 .
SPARQL FILTER functions like regex can test RDF literals. regex matches only string literals.
regex can be used to match the lexical forms of other literals by
using the str
function.
Query:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?title
WHERE { ?x dc:title ?title
FILTER regex(?title, "^SPARQL")
}
Query Result:
Regular expression matches may be made case-insensitive with the "i"
flag.
Query:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?title
WHERE { ?x dc:title ?title
FILTER regex(?title, "web", "i" )
}
Query Result:
The regular expression language is defined by XQuery 1.0 and XPath 2.0 Functions and Operators and is based on XML Schema Regular Expressions.
By constraining the price variable, only :book2 matches
the query because only :book2 has a price less than 30.5,
as the filter condition requires.
In addition to numeric types, SPARQL supports
types xsd:string, xsd:boolean and xsd:dateTime
(see Operand Data Types).
Section Operator Mapping describes the operators
and section Function Definitions the functions that can be
that can be applied to RDF terms.
This section covers the syntax used by SPARQL for RDF terms and triple patterns. The full grammar is given in section 19.
The iri production designates the set of IRIs [RFC3987]; IRIs are a generalization of URIs [RFC3986] and are fully compatible with URIs and URLs. The PrefixedName production designates a prefixed name. The mapping from a prefixed name to an IRI is described below. IRI references (relative or absolute IRIs) are designated by the IRIREF production, where the '<' and '>' delimiters do not form part of the IRI reference. Relative IRIs match the irelative-ref reference in section 2.2 ABNF for IRI References and IRIs in [RFC3987] and are resolved to IRIs as described below.
The set of RDF terms defined in RDF Concepts and Abstract Syntax
includes RDF URI references while SPARQL terms include IRIs. RDF URI
references containing "<", ">", '"' (double
quote), space, "{", "}", "|",
"\", "^", and
"`" are not IRIs. The behavior of a SPARQL query against RDF
statements composed of such RDF URI references is not defined.
The PREFIX keyword associates a prefix label with an IRI. A prefixed
name is a prefix label and a local part, separated by a colon ":".
A prefixed name is mapped to an IRI by concatenating the IRI associated with the prefix and the local part.
The prefix label or the local part may be empty.
Note that SPARQL local names allow leading digits while XML local names do not.
SPARQL local names also allow the non-alphanumeric characters allowed in IRIs
via backslash character escapes (e.g. ns:id\=123).
SPARQL local names have more syntactic restrictions than CURIEs.
Relative IRIs are combined with base IRIs as per Uniform Resource Identifier (URI): Generic Syntax [RFC3986] using only the basic algorithm in section 5.2. Neither Syntax-Based Normalization nor Scheme-Based Normalization (described in sections 6.2.2 and 6.2.3 of RFC3986) are performed. Characters additionally allowed in IRI references are treated in the same way that unreserved characters are treated in URI references, per section 6.5 of Internationalized Resource Identifiers (IRIs) [RFC3987].
The BASE keyword defines the Base IRI used to resolve relative IRIs
per RFC3986 section 5.1.1, "Base URI Embedded in Content". Section 5.1.2, "Base
URI from the Encapsulating Entity" defines how the Base IRI may come from an encapsulating
document, such as a SOAP envelope with an xml:base directive or a mime multipart
document with a Content-Location header. The "Retrieval URI" identified in 5.1.3,
Base "URI from the Retrieval URI", is the URL from which a particular SPARQL query
was retrieved. If none of the above specifies the Base URI, the default Base URI
(section 5.1.4, "Default Base URI") is used.
The following fragments are some of the different ways to write the same IRI:
<http://example.org/book/book1>
BASE <http://example.org/book/> <book1>
PREFIX book: <http://example.org/book/> book:book1
The general syntax for literals is a string (enclosed in either double
quotes, "...", or single quotes, '...'), with either an optional
language tag (introduced by @) or an optional datatype IRI or prefixed
name (introduced by ^^).
As a convenience, integers can be written directly (without quotation marks and an explicit datatype IRI) and are interpreted as typed
literals of datatype xsd:integer; decimal numbers for which there is '.'
in the number but no exponent are interpreted as xsd:decimal; and
numbers with exponents are interpreted as xsd:double. Values of
type xsd:boolean can also be written as true or
false.
To facilitate writing literal values which themselves contain quotation marks or which are long and contain newline characters, SPARQL provides an additional quoting construct in which literals are enclosed in three single- or double-quotation marks.
Examples of literal syntax in SPARQL include:
"chat"'chat'@fr with language tag "fr""xyz"^^<http://example.org/ns/userDatatype>"abc"^^appNS:appDataType'''The librarian said, "Perhaps you would enjoy 'War and Peace'."'''1, which is the same as "1"^^xsd:integer1.3, which is the same as "1.3"^^xsd:decimal1.300, which is the same as "1.300"^^xsd:decimal1.0e6, which is the same as "1.0e6"^^xsd:doubletrue, which is the same as "true"^^xsd:booleanfalse, which is the same as "false"^^xsd:boolean
Tokens matching the productions INTEGER, DECIMAL, DOUBLE and
BooleanLiteral are equivalent to a typed
literal with the lexical value of the token and the corresponding
datatype (xsd:integer, xsd:decimal, xsd:double, xsd:boolean).
A query variable is marked by the use of either "?" or "$";
the "?" or "$" is not part of the variable name.
In a query, $abc and ?abc identify the same variable. The
possible names for variables are given in the
SPARQL grammar.
Blank nodes in graph patterns act as variables, not as references to specific blank nodes in the data being queried.
Blank nodes are indicated by either the label form, such as "_:abc", or the abbreviated form "[]". A blank
node that is used in only one place in the query syntax can be indicated with
[]. A unique blank node will be used to form the triple
pattern. Blank node labels are written as "_:abc" for a blank node with
label "abc". The same blank node label cannot be used
in two different basic graph patterns in the same query.
The [:p :v] construct can be used in triple patterns. It creates
a blank node label which is used as the subject of all contained predicate-object
pairs. The created blank node can also be used in further triple patterns in the
subject and object positions.
The following two forms
[ :p "v" ] .
[] :p "v" .
allocate a unique blank node label (here "b57") and are equivalent
to writing:
_:b57 :p "v" .
This allocated blank node label can be used as the subject or object of further triple patterns. For example, as a subject:
[ :p "v" ] :q "w" .
which is equivalent to the two triples:
_:b57 :p "v" . _:b57 :q "w" .
and as an object:
:x :q [ :p "v" ] .
which is equivalent to the two triples:
:x :q _:b57 . _:b57 :p "v" .
Abbreviated blank node syntax can be combined with other abbreviations for common subjects and common predicates.
[ foaf:name ?name ;
foaf:mbox <mailto:alice@example.org> ]
This is the same as writing the following basic graph pattern for some uniquely
allocated blank node label, "b18":
_:b18 foaf:name ?name . _:b18 foaf:mbox <mailto:alice@example.org> .
Triple Patterns are written as subject, predicate and object; there are abbreviated ways of writing some common triple pattern constructs.
The following examples express the same query:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?title
WHERE { <http://example.org/book/book1> dc:title ?title }
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX : <http://example.org/book/>
SELECT $title
WHERE { :book1 dc:title $title }
BASE <http://example.org/book/>
PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT $title
WHERE { <book1> dc:title ?title }
Triple patterns with a common subject can be written so that the subject is only
written once and is used for more than one triple pattern by employing the ";"
notation.
?x foaf:name ?name ;
foaf:mbox ?mbox .
This is the same as writing the triple patterns:
?x foaf:name ?name .
?x foaf:mbox ?mbox .
If triple patterns share both subject and predicate, the objects may be separated
by ",".
?x foaf:nick "Alice" , "Alice_" .
is the same as writing the triple patterns:
?x foaf:nick "Alice" . ?x foaf:nick "Alice_" .
Object lists can be combined with predicate-object lists:
?x foaf:name ?name ; foaf:nick "Alice" , "Alice_" .
is equivalent to:
?x foaf:name ?name . ?x foaf:nick "Alice" . ?x foaf:nick "Alice_" .
RDF collections can be written in triple patterns using the syntax "(element1 element2 ...)". The
form "()" is an alternative for the IRI
http://www.w3.org/1999/02/22-rdf-syntax-ns#nil.
When used with collection elements, such as (1 ?x 3 4), triple patterns
with blank nodes are allocated for the collection. The blank node at the head
of the collection can be used as a subject or object in other triple patterns. The blank nodes allocated by the collection syntax do not occur elsewhere in the query.
(1 ?x 3 4) :p "w" .
is syntactic sugar for (noting that b0, b1, b2 and b3 do not occur anywhere else in the
query):
_:b0 rdf:first 1 ;
rdf:rest _:b1 .
_:b1 rdf:first ?x ;
rdf:rest _:b2 .
_:b2 rdf:first 3 ;
rdf:rest _:b3 .
_:b3 rdf:first 4 ;
rdf:rest rdf:nil .
_:b0 :p "w" .
RDF collections can be nested and can involve other syntactic forms:
(1 [:p :q] ( 2 ) ) .
is syntactic sugar for:
_:b0 rdf:first 1 ;
rdf:rest _:b1 .
_:b1 rdf:first _:b2 .
_:b2 :p :q .
_:b1 rdf:rest _:b3 .
_:b3 rdf:first _:b4 .
_:b4 rdf:first 2 ;
rdf:rest rdf:nil .
_:b3 rdf:rest rdf:nil .
The keyword "a" can be used as a predicate in a triple pattern and
is an alternative for the IRI
http://www.w3.org/1999/02/22-rdf-syntax-ns#type.
This keyword is case-sensitive.
?x a :Class1 . [ a :appClass ] :p "v" .
is syntactic sugar for:
?x rdf:type :Class1 . _:b0 rdf:type :appClass . _:b0 :p "v" .
SPARQL is based around graph pattern matching. More complex graph patterns can be formed by combining smaller patterns in various ways:
In this section we describe the two forms that combine patterns by conjunction: basic graph patterns, which combine triples patterns, and group graph patterns, which combine all other graph patterns.
The outer-most graph pattern in a query is called the query pattern. It is grammatically identified by GroupGraphPattern in
[17] | WhereClause | ::= | 'WHERE'? GroupGraphPattern |
Basic graph patterns are sets of triple patterns. SPARQL graph pattern matching is defined in terms of combining the results from matching basic graph patterns.
A sequence of triple patterns, with optional filters, comprises a single basic graph pattern. Any other graph pattern terminates a basic graph pattern.
When using blank nodes of the form _:abc, labels for blank
nodes are scoped to the basic graph pattern. A label can be used in only a
single basic graph pattern in any query.
SPARQL evaluates basic graph patterns using subgraph matching, which is defined for simple entailment. SPARQL can be extended to other forms of entailment given certain conditions as described below. The document SPARQL 1.1 Entailment Regimes describes several specific entailment regimes.
In a SPARQL query string, a group graph pattern is delimited with braces:
{}. For example, this query's query pattern is a group graph pattern of one basic
graph pattern.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE {
?x foaf:name ?name .
?x foaf:mbox ?mbox .
}
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE { { ?x foaf:name ?name . }
{ ?x foaf:mbox ?mbox . }
}The group pattern:
{ }matches any graph (including the empty graph) with one solution that does not bind any variables. For example:
SELECT ?x
WHERE {}
matches with one solution in which variable x is not bound.
A constraint, expressed by the keyword FILTER, is a
restriction on solutions over the whole group in which the filter appears. The
following patterns all have the same solutions:
{ ?x foaf:name ?name .
?x foaf:mbox ?mbox .
FILTER regex(?name, "Smith")
}
{ FILTER regex(?name, "Smith")
?x foaf:name ?name .
?x foaf:mbox ?mbox .
}
{ ?x foaf:name ?name .
FILTER regex(?name, "Smith")
?x foaf:mbox ?mbox .
}
{
?x foaf:name ?name .
?x foaf:mbox ?mbox .
}is a group of one basic graph pattern and that basic graph pattern consists of two triple patterns.
{
?x foaf:name ?name . FILTER regex(?name, "Smith")
?x foaf:mbox ?mbox .
}is a group of one basic graph pattern and a filter, and that basic graph pattern consists of two triple patterns; the filter does not break the basic graph pattern into two basic graph patterns.
{
?x foaf:name ?name .
{}
?x foaf:mbox ?mbox .
}is a group of three elements, a basic graph pattern of one triple pattern, an empty group, and another basic graph pattern of one triple pattern.
Basic graph patterns allow applications to make queries where the entire query pattern must match for there to be a solution. For every solution of a query containing only group graph patterns with at least one basic graph pattern, every variable is bound to an RDF Term in a solution. However, regular, complete structures cannot be assumed in all RDF graphs. It is useful to be able to have queries that allow information to be added to the solution where the information is available, but do not reject the solution because some part of the query pattern does not match. Optional matching provides this facility: if the optional part does not match, it creates no bindings but does not eliminate the solution.
Optional parts of the graph pattern may be specified syntactically with the OPTIONAL keyword applied to a graph pattern:
pattern OPTIONAL { pattern }
The syntactic form:
{ OPTIONAL { pattern } }
is equivalent to:
{ { } OPTIONAL { pattern } }
The OPTIONAL keyword is left-associative :
pattern OPTIONAL { pattern } OPTIONAL { pattern }
is the same as:
{ pattern OPTIONAL { pattern } } OPTIONAL { pattern }
In an optional match, either the optional graph pattern matches a graph, thereby defining and adding bindings to one or more solutions, or it leaves a solution unchanged without adding any additional bindings.
Data:
@prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . _:a rdf:type foaf:Person . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@example.com> . _:a foaf:mbox <mailto:alice@work.example> . _:b rdf:type foaf:Person . _:b foaf:name "Bob" .
There is no value of mbox in the solution where the name is
"Bob".
This query finds the names of people in the data. If there is a triple with predicate
mbox and the same subject, a solution will contain the object of that triple
as well. In this example, only a single triple pattern is given in the optional match
part of the query but, in general, the optional part may be any graph pattern. The entire
optional graph pattern must match for the optional graph pattern to affect
the query solution.
Constraints can be given in an optional graph pattern. For example:
@prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix : <http://example.org/book/> . @prefix ns: <http://example.org/ns#> . :book1 dc:title "SPARQL Tutorial" . :book1 ns:price 42 . :book2 dc:title "The Semantic Web" . :book2 ns:price 23 .
No price appears for the book with title "SPARQL Tutorial" because the optional
graph pattern did not lead to a solution involving the variable "price".
Graph patterns are defined recursively. A graph pattern may have zero or more optional graph patterns, and any part of a query pattern may have an optional part. In this example, there are two optional graph patterns.
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:homepage <http://work.example.org/alice/> . _:b foaf:name "Bob" . _:b foaf:mbox <mailto:bob@work.example> .
SPARQL provides a means of combining graph patterns so that one of several alternative graph patterns may match. If more than one of the alternatives matches, all the possible pattern solutions are found.
Pattern alternatives are syntactically specified with the UNION keyword.
@prefix dc10: <http://purl.org/dc/elements/1.0/> . @prefix dc11: <http://purl.org/dc/elements/1.1/> . _:a dc10:title "SPARQL Query Language Tutorial" . _:a dc10:creator "Alice" . _:b dc11:title "SPARQL Protocol Tutorial" . _:b dc11:creator "Bob" . _:c dc10:title "SPARQL" . _:c dc11:title "SPARQL (updated)" .
PREFIX dc10: <http://purl.org/dc/elements/1.0/>
PREFIX dc11: <http://purl.org/dc/elements/1.1/>
SELECT ?title
WHERE { { ?book dc10:title ?title } UNION { ?book dc11:title ?title } }
Query result:
This query finds titles of the books in the data, whether the title is recorded using Dublin Core properties from version 1.0 or version 1.1. To determine exactly how the information was recorded, a query could use different variables for the two alternatives:
PREFIX dc10: <http://purl.org/dc/elements/1.0/>
PREFIX dc11: <http://purl.org/dc/elements/1.1/>
SELECT ?x ?y
WHERE { { ?book dc10:title ?x } UNION { ?book dc11:title ?y } }
This will return results with the variable x bound for solutions from the left branch of the UNION, and y bound
for the solutions from the right branch. If neither part of the UNION
pattern matched, then the graph pattern would not match.
The UNION pattern combines graph patterns; each alternative possibility can contain more
than one triple
pattern:
PREFIX dc10: <http://purl.org/dc/elements/1.0/>
PREFIX dc11: <http://purl.org/dc/elements/1.1/>
SELECT ?title ?author
WHERE { { ?book dc10:title ?title . ?book dc10:creator ?author }
UNION
{ ?book dc11:title ?title . ?book dc11:creator ?author }
}
This query will only match a book if it has both a title and creator predicate from the same version of Dublin Core.
The SPARQL query language incorporates two styles of negation, one based on filtering results depending on whether a graph pattern does or does not match in the context of the query solution being filtered, and one based on removing solutions related to another pattern.
Filtering of query solutions is done within a FILTER
expression using NOT EXISTS and EXISTS.
Note that the filter scope rules
apply to the
whole group in which the filter appears.
The NOT EXISTS filter expression tests whether a graph pattern does
not match the dataset, given the values of variables in the group graph pattern
in which the filter occurs. It does
not generate any additional bindings.
Data:
@prefix : <http://example/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . :alice rdf:type foaf:Person . :alice foaf:name "Alice" . :bob rdf:type foaf:Person .
Query:
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?person
WHERE
{
?person rdf:type foaf:Person .
FILTER NOT EXISTS { ?person foaf:name ?name }
} Query Result:
| person |
|---|
| <http://example/bob> |
The filter expression EXISTS is also provided.
It tests whether the pattern can be found in the data;
it does not generate any additional bindings.
Query:
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?person
WHERE
{
?person rdf:type foaf:Person .
FILTER EXISTS { ?person foaf:name ?name }
}Query Result:
| person |
|---|
| <http://example/alice> |
The other style of negation provided in SPARQL is
MINUS which evaluates both its arguments,
then calculates solutions in the left-hand side that are not
compatible with the solutions on the right-hand side.
@prefix : <http://example/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
:alice foaf:givenName "Alice" ;
foaf:familyName "Smith" .
:bob foaf:givenName "Bob" ;
foaf:familyName "Jones" .
:carol foaf:givenName "Carol" ;
foaf:familyName "Smith" .PREFIX : <http://example/>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT DISTINCT ?s
WHERE {
?s ?p ?o .
MINUS {
?s foaf:givenName "Bob" .
}
}Results:
| s |
|---|
| <http://example/carol> |
| <http://example/alice> |
NOT EXISTS and MINUS represent two ways of
thinking about negation, one based on
testing whether a pattern exists in the data, given the bindings
already determined by the query pattern,
and one based on removing matches based on the evaluation of
two patterns. In some cases they can produce different answers.
@prefix : <http://example/> . :a :b :c .
SELECT *
{
?s ?p ?o
FILTER NOT EXISTS { ?x ?y ?z }
}evaluates to a result set with no solutions because { ?x ?y ?z }
matches given any ?s ?p ?o, so NOT EXISTS { ?x ?y ?z }
eliminates any solutions.
| s | p | o |
|---|
whereas with MINUS, there is no shared variable between the
first part (?s ?p ?o) and the second (?x ?y ?z)
so no bindings are eliminated.
SELECT *
{
?s ?p ?o
MINUS
{ ?x ?y ?z }
}Results:
| s | p | o |
|---|---|---|
| <http://example/a> | <http://example/b> | <http://example/c> |
Another case is where there is a concrete pattern (no variables) in the example:
PREFIX : <http://example/>
SELECT *
{
?s ?p ?o
FILTER NOT EXISTS { :a :b :c }
}evaluates to a result set with no query solutions:
Results:| s | p | o |
|---|
whereas
PREFIX : <http://example/>
SELECT *
{
?s ?p ?o
MINUS { :a :b :c }
}evaluates to result set with one query solution:
Results:
| s | p | o |
|---|---|---|
| <http://example/a> | <http://example/b> | <http://example/c> |
because there is no match of bindings and so no solutions are eliminated.
Differences also arise because in a filter, variables from the group are
in scope. In this example, the FILTER inside
the NOT EXISTS has access to the value of ?n for the solution being considered.
@prefix : <http://example.com/> . :a :p 1 . :a :q 1 . :a :q 2 . :b :p 3.0 . :b :q 4.0 . :b :q 5.0 .
When using FILTER NOT EXISTS, the test is on each possible solution to ?x :p ?n:
PREFIX : <http://example.com/>
SELECT * WHERE {
?x :p ?n
FILTER NOT EXISTS {
?x :q ?m .
FILTER(?n = ?m)
}
}| x | n |
|---|---|
| <http://example.com/b> | 3.0 |
whereas with MINUS, the FILTER inside the pattern does not have a value for ?n and it is always unbound:
PREFIX : <http://example/>
SELECT * WHERE {
?x :p ?n
MINUS {
?x :q ?m .
FILTER(?n = ?m)
}
}| x | n |
|---|---|
| <http://example.com/b> | 3.0 |
| <http://example.com/a> | 1 |
A property path is a possible route through a graph between two graph nodes. A trivial case is a property path of length exactly 1, which is a triple pattern. The ends of the path may be RDF terms or variables. Variables can not be used as part of the path itself, only the ends.
Property paths allow for more concise expressions for some SPARQL basic graph patterns and they also add the ability to match connectivity of two resources by an arbitrary length path.
In the description below, iri is either an IRI written in full or abbreviated by a prefixed name, or the keyword a. elt is a path element, which may itself be composed of path constructs.
| Syntax Form | Property Path Expression Name | Matches |
|---|---|---|
| iri | PredicatePath | An IRI. A path of length one. |
| ^elt | InversePath | Inverse path (object to subject). |
| elt1 / elt2 | SequencePath | A sequence path of elt1 followed by elt2. |
| elt1 | elt2 | AlternativePath | A alternative path of elt1 or elt2 (all possibilities are tried). |
| elt* | ZeroOrMorePath | A path that connects the subject and object of the path by zero or more matches of elt. |
| elt+ | OneOrMorePath | A path that connects the subject and object of the path by one or more matches of elt. |
| elt? | ZeroOrOnePath | A path that connects the subject and object of the path by zero or one matches of elt. |
| !iri or !(iri1| ...|irin) | NegatedPropertySet | Negated property set. An IRI which is not one of irii. !iri is short for !(iri). |
| !^iri or !(^iri1| ...|^irin) | NegatedPropertySet | Negated property set where the excluded matches are based on reversed path. That is, not one of iri1...irin as reverse paths. !^iri is short for !(^iri). |
| !(iri1| ...|irij|^irij+1| ...|^irin) | NegatedPropertySet | A combination of forward and reverse properties in a negated property set. |
| (elt) | A group path elt, brackets control precedence. |
The order of IRIs, and reverse IRIs, in a negated property set is not significant and they can occur in a mixed order.
The precedence of the syntax forms is, from highest to lowest:
Precedence is left-to-right within groups.
Alternatives: Match one or both possibilities
{ :book1 dc:title|rdfs:label ?displayString }which could have writen:
{ :book1 <http://purl.org/dc/elements/1.1/title> | <http://www.w3.org/2000/01/rdf-schema#label> ?displayString }Sequence: Find the name of any people that Alice knows.
{
?x foaf:mbox <mailto:alice@example> .
?x foaf:knows/foaf:name ?name .
}Sequence: Find the names of people 2 "foaf:knows" links away.
{
?x foaf:mbox <mailto:alice@example> .
?x foaf:knows/foaf:knows/foaf:name ?name .
}This is the same as the SPARQL query:
SELECT ?x ?name
{
?x foaf:mbox <mailto:alice@example> .
?x foaf:knows [ foaf:knows [ foaf:name ?name ]].
}or, with explicit variables:
SELECT ?x ?name
{
?x foaf:mbox <mailto:alice@example> .
?x foaf:knows ?a1 .
?a1 foaf:knows ?a2 .
?a2 foaf:name ?name .
}Filtering duplicates: Because someone Alice knows may well know Alice, the example above may include Alice herself. This could be avoided with:
{ ?x foaf:mbox <mailto:alice@example> .
?x foaf:knows/foaf:knows ?y .
FILTER ( ?x != ?y )
?y foaf:name ?name
}Inverse Property Paths: These two are the same query: the second is just reversing the property direction which swaps the roles of subject and object.
{ ?x foaf:mbox <mailto:alice@example> } { <mailto:alice@example> ^foaf:mbox ?x }Inverse Path Sequence: Find all the people who know someone ?x knows.
{
?x foaf:knows/^foaf:knows ?y .
FILTER(?x != ?y)
}which is equivalent to (?gen1 is a system generated variable):
{
?x foaf:knows ?gen1 .
?y foaf:knows ?gen1 .
FILTER(?x != ?y)
}Arbitrary length match: Find the names of all the people that can be reached from Alice by foaf:knows:
{
?x foaf:mbox <mailto:alice@example> .
?x foaf:knows+/foaf:name ?name .
}Alternatives in an arbitrary length path:
{ ?ancestor (ex:motherOf|ex:fatherOf)+ <#me> }Arbitrary length path match: Some forms of limited inference are possible as well. For example, for RDFS, all types and supertypes of a resource:
{ <http://example/thing> rdf:type/rdfs:subClassOf* ?type }All resources and all their inferred types:
{ ?x rdf:type/rdfs:subClassOf* ?type }Subproperty:
{ ?x ?p ?v . ?p rdfs:subPropertyOf* :property }Negated Property Paths: Find nodes connected but not by rdf:type (either way round):
{ ?x !(rdf:type|^rdf:type) ?y }Elements in an RDF collection:
{ :list rdf:rest*/rdf:first ?element }Note: This path expression does not guarantee the order of the results.
SPARQL property paths treat the RDF triples as a directed, possibly cyclic, graph with named edges. Some property paths are equivalent to a translation into triple patterns and SPARQL UNION graph patterns. Evaluation of a property path expression can lead to duplicates because any variables introduced in the equivalent pattern are not part of the results and are not already used elsewhere. They are hidden by implicit projection of the results to just the variables given in the query.
For example, on the data:
@prefix : <http://example/> . :order :item :z1 . :order :item :z2 . :z1 :name "Small" . :z1 :price 5 . :z2 :name "Large" . :z2 :price 5 .
Query:
PREFIX : <http://example/>
SELECT *
{ ?s :item/:price ?x . }Results:
| s | x |
|---|---|
| <http://example/order> | 5 |
| <http://example/order> | 5 |
whereas if the query were written out to include the intermediate variable
(?_a), no rows in the results are duplicates:
PREFIX : <http://example/>
SELECT *
{ ?s :item ?_a .
?_a :price ?x . }Results:
| s | _a | x |
|---|---|---|
| <http://example/order> | <http://example/z1> | 5 |
| <http://example/order> | <http://example/z2> | 5 |
The equivalance to graphs patterns is particularly significant when query also involves an aggregation operation. The total cost of the order can be found with
PREFIX : <http://example/>
SELECT (sum(?x) AS ?total)
{
:order :item/:price ?x
}| total |
|---|
| 10 |
Connectivity between the subject and object by a property path
of arbitrary length can be found using the "zero or more"
property path operator, *, and the "one or more"
property path operator, +.
There is also a "zero or one" connectivity property path operator,
?.
Each of these operators uses the property path expression to try to find a connection between subject and object, using the path step a number of times, as restricted by the operator.
For example, finding all the the possible types of a resource, including supertypes of resources, can be achieved with:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?x ?type
{
?x rdf:type/rdfs:subClassOf* ?type
}
Similarly, finding all the people :x connects to via the
foaf:knows relationship,
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX : <http://example/>
SELECT ?person
{
:x foaf:knows+ ?person
}Such connectivity matching does not introduce duplicates (it does not incorporate any count of the number of ways the connection can be made) even if the repeated path itself would otherwise result in duplicates.
The graph matched may include cycles. Connectivity matching is defined so that matching cycles does not lead to undefined or infinite results.
The value of an expression can be added to a solution mapping by binding a new variable to the value of the expression, which is an RDF term. The variable can then be used in the query and also can be returned in results.
Three syntax forms allow this: the BIND keyword,
expressions in the
SELECT clause and expressions in the GROUP BY clause.
The assignment form is (expression AS ?var).
If the evaluation of the expression produces an error, the variable remains unbound for that solution but the query evaluation continues.
Data can also be directly included in a query using
VALUES for inline data.
The BIND form allows a value to be assigned to a variable from a
basic graph pattern or property path expression. Use of BIND
ends the preceding basic graph pattern. The variable introduced by
the BIND clause must not have been used in the group graph
pattern up to the point of use in BIND.
Example:
Data:
@prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix : <http://example.org/book/> . @prefix ns: <http://example.org/ns#> . :book1 dc:title "SPARQL Tutorial" . :book1 ns:price 42 . :book1 ns:discount 0.2 . :book2 dc:title "The Semantic Web" . :book2 ns:price 23 . :book2 ns:discount 0.25 .
Query:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX ns: <http://example.org/ns#>
SELECT ?title ?price
{ ?x ns:price ?p .
?x ns:discount ?discount
BIND (?p*(1-?discount) AS ?price)
FILTER(?price < 20)
?x dc:title ?title .
}Equivalent query (BIND ends the basic graph pattern;
the FILTER applies to the whole group graph pattern):
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX ns: <http://example.org/ns#>
SELECT ?title ?price
{ { ?x ns:price ?p .
?x ns:discount ?discount
BIND (?p*(1-?discount) AS ?price)
}
{?x dc:title ?title . }
FILTER(?price < 20)
}Results:
| title | price |
|---|---|
| "The Semantic Web" | 17.25 |
Data can be directly written in a graph pattern or added to a query using
VALUES. VALUES provides inline data as a
solution sequence
which are combined with the results of query evaluation by a
join operation. It can be used by an
application to provide specific requirements on query results
and also by SPARQL query engine implementations that provide
federated query through
the SERVICE keyword to send a more constrained query to a
remote query service.
VALUES allows multiple variables to be specified in the
data block; there is a special syntax for the common case of specifying
just one variable and some values.
In the following example, there is a table of two variables,
?x and ?y. The second row has no value for
?y.
VALUES (?x ?y) {
(:uri1 1)
(:uri2 UNDEF)
}Optionally, when there is a single variable and some values:
VALUES ?z { "abc" "def" }which is the same as using the general form:
VALUES (?z) { ("abc") ("def") }A VALUES block of data can appear in a query pattern or
at the end of a SELECT query, including a
subquery.
Data:
@prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix : <http://example.org/book/> . @prefix ns: <http://example.org/ns#> . :book1 dc:title "SPARQL Tutorial" . :book1 ns:price 42 . :book2 dc:title "The Semantic Web" . :book2 ns:price 23 .
Query:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX : <http://example.org/book/>
PREFIX ns: <http://example.org/ns#>
SELECT ?book ?title ?price
{
VALUES ?book { :book1 :book3 }
?book dc:title ?title ;
ns:price ?price .
}Result:
If a variable has no value for a particular solution in the
VALUES clause, the keyword UNDEF is used
instead of an RDF term.
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX : <http://example.org/book/>
PREFIX ns: <http://example.org/ns#>
SELECT ?book ?title ?price
{
?book dc:title ?title ;
ns:price ?price .
VALUES (?book ?title)
{ (UNDEF "SPARQL Tutorial")
(:book2 UNDEF)
}
}| book | title | price |
|---|---|---|
| <http://example.org/book/book1> | "SPARQL Tutorial" | 42 |
| <http://example.org/book/book2> | "The Semantic Web" | 23 |
In this example, the VALUES might have been specified
to execute over the results of the SELECT query:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX : <http://example.org/book/>
PREFIX ns: <http://example.org/ns#>
SELECT ?book ?title ?price
{
?book dc:title ?title ;
ns:price ?price .
}
VALUES (?book ?title)
{ (UNDEF "SPARQL Tutorial")
(:book2 UNDEF)
}This is a different query but, in the example situation, has the same results.
Aggregates apply expressions over groups of solutions. By default a solution set consists of a single group, containing all solutions.
Grouping may be specified using the GROUP BY syntax.
Aggregates defined in version 1.1 of SPARQL are
COUNT, SUM, MIN, MAX, AVG, GROUP_CONCAT, and SAMPLE.
Aggregates are used where the querier wishes to see a result which is computed over a group of solutions, rather than a single solution. For example the maximum value that a particular variable takes, rather than each value individually.
Data:
@prefix : <http://books.example/> . :org1 :affiliates :auth1, :auth2 . :auth1 :writesBook :book1, :book2 . :book1 :price 9 . :book2 :price 5 . :auth2 :writesBook :book3 . :book3 :price 7 . :org2 :affiliates :auth3 . :auth3 :writesBook :book4 . :book4 :price 7 .
Query:
PREFIX : <http://books.example/>
SELECT (SUM(?lprice) AS ?totalPrice)
WHERE {
?org :affiliates ?auth .
?auth :writesBook ?book .
?book :price ?lprice .
}
GROUP BY ?org
HAVING (SUM(?lprice) > 10)Results:
| totalPrice |
|---|
| 21 |
This example demonstrates two features of aggregates: GROUP BY, which
groups query solutions according to one or more expressions (in this case
?org), and HAVING, which is analogous to a FILTER
expression, but operates over groups, rather than individual solutions.
The example is produced by grouping solutions according to the GROUP BY
expression (i.e. all solutions where ?org takes a particular value appear
within the same group), and evaluating the Set Function SUM over that group.
The groups are then filtered by the HAVING expression, which removes
all groups where SUM(?lprice) is not greater than 10.
In aggregate queries and sub-queries, variables that appear in the
query pattern, but are not in the GROUP BY clause, can only be
projected or used in select expressions if they are aggregated. The
SAMPLE aggregate may be used for this purpose. For details see the
section on Projection Restrictions.
It should be noted that as per functions, aggregate expressions are required to be aliased (again, similar to the BIND clause, using the keyword AS) in order to project them from queries or subqueries. In the example above this is done using the variable ?totalPrice. It is an error for aggregates to project variables with a name already used in other aggregate projections, or in the WHERE clause.
In order to calculate aggregate values for a solution, the solution is first divided into one or more groups, and the aggregate value is calculated for each group.
If aggregates are used in the query level in SELECT,
HAVING or ORDER BY but the GROUP BY term is not used,
then this is taken to be a single implicit group, to which all solutions belong.
Within GROUP BY clauses the binding keyword, AS, may be used, such as GROUP BY (?x + ?y AS ?z). This is equivalent to { ... BIND (?x + ?y AS ?z) } GROUP BY ?z.
For example, given a solution sequence S, ( {?x→2, ?y→3}, {?x→2, ?y→5}, {?x→6, ?y→7} ), we might wish to group the solutions according to the value of ?x, and calculate the average of the values of ?y for each group.
This could be written as:
SELECT (AVG(?y) AS ?avg)
WHERE {
?a :x ?x ;
:y ?y .
}
GROUP BY ?xHAVING operates over grouped solution sets, in the same way that FILTER operates over un-grouped ones.
HAVING expressions have the same evaluation rules as projections from
grouped queries, as described in the following section.
An example of the use of HAVING is given below.
PREFIX : <http://data.example/>
SELECT (AVG(?size) AS ?asize)
WHERE {
?x :size ?size
}
GROUP BY ?x
HAVING(AVG(?size) > 10)This will return average sizes, grouped by the subject, but only where the mean size is greater than 10.
In a query level which uses aggregates, only expressions consisting of aggregates and constants may be projected, with one exception. When GROUP BY is given with one or more simple expressions consisting of just a variable, those variables may be projected from the level.
For example, the following query is legal as ?x is given as a GROUP BY term.
PREFIX : <http://example.com/data/#>
SELECT ?x (MIN(?y) * 2 AS ?min)
WHERE {
?x :p ?y .
?x :q ?z .
} GROUP BY ?x (STR(?z))Note that it would not be legal to project STR(?z) as this is not a simple variable expression. However, with GROUP BY (STR(?z) AS ?strZ) it would be possible to project ?strZ.
Other expressions, not using GROUP BY variables, or aggregates may have non-deterministic values projected from their groups using the SAMPLE aggregate.
This section shows an example query using aggregation, which demonstrates how errors are handled in results, in the presence of aggregates.
Data:
@prefix : <http://example.com/data/#> . :x :p 1, 2, 3, 4 . :y :p 1, _:b2, 3, 4 . :z :p 1.0, 2.0, 3.0, 4 .
Query:
PREFIX : <http://example.com/data/#>
SELECT ?g (AVG(?p) AS ?avg) ((MIN(?p) + MAX(?p)) / 2 AS ?c)
WHERE {
?g :p ?p .
}
GROUP BY ?gResult:
| g | avg | c |
|---|---|---|
| <http://example.com/data/#x> | 2.5 | 2.5 |
| <http://example.com/data/#y> | ||
| <http://example.com/data/#z> | 2.5 | 2.5 |
Note that the bindings for the :y group is not included in the results as the evaluation of Avg({1, _:b2, 3, 4}), and (_:b2 + 4) / 2 is an error, removing the bindings from the solution.
Subqueries are a way to embed SPARQL queries within other queries, normally to achieve results which cannot otherwise be achieved, such as limiting the number of results from some sub-expression within the query.
Due to the bottom-up nature of SPARQL query evaluation, the subqueries are evaluated logically first, and the results are projected up to the outer query.
Note that only variables projected out of the subquery will be visible, or in scope, to the outer query.
Data:
@prefix : <http://people.example/> . :alice :name "Alice", "Alice Foo", "A. Foo" . :alice :knows :bob, :carol . :bob :name "Bob", "Bob Bar", "B. Bar" . :carol :name "Carol", "Carol Baz", "C. Baz" .
Return a name (the one with the lowest sort order) for all the people that know Alice and have a name.
Query:
PREFIX : <http://people.example/>
PREFIX : <http://people.example/>
SELECT ?y ?minName
WHERE {
:alice :knows ?y .
{
SELECT ?y (MIN(?name) AS ?minName)
WHERE {
?y :name ?name .
} GROUP BY ?y
}
}Results:
| y | minName |
|---|---|
| :bob | "B. Bar" |
| :carol | "C. Baz" |
This result is achieved by first evaluating the inner query:
SELECT ?y (MIN(?name) AS ?minName)
WHERE {
?y :name ?name .
} GROUP BY ?yThis produces the following solution sequence:
| y | minName |
|---|---|
| :alice | "A. Foo" |
| :bob | "B. Bar" |
| :carol | "C. Baz" |
Which is joined with the results of the outer query:
| y |
|---|
| :bob |
| :carol |
The RDF data model expresses information as graphs consisting of triples with subject, predicate and object. Many RDF data stores hold multiple RDF graphs and record information about each graph, allowing an application to make queries that involve information from more than one graph.
A SPARQL query is executed against an RDF Dataset which represents a collection of graphs. An RDF Dataset comprises one graph, the default graph, which does not have a name, and zero or more named graphs, where each named graph is identified by an IRI. A SPARQL query can match different parts of the query pattern against different graphs as described in section 13.3 Querying the Dataset.
An RDF Dataset may contain zero named graphs; an RDF Dataset always contains one default graph. A query does not need to involve matching the default graph; the query can just involve matching named graphs.
The graph that is used for matching a basic graph pattern is the active
graph. In the previous sections, all queries have been shown executed
against a single graph, the default graph of an RDF dataset as the active graph.
The GRAPH keyword is used to make the active graph one of all of
the named graphs in the dataset for part of the query.
The definition of RDF Dataset does not restrict the relationships of named and default graphs. Information can be repeated in different graphs; relationships between graphs can be exposed. Two useful arrangements are:
# Default graph @prefix dc: <http://purl.org/dc/elements/1.1/> . <http://example.org/bob> dc:publisher "Bob" . <http://example.org/alice> dc:publisher "Alice" .
# Named graph: http://example.org/bob @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Bob" . _:a foaf:mbox <mailto:bob@oldcorp.example.org> .
# Named graph: http://example.org/alice @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example.org> .
In this example, the default graph contains the names of the publishers of two named graphs. The triples in the named graphs are not visible in the default graph in this example.
Example 2:
RDF data can be combined by the RDF merge [RDF-MT] of graphs. One possible arrangement of graphs in an RDF Dataset is to have the default graph be the RDF merge of some or all of the information in the named graphs.
In this next example, the named graphs contain the same triples as before. The RDF dataset includes an RDF merge of the named graphs in the default graph, re-labeling blank nodes to keep them distinct.
# Default graph @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:x foaf:name "Bob" . _:x foaf:mbox <mailto:bob@oldcorp.example.org> . _:y foaf:name "Alice" . _:y foaf:mbox <mailto:alice@work.example.org> .
# Named graph: http://example.org/bob @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Bob" . _:a foaf:mbox <mailto:bob@oldcorp.example.org> .
# Named graph: http://example.org/alice @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example> .
In an RDF merge, blank nodes in the merged graph are not shared with blank nodes from the graphs being merged.
A SPARQL query may specify the dataset to be used for matching by using the
FROM clause and the FROM NAMED clause to describe the
RDF dataset. If a query provides such a dataset description, then it is used in
place of any dataset that the query service would use if no dataset description
is provided in a query. The RDF dataset may also be
specified in a SPARQL protocol request, in which case the protocol description
overrides any description in the query itself. A query service may refuse a query
request if the dataset description is not acceptable to the service.
The FROM and FROM NAMED keywords allow a query to specify
an RDF dataset by reference; they indicate that the dataset should include graphs
that are obtained from representations of the resources identified by the given
IRIs (i.e. the absolute form of the given IRI references). The dataset resulting
from a number of FROM and FROM NAMED clauses is:
FROM clauses, andFROM NAMED clause.If there is no FROM clause, but there is one or more FROM NAMED
clauses, then the dataset includes an empty graph for the default graph.
Each FROM clause contains an IRI that indicates a graph to be
used to form the default graph. This does not put the graph in as a named graph.
In this example, the RDF Dataset contains a single default graph and no named graphs:
# Default graph (located at http://example.org/foaf/aliceFoaf) @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example> .
If a query provides more than one FROM clause, providing more than
one IRI to indicate the default graph, then the default graph is the
RDF merge of the
graphs obtained from representations of the resources identified by the given IRIs.
A query can supply IRIs for the named graphs in the RDF Dataset using the
FROM NAMED clause. Each IRI is used to provide one named graph in the
RDF Dataset. Using the same IRI in two or more FROM NAMED clauses results
in one named graph with that IRI appearing in the dataset.
# Graph: http://example.org/bob @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Bob" . _:a foaf:mbox <mailto:bob@oldcorp.example.org> .
# Graph: http://example.org/alice @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example> .
... FROM NAMED <http://example.org/alice> FROM NAMED <http://example.org/bob> ...
The FROM NAMED syntax suggests that the IRI identifies the corresponding
graph, but the relationship between an IRI and a graph in an RDF dataset
is indirect. The IRI identifies a resource, and the resource is represented by a
graph (or, more precisely: by a document that serializes a graph). For
further details
see [WEBARCH].
The FROM clause and FROM NAMED clause can be used in
the same query.
# Default graph (located at http://example.org/dft.ttl) @prefix dc: <http://purl.org/dc/elements/1.1/> . <http://example.org/bob> dc:publisher "Bob Hacker" . <http://example.org/alice> dc:publisher "Alice Hacker" .
# Named graph: http://example.org/bob @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Bob" . _:a foaf:mbox <mailto:bob@oldcorp.example.org> .
# Named graph: http://example.org/alice @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example.org> .
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?who ?g ?mbox
FROM <http://example.org/dft.ttl>
FROM NAMED <http://example.org/alice>
FROM NAMED <http://example.org/bob>
WHERE
{
?g dc:publisher ?who .
GRAPH ?g { ?x foaf:mbox ?mbox }
}
The RDF Dataset for this query contains a default graph and two named graphs.
The GRAPH keyword is described below.
The actions required to construct the dataset are not determined by the
dataset description alone. If an IRI is given twice in a dataset
description, either by using two FROM clauses, or a FROM clause and a
FROM NAMED clause, then it does not assume that exactly one or exactly
two attempts are made to obtain an RDF graph associated with the IRI.
Therefore, no assumptions can be made about blank node identity in
triples obtained from the two occurrences in the dataset description.
In general, no assumptions can be made about the equivalence of the graphs.
When querying a collection of graphs, the GRAPH keyword is used
to match patterns against named graphs. GRAPH can provide an IRI to select
one graph or use a variable which will range over the IRI of all the named graphs in the query's RDF dataset.
The use of GRAPH changes the active graph for matching
graph patterns within that part of the query. Outside the use of GRAPH,
matching is done using the default graph.
The following two graphs will be used in examples:
# Named graph: http://example.org/foaf/aliceFoaf
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
_:a foaf:name "Alice" .
_:a foaf:mbox <mailto:alice@work.example> .
_:a foaf:knows _:b .
_:b foaf:name "Bob" .
_:b foaf:mbox <mailto:bob@work.example> .
_:b foaf:nick "Bobby" .
_:b rdfs:seeAlso <http://example.org/foaf/bobFoaf> .
<http://example.org/foaf/bobFoaf>
rdf:type foaf:PersonalProfileDocument .
# Named graph: http://example.org/foaf/bobFoaf
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
_:z foaf:mbox <mailto:bob@work.example> .
_:z rdfs:seeAlso <http://example.org/foaf/bobFoaf> .
_:z foaf:nick "Robert" .
<http://example.org/foaf/bobFoaf>
rdf:type foaf:PersonalProfileDocument .
The query below matches the graph pattern against each of the named graphs in the
dataset and forms solutions which have the src variable bound to
IRIs of the graph being matched. The graph pattern is matched with the active
graph being each of the named graphs in the dataset.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?src ?bobNick
FROM NAMED <http://example.org/foaf/aliceFoaf>
FROM NAMED <http://example.org/foaf/bobFoaf>
WHERE
{
GRAPH ?src
{ ?x foaf:mbox <mailto:bob@work.example> .
?x foaf:nick ?bobNick
}
}
The query result gives the name of the graphs where the information was found and the value for Bob's nick:
The query can restrict the matching applied to a specific graph by supplying
the graph IRI. This sets the active graph to the graph named by the IRI. This query looks for Bob's nick as given in the graph http://example.org/foaf/bobFoaf.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX data: <http://example.org/foaf/>
SELECT ?nick
FROM NAMED <http://example.org/foaf/aliceFoaf>
FROM NAMED <http://example.org/foaf/bobFoaf>
WHERE
{
GRAPH data:bobFoaf {
?x foaf:mbox <mailto:bob@work.example> .
?x foaf:nick ?nick }
}
which yields a single solution:
A variable used in the GRAPH clause may also be used in another
GRAPH clause or in a graph pattern matched against the default graph
in the dataset.
The query below uses the graph
with IRI http://example.org/foaf/aliceFoaf to find the profile document
for Bob; it then matches another pattern against that graph. The pattern in the
second GRAPH clause finds the blank node (variable w)
for the person with the same mail box (given by variable mbox) as
found in the first GRAPH clause (variable whom), because
the blank node used to match for variable whom from Alice's FOAF
file is not the same as the blank node in the profile document (they are in different
graphs).
PREFIX data: <http://example.org/foaf/>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?mbox ?nick ?ppd
FROM NAMED <http://example.org/foaf/aliceFoaf>
FROM NAMED <http://example.org/foaf/bobFoaf>
WHERE
{
GRAPH data:aliceFoaf
{
?alice foaf:mbox <mailto:alice@work.example> ;
foaf:knows ?whom .
?whom foaf:mbox ?mbox ;
rdfs:seeAlso ?ppd .
?ppd a foaf:PersonalProfileDocument .
} .
GRAPH ?ppd
{
?w foaf:mbox ?mbox ;
foaf:nick ?nick
}
}
Any triple in Alice's FOAF file giving Bob's nick is not used to
provide a nick for Bob because the pattern involving variable nick
is restricted by ppd to a particular Personal Profile Document.
Query patterns can involve both the default graph and the named graphs. In this example, an aggregator has read in a Web resource on two different occasions. Each time a graph is read into the aggregator, it is given an IRI by the local system. The graphs are nearly the same but the email address for "Bob" has changed.
In this example, the default graph is being used to record the provenance information and the RDF data actually read is kept in two separate graphs, each of which is given a different IRI by the system. The RDF dataset consists of two named graphs and the information about them.
RDF Dataset:
# Default graph @prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix g: <tag:example.org,2005-06-06:> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . g:graph1 dc:publisher "Bob" . g:graph1 dc:date "2004-12-06"^^xsd:date . g:graph2 dc:publisher "Bob" . g:graph2 dc:date "2005-01-10"^^xsd:date .
# Graph: locally allocated IRI: tag:example.org,2005-06-06:graph1 @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example> . _:b foaf:name "Bob" . _:b foaf:mbox <mailto:bob@oldcorp.example.org> .
# Graph: locally allocated IRI: tag:example.org,2005-06-06:graph2 @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example> . _:b foaf:name "Bob" . _:b foaf:mbox <mailto:bob@newcorp.example.org> .
This query finds email addresses, detailing the name of the person and the date the information was discovered.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?name ?mbox ?date
WHERE
{ ?g dc:publisher ?name ;
dc:date ?date .
GRAPH ?g
{ ?person foaf:name ?name ; foaf:mbox ?mbox }
}
The results show that the email address for "Bob" has changed.
This document incorporates the syntax for SPARQL federation extensions.
This feature is defined in the document SPARQL 1.1 Federated Query.
Query patterns generate an unordered collection of solutions, each solution being a partial function from variables to RDF terms. These solutions are then treated as a sequence (a solution sequence), initially in no specific order; any sequence modifiers are then applied to create another sequence. Finally, this latter sequence is used to generate one of the results of a SPARQL query form.
A solution sequence modifier is one of:
Modifiers are applied in the order given by the list above.
The ORDER BY clause establishes the order of a solution sequence.
Following the ORDER BY clause is a sequence of order comparators, composed of an expression and an optional order modifier (either ASC() or DESC()). Each ordering comparator is either ascending (indicated by the ASC() modifier or by no modifier) or descending (indicated by the DESC() modifier).
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name
WHERE { ?x foaf:name ?name }
ORDER BY ?name
PREFIX : <http://example.org/ns#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name
WHERE { ?x foaf:name ?name ; :empId ?emp }
ORDER BY DESC(?emp)
PREFIX : <http://example.org/ns#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name
WHERE { ?x foaf:name ?name ; :empId ?emp }
ORDER BY ?name DESC(?emp)
The "<" operator (see the Operator Mapping and 17.3.1 Operator Extensibility) defines
the relative order of pairs of numerics, simple literals, xsd:strings, xsd:booleans
and xsd:dateTimes. Pairs of IRIs are ordered by comparing them as simple literals.
SPARQL also fixes an order between some kinds of RDF terms that would not otherwise be ordered:
A plain literal is lower than an RDF literal with type xsd:string of the same lexical form.
SPARQL does not define a total ordering of all possible RDF terms. Here are a few examples of pairs of terms for which the relative order is undefined:
This list of variable bindings is in ascending order:
| RDF Term | Reason |
|---|---|
| Unbound results sort earliest. | |
_:z | Blank nodes follow unbound. |
_:a | There is no relative ordering of blank nodes. |
<http://script.example/Latin> | IRIs follow blank nodes. |
<http://script.example/Кириллица> | The character in the 23rd position, "К", has a unicode codepoint 0x41A, which is higher than 0x4C ("L"). |
<http://script.example/漢字> | The character in the 23rd position, "漢", has a unicode codepoint 0x6F22, which is higher than 0x41A ("К"). |
"http://script.example/Latin" | Simple literals follow IRIs. |
"http://script.example/Latin"^^xsd:string | xsd:strings follow simple literals. |
The ascending order of two solutions with respect to an ordering comparator is established by substituting the solution bindings into the expressions and comparing them with the "<" operator. The descending order is the reverse of the ascending order.
The relative order of two solutions is the relative order of the two solutions with respect to the first ordering comparator in the sequence. For solutions where the substitutions of the solution bindings produce the same RDF term, the order is the relative order of the two solutions with respect to the next ordering comparator. The relative order of two solutions is undefined if no order expression evaluated for the two solutions produces distinct RDF terms.
Ordering a sequence of solutions always results in a sequence with the same number of solutions in it.
Using ORDER BY on a solution sequence for a CONSTRUCT or
DESCRIBE query has no direct effect because only SELECT returns
a sequence of results. Used in combination with LIMIT and OFFSET,
ORDER BY can be used to return results generated from a different slice of the solution sequence.
An ASK query does not include ORDER BY, LIMIT or OFFSET.
The solution sequence can be transformed into one involving only a subset of the variables. For each solution in the sequence, a new solution is formed using a specified selection of the variables using the SELECT query form.
The following example shows a query to extract just the names of people described in an RDF graph using FOAF properties.
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example> . _:b foaf:name "Bob" . _:b foaf:mbox <mailto:bob@work.example> .
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name
WHERE
{ ?x foaf:name ?name }
| name |
|---|
| "Bob" |
| "Alice" |
A solution sequence with no DISTINCT or REDUCED query modifier
will preserve duplicate solutions.
Data:
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:x foaf:name "Alice" . _:x foaf:mbox <mailto:alice@example.com> . _:y foaf:name "Alice" . _:y foaf:mbox <mailto:asmith@example.com> . _:z foaf:name "Alice" . _:z foaf:mbox <mailto:alice.smith@example.com> .
Query:
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name WHERE { ?x foaf:name ?name }
Results:
| name |
|---|
| "Alice" |
| "Alice" |
| "Alice" |
The modifiers DISTINCT and REDUCED affect whether duplicates are included in the query results.
The DISTINCT solution modifier eliminates duplicate solutions.
Only one solution solution that binds the same variables to the same RDF terms is returned from the query.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT DISTINCT ?name WHERE { ?x foaf:name ?name }
| name |
|---|
| "Alice" |
Note that, per the order of solution sequence modifiers, duplicates are eliminated before either limit or offset is applied.
While the DISTINCT modifier ensures that duplicate solutions are eliminated from the solution set, REDUCED simply permits them to be eliminated. The cardinality of any set of variable bindings in a REDUCED solution set is at least one and not more than the cardinality of the solution set with no DISTINCT or REDUCED modifier. For example, using the data above, the query
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT REDUCED ?name WHERE { ?x foaf:name ?name }
may have one, two (shown here) or three solutions:
| name |
|---|
| "Alice" |
| "Alice" |
OFFSET causes the solutions generated to start after the specified
number of solutions. An OFFSET of zero has no effect.
Using
LIMIT and OFFSET to select different subsets of the query solutions
will not be useful unless the order is made predictable by using ORDER BY.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name
WHERE { ?x foaf:name ?name }
ORDER BY ?name
LIMIT 5
OFFSET 10The LIMIT clause puts an upper bound on the number of solutions returned. If the
number of actual solutions, after OFFSET is applied, is greater than the limit,
then at most the limit number of solutions will be returned.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name
WHERE { ?x foaf:name ?name }
LIMIT 20
A LIMIT of 0 would cause no results to be returned. A limit may not be negative.
SPARQL has four query forms. These query forms use the solutions from pattern matching to form result sets or RDF graphs. The query forms are:
- SELECT
- Returns all, or a subset of, the variables bound in a query pattern match.
- CONSTRUCT
- Returns an RDF graph constructed by substituting variables in a set of triple templates.
- ASK
- Returns a boolean indicating whether a query pattern matches or not.
- DESCRIBE
- Returns an RDF graph that describes the resources found.
Formats such as
SPARQL 1.1 Query Results JSON Format,
SPARQL Query Results XML Format or
SPARQL 1.1 Query Results CSV and TSV Formats
can be used to serialize the result set from a
SELECT query or the boolean result of an ASK query.
The SELECT form of results returns variables and their bindings directly. It combines the operations of projecting the required variables with introducing new variable bindings into a query solution.
Specific variables and their bindings are
returned when a list of variable names is given in the SELECT clause. The syntax
SELECT * is an abbreviation that
selects all of the variables that are in-scope
at that point in the query. It excludes variables only used in
FILTER, in the right-hand side of MINUS,
and takes account of subqueries.
Use of SELECT * is only permitted when the
query does not have a GROUP BY clause.
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:knows _:b . _:a foaf:knows _:c . _:b foaf:name "Bob" . _:c foaf:name "Clare" . _:c foaf:nick "CT" .
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?nameX ?nameY ?nickY
WHERE
{ ?x foaf:knows ?y ;
foaf:name ?nameX .
?y foaf:name ?nameY .
OPTIONAL { ?y foaf:nick ?nickY }
}Result sets can be accessed by a local API but also can be serialized into either JSON, XML, CSV or TSV.
SPARQL 1.1 Query Results JSON Format:
{
"head": {
"vars": [ "nameX" , "nameY" , "nickY" ]
} ,
"results": {
"bindings": [
{
"nameX": { "type": "literal" , "value": "Alice" } ,
"nameY": { "type": "literal" , "value": "Bob" }
} ,
{
"nameX": { "type": "literal" , "value": "Alice" } ,
"nameY": { "type": "literal" , "value": "Clare" } ,
"nickY": { "type": "literal" , "value": "CT" }
}
]
}
}SPARQL Query Results XML Format:
<?xml version="1.0"?>
<sparql xmlns="http://www.w3.org/2005/sparql-results#">
<head>
<variable name="nameX"/>
<variable name="nameY"/>
<variable name="nickY"/>
</head>
<results>
<result>
<binding name="nameX">
<literal>Alice</literal>
</binding>
<binding name="nameY">
<literal>Bob</literal>
</binding>
</result>
<result>
<binding name="nameX">
<literal>Alice</literal>
</binding>
<binding name="nameY">
<literal>Clare</literal>
</binding>
<binding name="nickY">
<literal>CT</literal>
</binding>
</result>
</results>
</sparql>As well as choosing which variables from the pattern matching are included in the results, the SELECT clause can also introduce new variables. The rules of assignment in SELECT expression are the same as for assignment in BIND. The expression combines variable bindings already in the query solution, or defined earlier in the SELECT clause, to produce a binding in the query solution.
The scoping for (expr AS v) applies immediately. In
SELECT expressions, the variable may be used in an expression
later in the same SELECT clause and may not be
be assigned again in the same SELECT clause.
Example:
Data:
@prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix : <http://example.org/book/> . @prefix ns: <http://example.org/ns#> . :book1 dc:title "SPARQL Tutorial" . :book1 ns:price 42 . :book1 ns:discount 0.2 . :book2 dc:title "The Semantic Web" . :book2 ns:price 23 . :book2 ns:discount 0.25 .
Query:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX ns: <http://example.org/ns#>
SELECT ?title (?p*(1-?discount) AS ?price)
{ ?x ns:price ?p .
?x dc:title ?title .
?x ns:discount ?discount
}Results:
| title | price |
|---|---|
| "The Semantic Web" | 17.25 |
| "SPARQL Tutorial" | 33.6 |
New variables can also be used in expressions if they are introduced earlier, syntactically, in the same SELECT clause:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX ns: <http://example.org/ns#>
SELECT ?title (?p AS ?fullPrice) (?fullPrice*(1-?discount) AS ?customerPrice)
{ ?x ns:price ?p .
?x dc:title ?title .
?x ns:discount ?discount
}Results:
| title | fullPrice | customerPrice |
|---|---|---|
| "The Semantic Web" | 23 | 17.25 |
| "SPARQL Tutorial" | 42 | 33.6 |
The CONSTRUCT query form returns a single RDF graph specified by
a graph template. The result is an RDF graph formed by taking each query solution
in the solution sequence, substituting for the variables in the graph template,
and combining the triples into a single RDF graph by set union.
If any such instantiation produces a triple containing an unbound variable or an illegal RDF construct, such as a literal in subject or predicate position, then that triple is not included in the output RDF graph. The graph template can contain triples with no variables (known as ground or explicit triples), and these also appear in the output RDF graph returned by the CONSTRUCT query form.
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@example.org> .
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX vcard: <http://www.w3.org/2001/vcard-rdf/3.0#>
CONSTRUCT { <http://example.org/person#Alice> vcard:FN ?name }
WHERE { ?x foaf:name ?name }
creates vcard properties from the FOAF information:
@prefix vcard: <http://www.w3.org/2001/vcard-rdf/3.0#> . <http://example.org/person#Alice> vcard:FN "Alice" .
A template can create an RDF graph containing blank nodes. The blank node labels are scoped to the template for each solution. If the same label occurs twice in a template, then there will be one blank node created for each query solution, but there will be different blank nodes for triples generated by different query solutions.
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:givenname "Alice" . _:a foaf:family_name "Hacker" . _:b foaf:firstname "Bob" . _:b foaf:surname "Hacker" .
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX vcard: <http://www.w3.org/2001/vcard-rdf/3.0#>
CONSTRUCT { ?x vcard:N _:v .
_:v vcard:givenName ?gname .
_:v vcard:familyName ?fname }
WHERE
{
{ ?x foaf:firstname ?gname } UNION { ?x foaf:givenname ?gname } .
{ ?x foaf:surname ?fname } UNION { ?x foaf:family_name ?fname } .
}
creates vcard properties corresponding to the FOAF information:
@prefix vcard: <http://www.w3.org/2001/vcard-rdf/3.0#> . _:v1 vcard:N _:x . _:x vcard:givenName "Alice" . _:x vcard:familyName "Hacker" . _:v2 vcard:N _:z . _:z vcard:givenName "Bob" . _:z vcard:familyName "Hacker" .
The use of variable x in the template, which in this example will be bound to
blank nodes with labels _:a and _:b in the data,
causes different blank node labels (_:v1 and _:v2) in the resulting RDF graph.
Using CONSTRUCT, it is possible to extract parts or the whole of
graphs from the target RDF dataset. This first example returns the graph (if it
is in the dataset) with IRI label http://example.org/aGraph; otherwise,
it returns an empty graph.
CONSTRUCT { ?s ?p ?o } WHERE { GRAPH <http://example.org/aGraph> { ?s ?p ?o } . }
The access to the graph can be conditional on other information. For example, if the default graph contains metadata about the named graphs in the dataset, then a query like the following one can extract one graph based on information about the named graph:
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX app: <http://example.org/ns#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
CONSTRUCT { ?s ?p ?o } WHERE
{
GRAPH ?g { ?s ?p ?o } .
?g dc:publisher <http://www.w3.org/> .
?g dc:date ?date .
FILTER ( app:customDate(?date) > "2005-02-28T00:00:00Z"^^xsd:dateTime ) .
}
where app:customDate identifies an
extension function to turn the date format into an xsd:dateTime
RDF term.
The solution modifiers of a query affect the results of a CONSTRUCT
query. In this example, the output graph from the CONSTRUCT template
is formed from just two of the solutions from graph pattern matching. The query outputs
a graph with the names of the people with the top two sites, rated by hits. The triples
in the RDF graph are not ordered.
@prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix site: <http://example.org/stats#> . _:a foaf:name "Alice" . _:a site:hits 2349 . _:b foaf:name "Bob" . _:b site:hits 105 . _:c foaf:name "Eve" . _:c site:hits 181 .
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX site: <http://example.org/stats#>
CONSTRUCT { [] foaf:name ?name }
WHERE
{ [] foaf:name ?name ;
site:hits ?hits .
}
ORDER BY desc(?hits)
LIMIT 2
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:x foaf:name "Alice" . _:y foaf:name "Eve" .
A short form for the CONSTRUCT query form is provided for the case where the template and
the pattern are the same and the pattern is just a basic graph pattern
(no FILTERs and no complex graph patterns are allowed in the short form).
The keyword WHERE is required in the short form.
The following two queries are the same; the first is a short form of the second.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
CONSTRUCT WHERE { ?x foaf:name ?name }
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
CONSTRUCT { ?x foaf:name ?name }
WHERE
{ ?x foaf:name ?name }
Applications can use the ASK form to test whether or not a query
pattern has a solution. No information is returned about the possible query solutions,
just whether or not a solution exists.
@prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:homepage <http://work.example.org/alice/> . _:b foaf:name "Bob" . _:b foaf:mbox <mailto:bob@work.example> .
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
ASK { ?x foaf:name "Alice" }
true
The SPARQL Query Results XML Format form of this result set gives:
<?xml version="1.0"?> <sparql xmlns="http://www.w3.org/2005/sparql-results#"> <head></head> <boolean>true</boolean> </sparql>
On the same data, the following returns no match because Alice's mbox
is not mentioned.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
ASK { ?x foaf:name "Alice" ;
foaf:mbox <mailto:alice@work.example> }
false
The DESCRIBE form returns a single result RDF graph containing RDF
data about resources. This data is not prescribed by a SPARQL query, where the query
client would need to know the structure of the RDF in the data source, but, instead,
is determined by the SPARQL query processor. The query pattern is used to create
a result set. The DESCRIBE form takes each of the resources identified
in a solution, together with any resources directly named by IRI, and assembles
a single RDF graph by taking a "description" which can come from any
information available including the target RDF Dataset. The
description is determined by the query service. The syntax DESCRIBE *
is an abbreviation that describes all of the variables in a query.
The DESCRIBE clause itself can take IRIs to identify the resources.
The simplest DESCRIBE query is just an IRI in the DESCRIBE
clause:
DESCRIBE <http://example.org/>
The resources to be described can also be taken from the bindings to a query variable in a result set. This enables description of resources whether they are identified by IRI or by blank node in the dataset:
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
DESCRIBE ?x
WHERE { ?x foaf:mbox <mailto:alice@org> }
The property foaf:mbox is defined as being an inverse functional property
in the FOAF vocabulary. If treated as such, this query will return information about
at most one person. If, however, the query pattern has multiple solutions, the RDF
data for each is the union of all RDF graph descriptions.
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
DESCRIBE ?x
WHERE { ?x foaf:name "Alice" }
More than one IRI or variable can be given:
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
DESCRIBE ?x ?y <http://example.org/>
WHERE {?x foaf:knows ?y}
The RDF returned is determined by the information publisher. It may be information the service deems relevant to the resources being described. It may include information about other resources: for example, the RDF data for a book may also include details about the author.
A simple query such as
PREFIX ent: <http://org.example.com/employees#>
DESCRIBE ?x WHERE { ?x ent:employeeId "1234" }
might return a description of the employee and some other potentially useful details:
@prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix vcard: <http://www.w3.org/2001/vcard-rdf/3.0> . @prefix exOrg: <http://org.example.com/employees#> . @prefixrdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix owl: <http://www.w3.org/2002/07/owl#>_:a exOrg:employeeId "1234" ;foaf:mbox_sha1sum "bee135d3af1e418104bc42904596fe148e90f033" ;vcard:N [ vcard:Family "Smith" ; vcard:Given "John" ] .foaf:mbox_sha1sum rdf:type owl:InverseFunctionalProperty .
which includes the blank node closure for the vcard vocabulary vcard:N. Other possible mechanisms for deciding what information to return include Concise Bounded Descriptions [CBD].
For a vocabulary such as FOAF, where the resources are typically blank nodes,
returning sufficient information to identify a node such as the InverseFunctionalProperty
foaf:mbox_sha1sum as well as information like name and other details recorded
would be appropriate. In the example, the match to the WHERE clause was returned,
but this is not required.
SPARQL FILTERs restrict the solutions of a graph pattern match according to a given constraint. Specifically,
FILTERs eliminate any solutions that, when substituted into the expression, either result in an effective boolean value of false or produce an error. Effective boolean values are defined in section 17.2.2 Effective Boolean Value and errors are defined in XQuery 1.0: An XML Query Language [XQUERY] section 2.3.1, Kinds of Errors. These errors have no effect outside of FILTER evaluation.
RDF literals may have a datatype IRI:
@prefix a: <http://www.w3.org/2000/10/annotation-ns#> . @prefix dc: <http://purl.org/dc/elements/1.1/> . _:a a:annotates <http://www.w3.org/TR/rdf-sparql-query/> . _:a dc:date "2004-12-31T19:00:00-05:00" . _:b a:annotates <http://www.w3.org/TR/rdf-sparql-query/> . _:b dc:date "2004-12-31T19:01:00-05:00"^^<http://www.w3.org/2001/XMLSchema#dateTime> .
The object of the first dc:date triple has no type information. The second has the datatype xsd:dateTime.
SPARQL expressions are constructed according to the grammar and provide access to functions (named by IRI) and operator functions (invoked by keywords and symbols in the SPARQL grammar). SPARQL operators can be used to compare the values of typed literals:
PREFIX a: <http://www.w3.org/2000/10/annotation-ns#>
PREFIX dc: <http://purl.org/dc/elements/1.1/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?annot
WHERE { ?annot a:annotates <http://www.w3.org/TR/rdf-sparql-query/> .
?annot dc:date ?date .
FILTER ( ?date > "2005-01-01T00:00:00Z"^^xsd:dateTime ) }The SPARQL operators are listed in section 17.3 and are associated with their productions in the grammar.
In addition, SPARQL provides the ability to invoke arbitrary functions, including a subset of the XPath casting functions, listed in section 17.5. These functions are invoked by name (an IRI) within a SPARQL query. For example:
... FILTER ( xsd:dateTime(?date) < xsd:dateTime("2005-01-01T00:00:00Z") ) ...Typographical convention in this section: XPath operators are labeled
with the prefix op:. XPath operators have no namespace;
op: is a labeling convention.
SPARQL functions and operators operate on RDF terms and SPARQL variables. A subset of these functions and operators are taken from the XQuery 1.0 and XPath 2.0 Functions and Operators [FUNCOP] and have XML Schema typed value arguments and return types.
RDF typed literals passed as arguments to these functions and operators are mapped to XML Schema typed values with a string value of the lexical form and an atomic datatype corresponding to the datatype IRI. The returned typed values are mapped back to RDF typed literals the same way.
SPARQL has additional operators which operate on specific subsets of RDF terms. When referring to a type, the following terms denote a typed literal with the corresponding XML Schema [XSDT] datatype IRI:
The following terms identify additional types used in SPARQL value tests:
typed literals with datatypes xsd:integer, xsd:decimal, xsd:float, and xsd:double.plain literal with no language tag.IRI, literal, and blank node.The following types are derived from numeric types and are valid arguments to functions and operators taking numeric arguments:
xsd:nonPositiveIntegerxsd:negativeIntegerxsd:longxsd:intxsd:shortxsd:bytexsd:nonNegativeIntegerxsd:unsignedLongxsd:unsignedIntxsd:unsignedShortxsd:unsignedBytexsd:positiveIntegerSPARQL language extensions may treat additional types as being derived from XML schema datatypes.
SPARQL provides a subset of the functions and operators defined by XQuery Operator Mapping. XQuery 1.0 section 2.2.3 Expression Processing describes the invocation of XPath functions. The following rules accommodate the differences in the data and execution models between XQuery and SPARQL:
xsd:boolean using the EBV rules in section 17.2.2.||) or logical-and (&&) that encounters an error will produce that error.The logical-and and logical-or truth table for true (T), false (F), and error (E) is as follows:
| A | B | A || B | A && B |
|---|---|---|---|
| T | T | T | T |
| T | F | T | F |
| F | T | T | F |
| F | F | F | F |
| T | E | T | E |
| E | T | T | E |
| F | E | E | F |
| E | F | E | F |
| E | E | E | E |
SPARQL defines a syntax for invoking functions on a list of arguments. Unless otherwise noted, these are invoked as follows:
If any of these steps fails, the invocation generates an error. The effects of errors are defined in Filter Evaluation.
There are also "functional forms" which have different evaluation rules to functions as specified by each such form.
Effective boolean value is used to calculate the arguments to the logical functions logical-and, logical-or, and fn:not, as well as evaluate the result of a FILTER expression.
The XQuery Effective Boolean Value rules rely on the definition of XPath's fn:boolean. The following rules reflect the rules for fn:boolean applied to the argument types present in SPARQL queries:
xsd:boolean or numeric is false if the lexical form is not valid for that datatype (e.g. "abc"^^xsd:integer).xsd:boolean, and it has a valid lexical form, the EBV is the value of that argument.xsd:string, the EBV is false if the operand value has zero length; otherwise the EBV is true.An EBV of true is represented as a typed literal with a datatype of xsd:boolean and a lexical value of "true"; an EBV of false is represented as a typed literal with a datatype of xsd:boolean and a lexical value of "false".
The SPARQL grammar identifies a set of operators (for instance, &&, *, isIRI) used to construct constraints. The following table associates each of these grammatical productions with the appropriate operands and an operator function defined by either XQuery 1.0 and XPath 2.0 Functions and Operators [FUNCOP] or the SPARQL operators specified in section 17.4. When selecting the operator definition for a given set of parameters, the definition with the most specific parameters applies. For instance, when evaluating xsd:integer = xsd:signedInt, the definition for = with two numeric parameters applies, rather than the one with two RDF terms. The table is arranged so that the upper-most viable candidate is the most specific. Operators invoked without appropriate operands result in a type error.
SPARQL follows XPath's scheme for numeric type promotions and subtype substitution for arguments to numeric operators. The XPath Operator Mapping rules for numeric operands (xsd:integer, xsd:decimal, xsd:float, xsd:double, and types derived from a numeric type) apply to SPARQL operators as well (see XML Path Language (XPath) 2.0 [XPATH20] for definitions of numeric type promotions and subtype substitution). Some of the operators are associated with nested function expressions, e.g. fn:not(op:numeric-equal(A, B)). Note that per the XPath definitions, fn:not and op:numeric-equal produce an error if their argument is an error.
The collation for fn:compare is defined by XPath and identified by http://www.w3.org/2005/xpath-functions/collation/codepoint. This collation allows for string comparison based on code point values. Codepoint string equivalence can be tested with RDF term equivalence.
| Operator | Type(A) | Function | Result type |
|---|---|---|---|
| XQuery Unary Operators | |||
| ! A | xsd:boolean (EBV) | fn:not(A) | xsd:boolean |
| + A | numeric | op:numeric-unary-plus(A) | numeric |
| - A | numeric | op:numeric-unary-minus(A) | numeric |
| Operator | Type(A) | Type(B) | Function | Result type |
|---|---|---|---|---|
| Logical Connectives | ||||
| A || B | xsd:boolean (EBV) | xsd[Truncated] | ||