SPARQL 1.2 Query Language

RDF is a directed, labeled graph data model 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-DAWG-UC ], the SPARQL 1.1 Working Group in [ SPARQL-FEATURES ], and the RDF-star Working Group.

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 1.1 Update languages, as given by a grammar expressed in EBNF notation.

In this document, examples assume the following namespace prefix definitions 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 RDF 1.1 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.

x	y	z
"Alice"	`<http://example/a>`

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. 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 1.2 Concepts and Abstract Syntax [ RDF12-CONCEPTS ] and used in SPARQL:

Blank node identifiers are part of SPARQL and RDF concrete serializations . In this document, the syntax form " _:abc " is used where the blank node identifier is abc. and the " _: " is the Turtle and SPARQL syntax used to introduce blank nodes with identifiers.

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 an RDF term 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.

Data:

<http://example.org/book/book1>
<http://purl.org/dc/elements/1.1/title>
"SPARQL
Tutorial"
.

Query:

SELECT ?title
WHERE
{
    <http://example.org/book/book1> <http://purl.org/dc/elements/1.1/title> ?title .
}

This query, on the data above, has one solution:

Query Result:

title
"SPARQL Tutorial"

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 literal with the datatype http://www.w3.org/2001/XMLSchema#integer ; and "abc"^^dt:specialDatatype is a 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 Tags for Identifying Languages [ 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 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.

SELECT
?v
WHERE
{
?v
?p
42
}

v
<http://example.org/ns#y>

Section 4.1.2 defines SPARQL shortened forms for xsd:float and xsd:double.

The following query has a solution with variable v bound to :z. The query processor does not have to have any understanding of the values in the space of the datatype. Because the lexical form and datatype IRI both match, the literal matches.

SELECT
?v
WHERE
{
?v
?p
"abc"^^<http://example.org/datatype#specialDatatype>
}

v
<http://example.org/ns#z>

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 identifier .

Blank node identifiers are scoped to a result set (see " SPARQL Query Results XML Format (Second Edition) " and " SPARQL 1.1 Query Results JSON Format ") or, for the CONSTRUCT query form, the result graph. Use of the same identifier within a result set indicates the same blank node.

Data:

PREFIX foaf:  <http://xmlns.com/foaf/0.1/>
_:a  foaf:name   "Alice" .
_:b
foaf:name
"Bob"
.

Query:

PREFIX foaf:   <http://xmlns.com/foaf/0.1/>
SELECT ?x ?name
WHERE
{
?x
foaf:name
?name
}

x	name
_:c	"Alice"
_:d	"Bob"

The results above could equally be given with different blank node identifiers because the blank node identifiers in the results only indicate whether RDF terms in the solutions are the same or different.

x	name
_:r	"Alice"
_:s	"Bob"

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 blank node identifier _:a in the result set and a blank node identifier used in the syntax for the data.

An application writer should not expect blank node identifiers in a query to refer to a particular blank node in the data.

SPARQL 1.2 allows values to be created from complex expressions. The queries below show how 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.

Data:

PREFIX foaf:  <http://xmlns.com/foaf/0.1/>
            
_:a  foaf:givenName   "John" .
_:a
foaf:surname
"Doe"
.

Query:

PREFIX foaf:   <http://xmlns.com/foaf/0.1/>
SELECT ( CONCAT(?G, " ", ?S) AS ?name )
WHERE
{
?P
foaf:givenName
?G
;
foaf:surname
?S
}

Query:

PREFIX foaf:   <http://xmlns.com/foaf/0.1/>
SELECT ?name
WHERE  { 
    ?P foaf:givenName ?G ; 
       foaf:surname ?S 
    BIND(CONCAT(?G, " ", ?S) AS ?name)
}

name
"John 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 FILTER s restrict solutions to those for which the filter expression evaluates to TRUE.

This section provides an informal introduction to SPARQL FILTER s; 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:

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
.

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:

title
"SPARQL Tutorial"

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:

title
"The Semantic Web"

The regular expression language is defined by XQuery and XPath Functions and Operators and is based on XML Schema Regular Expressions .

SPARQL FILTER s can restrict on arithmetic expressions.

Query:

PREFIX  dc:  <http://purl.org/dc/elements/1.1/>
PREFIX  ns:  <http://example.org/ns#>
SELECT  ?title ?price
WHERE   {
    ?x ns:price ?price .
    FILTER (?price < 30.5)
    ?x dc:title ?title . 
}

Query Result:

title	price
"The Semantic Web"	23

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 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 CURIE s.

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 literals with 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:integer
1.3, which is the same as "1.3"^^xsd:decimal
1.300, which is the same as "1.300"^^xsd:decimal
1.0e6, which is the same as "1.0e6"^^xsd:double
true, which is the same as "true"^^xsd:boolean
false, which is the same as "false"^^xsd:boolean

Tokens matching the productions INTEGER , DECIMAL , DOUBLE or 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 identifier form, such as " _:abc ", or an abbreviation form using " [] " or " [...] ".

Blank node identifiers are written as " _:abc " for a blank node with identifier " abc ". The same blank node identifier cannot be used in two different basic graph patterns in the same query.

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.

The [:p :v] construct can be used to create triple patterns with a unique blank node as the subject of contained predicate-object pairs.

The following two forms

[
:p
"v"
]
.

[]
:p
"v"
.

allocate a unique blank node (here, illustrated by " _:b57 ") and both are equivalent to writing:

_:b57
:p
"v"
.

The allocated blank node 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 using a blank node identifer instead.

_: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"
.

To cope with the language evolution of SPARQL, the VERSION directive can be used. When writing SPARQL queries with new features such as triple terms or functions on triple terms , authors MAY announce the use of the new syntax forms by including this directive.

VERSION "1.2"
PREFIX : <http://example/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?s ?date {
    ?s ?p ?o .
    BIND( <<( ?s ?p ?o )>> AS ?tt )
    :myreifier rdf:reifies ?tt .
    :myreifier :tripleAdded ?date .
}

SPARQL is based around graph pattern matching. More complex graph patterns can be formed by combining smaller patterns in various ways:

Basic Graph Patterns , where a set of triple patterns must match
Group Graph Pattern , where a set of graph patterns must all match
Optional Graph patterns , where additional patterns may extend the solution
Alternative Graph Pattern , where two or more possible patterns are tried
Patterns on Named Graphs , where patterns are matched against named graphs

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, identifiers for blank nodes are scoped to the basic graph pattern. A blank node identifier can only be used in one 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 .
}

The same solutions would be obtained from a query that grouped the triple patterns into two basic graph patterns. For example, the query below has a different structure but would yield the same solutions as the previous query:

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"
.

Query:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE  {
    ?x foaf:name  ?name .
    OPTIONAL { ?x  foaf:mbox  ?mbox }
}

With the data above, the query result is:

name	mbox
"Alice"	<mailto:alice@example.com>
"Alice"	<mailto:alice@work.example>
"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
.

PREFIX  dc:  <http://purl.org/dc/elements/1.1/>
PREFIX  ns:  <http://example.org/ns#>
SELECT  ?title ?price
WHERE   { 
    ?x dc:title ?title .
    OPTIONAL { ?x ns:price ?price . FILTER (?price < 30) }
}

title	price
"SPARQL Tutorial"
"The Semantic Web"	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.

Data:

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>
.

Query:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox ?hpage
WHERE  {
    ?x foaf:name  ?name .
    OPTIONAL { ?x foaf:mbox ?mbox } .
    OPTIONAL { ?x foaf:homepage ?hpage }
}

Query result:

name	mbox	hpage
"Alice"		<http://work.example.org/alice/>
"Bob"	<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.

Data:

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)"
.

Query:

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:

title
"SPARQL Protocol Tutorial"
"SPARQL"
"SPARQL (updated)"
"SPARQL Query Language Tutorial"

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
}
}

x	y
	"SPARQL (updated)"
	"SPARQL Protocol Tutorial"
"SPARQL"
"SPARQL Query Language Tutorial"

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 }
}

title	author
"SPARQL Query Language Tutorial"	"Alice"
"SPARQL Protocol Tutorial"	"Bob"

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.

Data:

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"
.

Query:

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 `!( iri ₁ \| ...\| iri _n )`	NegatedPropertySet	Negated property set. An IRI which is not one of `iri _i`. `! iri` is short for `! (iri)`.
`!^ iri` or `!(^ iri ₁ \| ...\|^ iri _n )`	NegatedPropertySet	Negated property set where the excluded matches are based on reversed path. That is, not one of iri ₁ ... iri _n as reverse paths. `!^ iri` is short for `!(^ iri )`.
`!( iri ₁ \| ...\| iri _j \|^ iri _j+1 \| ...\|^ iri _n )`	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:

IRI, prefixed names
Negated property sets
Groups
Unary operators *, ? and +
Unary ^ inverse links
Binary operator /
Binary operator |

Precedence is left-to-right within groups.

Alternatives : Match one or both possibilities

{
:book1
dc:title|rdfs:label
?displayString
}

which could have written:

{ 
   :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. 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 equivalence 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:

book	title	price
<http://example.org/book/book1>	"SPARQL Tutorial"	42

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
?x

HAVING 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
?g

Result:

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
?y

This 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 [ RDF12-CONCEPTS ] 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 or a blank node. 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 [ RDF12-CONCEPTS ] 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:

to have information in the default graph that includes provenance information about the named graphs
to include the information in the named graphs in the default graph as well.

Example 1:

PREFIX dc: <http://purl.org/dc/elements/1.1/>
<http://example.org/bob>    dc:publisher  "Bob" .
<http://example.org/alice>  dc:publisher  "Alice" .
GRAPH <http://example.org/bob> {
    _:a foaf:name "Bob" .
    _:a foaf:mbox <mailto:bob@oldcorp.example.org> .
}
GRAPH <http://example.org/alice> {
    _: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 [ RDF12-SEMANTICS ] 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, which keeps blank nodes distinct.

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> .
GRAPH <http://example.org/bob> {
    _:a foaf:name "Bob" .
    _:a foaf:mbox <mailto:bob@oldcorp.example.org> .
}
GRAPH <http://example.org/alice> {
    _: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:

a default graph consisting of the RDF merge of the graphs referred to in the FROM clauses, and
a set of (IRI, graph) pairs, one from each FROM 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>
.

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT  ?name
FROM    <http://example.org/foaf/aliceFoaf>
WHERE
{
?x
foaf:name
?name
}

name
"Alice"

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:

src	bobNick
<http://example.org/foaf/aliceFoaf>	"Bobby"
<http://example.org/foaf/bobFoaf>	"Robert"

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:

nick
"Robert"

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
    }
}

mbox	nick	ppd
<mailto:bob@work.example>	"Robert"	<http://example.org/foaf/bobFoaf>

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.

name	mbox	date
"Bob"	<mailto:bob@oldcorp.example.org>	"2004-12-06"^^xsd:date
"Bob"	<mailto:bob@newcorp.example.org>	"2005-01-10"^^xsd:date

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:

Order modifier: put the solutions in order
Projection modifier: choose certain variables
Distinct modifier: ensure solutions in the sequence are unique
Reduced modifier: permit elimination of some non-distinct solutions
Offset modifier: control where the solutions start from in the overall sequence of solutions
Limit modifier: restrict the number of solutions

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, xsd:strings, xsd:booleans and xsd:dateTimes. Pairs of IRIs are ordered by comparing them as literals with datatype xsd:string.

SPARQL also fixes an order between some kinds of RDF terms that would not otherwise be ordered:

(Lowest) no value assigned to the variable or expression in this solution.
Blank nodes
IRIs
RDF literals

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:

"a" and "a"@en_gb (a literal with datatype xsd:string and a literal with a language tag)
"a"@en_gb and "b"@en_gb (two literals with language tags)
"a" and "1"^^xsd:integer (a literal with datatype xsd:string and a literal with a supported datatype)
"1"^^my:integer and "2"^^my:integer (two unsupported datatypes)
"1"^^xsd:integer and "2"^^my:integer (a supported datatype and an unsupported datatype)

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"`	`xsd:strings` follow IRIs.

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 multiplicity of any solution in a REDUCED solution set is at least one and not more than the multiplicity of the solution within 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
10

The 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 (Second Edition) 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 }
}

nameX	nameY	nickY
"Alice"	"Bob"
"Alice"	"Clare"	"CT"

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 (Second Edition) :

<?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.

Note

The construction of the result graph by "set union" does not enforce whether or not duplicated triples appear in the graph serialization. Implementations are allowed to produce duplicate triples or to deduplicate them.

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 identifiers inside the template are scoped to the template for each solution, while blank nodes from query solutions are not scoped. If the same identifier occurs twice in a template, every occurrence is replaced by the same blank node which is created for each query solution, and 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#>
_:a vcard:N         _:v1 .
_:v1 vcard:givenName  "Alice" .
_:v1 vcard:familyName "Hacker" .
_:b vcard:N         _:v2 .
_:v2 vcard:givenName  "Bob" .
_:v2
vcard:familyName
"Hacker"
.

The blank node with identifier _:v in the template will be replaced by a different blank node when the template is applied to each of the two query solutions. In this example, this will cause the template to generate blank nodes with identifier _:v1 and _:v2 in the results graph.

The blank nodes in the query solutions, shown with identifiers _:a and _:b, originate from the underlying RDF dataset and will not be altered.

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 derived 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 FILTER s 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 (Second Edition) 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#>
PREFIX rdf:    <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 3.1: An XML Query Language [ XQUERY-31 ] section 2.3.1, Kinds of Errors . These errors have no effect outside of FILTER evaluation.

RDF Literals have datatypes that determine the value of the literal.

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 is a literal that has a datatype of xsd:string. The second has the datatype xsd:dateTime. They are different RDF terms with different values.

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 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 XPath and XQuery Functions and Operators 3.1 [ XPATH-FUNCTIONS-31 ] and have XML Schema typed value arguments and return types. RDF 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 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 literal with the corresponding W3C XML Schema Definition Language (XSD) 1.1 Part 2: Datatypes [ XMLSCHEMA11-2 ] datatype IRI :

The following terms identify additional types used in SPARQL value tests:

numeric denotes literals with datatypes xsd:integer, xsd:decimal, xsd:float, or xsd:double.
RDF term denotes the types IRI , literal , blank node , or triple term .
variable denotes a SPARQL variable.

The following types are derived from numeric types and are valid arguments to functions and operators taking numeric arguments:

SPARQL 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 . The XQuery section Expression Processing describes the invocation of XPath functions. The following rules accommodate the differences in the data and execution models between XQuery and SPARQL:

Unlike XPath/XQuery, SPARQL functions do not process node sequences. When interpreting the semantics of XPath functions, assume that each argument is a sequence of a single node.
Functions invoked with an argument of the wrong type will produce a type error . Effective boolean value arguments (labeled "xsd:boolean (EBV)" in the operator mapping table below), are coerced to xsd:boolean using the EBV rules in section 17.2.2.
Apart from the functional forms BOUND , COALESCE , IF , IN , NOT IN , logical-or ( || ), logical-and ( && ), NOT EXISTS , and EXISTS , all functions operate on RDF Terms and will produce a type error if any arguments are unbound.
Any expression other than logical-or ( || ) or logical-and ( && ) that encounters an error will produce that error.
A logical-or that encounters an error on only one branch will return TRUE if the other branch is TRUE and an error if the other branch is FALSE.
A logical-and that encounters an error on only one branch will return an error if the other branch is TRUE and FALSE if the other branch is FALSE.
A logical-or or logical-and that encounters errors on both branches will produce either of the errors.

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:

Argument expressions are evaluated, producing argument values. The order of argument evaluation is not defined.
Numeric arguments are promoted as necessary to fit the expected types for that function or operator.
The function or operator is invoked on the argument values.

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:

The EBV of any literal whose type is xsd:boolean or numeric is false if the lexical form is not valid for that datatype, such as "abc"^^xsd:integer.
If the argument is a typed literal with a datatype of xsd:boolean, and it has a valid lexical form, the EBV is the value of that argument.
If the argument is a literal with a datatype of xsd:string, the EBV is false if the operand value has zero length; otherwise the EBV is true.
If the argument is a numeric type or a typed literal with a datatype derived from a numeric type, and it has a valid lexical form, the EBV is false if the operand value is NaN or is numerically equal to zero; otherwise the EBV is true.
All other arguments, including unbound arguments, produce a type error.

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 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 XPath and XQuery Functions and Operators 3.1 [ XPATH-FUNCTIONS-31 ] 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) 3.1 [ XPATH-31 ] 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.

SPARQL Unary Operators
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

SPARQL Binary Operators
Operator	Type(A)	Type(B)	Function	Result type
Logical Connectives
A \|\| B	xsd:boolean (EBV)	xsd:boolean (EBV)	logical-or (A, B)	xsd:boolean
A && B	xsd:boolean (EBV)	xsd:boolean (EBV)	logical-and (A, B)	xsd:boolean
XPath Tests
A = B	numeric	numeric	op:numeric-equal (A, B)	xsd:boolean
A = B	xsd:string	xsd:string	op:numeric-equal ( fn:compare ( STR (A), STR (B)), 0)	xsd:boolean
A = B	xsd:boolean	xsd:boolean	op:boolean-equal (A, B)	xsd:boolean
A = B	xsd:dateTime	xsd:dateTime	op:dateTime-equal (A, B)	xsd:boolean
A != B	numeric	numeric	fn:not ( op:numeric-equal (A, B))	xsd:boolean
A != B	xsd:string	xsd:string	fn:not ( op:numeric-equal ( fn:compare ( STR (A), STR (B)), 0))	xsd:boolean
A != B	xsd:boolean	xsd:boolean	fn:not ( op:boolean-equal (A, B))	xsd:boolean
A != B	xsd:dateTime	xsd:dateTime	fn:not ( op:dateTime-equal (A, B))	xsd:boolean
A < B	numeric	numeric	op:numeric-less-than (A, B)	xsd:boolean
A < B	xsd:string	xsd:string	op:numeric-equal ( fn:compare ( STR (A), STR (B)), -1)	xsd:boolean
A < B	xsd:boolean	xsd:boolean	op:boolean-less-than (A, B)	xsd:boolean
A < B	xsd:dateTime	xsd:dateTime	op:dateTime-less-than (A, B)	xsd:boolean
A > B	numeric	numeric	op:numeric-greater-than (A, B)	xsd:boolean
A > B	xsd:string	xsd:string	op:numeric-equal ( fn:compare ( STR (A), STR (B)), 1)	xsd:boolean
A > B	xsd:boolean	xsd:boolean	op:boolean-greater-than (A, B)	xsd:boolean
A > B	xsd:dateTime	xsd:dateTime	op:dateTime-greater-than (A, B)	xsd:boolean
A <= B	numeric	numeric	logical-or ( op:numeric-less-than (A, B), op:numeric-equal (A, B))	xsd:boolean
A <= B	xsd:string	xsd:string	fn:not ( op:numeric-equal ( fn:compare ( STR (A), STR (B)), 1))	xsd:boolean
A <= B	xsd:boolean	xsd:boolean	fn:not ( op:boolean-greater-than (A, B))	xsd:boolean
A <= B	xsd:dateTime	xsd:dateTime	fn:not ( op:dateTime-greater-than (A, B))	xsd:boolean
A >= B	numeric	numeric	logical-or ( op:numeric-greater-than (A, B), op:numeric-equal (A, B))	xsd:boolean
A >= B	xsd:string	xsd:string	fn:not ( op:numeric-equal ( fn:compare ( STR (A), STR (B)), -1))	xsd:boolean
A >= B	xsd:boolean	xsd:boolean	fn:not ( op:boolean-less-than (A, B))	xsd:boolean
A >= B	xsd:dateTime	xsd:dateTime	fn:not ( op:dateTime-less-than (A, B))	xsd:boolean
XPath Arithmetic
A * B	numeric	numeric	op:numeric-multiply (A, B)	numeric
A / B	numeric	numeric	op:numeric-divide (A, B)	numeric ; but xsd:decimal if both operands are xsd:integer
A + B	numeric	numeric	op:numeric-add (A, B)	numeric
A - B	numeric	numeric	op:numeric-subtract (A, B)	numeric
SPARQL Tests
A = B	IRI	IRI	sameTerm (A, B)	xsd:boolean
A = B	Blank Node	Blank Node	sameTerm (A, B)	xsd:boolean
A = B	Triple Term	Triple Term	( A.subject = B.subject ) && ( A.predicate = B.predicate ) && ( A.object = B.object )	xsd:boolean
A != B	IRI	IRI	fn:not ( sameTerm (A, B))	xsd:boolean
A != B	Blank Node	Blank Node	fn:not ( sameTerm (A, B)	xsd:boolean
A != B	Triple Term	Triple Term	( A.subject != B.subject ) \|\| ( A.predicate != B.predicate ) \|\| ( A.object != B.object )	xsd:boolean
A = B	RDF term	RDF term	sameValue (A, B)	xsd:boolean
A != B	RDF term	RDF term	fn:not ( sameValue (A, B))	xsd:boolean

xsd:boolean function arguments marked with "(EBV)" are coerced to xsd:boolean by evaluating the effective boolean value of that argument.

Operators = and != applied to triple terms apply the operator to each of the components.

SPARQL language extensions may provide additional associations between operators and operator functions; this amounts to adding rows to the table above. No additional operator may yield a result that replaces any result other than a type error. The consequence of this rule is that SPARQL FILTER s will produce at least the same intermediate bindings after applying a FILTER as an unextended implementation.

Additional mappings of the '<' operator are expected to control the relative ordering of the operands, specifically, when used in an ORDER BY clause.

This section defines the operators and functions introduced by the SPARQL query language. The examples show the behavior of the operators as invoked by the appropriate grammatical constructs.


xsd:boolean


BOUND

(

variable


var

)

Returns true if var is bound to a value. Returns false otherwise. Variables with the value NaN or INF are considered bound.

Data:

PREFIX foaf:        <http://xmlns.com/foaf/0.1/>
PREFIX dc:          <http://purl.org/dc/elements/1.1/>
PREFIX xsd:          <http://www.w3.org/2001/XMLSchema#>
_:a  foaf:givenName  "Alice".
_:b  foaf:givenName  "Bob" .
_:b
dc:date
"2005-04-04T04:04:04Z"^^xsd:dateTime
.

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX dc:   <http://purl.org/dc/elements/1.1/>
PREFIX xsd:   <http://www.w3.org/2001/XMLSchema#>
SELECT ?givenName
WHERE {
   ?x foaf:givenName  ?givenName .
   OPTIONAL { ?x dc:date ?date } .
   FILTER ( bound(?date) )
}

Query result:

givenName
"Bob"

One may test whether a graph pattern is not expressed by specifying an OPTIONAL graph pattern that introduces a variable and testing to see whether the variable is not bound This is called Negation as Failure in logic programming.

This query matches the people with a name but no expressed date:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX dc:   <http://purl.org/dc/elements/1.1/>
SELECT ?name
WHERE { 
    ?x foaf:givenName  ?name .
    OPTIONAL { ?x dc:date ?date } .
    FILTER (!bound(?date))
}

Query result:

name
"Alice"

Because Bob's dc:date was known, "Bob" was not a solution to the query.


rdfTerm


IF

(

expression1
,

expression2
,

expression3

)

The IF function form evaluates the first argument, interprets it as a effective boolean value , then returns the value of expression2 if the EBV is true, otherwise it returns the value of expression3. Only one of expression2 and expression3 is evaluated. If evaluating the first argument raises an error, then an error is raised for the evaluation of the IF expression.

Examples: Suppose ?x = 2, ?z = 0 and ?y is not bound in some query solution:

`IF(?x = 2, "yes", "no")`	returns "yes"
`IF(bound(?y), "yes", "no")`	returns "no"
`IF(?x=2, "yes", 1/?z)`	returns "yes", the expression `1/?z` is not evaluated
`IF(?x=1, "yes", 1/?z)`	raises an error
`IF("2" > 1, "yes", "no")`	raises an error


rdfTerm


COALESCE

(

expression,
....

)

The COALESCE function form returns the RDF term value of the first expression that evaluates without error. In SPARQL, evaluating an unbound variable raises an error.

If none of the expressions evaluate without error, an error is raised.

If there are zero expressions, an error is raised.

Examples: Suppose ?x = 2 and ?y is not bound in some query solution:

`COALESCE(?x, 1/0)`	returns 2, the value of `x`
`COALESCE(1/0, ?x)`	returns 2
`COALESCE(5, ?x)`	returns 5
`COALESCE(?y, 3)`	returns 3
`COALESCE(?y)`	raises an error because `y` is not bound.
`COALESCE()`	raises an error because there are zero arguments.

There is a filter operator EXISTS that takes a graph pattern. EXISTS returns true / false depending on whether the pattern matches the dataset given the bindings in the current group graph pattern, the dataset and the active graph at this point in the query evaluation. No additional binding of variables occurs. The NOT EXISTS form translates into fn:not(EXISTS{...}).


xsd:boolean


NOT
EXISTS

{

pattern

}

Returns false if pattern matches. Returns true otherwise.

NOT EXISTS { pattern } is equivalent to fn:not(EXISTS { pattern }).


xsd:boolean

EXISTS
{

pattern

}

Returns true if pattern matches. Returns false otherwise.

Variables in the pattern that are bound in the current solution mapping take the value that they have from the solution mapping. Variables in the pattern pattern that are not bound in the current solution mapping take part in pattern matching.

To facilitate this, we introduce a function Exists that evaluates a SPARQL Algebra expression and returns true or false, depending on whether there are any solutions to the pattern, given the solution mapping being tested by the filter operation.


xsd:boolean


logical-or

(

xsd:boolean


left
,

xsd:boolean


right

)

This function cannot be used directly in expressions. The purpose of this function is to define the semantics of the " || " operator.

The function returns a logical OR of left and right. Note that logical-or operates on the effective boolean value of its arguments.

Note: see section 17.2, Filter Evaluation , for the || operator's treatment of errors.


xsd:boolean


logical-and

(

xsd:boolean


left
,

xsd:boolean


right

)

This function cannot be used directly in expressions. The purpose of this function is to define the semantics of the " && " operator.

The function returns a logical AND of left and right. Note that logical-and operates on the effective boolean value of its arguments.

Note: see section 17.2, Filter Evaluation , for the && operator's treatment of errors.


boolean

rdfTerm

IN

(

expression
,
...

)

The IN operator tests whether the RDF term on the left-hand side is found in the list of values of the expressions on the right-hand side. The test is done with the "=" operator, which tests for the same value, as determined by the operator mapping .

A list of zero terms on the right-hand side is legal and evaluates to false.

Errors in comparisons cause the IN expression to raise an error if the RDF term being tested is not found elsewhere in the list of terms.

If IN is used with an expression to produce the rdfTerm, then that expression is evaluated only once, before evaluating the IN expression.

The IN operator is equivalent to the SPARQL expression:


(rdfTerm
=
value
of
expression1)
||
(rdfTerm
=
value
of
expression2)
||
...

Examples:

`2 IN (1, 2, 3)`	true
`2 IN ()`	false
`2 IN (<http://example/iri>, "str", 2.0)`	true
`2 IN (1/0, 2)`	true
`2 IN (2, 1/0)`	true
`2 IN (3, 1/0)`	raises an error


boolean

rdfTerm

NOT
IN

(

expression
,
...

)

The NOT IN operator tests whether the RDF term on the left-hand side is not found in the values of list of the expressions on the right-hand side. The test is done with the "!=" operator, which tests that two values are not the same value, as determined by the operator mapping .

A list of zero terms on the right-hand side is legal and evaluates to true.

If NOT IN is used with an expression to produce the rdfTerm, then that expression is evaluated only once, before evaluating the NOT IN expression.

Errors in comparisons cause the NOT IN expression to raise an error if the RDF term being tested is not found elsewhere in the list of terms.

The NOT IN operator is equivalent to the SPARQL expression:



(rdfTerm

!=


value


of


expression1)


&&


(rdfTerm

!=


value


of


expression2)


&&

...

NOT IN (...) is equivalent to !(IN (...)).

Examples:

`2 NOT IN (1, 2, 3)`	false
`2 NOT IN ()`	true
`2 NOT IN (<http://example/iri>, "str", 2.0)`	false
`2 NOT IN (1/0, 2)`	false
`2 NOT IN (2, 1/0)`	false
`2 NOT IN (3, 1/0)`	raises an error


xsd:boolean


sameTerm

(


RDF
term



term1
,


RDF
term



term2

)

Returns TRUE if term1 and term2 are the same RDF term as defined in RDF 1.2 Concepts and Abstract Syntax [ RDF12-CONCEPTS ]; returns FALSE otherwise.

term1 and term2 are the same RDF term if one of the following is true:

term1 and term2 are IRIs that are the same as IRIs .
term1 and term2 are literals that are equal as literal terms .
term1 and term2 are blank nodes that are equal as blank nodes .
term1 and term2 are triple terms that are equal as triple terms ; that is, the subject , predicate , and object components are pair-wise the same term.

`sameTerm(<http://example/>, <http://example/>)`	true
`sameTerm(<http://example/>, <https://example/>)`	false
`sameTerm("abc", "abc")`	true
`sameTerm("abc"@en, "abc")`	false
`sameTerm("abc"@en, "abc"@EN)`	true
`sameTerm("abc"@en--rtl, "abc"@en)`	false
`sameTerm(2, 2.0)`	false
`sameTerm(2, "2"^^xsd:integer)`	true
`sameTerm(2, "02"^^xsd:integer)`	false


xsd:boolean


sameValue

(


RDF
term



term1
,


RDF
term



term2

)

This function cannot be used directly in expressions. The purpose of this function is to define the semantics of the "=" operator when applied to two RDF terms that do not fall into the concrete cases covered in the operator mapping table in Section 17.3 Operator Mapping .

The result of this function is determined by going through the following steps.

If term1 and term2 are equal RDF terms , then return TRUE.
If term1 or term2 is an IRI or a blank node then return FALSE.
If term1 and term2 are both literals and one or both of these literals has a datatype that is not handled by the SPARQL processor, then produce a type error.
If term1 and term2 are both literals and one or both of these literals are known to be ill-typed , then produce a type error.
"NaN"^^xsd:double and "NaN"^^xsd:float are considered to represent the same value. If term1 and term2 are both "NaN" for either xsd:double or xsd:float, then return TRUE.
If term1 and term2 are both literals and the SPARQL processor can determine that their the values are equal, then return TRUE.
If term1 and term2 are both literals and the SPARQL processor can determine the values can not be equal, then return FALSE.
If term1 and term2 are both triple terms , apply the function sameValue pair-wise to each of the components. Return TRUE if each component pair returns TRUE; produce a type error if any component pair produces an error; otherwise return FALSE.
Otherwise, return FALSE.

Note

A literal is ill-typed if its datatype is handled by the SPARQL processor and its lexical form is not in the lexical space of the datatype.

If the two arguments are literals, the function sameValue returns true or false in cases where the SPARQL processor can determine that the values of these literals are equal or are not equal. If the SPARQL processor can not be sure, it returns error.

Note

The Operator Mapping for " = " is the function fn:numeric-equal which is defined to return false when comparing arguments involving NaN. However, sameTerm("NaN"^^xsd:double, "NaN"^^xsd:double) is true. The function sameValue defines sameValue("NaN"^^xsd:double, "NaN"^^xsd:double) to be true because the arguments are the same element of the value space.

sameValue treats the values of "NaN"^^xsd:double and "NaN"^^xsd:float as being the same. sameValue("NaN"^^xsd:double, "NaN"^^xsd:float) is true.

Note

For xsd:double and xsd:float, +0, -0 and 0 are same value.

Note

An extended implementation may support additional datatypes for literals. An implementation processing a query that tests for equivalence of literals with non-recognized datatypes (and non-identical lexical form and datatype IRI) returns an error, indicating that it is unable to determine whether or not the values of the compared literals are equivalent. For example, an unextended implementation will produce an error when testing either "iiii"^^my:romanNumeral = "iv"^^my:romanNumeral or "iiii"^^my:romanNumeral != "iv"^^my:romanNumeral .

Examples:

sameValue	Results
`sameValue(1e10, "NaN"^^xsd:double)`	false
`sameValue("NaN"^^xsd:double, "NaN"^^xsd:double)`	true
`sameValue("NaN"^^xsd:double, "NaN"^^xsd:float)`	true
`sameValue( <<(:s :p 123)>> , <<(:s :p 123.0)>> )`	true

Note

This function was called RDFterm-equal up until SPARQL 1.1.

xsd:boolean  isIRI (RDF term term)

xsd:boolean


isURI

(

RDF
term


term

)

Returns true if term is an IRI . Returns false otherwise. isURI is an alternate spelling for the isIRI operator.

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
"bob@work.example"
.

This query matches the people with a name and an mbox which is an IRI:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE {
    ?x foaf:name  ?name ;
       foaf:mbox  ?mbox .
    FILTER isIRI(?mbox) 
}

Query result:

name	mbox
"Alice"	<mailto:alice@work.example>


xsd:boolean


isBLANK

(


RDF
term



term

)

Returns true if term is a blank node . Returns false otherwise.

PREFIX a:          <http://www.w3.org/2000/10/annotation-ns#>
PREFIX dc:         <http://purl.org/dc/elements/1.1/>
PREFIX foaf:       <http://xmlns.com/foaf/0.1/>
_:a   a:annotates   <http://www.w3.org/TR/rdf-sparql-query/> .
_:a   dc:creator    "Alice B. Toeclips" .
_:b   a:annotates   <http://www.w3.org/TR/rdf-sparql-query/> .
_:b   dc:creator    _:c .
_:c   foaf:given    "Bob".
_:c
foaf:family
"Smith".

This query matches the people with a dc:creator which uses predicates from the FOAF vocabulary to express the name.

PREFIX a:      <http://www.w3.org/2000/10/annotation-ns#>
PREFIX dc:     <http://purl.org/dc/elements/1.1/>
PREFIX foaf:   <http://xmlns.com/foaf/0.1/>
SELECT ?given ?family
WHERE { 
    ?annot  a:annotates  <http://www.w3.org/TR/rdf-sparql-query/> .
    ?annot  dc:creator   ?c .
    OPTIONAL { ?c  foaf:given   ?given ; foaf:family  ?family } .
    FILTER isBLANK(?c)
}

Query result:

given	family
"Bob"	"Smith"

In this example, there were two objects of dc:creator predicates, but only one ( _:c ) was a blank node.


xsd:boolean


isLITERAL

(


RDF
term



term

)

Returns true if term is a literal . Returns false otherwise.

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
"bob@work.example"
.

This query is similar to the one in 17.4.2.1 except that is matches the people with a name and an mbox which is a literal. This could be used to look for erroneous data ( foaf:mbox should only have an IRI as its object).

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE {
    ?x foaf:name  ?name ;
       foaf:mbox  ?mbox .
    FILTER isLiteral(?mbox)
}

Query result:

name	mbox
"Bob"	"bob@work.example"


xsd:boolean


isNUMERIC

(


RDF
term



term

)

Returns true if term is a numeric value. Returns false otherwise. term is numeric if it has an appropriate datatype (see the section Operand Data Types ) and has a valid lexical form, making it a valid argument to functions and operators taking numeric arguments.

Examples:

`isNUMERIC(12)`	true
`isNUMERIC("12")`	false
`isNUMERIC("12"^^xsd:nonNegativeInteger)`	true
`isNUMERIC("1200"^^xsd:byte)`	false
`isNUMERIC(<http://example/>)`	false

xsd:string  STR (literal literal)

xsd:string


STR

(


IRI



rsrc

)

Returns the lexical form of literal (a literal ); returns the codepoint representation of rsrc (an IRI ). This is useful for examining parts of an IRI, for instance, the host-name.

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@home.example>
.

This query selects the set of people who use their work.example address in their foaf profile:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE {
    ?x foaf:name  ?name ;
      foaf:mbox  ?mbox .
    FILTER regex(str(?mbox), "@work\\.example$")
}

Query result:

name	mbox
"Alice"	<mailto:alice@work.example>


xsd:string


LANG

(


literal



ltrl

)

Returns the language tag of ltrl, if it has one. It returns an empty string if ltrl has no language tag . Note that the RDF data model does not include literals with an empty language tag .

PREFIX foaf:       <http://xmlns.com/foaf/0.1/>
_:a  foaf:name       "Robert"@en.
_:a  foaf:name       "Roberto"@es.
_:a
foaf:mbox
<mailto:bob@work.example>
.

This query finds the Spanish foaf:name and foaf:mbox:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE {
    ?x foaf:name  ?name ;
       foaf:mbox  ?mbox .
    FILTER ( lang(?name) = "es" )
}

Query result:

name	mbox
"Roberto"@es	<mailto:bob@work.example>

Function examples:

Expression	Result
`LANG("abc"@en)`	`"en"`
`LANG("abc"@en--ltr)`	`"en"`
`LANG("abc")`	`""`
`LANG(1)`	`""`
`LANG(<http://example/>)`	`error`


xsd:string


LANGDIR

(


literal



ltrl

)

Returns the base direction of ltrl, if it has one. It returns an empty string if ltrl has no base direction . Note that the RDF data model does not include literals with an empty base direction .

Expression	Result
`LANGDIR("abc"@en--ltr)`	`"ltr"`
`LANGDIR("abc"@en)`	`""`
`LANGDIR("abc")`	`""`
`LANGDIR(1)`	`""`
`LANGDIR(<http://example/>)`	`error`


xsd:string


hasLANG

(

RDF
term


term

)

Returns true if the RDF term argument is a literal with a language tag . Otherwise, the function returns false.

If the argument is a literal, the function is equivalent to testing for the datatype of the literal being either rdf:langString or rdf:dirLangString.

Expression	Result
`hasLANG("abc"@en)`	`true`
`hasLANG("abc@"en--ltr)`	`true`
`hasLANG("تصميم المواقع"@ar--rtl)`	`true`
`hasLANG(1)`	`false`
`hasLANG(<http://example/>)`	`false`


xsd:string


hasLANGDIR

(

RDF
term


term

)

Returns true if the RDF term argument is a literal with a base direction . Otherwise, the function returns false.

If the argument is a literal, the function is equivalent to testing for the datatype of the literal being rdf:dirLangString.

Expression	Result
`hasLANGDIR("abc"@en)`	`false`
`hasLANGDIR("abc@"en--ltr)`	`true`
`hasLANGDIR("تصميم المواقع"@ar--rtl)`	`true`
`hasLANGDIR(1)`	`false`
`hasLANGDIR(<http://example/>)`	`false`



iri



DATATYPE

(


literal



literal

)

Returns the datatype IRI of the given literal.

Note

The datatype IRI of a literal with a language tag and no base direction is rdf:langString.

The datatype IRI of a literal with a language tag and a base direction is rdf:dirLangString.

PREFIX foaf:       <http://xmlns.com/foaf/0.1/>
PREFIX eg:         <http://biometrics.example/ns#>
PREFIX xsd:        <http://www.w3.org/2001/XMLSchema#>
_:a  foaf:name       "Alice".
_:a  eg:shoeSize     "9.5"^^xsd:float .
_:b  foaf:name       "Bob".
_:b
eg:shoeSize
"42"^^xsd:integer
.

This query finds the foaf:name and foaf:shoeSize of everyone with a shoeSize that is an integer:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX xsd:  <http://www.w3.org/2001/XMLSchema#>
PREFIX eg:   <http://biometrics.example/ns#>
SELECT ?name ?shoeSize
WHERE { 
    ?x foaf:name  ?name ;
       eg:shoeSize  ?shoeSize .
    FILTER ( datatype(?shoeSize) = xsd:integer )
}

Query result:

name	shoeSize
"Bob"	42

iri  IRI(xsd:string)
iri  IRI(iri)
iri  URI(xsd:string)

iri


URI

(

iri

)

The IRI function constructs an IRI by resolving the string argument (see [ RFC3986 ] and [ RFC3987 ] or any later RFC that superceeds RFC 3986 or RFC 3987). The IRI is resolved against the base IRI of the query and must result in an absolute IRI.

The URI function is a synonym for IRI .

If the function is passed an IRI, it returns the IRI unchanged.

Passing any RDF term other than a literal with datatype xsd:string or an IRI is an error.

An implementation MAY normalize the IRI.

Examples:

`IRI("http://example/")`	<http://example/>
`IRI(<http://example/>)`	<http://example/>


blank
node


BNODE

()


blank
node


BNODE

(

xsd:string

)

The BNODE function constructs a blank node that is distinct from all blank nodes in the dataset being queried and distinct from all blank nodes created by calls to this constructor for other query solutions. If the no argument form is used, every call results in a distinct blank node. If the form with an xsd:string literal is used, every call results in distinct blank nodes for different xsd:string literals, and the same blank node for calls with the same xsd:string literal within expressions for one solution mapping .

This functionality is compatible with the treatment of blank nodes in SPARQL CONSTRUCT templates .


literal


STRDT

(

xsd:string

lexicalForm,

IRI

datatypeIRI)

The STRDT function constructs a literal with lexical form and datatype IRI as specified by the arguments.

Expression	Result
`STRDT("123", xsd:integer)`	"123"^^<http://www.w3.org/2001/XMLSchema#integer>
`STRDT("iiii", <http://example/romanNumeral>)`	"iiii"^^<http://example/romanNumeral>

Note


STRDT

should not be called with


datatypeIRI

argument


rdf:langString


rdf:dirLangString

. To create literals with these IRIs as datatype IRI, function


STRLANG


STRLANGDIR

should be used.


literal


STRLANG

(

xsd:string

lexicalForm,

xsd:string

langTag)

The STRLANG function constructs a literal with lexical form and language tag , as specified by the arguments, and a datatype IRI of rdf:langString.

The argument langTag MUST not be an empty string and SHOULD be a a valid language tag .

Expression	Result
`STRLANG("chat", "fr")`	"chat"@fr
`STRLANG("abc", "")`	error
`STRLANG(123, "en")`	error


literal


STRLANGDIR

(

xsd:string

lexicalForm,

xsd:string

langTag,

xsd:string

baseDirection)

The STRLANGDIR function constructs a literal with lexical form , language tag and base direction , as specified by the arguments, and a datatype IRI of rdf:dirLangString.

The argument langTag MUST NOT be an empty string and SHOULD be a a valid language tag . The argument baseDirection MUST be either "ltr" or "rtl".

Expression	Result
`STRLANGDIR("abc", "en", "ltr")`	`"abc"@en--ltr`
`STRLANGDIR("abc", "en", "LTR")`	error
`STRLANGDIR("قطة", "ar", "rtl")`	"قطة"@ar--rlt
`STRLANGDIR("abc", "en", "")`	error
`STRLANGDIR("abc", "", "ltr")`	error
`STRLANGDIR(123, "", "ltr")`	error
`STRLANGDIR(<x:uri>, "en", "ltr")`	error


iri


UUID

()

Returns a fresh IRI from the A Universally Unique IDentifier (UUID) URN Namespace . Each call of UUID() returns a different UUID. It must not be the "nil" UUID (all zeroes). The variant and version of the UUID is implementation dependent.

UUID() <urn:uuid:b9302fb5-642e-4d3b-af19-29a8f6d894c9>


xsd:string


STRUUID

()

Returns a string that is the scheme-specific part of UUID. That is, as a literal with datatype xsd:string, the result of generating a UUID, converting to a literal with datatype xsd:string and removing the initial urn:uuid:.

STRUUID() "73cd4307-8a99-4691-a608-b5bda64fb6c1"

Certain functions (e.g., REGEX , STRLEN , CONTAINS ) take a string literal as an argument. A string literal is one of

a literal with datatype xsd:string
a literal with datatype rdf:langString and with language tag
a literal with datatype rdf:dirLangString and with both a language tag and a base direction

Use of any other RDF term will cause a call to the function to raise an error.

Note

"abc" is a simple literal syntactic shorthand for "abc"^^xsd:string.

The functions SUBSTR , STRBEFORE , STRAFTER , and REPLACE return a string literal of the same kind as their first argument.

The functions STRSTARTS , STRENDS , CONTAINS , STRBEFORE , STRAFTER and CONCAT take two or more arguments. These arguments must be argument compatible ; otherwise, invocation of the function raises an error.

Two string literal arguments are argument compatible if:

The arguments are literals with datatype xsd:string
The arguments are literals with datatype rdf:langString and have the same language tag
The arguments are literals with datatype rdf:dirLangString and have the same language tag and the same base direction
The first argument is a literal with datatype rdf:langString and the second argument is a literal with datatype xsd:string
The first argument is a literal with datatype rdf:dirLangString, and the second argument has datatype xsd:string

Argument1	Argument2	Compatible?
"abc"	"b"	yes
"abc"@en	"b"	yes
"abc"@en	"b"@en	yes
"abc"@fr	"b"@ja	no
"abc"	"b"@ja	no
"abc"	"b"@en--ltr	no
"abc"@en--ltr	"b"@en--ltr	yes
"abc"@en--ltr	"b"@en	no
"abc"@en--ltr	"z"	yes


xsd:integer


STRLEN

(

string
literal

str)

The strlen function corresponds to the XPath fn:string-length function and returns an xsd:integer equal to the length in characters of the lexical form of the literal.

`strlen("chat")`	4
`strlen("chat"@en)`	4
`strlen("chat"@en--ltr)`	4
`strlen("chat"^^xsd:string)`	4

string literal  SUBSTR(string literal source, xsd:integer startingLoc)

string
literal


SUBSTR

(

string
literal

source,

xsd:integer

startingLoc,

xsd:integer

length)

The substr function corresponds to the XPath fn:substring function and returns a literal of the same kind (literal with datatype xsd:string, literal with the same language tag, literal with the same language tag and base direction) as the source input parameter but with a lexical form derived from the substring of the lexical form of the source.

The arguments startingLoc and length may be derived types of xsd:integer.

The index of the first character in a string is 1.

`substr("foobar", 4)`	"bar"
`substr("foobar"@en, 4)`	"bar"@en
`substr("foobar"^^xsd:string, 4)`	"bar"^^xsd:string
`substr("foobar", 4, 1)`	"b"
`substr("foobar"@en, 4, 1)`	"b"@en
`substr("foobar"^^xsd:string, 4, 1)`	"b"^^xsd:string


string
literal


UCASE

(

string
literal

str)

The UCASE function corresponds to the XPath fn:upper-case function. It returns a string literal whose lexical form is the upper case of the lexical form of the argument.

`ucase("foo")`	"FOO"
`ucase("Foo"@en)`	"FOO"@en
`ucase("foo"@en--ltr)`	"FOO"@en--ltr
`ucase("foo"^^xsd:string)`	"FOO"^^xsd:string


string
literal


LCASE

(

string
literal

str)

The LCASE function corresponds to the XPath fn:lower-case function. It returns a string literal whose lexical form is the lower case of the lexical form of the argument.

`lcase("BAR")`	"bar"
`lcase("Bar"@en)`	"bar"@en
`lcase("BAR"@en--ltr)`	"bar"@en--ltr
`lcase("BAR"^^xsd:string)`	"bar"^^xsd:string


xsd:boolean


STRSTARTS

(

string
literal

arg1,

string
literal

arg2)

The STRSTARTS function corresponds to the XPath fn:starts-with function. The arguments must be argument compatible , otherwise an error is raised.

For such input pairs, the function returns true if the lexical form of arg1 starts with the lexical form of arg2, otherwise it returns false.

`strStarts("foobar", "foo")`	true
`strStarts("foobar", "abc")`	false
`strStarts("foobar"@en, "foo"@en)`	true
`strStarts("foobar"^^xsd:string, "foo"^^xsd:string)`	true
`strStarts("foobar"^^xsd:string, "foo")`	true
`strStarts("foobar", "foo"^^xsd:string)`	true
`strStarts("foobar"@en, "foo")`	true
`strStarts("foobar"@en, "foo"^^xsd:string)`	true
`strStarts("foobar", "foo"@en)`	error


xsd:boolean


STRENDS

(

string
literal

arg1,

string
literal

arg2)

The STRENDS function corresponds to the XPath fn:ends-with function. The arguments must be argument compatible , otherwise an error is raised.

For such input pairs, the function returns true if the lexical form of arg1 ends with the lexical form of arg2, otherwise it returns false.

`strEnds("foobar", "bar")`	true
`strEnds("foobar", "abc")`	false
`strEnds("foobar"@en, "bar"@en)`	true
`strEnds("foobar"^^xsd:string, "bar"^^xsd:string)`	true
`strEnds("foobar"^^xsd:string, "bar")`	true
`strEnds("foobar", "bar"^^xsd:string)`	true
`strEnds("foobar"@en, "bar")`	true
`strEnds("foobar"@en, "bar"^^xsd:string)`	true
`strEnds("foobar"@en, "bar"@en)`	error


xsd:boolean


CONTAINS

(

string
literal

arg1,

string
literal

arg2)

The CONTAINS function corresponds to the XPath fn:contains . The arguments must be argument compatible , otherwise an error is raised.

`contains("foobar", "bar")`	true
`contains("foobar"@en, "foo"@en)`	true
`contains("foobar"^^xsd:string, "bar"^^xsd:string)`	true
`contains("foobar"^^xsd:string, "foo")`	true
`contains("foobar", "bar"^^xsd:string)`	true
`contains("foobar"@en, "foo")`	true
`contains("foobar"@en, "bar"^^xsd:string)`	true
`contains("foobar", "bar"@en)`	error


literal


STRBEFORE

(

string
literal

arg1,

string
literal

arg2)

The STRBEFORE function corresponds to the XPath fn:substring-before function. The arguments must be argument compatible , otherwise an error is raised.

For compatible arguments, if the lexical part of the second argument occurs as a substring of the lexical part of the first argument, the function returns a literal of the same kind as the first argument arg1 (literal with datatype xsd:string, literal with the same language tag). The lexical form of the result is the substring of the lexical form of arg1 that precedes the first occurrence of the lexical form of arg2. If the lexical form of arg2 is the empty string, this is considered to be a match and the lexical form of the result is the empty string.

If there is no such occurrence, an empty literal with datatype xsd:string is returned.

`strBefore("abc","b")`	`"a"`
`strBefore("abc"@en,"bc")`	`"a"@en`
`strBefore("abc"@en,"b"@cy)`	error
`strBefore("abc"^^xsd:string,"")`	`""^^xsd:string`
`strBefore("abc","xyz")`	`""`
`strBefore("abc"@en, "z"@en)`	`""`
`strBefore("abc"@en, "z")`	`""`
`strBefore("abc"@en, ""@en)`	`""@en`
`strBefore("abc"@en, "")`	`""@en`


literal


STRAFTER

(

string
literal

arg1,

string
literal

arg2)

The STRAFTER function corresponds to the XPath fn:substring-after function. The arguments must be argument compatible , otherwise an error is raised.

For compatible arguments, if the lexical part of the second argument occurs as a substring of the lexical part of the first argument, the function returns a literal of the same kind as the first argument arg1 (literal with datatype xsd:string, literal with the same language tag). The lexical form of the result is the substring of the lexical form of arg1 that follows the first occurrence of the lexical form of arg2. If the lexical form of arg2 is the empty string, this is considered to be a match and the lexical form of the result is the lexical form of arg1.

If there is no such occurrence, an empty literal with datatype xsd:string is returned.

`strAfter("abc","b")`	`"c"
`strAfter("abc"@en,"ab")`	`"c"@en`
`strAfter("abc"@en,"b"@cy)`	error
`strAfter("abc"^^xsd:string,"")`	`"abc"^^xsd:string`
`strAfter("abc","xyz")`	`""`
`strAfter("abc"@en, "z"@en)`	`""`
`strAfter("abc"@en, "z")`	`""`
`strAfter("abc"@en, ""@en)`	`"abc"@en`
`strAfter("abc"@en, "")`	`"abc"@en`


string
literal


CONCAT

(

string
literal
,
...,

string
literal

)

The CONCAT function takes zero or more arguments. The arguments must be pair-wise argument compatible , otherwise an error is raised.

If zero arguments are given, the result is an empty string of datatype xsd:string.

If one argument is given, the result is that argument value.

If two or more arguments are given, the function returns a string literal such that the lexical form of the resulting string literal is obtained by concatenating the lexical forms of the arguments of the function using the fn:concat function. If all input literals are literals with the same language tag and the same base direction , then the returned string literal is a literal with that language tag and base direction. If all input literals are literals with the same language tag , but not all the same base direction , the returned literal is a literal with that language tag and no base direction.

`concat("foo", "bar")`	"foobar"
`concat("foo"@en, "bar"@en)`	"foobar"@en
`concat("foo", "bar")`	"foobar"
`concat("foo"@en, "bar")`	"foobar"
`concat("foo"@en, "bar"@es)`	"foobar"
`concat("abc")`	"abc"
`concat("abc"@en)`	"abc"@en
`concat()`	""


xsd:boolean


langMatches

(


xsd:string



language-tag
,


xsd:string



language-range

)

Returns true if the language tag (first argument) matches language-range (second argument). Otherwise, the function returns false. Matching is performed according to the basic filtering scheme defined in [ RFC4647 ] section 3.3.1. language-range is a basic language range per Matching of Language Tags [ RFC4647 ] section 2.1. A language-range of "*" matches any non-empty language-tag string. Otherwise, the function returns false.

PREFIX dc:       <http://purl.org/dc/elements/1.1/>
_:a  dc:title         "That Seventies Show"@en .
_:a  dc:title         "Cette Série des Années Soixante-dix"@fr .
_:a  dc:title         "Cette Série des Années Septante"@fr-BE .
_:b
dc:title
"Il
Buono,
il
Bruto,
il
Cattivo"
.

This query uses langMatches and lang to find the French titles for the show known in English as "That Seventies Show":

PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?title
WHERE {
    ?x dc:title  "That Seventies Show"@en ;
       dc:title  ?title .
    FILTER langMatches( lang(?title), "FR" )
}

Query result:

title
"Cette Série des Années Soixante-dix"@fr
"Cette Série des Années Septante"@fr-BE

The idiom langMatches( lang( ?v ), "*" ) will not match literals without a language tag as lang( ?v ) will return an empty string, so

PREFIX dc: <http://purl.org/dc/elements/1.1/>
SELECT ?title
WHERE {
    ?x dc:title  ?title .
    FILTER langMatches( lang(?title), "*" )
}

will report all of the titles with a language tag:

title
"That Seventies Show"@en
"Cette Série des Années Soixante-dix"@fr
"Cette Série des Années Septante"@fr-BE

xsd:boolean  REGEX (string literal text, xsd:string pattern)

xsd:boolean


REGEX

(


string
literal



text
,


xsd:string



pattern
,


xsd:string



flags

)

Invokes the XPath fn:matches function to match text against a regular expression pattern. The regular expression language is defined in XQuery 1.0 and XPath 2.0 Functions and Operators section 7.6.1 Regular Expression Syntax [ XPATH-FUNCTIONS-31 ].

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 ?name
WHERE { 
    ?x foaf:name  ?name
    FILTER regex(?name, "^ali", "i")
}

Query result:

name
"Alice"

string literal  REPLACE (string literal arg, xsd:string pattern, xsd:string replacement )


string
literal



REPLACE

(


string
literal


arg,


xsd:string


pattern,


xsd:string


replacement,


xsd:string


flags)

The REPLACE function corresponds to the XPath fn:replace function. It replaces each non-overlapping occurrence of the regular expression pattern with the replacement string. Regular expession matching may involve modifier flags. See REGEX .

replace("abcd", "b", "Z")	"aZcd"
replace("abab", "B", "Z","i")	"aZaZ"
replace("abab", "B.", "Z","i")	"aZb"


xsd:string


ENCODE_FOR_URI

(

string
literal

ltrl)

The ENCODE_FOR_URI function corresponds to the XPath fn:encode-for-uri function. It returns a literal with datatype xsd:string with the lexical form obtained from the lexical form of its input after translating reserved characters according to the fn:encode-for-uri function.

`encode_for_uri("Los Angeles")`	`"Los%20Angeles"`
`encode_for_uri("Los Angeles"@en)`	`"Los%20Angeles"`
`encode_for_uri("Los Angeles"^^xsd:string)`	`"Los%20Angeles"`


numeric


ABS

(


numeric



term

)

Returns the absolute value of arg. An error is raised if arg is not a numeric value.

This function is the same as fn:numeric-abs for terms with a datatype from XDM .

`ABS(1)`	`1`
`ABS(-1.5)`	`1.5`


numeric


ROUND

(


numeric



term

)

Returns the number with no fractional part that is closest to the argument. If there are two such numbers, then the one that is closest to positive infinity is returned. An error is raised if arg is not a numeric value.

This function is the same as fn:numeric-round for terms with a datatype from XDM .

`ROUND(2.4999)`	`2.0`
`ROUND(2.5)`	`3.0`
`ROUND(-2.5)`	`-2.0`


numeric


CEIL

(


numeric



term

)

Returns the smallest (closest to negative infinity) number with no fractional part that is not less than the value of arg. An error is raised if arg is not a numeric value.

This function is the same as fn:numeric-ceil for terms with a datatype from XDM .

`CEIL(10.5)`	`11.0`
`CEIL(-10.5)`	`-10.0`


numeric


FLOOR

(


numeric



term

)

Returns the largest (closest to positive infinity) number with no fractional part that is not greater than the value of arg. An error is raised if arg is not a numeric value.

This function is the same as fn:numeric-floor for terms with a datatype from XDM .

`FLOOR(10.5)`	`10.0`
`FLOOR(-10.5)`	`-11.0`


xsd:double


RAND

(
)

Returns a pseudo-random number between 0 (inclusive) and 1.0e0 (exclusive). Different numbers can be produced every time this function is invoked. Numbers should be produced with approximately equal probability.

rand() "0.31221030831984886"^^xsd:double


xsd:dateTime


NOW

()

Returns an XSD dateTime value for the current query execution. All calls to this function in any one query execution must return the same value. The exact moment returned is not specified.

NOW() "2011-01-10T14:45:13.815-05:00"^^xsd:dateTime


xsd:integer


YEAR

(


xsd:dateTime



arg

)

Returns the year part of arg as an integer.

This function corresponds to fn:year-from-dateTime .

YEAR("2011-01-10T14:45:13.815-05:00"^^xsd:dateTime) 2011


xsd:integer


MONTH

(


xsd:dateTime



arg

)

Returns the month part of arg as an integer.

This function corresponds to fn:month-from-dateTime .

MONTH("2011-01-10T14:45:13.815-05:00"^^xsd:dateTime) 1


xsd:integer


DAY

(


xsd:dateTime



arg

)

Returns the day part of arg as an integer.

This function corresponds to fn:day-from-dateTime .

day("2011-01-10T14:45:13.815-05:00"^^xsd:dateTime) 10


xsd:integer


HOURS

(


xsd:dateTime



arg

)

Returns the hours part of arg as an integer. The value is as given in the lexical form of the XSD dateTime.

This function corresponds to fn:hours-from-dateTime .

HOURS("2011-01-10T14:45:13.815-05:00"^^xsd:dateTime) 14


xsd:integer


MINUTES

(


xsd:dateTime



arg

)

Returns the minutes part of the lexical form of arg. The value is as given in the lexical form of the XSD dateTime.

This function corresponds to fn:minutes-from-dateTime .

MINUTES("2011-01-10T14:45:13.815-05:00"^^xsd:dateTime) 45


xsd:decimal


SECONDS

(


xsd:dateTime



arg

)

Returns the seconds part of the lexical form of arg.

This function corresponds to fn:seconds-from-dateTime .

SECONDS("2011-01-10T14:45:13.815-05:00"^^xsd:dateTime) 13.815


xsd:dayTimeDuration


TIMEZONE

(


xsd:dateTime



arg

)

Returns the timezone part of arg as an xsd:dayTimeDuration. Raises an error if there is no timezone.

This function corresponds to fn:timezone-from-dateTime except for the treatment of literals with no timezone.

`TIMEZONE("2011-01-10T14:45:13.815-05:00"^^xsd:dateTime)`	`"-PT5H"^^xsd:dayTimeDuration`
`TIMEZONE("2011-01-10T14:45:13.815Z"^^xsd:dateTime)`	`"PT0S"^^xsd:dayTimeDuration`
`TIMEZONE("2011-01-10T14:45:13.815"^^xsd:dateTime)`	error


xsd:string


TZ

(


xsd:dateTime



arg

)

Returns the timezone part of arg as a literal with datatype xsd:string. Returns the empty string if there is no timezone.

`TZ("2011-01-10T14:45:13.815-05:00"^^xsd:dateTime)`	`"-05:00"`
`TZ("2011-01-10T14:45:13.815Z"^^xsd:dateTime)`	`"Z"`
`TZ("2011-01-10T14:45:13.815"^^xsd:dateTime)`	`""`


triple
term


TRIPLE

(

RDF
term


subj
,

RDF
term


pred
,

RDF
term


obj

)


<<(

subj
pred
obj

)>>

If the 3-tuple ( subj, pred, obj ) is an RDF triple (that is, subj is an IRI or blank node ; pred is an IRI ; and obj is an IRI , triple term , blank node or literal ) the function returns a triple term with these three elements. Otherwise, the function raises an error.

As a shorthand notation, the TRIPLE function can also be written in the form of a triple term expression using <<( and )>>. There is a syntax limitation to this shorthand form: the three elements of the triple term expression can only be variables and directly written RDF terms, not arbitrary expressions. In contrast, the function form, TRIPLE, can be used with arbitrary expressions.

VERSION "1.2"
PREFIX : <http://example/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?s ?date {
    ?s ?p ?o .
    BIND( <<( ?s ?p ?o )>> AS ?tt )
    :myreifier rdf:reifies ?tt .
    :myreifier :tripleAdded ?date .
}

VERSION "1.2"
PREFIX : <http://example/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?s ?date {
    ?s ?p ?o .
    BIND( TRIPLE(?s, ?p, ?o) AS ?tt )
    :myreifier rdf:reifies ?tt .
    :myreifier :tripleAdded ?date .
}


RDF
term


SUBJECT

(

triple
term


triple-term

)

If the argument is a triple term , the function returns the subject of the triple term. If the argument is not a triple term , an error is raised.


RDF
term


PREDICATE

(

triple
term


triple-term

)

If the argument is a triple term , the function returns the predicate of the triple term. If the argument is not a triple term , an error is raised.


RDF
term


OBJECT

(

triple
term


triple-term

)

If the argument is a triple term , the function returns the object of the triple term. If the argument is not a triple term , an error is raised.


xsd:boolean


isTRIPLE

(

RDF
term


term

)

If the argument is a triple term , the function returns true. If the argument is any other kind of RDF term , the function returns false.


xsd:string


MD5

(


xsd:string



arg

)

Returns the MD5 checksum, as a hex digit string, calculated on the lexical form of the xsd:string. Hex digits SHOULD be in lower case.

MD5("abc") "900150983cd24fb0d6963f7d28e17f72"


xsd:string


SHA1

(


xsd:string



arg

)

Returns the SHA1 checksum, as a hex digit string, calculated on the lexical form of the xsd:string. Hex digits SHOULD be in lower case.

SHA1("abc") "a9993e364706816aba3e25717850c26c9cd0d89d"


xsd:string


SHA256

(


xsd:string



arg

)

Returns the SHA256 checksum, as a hex digit string, calculated on the lexical form of the xsd:string. Hex digits SHOULD be in lower case.

SHA256("abc") "ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"


xsd:string


SHA384

(


xsd:string



arg

)

Returns the SHA384 checksum, as a hex digit string, calculated on the lexical form of the xsd:string. Hex digits SHOULD be in lower case.

SHA384("abc") "cb00753f45a35e8bb5a03d699ac65007272c32ab0eded1631a8b605a43ff5bed8086072ba1e7cc2358baeca134c825a7"


xsd:string


SHA512

(


xsd:string



arg

)

Returns the SHA512 checksum, as a hex digit string, calculated on the lexical form of the xsd:string. Hex digits SHOULD be in lower case.

SHA512("abc") "ddaf35a193617abacc417349ae20413112e6fa4e89a97ea20a9eeee64b55d39a2192992a274fc1a836ba3c23a3feebbd454d4423643ce80e2a9ac94fa54ca49f"

SPARQL imports a subset of the XPath constructor functions defined in XPath and XQuery Functions and Operators 3.1 [ XPATH-FUNCTIONS-31 ] in section 19.1 Casting from primitive types to primitive types . SPARQL constructors include all of the XPath constructors for the SPARQL operand datatypes plus the additional datatypes imposed by the RDF data model. Casting in SPARQL is performed by calling a constructor function for the target type on an operand of the source type.

XPath defines only the casts from one XML Schema datatype to another. The remaining cast is defined as follows:

Casting an IRI to an xsd:string produces a literal with a lexical value of the codepoints comprising the IRI, and a datatype of xsd:string.

The table below summarizes the casting operations that are always allowed ( Y ), never allowed ( N ) and dependent on the lexical value ( M ). For example, a casting operation from an xsd:string (the first row) to an xsd:float (the second column) is dependent on the lexical value ( M ).

bool = xsd:boolean
dbl = xsd:double
flt = xsd:float
dec = xsd:decimal
int = xsd:integer
dT = xsd:dateTime
str = xsd:string
IRI = IRI

From \ To	str	flt	dbl	dec	int	dT	bool
str	Y	M	M	M	M	M	M
flt	Y	Y	Y	M	M	N	Y
dbl	Y	Y	Y	M	M	N	Y
dec	Y	Y	Y	Y	Y	N	Y
int	Y	Y	Y	Y	Y	N	Y
dT	Y	N	N	N	N	Y	N
bool	Y	Y	Y	Y	Y	N	Y
IRI	Y	N	N	N	N	N	N

It should be noted that any function or operator that is specified to return an error under some conditions is a valid extension point. That is, an implementation may return a non-error value in these error cases, and still be conformant with this recommendation.

A PrimaryExpression grammar rule can be a call to an extension function named by an IRI. An extension function takes some number of RDF terms as arguments and returns an RDF term. The semantics of these functions are identified by the IRI that identifies the function.

SPARQL queries using extension functions are likely to have limited interoperability.

As an example, consider a function called func:even:


xsd:boolean


func:even

(


numeric



value

)

This function would be invoked in a FILTER as such:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX func: <http://example.org/functions#>
SELECT ?name ?id
WHERE { 
    ?x foaf:name  ?name ;
       func:empId   ?id .
    FILTER (func:even(?id))
}

For a second example, consider a function aGeo:distance that calculates the distance between two points, which is used here to find the places near Grenoble:


xsd:double


aGeo:distance

(


numeric



x1
,


numeric



y1
,


numeric



x2
,


numeric



y2

)

PREFIX aGeo: <http://example.org/geo#>
SELECT ?neighbor
WHERE {
    ?a aGeo:placeName "Grenoble" .
    ?a aGeo:locationX ?axLoc .
    ?a aGeo:locationY ?ayLoc .
    ?b aGeo:placeName ?neighbor .
    ?b aGeo:locationX ?bxLoc .
    ?b aGeo:locationY ?byLoc .
    FILTER ( aGeo:distance(?axLoc, ?ayLoc, ?bxLoc, ?byLoc) < 10 ) .
}

An extension function might be used to test some application datatype not supported by the core SPARQL specification, it might be a transformation between datatype formats, for example into an XSD dateTime RDF term from another date format.

This section defines the correct behavior for evaluation of graph patterns and solution modifiers, given a query string and an RDF dataset. It does not imply a SPARQL implementation must use the process defined here.

The outcome of executing a SPARQL query is defined by a series of steps, starting from the SPARQL query as a string, turning that string into an abstract syntax form, then turning the abstract syntax into a SPARQL abstract query comprising operators from the SPARQL algebra. This abstract query is then evaluated on an RDF dataset.

The concept of an RDF Dataset is defined in [ RDF12-CONCEPTS ].

For the following definitions, we capture each RDF dataset as a set:

{ G, (, G ₁ ), (, G ₂ ), ... (, G _n ) } where G and each G _i are graphs, and each is an IRI or blank node. Each is distinct.

G is called the default graph. (, G _i ) are called named graphs.

Definition: Active Graph

The active graph is the graph from the dataset used for basic graph pattern matching.

Definition: Query Variable

We assume a countably infinite set V that is disjoint from the set of all RDF terms . Every member of this set V is a query variable .

Definition: Triple Pattern

A triple pattern is a 3-tuple ( s, p, o ) where:

s is an RDF term or a variable ,
p is an IRI or a variable , and
o is an RDF term or a variable .

This definition of Triple Pattern includes literal subjects. This has been noted by RDF-core .

"[The RDF core Working Group] noted that it is aware of no reason why literals should
            not be subjects and a future WG with a less restrictive charter may
extend
the
syntaxes

to

allow
literals
as
the
subjects
of
statements."

Because RDF graphs may not contain literal subjects, any SPARQL triple pattern with a literal as subject will fail to match on any RDF graph.

Definition: Basic Graph Pattern

A Basic Graph Pattern is a set of Triple Patterns .

The empty graph pattern is a basic graph pattern which is the empty set.

Definition: Property Path

A Property Path is a sequence of triples, t _i in sequence ST, with n = length(ST)-1, such that, for i=0 to n, the object of t _i is the same term as the subject of t _i+1.

We call the subject of t ₀ the start of the path.

We call the object of t _n the end of the path.

A Property Path is a path in graph G if each t _i is a triple of G.

A property path does not span multiple graphs in a dataset.

Definition: Property Path Expression

A property path expression is an expression using the property path forms described above.

Definition: Property Path Pattern

A property path pattern is a 3-tuple ( s, p, o ) where:

s is an RDF term or a variable ,
p is a property path expression , and
o is an RDF term or a variable .

A Property Path Pattern is a generalization of a Triple Pattern to include a property path expression in the predicate position.

A solution mapping is a mapping from a set of variables to a set of RDF terms. We use the term 'solution' where it is clear.

Definition: Solution Mapping

A solution mapping , μ, is a partial function μ : V → T, where V is the set of all variables and T is the set of all RDF terms .

The domain of μ, denoted by dom( μ ), is the subset of V for which μ is defined.

Definition: Solution Sequence

A solution sequence is a list of solutions, possibly unordered.

Write expr(μ) for the value of the expression expr, using the terms for variables given by μ. Evaluation may result in an error.

Definition: Solution Sequence Modifier

A solution sequence modifier is one of:

Order By modifier: put the solutions in order
Projection modifier: choose certain variables
Distinct modifier: ensure solutions in the sequence are unique
Reduced modifier: permit any non-distinct solutions to be eliminated
Offset modifier: control where the solutions start from in the overall sequence of solutions
Limit modifier: restrict the number of solutions

Definition: SPARQL Query

A SPARQL Abstract Query is a tuple (E, DS, QF) where:

E is a SPARQL algebra expression
DS is an RDF Dataset [ RDF12-CONCEPTS ]
QF is a query form

Definition: Query Level

A query level is a graph pattern, a set of group and aggregation, and a set of solution modifiers.

A query is a tree of "query levels", where each subquery forms one query level in the tree.

To define the evaluation semantics of a SPARQL query, the abstract syntax tree of the SPARQL query string (as defined by the SPARQL grammar ) is first translated into a syntax that resembles the SPARQL algebra . This section defines the expressions that can be formed in this algebraic syntax, and the translation of SPARQL query strings into this algebraic syntax is then defined in Section 18.3 Translation to the Algebraic Syntax .

An algebraic query expression is defined recursively as follows:

A basic graph pattern is an algebraic query expression.
A multiset of solution mappings is an algebraic query expression.
A sequence of solution mappings is an algebraic query expression.

Issue 231 : Keep both sequences and multisets of solution mappings as algebraic expressions? spec:enhancement

Do we really need both of the previous two points?
Path ( x, ppe, y ) is an algebraic query expression if ppe is an algebraic property path expression , x is an RDF term or a variable , and y is an RDF term or a variable .
Union ( A ₁, A ₂ ) is an algebraic query expression if A ₁ and A ₂ are algebraic query expressions.
Join ( A ₁, A ₂ ) is an algebraic query expression if A ₁ and A ₂ are algebraic query expressions.
Minus ( A ₁, A ₂ ) is an algebraic query expression if A ₁ and A ₂ are algebraic query expressions.
LeftJoin ( A ₁, A ₂, expr ) is an algebraic query expression if A ₁ and A ₂ are algebraic query expressions and expr is an expression .
Filter ( expr, A ) is an algebraic query expression if expr is an expression and A is an algebraic query expression.
Extend ( A, var, expr ) is an algebraic query expression if A is an algebraic query expression, var is a variable , and expr is an expression .
Graph ( x, A ) is an algebraic query expression if x is an IRI or a variable and A is an algebraic query expression.
ToMultiset ( A ) is an algebraic query expression if A is an algebraic query expression.
ToList ( A ) is an algebraic query expression if A is an algebraic query expression.
Group ( exprlist, A ) is an algebraic query expression if exprlist is a nonempty sequence of expressions and A is an algebraic query expression.
Aggregation ( exprlist, func, scalarvals, grp ) is an algebraic query expression if exprlist is a nonempty sequence of expressions or the asterisk character (*), func is a set function , scalarvals is a partial function (which may be the empty function, i.e., with an empty domain), and grp is an algebraic query expression of the form Group ( exprlist', A ) where exprlist' is a sequence of expressions and A is an algebraic query expression.

Issue 230 : 'Group' and 'Aggregation' should not be operators of the algebraic syntax spec:bug

Group and Aggregation should not be independent operators but, instead, should be integrated into the definition of AggregateJoin .
AggregateJoin ( A ₁, ..., A _n ) is an algebraic query expression if A ₁, ..., A _n is a non-empty sequence of algebraic query expressions (i.e., n ≥ 1) such that every expression A _i in this sequence is of the form Aggregation ( exprlist _i, func _i, scalarvals _i, grp _i ) that is captured by the previous point .
OrderBy ( A, condition ) is an algebraic query expression if A is an algebraic query expression and condition is an ordering condition.

Issue 229 : Notion of "ordering condition" undefined spec:bug

The term "ordering condition" should link to some definition of this notion.
Project ( A, PV ) is an algebraic query expression if A is an algebraic query expression and PV is a set of variables .
Distinct ( A ) is an algebraic query expression if A is an algebraic query expression.
Reduced ( A ) is an algebraic query expression if A is an algebraic query expression.
Slice ( A, start, length ) is an algebraic query expression if A is an algebraic query expression and start and length are integers.

The notion of an algebraic property path expression , as used in the previous definition, is defined recursively as follows:

link ( iri ) is an algebraic property path expression if iri is an IRI .
NPS ( I ) is an algebraic property path expression if I is a nonempty set of IRIs . NPS is an acronym for negated property set .
seq ( ppe ₁, ppe ₂ ) is an algebraic property path expression if ppe ₁ and ppe ₂ are algebraic property path expressions.
alt ( ppe ₁, ppe ₂ ) is an algebraic property path expression if ppe ₁ and ppe ₂ are algebraic property path expressions.
inv ( ppe ) is an algebraic property path expression if ppe is an algebraic property path expression.
ZeroOrOnePath ( ppe ) is an algebraic property path expression if ppe is an algebraic property path expression.
ZeroOrMorePath ( ppe ) is an algebraic property path expression if ppe is an algebraic property path expression.
OneOrMorePath ( ppe ) is an algebraic property path expression if ppe is an algebraic property path expression.

This section defines the process of converting graph patterns and solution modifiers in a SPARQL query string into an algebraic query expression . The process described converts one level of query nesting, as formed by subqueries using the nested SELECT syntax and is applied recursively on subqueries. Each level consists of graph pattern matching and filtering, followed by the application of solution modifiers.

The SPARQL query string is parsed and the abbreviations for IRIs and triple patterns given in Section 4. SPARQL Syntax are applied. At this point, the abstract syntax tree is composed of the following:

Patterns	Modifiers	Query Forms	Other
RDF terms	DISTINCT	SELECT	VALUES
Property path expression	REDUCED	CONSTRUCT	SERVICE
Property path patterns	Projection	DESCRIBE
Groups	ORDER BY	ASK
OPTIONAL	LIMIT
UNION	OFFSET
GRAPH	Select expressions
BIND
GROUP BY
HAVING
MINUS
FILTER

We define a variable to be in-scope if there is a way for the variable to be in the domain of a solution mapping at that point in the evaluation of the algebraic expression of the query. The definition below provides a way of determining this from the abstract syntax tree of a query.

Note that a subquery with a projection can hide variables; use of a variable in FILTER, or in MINUS does not cause the variable to be in-scope outside of those forms.

Let P , P1 , P2 be graph patterns and E , E1 ,... En be expressions. A variable v is in-scope if:

Syntax Form	In-scope variables
Basic Graph Pattern (BGP)	`v` occurs in the BGP
Path	`v` occurs in the path
Group `{ P1 P2 ... }`	`v` is in-scope if it is in-scope in one or more of P1, P2, ...
`GRAPH term { P }`	`v` is `term` or `v` is in-scope in P
`{ P1 } UNION { P2 }`	`v` is in-scope in P1 or in-scope in P2
`OPTIONAL {P}`	`v` is in-scope in P
`SERVICE term {P}`	`v` is `term` or `v` is in-scope in P
`BIND (expr AS v)`	`v` is in-scope
`SELECT .. v .. { P }`	`v` is in-scope
`SELECT ... (expr AS v)`	`v` is in-scope
`GROUP BY (expr AS v)`	`v` is in-scope
`SELECT * { P }`	`v` is in-scope in `P`
`VALUES v { values }`	`v` is in-scope
`VALUES varlist { values }`	`v` is in-scope if `v` is in `varlist`

The variable v must not be in-scope at the point of the (expr AS v) form. The scoping for (expr AS v) applies immediately in SELECT expressions.

In BIND (expr AS v) requires that the variable v is not in-scope from the preceeding elements in the group graph pattern in which it is used.

In SELECT, the variable v must not be in-scope in the graph pattern of the SELECT clause, nor used in another select expression earlier in the clause.

This section describes the process for translating a SPARQL graph pattern into an algebraic query expression . This process is applied to the group graph pattern (the unit between brace (" { } ") delimiters) forming the WHERE clause of a query, and recursively to each syntactic element within the group graph pattern. The result of the translation is an algebraic query expression .

In summary, the steps are applied as follows:

Expand syntax forms for IRIs, literals and triple patterns.
Translate property path expressions
Convert some property path patterns to triples
Collect the FILTER s in the group
Translate Basic Graph Patterns
Translate the remaining graph patterns in the group
Add in Filters
Simplify the resulting expression

We write

translate(graph pattern)

for the algorithm described here to translate graph patterns.

The working group notes that in SPARQL 1.0, the point at which the simplification step is applied leads to ambiguous transformation of queries involving a doubly nested filter and pattern in an optional:


OPTIONAL
{
{
...

FILTER

(
...
?

x

...
)
}
}.
.

This is illustrated by two non-normative test cases:

Simplification applied after all transformations or not at all.
Simplification applied during transformation .

Applying the simpification step after all the translation of graph patterns is the preferred reading.

Expand abbreviations for IRIs and triple patterns given in Section 4. SPARQL Syntax .

FILTER expressions apply to the whole group graph pattern in which they appear. The algebra operators to perform filtering are added to the group after translation of each group element. We collect the filters together here and remove them from group, then apply them to the whole translated group graph pattern .

In this step, we also translate graph patterns within FILTER expressions EXISTS and NOT EXISTS .

Let FS := empty set
For each form FILTER(expr) in the group graph pattern
    In expr, replace NOT EXISTS{P} with fn:not(exists(translate(P))) 
    In expr, replace EXISTS{P} with exists(translate(P))
    FS := FS ∪ {expr}
End

The set of filter expressions FS is used later .

The following table gives the translation of property path expressions in SPARQL query strings into algebraic property path expressions . This applies to all elements of a property path expression recursively.

The next step after this one translates certain forms to triple patterns, and these are converted later to basic graph patterns by adjacency (without intervening group pattern delimiters { and }) or other syntax forms. Overall, SPARQL syntax property paths of just an IRI become triple patterns and these are aggregated into basic graph patterns.

Notes:

The order of forms IRI and ^IRI in a negated property set (NPS) is not relevant.

Syntax Form (path)	Algebraic Form (path)
`iri`	`link (iri)`
`^path`	`inv (path)`
`!(:iri ₁ \|...\|:iri _n )`	`NPS ({:iri ₁ ... :iri _n })`
`!(^:iri ₁ \|...\|^:iri _n )`	`inv ( NPS ({:iri ₁ ... :iri _n }) )`
`!(:iri ₁ \|...\|:iri _i \|^:iri _i+1 \|...\|^:iri _m )`	`alt ( NPS ({:iri ₁ ...:iri _i }), inv ( NPS ({:iri _i+1, ..., :iri _m })) )`
`path1 / path2`	`seq (path1, path2)`
`path1 \| path2`	`alt (path1, path2)`
`path*`	`ZeroOrMorePath (path)`
`path+`	`OneOrMorePath (path)`
`path?`	`ZeroOrOnePath (path)`

The previous step translated property path expressions . This step translates property path patterns , which are a subject end point, a property path expression, and an object end point. This step assumes that the property path expression of the property path pattern is already given in the form of an algebraic property path expression . The result of this step may be triple patterns and algebraic query expressions of the form Path (...).

Notes:

x and y are RDF terms or variables .
var is a fresh variable .
ppe, ppe ₁, and ppe ₂ are algebraic property path expressions .
These are only applied to property path patterns, not within property path expressions.
Translations earlier in the table are applied in preference to the last translation.
The final translation simply wraps any remaining property path expression to use a common form Path (...).

Algebraic Form (path)	Translation
`x` link ( `iri` ) `y`	`x` `iri` `y`
`x` inv ( `iri` ) `y`	`y` `iri` `x`
`x` seq ( `ppe ₁`, `ppe ₂` ) `y`	`x` `ppe ₁` `var` . `var` `ppe ₂` `y`
`x` `ppe` `y`	Path ( `x`, `ppe`, `y` )

Issue 226 : Translation of property path patterns incomplete spec:bug

I assume that the translation rules in this table are meant to be applied recursively, but the section doesn't say anything about that. In particular, for the " x seq ( ppe ₁, ppe ₂ ) y " case: ppe ₁ and ppe ₂ in the resulting translation may still be arbitrary algebraic property path expressions and, thus, the translation should be applied again for each of the two resulting property path patterns (i.e., for " x ppe ₁ var " and for " var ppe ₂ y ").

Examples of the whole path translation process ( ?_V is a fresh variable):

?s :p/:q ?o

?s :p ?_V .
?_V :q ?o

?s :p* ?o

Path (?s, ZeroOrMorePath ( link (:p)), ?o)

:list rdf:rest*/rdf:first ?member

Path (:list, ZeroOrMorePath ( link (rdf:rest)), ?_V) .
?_V rdf:first ?member

After translating property paths, any adjacent triple patterns are collected together to form a basic graph pattern BGP(triples).

Next, we translate each remaining graph pattern form, recursively applying the translation process.

If the form is GroupOrUnionGraphPattern

Let A := undefined
          
For each element G in the GroupOrUnionGraphPattern
    If A is undefined
        A := Translate(G)
    Else
        A := Union(A, Translate(G))
    End
The
result
is

A

If the form is GraphGraphPattern

If the form is GRAPH IRI GroupGraphPattern
The
result
is

Graph

(IRI,
Translate(GroupGraphPattern))

If the form is GRAPH Var GroupGraphPattern
The
result
is

Graph

(Var,
Translate(GroupGraphPattern))

If the form is GroupGraphPattern:

Let FS := the empty set
Let G := the empty pattern, a basic graph pattern which is the empty set.
For each element E in the sequence of elements in the GroupGraphPattern
    If E is of the form OPTIONAL{P} 
        Let A := Translate(P)
        If A is of the form Filter(F, A2)
            G := LeftJoin(G, A2, F)
        Else 
            G := LeftJoin(G, A, true)
            End
        End
    If E is of the form MINUS{P}
        G := Minus(G, Translate(P))
        End
    If E is of the form BIND(expr AS var)
        G := Extend(G, var, expr)
        End
    If E is any other form 
        Let A := Translate(E)
        G := Join(G, A)
        End
   End
   
The
result
is

G
.

If the form is InlineData

The
result
is
a
multiset

data

of
solution
mappings.

data is formed by forming a solution mapping from the variable in the corresponding position in list of variables (or single variable), omitting a binding if the DataBlockValue is the word UNDEF.

If the form is SubSelect

The
result
is

ToMultiset

(Translate(SubSelect))

After the group has been translated, the filter expressions are added so they wil apply to the whole of the rest of the group:

If FS is not empty
    Let G := output of preceding step
    Let X := Conjunction of expressions in FS
    G := Filter(X, G)
End

Some groups of one graph pattern become Join ( Z, A ), where Z is the empty basic graph pattern (which is the empty set). These are replaced by A. The empty graph pattern Z is the identity for join:

Replace Join(Z, A) by A
Replace

Join

(

A
,

Z

)
by

A

The second form of a rewrite example is the first with empty group joins removed by the simplification step. Z is the empty basic graph pattern.

Example: group with a basic graph pattern consisting of a single triple pattern:

{ ?s ?p ?o }

Join ( Z, BGP(?s ?p ?o) )

BGP(?s ?p ?o)

Example: group with a basic graph pattern consisting of two triple patterns:

{ ?s :p1 ?v1 ; :p2 ?v2 }

BGP( ?s :p1 ?v1 . ?s :p2 ?v2 )

Issue 246 : Examples of translation of graph patterns are inconsistent spec:editorial

The example above does not include the version of the resulting expression before the simplification step. The same is true for several other examples below. The examples should be consistent in this regard.

Example: group consisting of a union of two basic graph patterns:

{ { ?s :p1 ?v1 } UNION {?s :p2 ?v2 } }

Union ( Join ( Z, BGP(?s :p1 ?v1)),
Join ( Z, BGP(?s :p2 ?v2)) )

Union ( BGP(?s :p1 ?v1) , BGP(?s :p2 ?v2) )

Example: group consisting of a union of a union and a basic graph pattern:

{ { ?s :p1 ?v1 } UNION {?s :p2 ?v2 } UNION {?s :p3 ?v3 } }

Union (
    Union ( Join ( Z, BGP(?s :p1 ?v1)),
           Join ( Z, BGP(?s :p2 ?v2))) ,
    Join ( Z, BGP(?s :p3 ?v3)) )

Union (
    Union ( BGP(?s :p1 ?v1) ,
           BGP(?s :p2 ?v2),
    BGP(?s :p3 ?v3))

Example: group consisting of a basic graph pattern and an optional graph pattern:

{ ?s :p1 ?v1 OPTIONAL {?s :p2 ?v2 } }

LeftJoin (
    Join ( Z, BGP(?s :p1 ?v1)),
    Join ( Z, BGP(?s :p2 ?v2)),
    true)

LeftJoin (BGP(?s :p1 ?v1), BGP(?s :p2 ?v2), true)

Example: group consisting of a basic graph pattern and two optional graph patterns:

{ ?s :p1 ?v1 OPTIONAL {?s :p2 ?v2 } OPTIONAL { ?s :p3 ?v3 } }

LeftJoin (
    LeftJoin (
        BGP(?s :p1 ?v1),
        BGP(?s :p2 ?v2),
        true) ,
    BGP(?s :p3 ?v3),
    true)

Example: group consisting of a basic graph pattern and an optional graph pattern with a filter:

{ ?s :p1 ?v1 OPTIONAL {?s :p2 ?v2 FILTER(?v1<3) } }

LeftJoin (
 Join ( Z, BGP(?s :p1 ?v1)),
 Join ( Z, BGP(?s :p2 ?v2)),
 (?v1<3) )

LeftJoin (
 BGP(?s :p1 ?v1) ,
 BGP(?s :p2 ?v2) ,
 (?v1<3) )

Example: group consisting of a union graph pattern and an optional graph pattern:

{ {?s :p1 ?v1} UNION {?s :p2 ?v2} OPTIONAL {?s :p3 ?v3} }

LeftJoin (
Union (BGP(?s :p1 ?v1),
BGP(?s :p2 ?v2)) ,
BGP(?s :p3 ?v3) ,
true )

Example: group consisting of a basic graph pattern, a filter and an optional graph pattern:

{ ?s :p1 ?v1 FILTER (?v1 < 3 ) OPTIONAL {?s :p2 ?v2} }

Filter ( ?v1 < 3 ,
LeftJoin ( BGP(?s :p1 ?v1), BGP(?s :p2 ?v2), true) ,
)

Example: Pattern involving BIND:

{ ?s :p ?v . BIND (2*?v AS ?v2) ?s :p1 ?v2 }

Join (
Extend ( BGP(?s :p ?v), ?v2, 2*?v) ,
BGP(?s :p1 ?v2) )

Example: Pattern involving BIND, with a simplification step:

Issue 246 : Examples of translation of graph patterns are inconsistent spec:editorial

The following example uses

{}

to represent the empty BGP in the first version of the resulting expression (the one before the simplification step), whereas the previous examples above are using Z instead. The examples should be consistent in this regard.

{ ?s :p ?v . {} BIND (2*?v AS ?v2) }

Extend (
   Join (
     Join ( {}, BGP(?s :p ?v)),
     {}),
   ?v2, 2*?v
)

Extend (
BGP(?s :p ?v) ,
?v2, 2*?v
)

Example: Pattern involving MINUS:

{ ?s :p ?v . MINUS {?s :p1 ?v2 } }

Minus (
BGP(?s :p ?v) ,
BGP(?s :p1 ?v2)
)

Example: Pattern involving a subquery:

{ ?s :p ?o . {SELECT DISTINCT ?o {?o ?p ?z} } }

Join (
   BGP(?s :p ?o) ,
   ToMultiset (
     Distinct (
       Project ( ToList (BGP(?o ?p ?z)), {?o} )
     )
   )
)

In this step, we process clauses on the query level in the following order:

Grouping
Aggregates
HAVING
VALUES
Select expressions

Step: GROUP BY

If the GROUP BY keyword is used, or there is implicit grouping due to the use of aggregates in the projection, then grouping is performed by the Group function. In this case, before grouping, the solution set is converted into a solution sequence by applying the ToList function. Next, the Group function divides this solution sequence into groups of one or more solutions, with the same overall cardinality. In case of implicit grouping, a fixed constant (1) is used to group all solutions into a single group.

Step: Aggregates

The aggregation step is applied as a transformation on the query level, replacing aggregate expressions in the query level with Aggregation () algebraic expressions.

The transformation for query levels that use any aggregates is given below:

Issue 247 : Minor issues in translation algorithm for Grouping and Aggregation spec:editorial

There are a few minor issues in the following algorithm.

Let A := the empty sequence
Let Q := the query level being evaluated
Let P := algebraic query expression produced for the GroupGraphPattern of the query level
Let E := [], a list of pairs of the form (variable, expression)
If Q contains GROUP BY exprlist
   Let Grp := Group(exprlist, ToList(P))
Else If Q contains an aggregate in SELECT, HAVING, ORDER BY
   Let Grp := Group((1), ToList(P))
Else
   skip the rest of the Aggregates step
   End
Global i := 1   # Initially 1 for each query processed
For each (X AS Var) in SELECT, each HAVING(X), and each ORDER BY X in Q
  For each unaggregated variable V in X
      Replace V with SAMPLE(V)
      End
  For each aggregate R(args ; scalarvals) now in X
      # note: scalarvals may be omitted; if so, it is equivalent to the empty function
      A_i := Aggregation(args, R, scalarvals, Grp)
      Replace R(...) with agg_i in Q
      i := i + 1
      End
  End
For each variable V appearing outside of an aggregate
   A_i := Aggregation(V, Sample, {}, Grp)
   E := E append (V, agg_i)
   i := i + 1
   End
A := A_i, ..., A_i-1

P

:=

AggregateJoin

(

A

)

The list E will be used when translating SELECT expressions in Section 18.3.4.4 SELECT Expressions .

The HAVING expression is evaluated using the same rules as FILTER(). Note that, due to the logic position in which the HAVING clause is evaluated, expressions projected by the SELECT clause are not visible to the HAVING clause.

Let Q := the query level being evaluated
Let P := the algebraic query expression produced for the query level so far
For each HAVING(E) in Q
    P := Filter(E, P)
End

If the query has a trailing VALUES clause:

Let P := the algebraic query expression produced for the query level so far
P := Join(P, ToMultiset(data))
where

data

is
a
solution
sequence
derived
from
the
VALUES
clause

The translation of the data is the same as for inline data .

Step: Select expressions

We have two forms of the abstract syntax to consider:

SELECT selItem ... { pattern }
SELECT
*
{
pattern
}

Let X := algebraic query expression from earlier steps
Let VS := set of all variables visible in the pattern,
           so restricted by sub-SELECT projected variables and GROUP BY variables.
           Not visible: only in filter, exists/not exists, masked by a subselect, 
                        non-projected GROUP variables, only in the right hand side of MINUS
Let PV := {}, a set of variable names
Let E := a list of pairs of the form (variable, expression), populated in Section 18.3.4.1 Grouping and Aggregation
  
If "SELECT *"
    PV := VS
If  "SELECT selItem ..."
    For each selItem
        If selItem is a variable
            PV := PV ∪ { variable }
        End
        If selItem is (expr AS var)
            var must not appear in VS nor in PV; if it does then generate a syntax error and stop
            PV := PV ∪ { var }
            E := E append (var, expr) 
        End
    End
For each pair (var, expr) in E
    X := Extend(X, var, expr)
    End
  
Result is X  
The
set

PV

is
used
later
for
projection
(see
Section 


18.3.5.2

Projection

).

The syntax error arises for use of a variable as the named target of AS (e.g. ... AS ?x) when the variable is used inside the WHERE clause of the SELECT or if already used as the target of AS in this SELECT expression.

Solution modifiers apply to the processing of a SPARQL query after pattern matching.

Since the solution modifiers operate on sequences of solution mappings, the query result produced up to this point is first turned from a multiset of solution mappings into such a sequence. While there is no implied ordering to this sequence, and duplicates need not be adjacent, the sequence is identical to the multiset in terms of the elements that it contains, and their multiplicities. To apply this conversion from a multiset into a sequence, the algorithm for translating the solution modifiers into algebraic query expressions begins with the following step, where A is the algebraic query expression produced by the algorithm in the previous section.

Let M := ToList ( A )

Now, the solution modifiers are applied in the following order:

Order by
Projection
Distinct
Reduced
Offset
Limit

If the query string has an ORDER BY clause

M := OrderBy ( M, list of order comparators)

The set PV of projection variables was calculated in the processing of SELECT expressions .

M := Project ( M, PV )

If the query contains DISTINCT,

M := Distinct ( M )

If the query contains REDUCED,

M := Reduced ( M )

If the query contains "OFFSET start " or "LIMIT length "

M := Slice ( M, start, length )

start defaults to 0

length defaults to (size( M )- start ).

Issue 248 : Translation of OFFSET and LIMIT to Slice(..) is formally incorrect spec:bug

The definition of this translation step is formally incorrect.

The overall algebraic query expression is M.

When matching graph patterns, the possible solutions form a multiset , also known as a bag . A multiset is an unordered collection of elements in which each element may appear more than once. It is described by a set of elements and a function giving the multiplicity of each of these elements (i.e., the number of times the element is contained in the multiset).

Write μ for solution mappings.

Write μ ₀ for the mapping such that dom ( μ ₀ ) is the empty set.

Write Ω ₀ for the multiset consisting of exactly the empty mapping μ ₀, with multiplicity 1. This is the join identity.

Write μ ( x ) for the solution mapping variable x to RDF term t : { ( x, t ) }.

Definition: Compatible Mappings

Two solution mappings μ ₁ and μ ₂ are compatible if, for every variable v in dom(μ ₁ ) and in dom(μ ₂ ), μ ₁ (v) = μ ₂ (v).

Here, μ ₁ (v) = μ ₂ (v) means that μ ₁ (v) and μ ₂ (v) are the same RDF term.

If μ ₁ and μ ₂ are compatible then μ ₁ ∪ μ ₂ is also a mapping. Write merge(μ ₁, μ ₂ ) for μ ₁ ∪ μ ₂

Definition: Multiplicity

Given a multiset Ω of solution mappings and a solution mapping μ, we write multiplicity ( μ | Ω ) to denote the number of times μ appears in Ω.

Similarly, given a solution sequence Ψ and a solution mapping μ, we write multiplicity ( μ | Ψ ) to denote the number of times μ appears in Ψ.

A basic graph pattern is matched against the active graph for that part of the query. Basic graph patterns can be instantiated by replacing both variables and blank nodes by terms, giving two notions of instance. Blank nodes are replaced using an RDF instance mapping , σ, from blank nodes to RDF terms; variables are replaced by a solution mapping from query variables to RDF terms.

Definition: Pattern Instance Mapping

A Pattern Instance Mapping , P, is the combination of an RDF instance mapping, σ, and solution mapping, μ. P(x) = μ(σ(x))

For a BGP 'x', P(x) denotes the result of replacing blank nodes b in x for which σ is defined with σ(b) and all variables v in x for which μ is defined with μ(v).

Any pattern instance mapping defines a unique solution mapping and a unique RDF instance mapping obtained by restricting it to query variables and blank nodes respectively.

Definition: Basic Graph Pattern Matching

Let BGP be a basic graph pattern and let G be an RDF graph.

μ is a solution for BGP from G when there is a pattern instance mapping P such that P(BGP) is a subgraph of G and μ is the restriction of P to the query variables in BGP.

multiplicity ( μ | Ω ) = number of distinct RDF instance mappings, σ, such that P = μ(σ) is a pattern instance mapping and P(BGP) is a subgraph of G.

If a basic graph pattern is the empty set, then the solution is Ω ₀.

This definition allows the solution mapping to bind a variable in a basic graph pattern, BGP, to a blank node in G. Since SPARQL treats blank node identifiers in a results format document ( SPARQL Query Results XML Format (Second Edition) , SPARQL 1.1 Query Results JSON Format and SPARQL 1.1 Query Results CSV and TSV Formats ) as scoped to the document, they cannot be understood as identifying nodes in the active graph of the dataset. If DS is the dataset of a query, pattern solutions are therefore understood to be not from the active graph of DS itself, but from an RDF graph, called the scoping graph, which is graph-equivalent to the active graph of DS but shares no blank nodes with DS or with BGP. The same scoping graph is used for all solutions to a single query. The scoping graph is purely a theoretical construct; in practice, the effect is obtained simply by the document scope conventions for blank node identifiers.

Since RDF blank nodes allow infinitely many redundant solutions for many patterns, there can be infinitely many pattern solutions (obtained by replacing blank nodes by different blank nodes). It is necessary, therefore, to somehow delimit the solutions for a basic graph pattern. SPARQL uses the subgraph match criterion to determine the solutions of a basic graph pattern. There is one solution for each distinct pattern instance mapping from the basic graph pattern to a subset of the active graph.

This is optimized for ease of computation rather than redundancy elimination. It allows query results to contain redundancies even when the active graph of the dataset is lean , and it allows logically equivalent datasets to yield different query results.

This section defines the evaluation of property path patterns . A property path pattern is a subject endpoint (an RDF term or a variable), a property path express and an object endpoint. The translation of property path expressions converts some forms to other SPARQL expressions, such as converting property paths of length one to triple patterns, which in turn are combined into basic graph patterns. This leaves property path operators ZeroOrOnePath, ZeroOrMorePath, OneOrMorePath and NegatedPropertySets and also path expressions contained within these operators.

All remaining property path expressions are present in the algebra in the form Path(X, path, Y) for endpoints X and Y. For example: syntax (:p/:q)* is a ZeroOrMorePath expression involving a sequence property path becoming the algebra expession ZeroOrMorePath(seq(link(:p), link(:q))).

Notation

Write


eval(

Path

(

X
,
PP,

Y

))

for the evaluation of the property path patterns. This produces a multiset of solution mappings μ, each solution mapping having a binding for variables used (each of X and Y can be a variable). Some operators only produce a set of solution mappings.

Write

Var(x1, x2, ..., xn) = { xi | i in 1...n and xi is a variable
}

for the variables in x ₁, x ₂, ..., x _n.

Write

`x:term`	when `x` is an RDF term
`x:var`	when `x` is a variable
`x:path`	when `x` is a path expression

All evaluation is carried out by matching the active graph at that point in the overall query evaluation. We omit explicitly including the active graph in each definition for clarity.

Definition: Evaluation of Predicate Property Path

Let Path(X, link(iri), Y) be an predicate inverse property path pattern, using some IRI iri.



eval

(

Path

(X,

link

(iri),
Y))
=
evaluation

of

basic
graph
pattern
{X
iri
Y}

If both X and Y are variables, this is the same as:



eval

(

Path

(

X
:

var
,

link

(iri),

Y
:

var

))
=
{
(X,
xn)
(Y,
yn)
|
xn
and
yn
are

RDF

terms
and

triple

(xn
iri
yn)
is

in

the
active
graph
}

If X is a variable and Y an RDF term:

eval(Path(X:var, link(iri), Y:term)) = { (X, xn) | xn is an RDF term and triple (xn iri Y) is in the active graph
}

If X is an RDF term and Y is a variable:

eval(Path(X:term, link(iri), Y:var)) = { (Y, yn) | yn is an RDF term and triple (X iri yn) is in the active graph
}

If both X and Y are RDF terms:

eval(Path(X:term, link(iri), Y:term)) 
    = { μ0 } if triple (X iri Y) is in the active graph
    = { { } } = Ω0 

eval

(

Path

(

X
:term,

link

(iri),

Y
:term))
=
{
}

if


triple

(X
iri
Y)
is
not

in

the
active
graph

Informally, evaluating a Predicate Property Path is the same as executing a subquery SELECT * { X P Y } at that point in the query evaluation.

Definition: Evaluation of Inverse Property Path

Let P be a property path expression, then:



eval

(

Path

(X,

inv

(P),
Y))
=

eval

(

Path

(Y,
P,
X))

Definition: Evaluation of Sequence Property Path

Let P and Q be property path expressions. Let V be a fresh variable.


A
=

Join

(

eval

(

Path

(X,
P,
V)),

eval

(

Path

(V,
Q,
Y))
)



eval

(

Path

(X,

seq

(P,Q),
Y))
=

Project

(A,

Var

(X,Y))

Informally, this is the same as:



SELECT

*
{

X


P

_:a
.
_:a
Q
Y
}

using the fact that a blank node _:a acts like a variable (under simple entailment) except it does not appear in the results from SELECT *.

Definition: Evaluation of Alternative Property Path

Let P and Q be property path expressions.

eval(Path(X, alt(P,Q), Y)) = 

Union

(

eval

(

Path

(X,
P,
Y)),

eval

(

Path

(X,
Q,
Y)))

Informally, this is the same as:



SELECT

*
{
{

X


P


Y

}
UNION
{

X


Q


Y

}
}

Definition: Node set of a graph

The node set of a graph G, nodes(G), is:

nodes(G) = { n | n is an RDF term that is used as a subject or object of a triple of G}

Definition: Evaluation of ZeroOrOnePath

eval(Path(X:term, ZeroOrOnePath(P), Y:var)) = 
{
(Y,
yn)
|
yn
=
X
or
{(Y,
yn)}

in


eval

(

Path

(X,P,Y))
}

eval(Path(X:var, ZeroOrOnePath(P), Y:term)) =
{
(X,
xn)
|
xn
=
Y
or
{(X,
xn)}

in


eval

(

Path

(X,P,Y))
}

eval(Path(X:term, ZeroOrOnePath(P), Y:term)) = 
    { {} } if X = Y or eval(Path(X,P,Y)) is not empty
{
}
othewise

eval(Path(X:var, ZeroOrOnePath(P), Y:var)) = 
{
(X,
xn)
(Y,
yn)
|

either

(yn

in


nodes

(G)
and
xn
=
yn)
or
{(X,xn),
(Y,yn)}

in


eval

(

Path

(X,P,Y))
}

We define an auxillary function, ALP, used in the definitions of ZeroOrMorePath and OneOrMorePath. Note that the algorithm given here serves to specify the feature. An implementation is free to implement evaluation by any method that produces the same results for the query overall. The ZeroOrMorePath and OneOrMorePath forms return matches based on distinct nodes connected by the path.

The matching algorithm is based on following all paths, and detecting when a graph node (subject or object), has been already visited on the path.

Informally, this algorithm attempts to extend the multiset of results by one application of path at each step, noting which nodes it has visited for this particular path. If a node has been visited for the path under consideration, it is not a candidate for another step.

Definition: Function ALP

Let eval(x:term, path) be the evaluation of 'path', starting at RDF term x, 
 and returning a multiset of RDF terms reached 
 by repeated matches of path.
  ALP(x:term, path) = 
      Let V = empty set
      ALP(x:term, path, V)
      return is V
  # V is the set of nodes visited
  ALP(x:term, path, V:set of RDF terms) =
      if ( x in V ) return 
      add x to V
      X = eval(x,path) 
      For n:term in X
          ALP(n, path, V)
End

Definition: Evaluation of

ZeroOrMorePath

eval(Path(X:term, ZeroOrMorePath(path), vy:var)) =
    { { (vy, n) } | n in ALP(X, path) }
eval(Path(vx:var, ZeroOrMorePath(path), vy:var)) =
    { { (vx, t), (vy, n) } |  t in nodes(G), (vy, n) in eval(Path(t, ZeroOrMorePath(path), vy)) }
eval(Path(vx:var, ZeroOrMorePath(path), y:term)) = 
    eval(Path(y:term, ZeroOrMorePath(inv(path)), vx:var))
eval(Path(x:term, ZeroOrMorePath(path), y:term)) = 
    { { } } if { (vy:var,y) } in eval(Path(x, ZeroOrMorePath(path) vy)
{
}
otherwise

Definition: Evaluation of

OneOrMorePath

eval(Path(X, OneOrMorePath(path), Y))

# For OneOrMorePath, we take one step of the path then start
# recording nodes for results.
eval(Path(x:term, OneOrMorePath(path), vy:var)) =
    Let X = eval(x, path)
    Let V = the empty multiset
    For n in X
        ALP(n, path, V)
    End
    result is V
eval(Path(vx:var, OneOrMorePath(path), vy:var)) =
     { { (vx, t), (vy, n) } |  t in nodes(G), (vy, n) in eval(Path(t, OneOrMorePath(path), vy)) }
eval(Path(vx:var, OneOrMorePath(path), y:term)) =
    eval(Path(y:term, OneOrMorePath(inv(path)), vx))
eval(Path(x:term, OneOrMorePath(path), y:term)) =
    { { } } if { (vy:var, y) } in eval(Path(x, OneOrMorePath(path), vy))
{
}

otherwise

Definition: Evaluation of NegatedPropertySet

Write μ' as the extension of a solution mapping:
μ'(μ,x) = μ(x)   if x is a variable
μ'(μ,t)
=
t
if
t
is
a
RDF
term

Let x and y be variables or RDF terms, and S a set of IRIs:
eval(Path(x,
NPS(S),
y))
=
{
μ
|
∃
triple(μ'(μ,x),
p,
μ'(μ,y))
in
G,
such
that
the
IRI
of
p
∉
S
}

For each remaining symbol in a SPARQL abstract query, we define an operator for evaluation. The SPARQL algebra operators of the same name are used to evaluate SPARQL abstract query nodes as described in the section " Evaluation Semantics ". Evaluation of basic graph patterns and property path patterns has been described above.

Definition: Filter

Let Ω be a multiset of solution ~~mappings and~~ mappings, expr be an ~~expression.~~ expression ,D be a dataset , and G be the active graph . We define:

Filter ( expr, Ω, D,G ) = { μ ~~| μ~~ in Ω ~~and~~ | expr ( μ ) is an expression that has an effective boolean value of true }

Issue 254 : Expressions and their evaluation are ill-defined

It is not clear what expr ( μ ) is, and it is not apparent in the formula that the expression expr is meant to be evaluated not only with respect to μ but also with respect to D with active graph G.

multiplicity ( μ | Filter ( expr, Ω, D,G ) ) = multiplicity ( μ | Ω )

Note that evaluating an exists(pattern) expression uses the dataset D and active ~~graph, D(G).~~ graph G. See the evaluation of filter .

Definition: Join

Let Ω ₁ and Ω ₂ be multisets of solution mappings. We define:

Join ( Ω ₁, Ω ₂ ) = { merge( μ ₁, μ ₂ ) | μ ₁ in Ω ₁ and μ ₂ in Ω ₂, and μ ₁ and μ ₂ are compatible }

multiplicity ( μ | Join ( Ω ₁, Ω ₂ ) ) =
for each merge( μ ₁, μ ₂ ), μ ₁ in Ω ₁ and μ ₂ in Ω ₂ such that μ = merge( μ ₁, μ ₂ ),
sum over ( μ ₁, μ ₂ ), multiplicity ( μ ₁ | Ω ₁ ) * multiplicity ( μ ₂ | Ω ₂ )

It is possible that a solution mapping μ in a Join can arise in different solution mappings, μ ₁ and μ ₂ in the multisets being joined. The multiplicity of μ is the sum of the multiplicities from all possibilities.

Definition: Diff

Let Ω ₁ and Ω ₂ be multisets of solution mappings and expr be an ~~expression.~~ expression . We define:

Diff ( Ω ₁, Ω ₂, expr ) = { μ | μ in Ω ₁ such that ∀ μ' in Ω ₂, either μ and μ' are not compatible or μ and μ' are compatible and expr (merge( μ, μ' )) does not have an effective boolean value of true }

Issue 254 : Expressions and their evaluation are ill-defined

multiplicity ( μ | Diff ( Ω ₁, Ω ₂, expr ) ) = multiplicity ( μ | Ω ₁ )

The evaluation of expr (merge( μ, μ' )) does not have an effective boolean value of true if it evaluates to false or if it raises an error.

Diff is used internally for the definition of LeftJoin .

Definition: LeftJoin

Let Ω ₁ and Ω ₂ be multisets of solution mappings and expr be an ~~expression.~~ expression . We define:

LeftJoin ( Ω ₁, Ω ₂, expr ) = Filter ( expr, Join ( Ω ₁, Ω ₂ )) ∪ Diff ( Ω ₁, Ω ₂, expr )

multiplicity ( μ | LeftJoin ( Ω ₁, Ω ₂, expr ) ) = multiplicity ( μ | Filter ( expr, Join ( Ω ₁, Ω ₂ )) ) + multiplicity ( μ | Diff ( Ω ₁, Ω ₂, expr ) )

Definition: Union

Let Ω ₁ and Ω ₂ be multisets of solution mappings. We define:

Union ( Ω ₁, Ω ₂ ) = { μ | μ in Ω ₁ or μ in Ω ₂ }

multiplicity ( μ | Union ( Ω ₁, Ω ₂ ) ) = multiplicity ( μ | Ω ₁ ) + multiplicity ( μ | Ω ₂ )

Definition: Minus

Let Ω ₁ and Ω ₂ be multisets of solution mappings. We define:

Minus ( Ω ₁, Ω ₂ ) = { μ | μ in Ω ₁ . ∀ μ' in Ω ₂, either μ and μ' are not compatible or dom( μ ) and dom( μ' ) are disjoint }

multiplicity ( μ | Minus ( Ω ₁, Ω ₂ ) ) = multiplicity ( μ | Ω ₁ )

The additional restriction on dom( μ ) and dom( μ' ) is added because otherwise if there is a solution mapping in Ω ₂ that has no variables in common with the solution mappings of Ω ₁, then Minus ( Ω ₁, Ω ₂ ) would be empty, regardless of the rest of Ω ₂. The empty solution mapping is compatible with every other solution mapping so P MINUS {} would otherwise be empty for any pattern P.

Definition: Extend

Let μ be a solution mapping, Ω a multiset of solution mappings, var a variable and expr be an expression , then we define:

Extend ( μ, var, expr ) = μ ∪ { ( var, value ) | var not in dom( μ ) and value = expr ( μ ) }

Issue 254 : Expressions and their evaluation are ill-defined

Extend ( μ, var, expr ) = μ if var not in dom( μ ) and expr( μ ) is an error

Extend is undefined if var in dom( μ ).

Extend ( Ω, var, expr ) = { Extend ( μ, var, expr ) | μ in Ω }

Write [ x | C ] for a sequence of elements where C is a condition on x.

Definition: ToList

Let Ω be a multiset of solution mappings. We define:

ToList ( Ω ) = a sequence of mappings μ in Ω in any order, with multiplicity ( μ | Ω ) occurrences of μ

multiplicity ( μ | ToList ( Ω ) ) = multiplicity ( μ | Ω )

Definition: OrderBy

Let Ψ be a sequence of solution mappings. We define:

OrderBy ( Ψ, condition) = [ μ | μ in Ψ and the sequence satisfies the ordering condition]

multiplicity ( μ | OrderBy ( Ψ, condition) ) = multiplicity ( μ | Ψ )

Definition: Project

Let Ψ be a sequence of solution mappings and PV a set of variables.

For mapping μ, write Proj( μ, PV ) to be the restriction of μ to variables in PV.

Project ( Ψ, PV ) = [ Proj( μ, PV ) | μ in Ψ ]

multiplicity ( μ | Project ( Ψ, PV ) ) = sum( multiplicity ( μ' | Ψ ) | μ' in Ψ such that μ' = Proj( μ, PV ) )

The order of Project ( Ψ, PV ) must preserve any ordering given by OrderBy .

Definition: Distinct

Let Ψ be a sequence of solution mappings. We define:

Distinct ( Ψ ) = [ μ | μ in Ψ ]

multiplicity ( μ | Distinct ( Ψ ) ) = 1 for every μ ∈ Distinct ( Ψ )

multiplicity ( μ | Distinct ( Ψ ) ) = 0 for every μ ∉ Distinct ( Ψ )

The order of Distinct ( Ψ ) must preserve any ordering given by OrderBy .

Definition: Reduced

Let Ψ be a sequence of solution mappings. We define:

Reduced ( Ψ ) = [ μ | μ in Ψ ]

multiplicity ( μ | Reduced ( Ψ ) ) is between 1 and multiplicity ( μ | Ψ ) for every μ ∈ Reduced ( Ψ )

multiplicity ( μ | Reduced ( Ψ ) ) = 0 for every μ ∉ Reduced ( Ψ )

The order of Reduced ( Ψ ) must preserve any ordering given by OrderBy .

The Reduced solution sequence modifier does not guarantee a defined multiplicity.

Definition: Slice

Let Ψ be a sequence of solution mappings. We define:

Slice ( Ψ, start, length )[ i ] = Ψ [ start + i ] for i = 0 to ( length -1)

Definition: ToMultiSet

Let Ψ be a solution sequence. We define:

ToMultiSet ( Ψ ) = { μ | μ in Ψ }

multiplicity ( μ | ToMultiSet ( Ψ ) ) = multiplicity ( μ | Ψ )

Definition: Exists

exists(pattern) is a function that returns true if the pattern evaluates to a non-empty solution sequence, given the current solution mapping and active graph at the time of evaluation; otherwise it returns false.

Group is a function which groups a solution sequence into multiple solutions, based on some attribute of the solutions.

Definition: Group

Group evaluates a list of expressions against a solution sequence Ψ, producing a partial function from keys to solution sequences.

Group ( exprlist, Ψ ) = { ListEval ( exprlist, μ ) → [ μ' | μ' in Ψ such that ListEval ( exprlist, μ' ) and ListEval ( exprlist, μ ) are the same ] | μ in Ψ },

where two lists L and L' (as produced by the ListEval function) are considered the same iff they have the same number of elements and, for every position k within the two lists, either of the following two conditions is true:

the element at the k -th position of L is an RDF term; the element at the k -th position of L' is also an RDF term; and these two RDF terms are the same term
the element at the k -th position of L is an error, and the element at the k -th position of L' is also an error

Definition: ListEval

ListEval (( expr ₁, ..., expr _n ), μ ) returns a list ( e ₁, ..., e _n ), where e _i = expr _i ( μ ) or error.

ListEval retains errors resulting from the evaluation of the list elements.

Note that, although the result of ListEval may contain errors, and errors may be used to group, solutions containing error values are removed at the end of evaluating the group and any aggregation functions.

Note also that the result of ListEval ((unbound), μ ) is the list (error), as the evaluation of an unbound expression is an error.

Aggregation , a function which calculates a scalar value as an output of the aggregate expression. It is used in the SELECT clause, the HAVING evaluation process, and in ORDER BY (where required). Aggregation calculates aggregated values over groups of solutions, using set functions.

Definition: Aggregation

Let exprlist be a list of expressions or * ; func, a set function; scalarvals, a partial function (possibly with an empty domain) passed from the aggregate in the query; and { key ₁ → Ψ ₁, ..., key _m → Ψ _m }, a partial function from keys to solution sequences as produced by the grouping step.

Aggregation applies the set function func to the given set and produces a single value for each key and a group of solutions for that key.

Aggregation ( exprlist, func, scalarvals, { key ₁ → Ψ ₁, ..., key _m → Ψ _m } )
= { ( key, F ( Ψ )) | key → Ψ in { key ₁ → Ψ ₁, ..., key _m → Ψ _m } }

where
  M( Ψ ) = [ ListEval ( exprlist, μ ) | μ in Ψ ]
  F( Ψ ) = func (M( Ψ ), scalarvals ), for non- DISTINCT
  F( Ψ ) = func (Dedup(M( Ψ )), scalarvals ), for DISTINCT

with Dedup(M( Ψ )) being an order-preserving, duplicate-free version of the sequence M( Ψ ); that is, Dedup(M( Ψ )) is a sequence of lists that has the following four properties (where each such list in this sequence may contain RDF terms and errors, as it is produced by the ListEval function).

For every list L in M( Ψ ) there exists a list L' in Dedup(M( Ψ )) such that L and L' are the same, where two lists L and L' from M( Ψ ) are considered the same as specified in the definition of the Group operator .
For every list L in Dedup(M( Ψ )) there exists a list L' in M( Ψ ) such that L and L' are the same.
Dedup(M( Ψ )) is free of duplicates. That is, the list at the i -th position in Dedup(M( Ψ )) is not the same list as the list at the j -th position in Dedup(M( Ψ )) for every two natural numbers i and j such that i ≠ j.
For any two lists L ₁ and L ₂ in Dedup(M( Ψ )), the relative order of their first occurrences in M( Ψ ) is preserved in Dedup(M( Ψ )). That is, if i ₁ < i ₂, then j ₁ < j ₂, where
- i ₁ is the smallest natural number such that L ₁ is at the i ₁ -th position in M( Ψ ),
- i ₂ is the smallest natural number such that L ₂ is at the i ₂ -th position in M( Ψ ),
- j ₁ is the position of L ₁ in Dedup(M( Ψ )), and
- j ₂ is the position of L ₂ in Dedup(M( Ψ )).

Special Case: when COUNT is used with the expression *, then F( Ψ ) is the cardinality of the group solution sequence, i.e., F( Ψ ) = Card ( Ψ ), or F( Ψ ) = Card ( Distinct ( Ψ )) if the DISTINCT keyword is present.

scalarvals are used to pass values to the underlying set function, bypassing the mechanics of the grouping. For example, the aggregate expression GROUP_CONCAT(?x ; separator="|") has a scalarvals argument of { "separator" → "|" }.

All aggregates may have the DISTINCT keyword as the first token in their argument list. If this keyword is present, then first argument to func is Dedup(M( Ψ )).

Example

Given a solution sequence Ψ with the following values:

solution	?x	?y	?z
`μ ₁`	1	2	3
`μ ₂`	1	3	4
`μ ₃`	2	5	6

And the query expression SELECT (ex:agg(?y, ?z) AS ?agg) WHERE { ?x ?y ?z } GROUP BY ?x.

We produce G = Group ((?x), Ψ ) = { (1) → [ μ ₁, μ ₂ ], (2) → [ μ ₃ ] }

And so Aggregation ((?y, ?z), ex:agg, {}, G ) =
{ ((1), eg:agg([(2, 3), (3, 4)], {})), ((2), eg:agg([(5, 6)], {})) }.

Definition: AggregateJoin

Let S ₁, ..., S _n be a list of sets, where each set S _i contains key to (aggregated) value maps as produced by Aggregation .

Let K = { key | key in dom( S _j ) for some 1 ≤ j ≤ n } be the set of keys, then
AggregateJoin ( S ₁, ..., S _n ) = { agg ₁ → val ₁, ..., agg _n → val _n | key in K and key → val _i in S _i for each 1 ≤ i ≤ n }

The set functions which underlie SPARQL aggregates all have a common signature: SetFunc( S ), or SetFunc( S, scalarvals ) where S is a sequence of lists, and scalarvals is one or more scalar values that are passed to the set function indirectly via the ( ... ; key=value ) syntax for aggregates in the SPARQL grammar. The only use of this that is supported by the built-in aggregates in SPARQL Query 1.1 is GROUP_CONCAT, as in GROUP_CONCAT(?x ; separator=", ").

Note that the name "Set Function" is somewhat historical — the arguments to set functions are in fact sequences. The name is retained due to the commonality with SQL Set Functions, which operate over multisets.

The set functions defined in this document are Count , Sum , Min , Max , Avg , GroupConcat , and Sample — corresponding to the aggregates COUNT, SUM, MIN, MAX, AVG, GROUP_CONCAT, and SAMPLE. Definitions may be found in the following sections. Systems may choose to expand this set using local extensions, using the same notation as for functions and casts. Note that, unless the ; separator is used this requires the parser to know whether some IRI refers to a function, cast, or aggregate before it can determine if there are any errors in a query where aggregates are used.

The definitions of the set functions in the following sections are based on two functions, Flatten and Card , which are defined as follows.

Flatten is a function which is used to collapse a sequence of lists into a single list. For example, [(1, 2), (3, 4)] becomes (1, 2, 3, 4).

Definition: Flatten

Let S be a sequence of lists, i.e., S = [ L ₁, L ₂, ..., L _m ] where, for every i ∈ {1, ..., m }, L _i is a list.

Flatten ( S ) is the list ( x | L in S and x in L ).

Card is a function that returns the cardinality of a sequence or a list of elements (which may be solution mappings or other types of elements, depending on the context).

Definition: Card

Given a sequence or a list L, Card ( L ) is the cardinality of L.

Count is a SPARQL set function which counts the number of times a given expression has a bound, non-error value within the aggregate group.

Definition: Count

xsd:integer

Count

(sequence

S

)

Count ( S ) = Card ( L' ),

where L' is the list L = Flatten ( S ) with all error elements removed.

Sum is a SPARQL set function that returns the numeric value obtained by summing the values within the aggregate group. Type promotion happens as per the op:numeric-add function, applied transitively, (see definition below) so the value of SUM(?x), in an aggregate group where ?x has values 1 (integer), 2.0e0 (float), and 3.0 (decimal) will be 6.0 (float).

Definition: Sum

numeric

Sum

(sequence

S

)

Sum ( S ) = SumList ( L ),

where L = Flatten ( S ) and SumList ( L ) is defined recursively as follows.

If Card ( L ) = 0, then SumList ( L ) = "0"^^ xsd:integer.
If Card ( L ) = 1, then SumList ( L ) = op:numeric-add ( L ₁, 0).
If Card ( L ) > 1, then SumList ( L ) = op:numeric-add ( L ₁, SumList ( L _2..n )).

Note that L ₁ is the first element in L, and L _2..n is L without its first element.

In this way, Sum ( [(1), (2), (3)] ) = SumList ( (1, 2, 3) ) = op:numeric-add(1, op:numeric-add(2, op:numeric-add(3, 0))).

The Avg set function calculates the average value for an expression over a group. It is defined in terms of Sum and Count.

Definition: Avg

numeric

Avg

(sequence

S

)

If Count ( S ) = 0, then Avg ( S ) = "0"^^ xsd:integer.

If Count ( S ) > 0, then Avg ( S ) = Sum ( S ) / Count ( S ).

For example, Avg ([(1), (2), (3)]) = Sum ([(1), (2), (3)])/ Count ([(1), (2), (3)]) = 6/3 = 2.

Min is a SPARQL set function that returns the minimum value from a group respectively.

It makes use of the SPARQL ORDER BY ordering definition, to allow ordering over arbitrarily typed expressions.

Definition: Min

term

Min

(sequence

S

)

Min ( S ) = MinList ( L ),

where L is the list of values obtained by Flatten ( S ) and then ordered as per the ORDER BY ASC clause, and MinList ( L ) is defined as follows.

If Card ( L ) = 0, then MinList ( L ) = error.
If Card ( L ) > 0, then MinList ( L ) = L ₁, where L ₁ is the first element in L.

Max is a SPARQL set function that returns the maximum value from a group respectively.

It makes use of the SPARQL ORDER BY ordering definition, to allow ordering over arbitrarily typed expressions.

Definition: Max

term

Max

(sequence

S

)

Max ( S ) = MaxList ( L ),

where L is the list of values obtained by Flatten ( S ) and then ordered as per the ORDER BY DESC clause, and MaxList ( L ) is defined as follows.

If Card ( L ) = 0, then MaxList ( L ) = error.
If Card ( L ) > 0, then MaxList ( L ) = L ₁, where L ₁ is the first element in L.

GroupConcat is a set function which performs a string concatenation across the values of an expression with a group. The order of the strings is not specified. The separator character used in the concatenation may be given with the scalar argument SEPARATOR.

Definition: GroupConcat

literal

GroupConcat

(sequence

S
,
function

scalarvals

)

If the scalarvals argument is absent from GROUP_CONCAT, then scalarvals is taken to be the empty function.

Let sep be a string that is defined as follows.

If scalarvals is defined for the argument "separator", then sep = scalarvals ("separator").
If scalarvals is undefined for the argument "separator", then sep is the "space" character (i.e., unicode codepoint U+0020).

GroupConcat ( S, scalarvals ) = GCList ( L, sep ),

where L = Flatten ( S ) and GCList ( L, sep ) is defined recursively as follows.

If Card ( L ) = 0, then GCList ( L, sep ) = "".
If Card ( L ) = 1, then GCList ( L, sep ) = CONCAT ("", L ₁ ).
If Card ( L ) > 1, then GCList ( L, sep ) = CONCAT ( L ₁, sep, GCList ( L _2..n, sep )).

Note that L ₁ is the first element in L, and L _2..n is L without its first element.

For example, GroupConcat ([("a"), ("b"), ("c")], {"separator" → "."}) = GCList ( ("a", "b", "c"), "." ) = "a.b.c".

Sample is a set function which returns an arbitrary value from the sequence passed to it.

Definition: Sample

RDFTerm

Sample

(sequence

S

)

If Card ( S ) = 0, then Sample ( S ) = error.

If Card ( S ) > 0, then Sample ( S ) = v, where v in Flatten ( S ).

For example, given Sample ([("a"), ("b"), ("c")]), "a", "b", and "c" are all valid return values. Note that the Sample function is not required to be deterministic for a given input. The only restriction is that the output value must be present in the input sequence.

We define eval ( D ( G ), A ) as the evaluation of an algebraic query expression A with respect to a dataset D having active graph G. The active graph is initially the default graph of D. Further symbols used in the following definitions are:

P, P ₁, P ₂ : graph patterns
L : a solution sequence
F : an expression

Issue 225 : eval function undefined for multisets and sequences of solution mappings spec:bug

The definitions in this section do not cover the cases in which A is a sequence or a multiset of solution mappings.

Definition: Evaluation of a Basic Graph Pattern

eval ( D ( G ), BGP ) = multiset of solution mappings

See section Basic Graph Patterns

Definition: Evaluation of a Property Path Pattern

eval ( D ( G ), Path ( X, path, Y ) ) = multiset of solution mappings

See section Property Path Patterns

Definition: Evaluation of Filter

eval ( D ( G ), Filter ( F, P ) ) = Filter ( F, eval ( D ( G ), P ), D (, G ) )

'substitute' is a filter function in support of the evaluation of EXISTS and NOT EXISTS forms which were translated to exists.

Definition: Substitute

Let μ be a solution mapping.

substitute( pattern, μ ) = the pattern formed by replacing every occurrence of a variable v in pattern by μ ( v ) for each v in dom( μ )

Definition: Evaluation of Exists

Let μ be the current solution mapping for a filter and P a graph pattern:

The value exists( P ), given D ( G ) is true if and only if eval ( D ( G ), substitute( P, μ )) is a non-empty sequence.

Definition: Evaluation of Join

eval ( D ( G ), Join ( P ₁, P ₂ ) ) = Join ( eval ( D ( G ), P ₁ ), eval ( D ( G ), P ₂ ) )

Definition: Evaluation of LeftJoin

eval ( D ( G ), LeftJoin ( P ₁, P ₂, F ) ) = LeftJoin ( eval ( D ( G ), P ₁ ), eval ( D ( G ), P ₂ ), F )

Definition: Evaluation of Union

eval ( D ( G ), Union ( P ₁, P ₂ ) ) = Union ( eval ( D ( G ), P ₁ ), eval ( D ( G ), P ₂ ) )

Definition: Evaluation of Graph

For every x that is an IRI or a variable , eval ( D ( G ), Graph ( x, P ) ) is defined as follows:

If x is an IRI that is a graph name in D,
eval ( D ( G ), Graph ( x, P ) ) = eval ( D ( G _x ), P ),
where G _x is the RDF graph of the named graph with name x in D.
If x is an IRI that is not a graph name in D,
eval ( D ( G ), Graph ( x, P ) ) is the empty multiset.

If x is a variable,

eval ( D ( G ), Graph ( x, P ) ) = Ω,

where Ω is the multiset of solution mappings produced by the following algorithm:

Ω := the empty multiset
for each graph name gn in D (recall that a graph name may be an IRI or a blank node)
    G' := the RDF graph of the named graph with name gn in D
    Ω' := eval( D(G'), P )
    Ω := Union( Ω, Join(Ω', μ) ), where μ = {x → gn}
the
result
is

Ω

Definition: Evaluation of Group

eval ( D ( G ), Group ( exprlist, P ) ) = Group ( exprlist, eval ( D ( G ), P ) )

Definition: Evaluation of Aggregation

eval ( D ( G ), Aggregation ( exprlist, func, scalarvals, Grp ) ) = Aggregation ( exprlist, func, scalarvals, eval ( D ( G ), Grp ) )

Definition: Evaluation of AggregateJoin

eval ( D ( G ), AggregateJoin ( A ₁, ..., A _n ) ) = AggregateJoin ( eval ( D ( G ), A ₁ ), ..., eval ( D ( G ), A _n ) )

Note that if eval ( D ( G ), A _i ) is an error, it is ignored.

Definition: Evaluation of Extend

eval ( D ( G ), Extend ( P, var, expr ) ) = Extend ( eval ( D ( G ), P ), var, expr )

Definition: Evaluation of ToList

eval ( D ( G ), ToList ( P ) ) = ToList ( eval ( D ( G ), P ) )

Definition: Evaluation of Distinct

eval ( D ( G ), Distinct ( L ) ) = Distinct ( eval ( D ( G ), L ) )

Definition: Evaluation of Reduced

eval ( D ( G ), Reduced ( L ) ) = Reduced ( eval ( D ( G ), L ) )

Definition: Evaluation of Project

eval ( D ( G ), Project ( L, vars ) ) = Project ( eval ( D ( G ), L ), vars )

Definition: Evaluation of OrderBy

eval ( D ( G ), OrderBy ( L, condition ) ) = OrderBy ( eval ( D ( G ), L ), condition )

Definition: Evaluation of ToMultiSet

eval ( D ( G ), ToMultiset ( L ) ) = ToMultiSet ( eval ( D ( G ), L ) )

Definition: Evaluation of Slice

eval ( D ( G ), Slice ( L, start, length ) ) = Slice ( eval ( D ( G ), L ), start, length )

The overall SPARQL design can be used for queries which assume a more elaborate form of entailment than simple entailment, by re-writing the matching conditions for basic graph patterns. Since it is an open research problem to state such conditions in a single general form which applies to all forms of entailment and optimally eliminates needless or inappropriate redundancy, this document only gives necessary conditions which any such solution should satisfy. These will need to be extended to full definitions for each particular case.

Basic graph patterns stand in the same relation to triple patterns that RDF graphs do to RDF triples, and much of the same terminology can be applied to them. In particular, two basic graph patterns are said to be equivalent if there is a bijection M between the terms of the triple patterns that maps blank nodes to blank nodes and maps variables, literals and IRIs to themselves, such that a triple ( s, p, o ) is in the first pattern if and only if the triple ( M(s), M(p), M(o) ) is in the second. This definition extends that for RDF graph equivalence to basic graph patterns by preserving variable names across equivalent patterns.

An entailment regime specifies

a subset of RDF graphs called well-formed for the regime
an entailment relation between subsets of well-formed graphs and well-formed graphs.

Detailed definitions for querying various entailment regimes can be found in SPARQL 1.1 Entailment Regimes .

Some entailment regimes can categorize some RDF graphs as inconsistent. For example, the RDF graph:

_:x rdf:type xsd:string .
_:x
rdf:type
xsd:decimal
.

is D-inconsistent when D contains the XSD datatypes. The effect of a query on an inconsistent graph is not covered by this specification, but must be specified by the particular SPARQL extension.

An entailment regime E must provide conditions on basic graph pattern evaluation such that for any basic graph pattern BGP, any RDF graph G, and any evaluation that satisfies the conditions, the resulting multiset of solutions is uniquely determined up to RDF graph equivalence. We denote the multiset of solutions from evaluating BGP over G using E with Eval-E(G, BGP).
An entailment regime must further satisfy the following conditions:

For any E-consistent active graph AG, the entailment regime E uniquely specifies a scoping graph SG that is E-equivalent to AG.
A set of well-formed graphs for E is specified such that, for any basic graph pattern BGP, scoping graph SG, and solution mapping μ in Eval-E(SG, BGP), the graph μ(BGP) is well-formed for E.
For any basic graph pattern BGP and scoping graph SG, if μ ₁, ..., μ _n in Eval-E(SG, BGP) and BGP ₁, ..., BGP _n are basic graph patterns all equivalent to BGP but not sharing any blank nodes with each other or with SG, then

SG E-entails (SG union μ ₁ (BGP ₁ ) union ... union μ _n (BGP _n ))

These conditions do not fully determine the set of possible answers, since RDF allows unlimited amounts of redundancy. In addition, therefore, the following must hold.
Entailment regimes should provide conditions to prevent trivial infinite solution multisets as appropriate to the regime.

(a) SG will often be graph equivalent to AG, but restricting this to E-equivalence allows some forms of normalization, for example elimination of semantic redundancies, to be applied to the source documents before querying.

(b) The construction in condition 3 ensures that any blank nodes introduced by the solution mapping are used in a way which is internally consistent with the way that blank nodes occur in SG. This ensures that blank node identifiers occur in more than one answer in an answer set only when the blank nodes so identified are indeed identical in SG. If the extension does not allow bindings to blank nodes, then this condition can be simplified to the condition:

SG E-entails μ(BGP) for each solution mapping μ.

(c) These conditions do not impose the SPARQL requirement that SG shares no blank nodes with AG or BGP. In particular, it allows SG to actually be AG. This allows query protocols in which blank node identifiers retain their meaning between the query and the source document, or across multiple queries. Such protocols are not supported by the current SPARQL protocol specification, however.

(d) Since conditions 1 to 3 are only necessary conditions on answers, condition 4 allows cases where the set of legal answers can be restricted in various ways.

(e) None of these conditions refer explicitly to instance mappings on blank nodes in BGP. For some entailment regimes, the existential interpretation of blank nodes cannot be fully captured by the existence of a single instance mapping. These conditions allow such regimes to give blank nodes in query patterns a 'fully existential' reading.

It is straightforward to show that SPARQL satisfies these conditions for the case where E is simple entailment, given that the SPARQL condition on SG is that it is graph-equivalent to AG but shares no blank nodes with AG or BGP (which satisfies the first condition). The only condition which is nontrivial is (3).

For every solution mapping μ _i, there is, by definition of basic graph pattern matching, an RDF instance mapping σ _i such that P _i (BGP _i ) is a subgraph of SG where P _i is the pattern instance mapping composed of μ _i and σ _i. Since BGP _i and SG have no blank nodes in common, the ranges of σ _i and μ _i contain no blank nodes from BGP _i ; therefore, the solution mapping μ _i and the RDF instance mapping σ _i of P _i commute, so P _i (BGP _i ) = σ _i (μ _i (BGP _i )). So

P ₁ (BGP ₁ ) union ... union P _n (BGP _n )
= σ ₁ (μ ₁ (BGP ₁ )) union ... union σ _n (μ _n (BGP _n ))
= [ σ ₁ + ... + σ _n ]( μ ₁ (BGP ₁ ) union ... union μ _n (BGP _n ) )

since the domains of the σ _i RDF instance mappings are all mutually exclusive. Since they are also exclusive from SG,

SG union [ σ ₁ + ... + σ _n ]( μ ₁ (BGP ₁ ) union ... union μ _n (BGP _n ) )
= [ σ ₁ + ... + σ _n ](SG union μ ₁ (BGP ₁ ) union ... union μ _n (BGP _n ) )

i.e.

SG union μ ₁ (BGP ₁ ) union ... union μ _n (BGP _n )

has an instance which is a subgraph of SG, so is simply entailed by SG by the RDF interpolation lemma [ RDF12-SEMANTICS ].

The SPARQL grammar covers both SPARQL Query and SPARQL 1.1 Update .

A SPARQL string is an RDF string that conforms to the grammar given in this section.

Note

An RDF string is a sequence of Unicode code points which are Unicode scalar values . Unicode scalar values do not include the surrogate code points .

A SPARQL query string is a SPARQL string that conforms to the grammar starting at the QueryUnit production.

A SPARQL update string is a SPARQL string that conforms to the grammar starting at the UpdateUnit production.

For compatibility with future versions of Unicode, the characters in this string may include Unicode codepoints that are unassigned as of the date of this publication (see Unicode Identifiers and Syntax [ UAX31 ] section 4 Pattern Syntax). For productions with excluded character classes (for example [^<>'{}|^`] ), the characters are excluded from the range #x0 - #x10FFFF.

A SPARQL string is processed for codepoint escape sequences before parsing by the grammar defined in EBNF below. The codepoint escape sequences for a SPARQL query string are:

Escape	Unicode code point
'\u' HEX HEX HEX HEX	A Unicode code point in the range U+0 to U+FFFF inclusive corresponding to the encoded hexadecimal value, excluding U+D800 to U+DFFF, the surrogate code points .
'\U' HEX HEX HEX HEX HEX HEX HEX HEX	A Unicode code point in the range U+0 to U+10FFFF inclusive corresponding to the encoded hexadecimal value, excluding U+D800 to U+DFFF, the surrogate code points .

where HEX is a hexadecimal character

HEX ::= [0-9] | [A-F] | [a-f]

Examples:

<ab\u00E9xy>        # Codepoint 00E9 is Latin small e with acute - é
\u03B1:a            # Codepoint x03B1 is Greek small alpha - α
a\u003Ab
#
a:b
--
codepoint
x3A
is
colon

Codepoint escape sequences can appear anywhere in the query string. They are processed before parsing based on the grammar rules and so may be replaced by codepoints with significance in the grammar, such as " : " marking a prefixed name.

These escape sequences are not included in the grammar below. Only escape sequences for characters that would be legal at that point in the grammar may be given. For example, the variable " ?x\u0020y " is not legal ( \u0020 is a space and is not permitted in a variable name).

White space (production WS ) is used to separate two terminals which would otherwise be (mis-)recognized as one terminal. Rule names below in capitals indicate where white space is significant; these form a possible choice of terminals for constructing a SPARQL parser. White space is significant in strings. Otherwise, white space is ignored between tokens.

For example:

?a<?b&&?c>?d

is the token sequence variable ' ?a ', an IRI ' <?b&&?c> ', and variable ' ?d ', not a expression involving the operator ' && ' connecting two expression using ' < ' (less than) and ' > ' (greater than).

Comments in SPARQL queries take the form of ' # ', outside an IRI or string, and continue to the end of line (marked by characters 0x0D or 0x0A ) or end of file if there is no end of line after the comment marker. Comments are treated as white space.

Text matched by the IRIREF production and PrefixedName (after prefix expansion) production, after escape processing, must conform to the generic syntax of IRI references in section 2.2 of RFC 3987 "ABNF for IRI References and IRIs" [ RFC3987 ]. For example, the IRIREF <abc#def> may occur in a SPARQL query string, but the IRIREF <abc##def> must not.

Base IRIs declared with the BASE keyword must be absolute IRIs. A prefix declared with the PREFIX keyword may not be re-declared in the same query. See section 4.1.1, Syntax of IRI Terms , for a description of BASE and PREFIX .

Blank nodes can not be used in:

DELETE WHERE
DELETE DATA
a DeleteClause

in a SPARQL update request .

Blank node identifiers are scoped to the SPARQL string in which they occur. Different uses of the same blank node identifier in a request string refer to the same blank node. Fresh blank nodes are generated for each request; blank nodes can not be referenced by identifier across requests.

The same blank node identifier can not be used in:

two separate basic graph patterns in a SPARQL Query
two WHERE clauses within a single SPARQL update request
two INSERT DATA operations within a single SPARQL update request

Note that the same blank node identifier can occur in different QuadPattern clauses in a SPARQL 1.1 Update request.

In addition to the codepoint escape sequences , the following escape sequences apply to any string production (e.g. STRING_LITERAL1, STRING_LITERAL2, STRING_LITERAL_LONG1, STRING_LITERAL_LONG2 ):

Escape	Unicode code point
'\t'	U+0009 (tab)
'\n'	U+000A (line feed)
'\r'	U+000D (carriage return)
'\b'	U+0008 (backspace)
'\f'	U+000C (form feed)
'\"'	U+0022 (quotation mark, double quote mark)
"\'"	U+0027 (apostrophe-quote, single quote mark)
'\\'	U+005C (backslash)

Examples:

"abc\n"
"xy\rz"
'xy\tz'

The EBNF notation used in the grammar is defined in Extensible Markup Language (XML) 1.1 [ XML11 ] section 6 Notation .

Notes:

Keywords are matched in a case-insensitive manner with the exception of the keyword ' a ' which, in line with Turtle and N3, is used in place of the IRI rdf:type (in full, http://www.w3.org/1999/02/22-rdf-syntax-ns#type ).
Escape sequences are case sensitive.
When tokenizing the input and choosing grammar rules, the longest match is chosen.
The SPARQL grammar is LL(1) when the rules with uppercased names are used as terminals.
There are two entry points into the grammar: QueryUnit for the SPARQL query language and UpdateUnit for the SPARQL update language.
In signed numbers, no white space is allowed between the sign and the number. The AdditiveExpression grammar rule allows for this by covering the two cases of an expression followed by a signed number. These produce an addition or subtraction of the unsigned number as appropriate.
The tokens INSERT DATA, DELETE DATA and DELETE WHERE allow any amount of white space between the words. The single space version is used in the grammar for clarity.
The QuadData and QuadPattern rules both use rule Quads. The rule QuadData, used in INSERTDATA and DELETE DATA , must not allow variables in the quad patterns.
Blank node syntax is not allowed in DELETE WHERE, the DeleteClause for DELETE, nor in DELETE DATA.
Rules for limiting the use of blank node identifiers are given in section 19.6 .
The number of variables in the variable list of VALUES block must be the same as the number of each list of associated values in the DataBlock.
Variables introduced by AS in a SELECT clause must not already be in-scope .
The variable assigned in a BIND clause must not be already in-use within the immediately preceding TriplesBlock within a GroupGraphPattern.
Aggregate functions can be one of the built-in keywords for aggregates or a custom aggregate, which is syntactically a function call . Aggregate functions may only be used in SELECT , HAVING and ORDER BY clauses.
The expression argument of an aggregate function can not contain an aggregate function.
Only custom aggregate functions use the DISTINCT keyword in a function call .
A reifier or annotation syntax is only permitted after a triple when the property position is a simple path (an IRI, the keyword a, or a variable), and not for other path expressions.

`[1]`	`QueryUnit`	::=	`Query`
`[2]`	`Query`	::=	`Prologue ( SelectQuery \| ConstructQuery \| DescribeQuery \| AskQuery ) ValuesClause`
`[3]`	`UpdateUnit`	::=	`Update`
`[4]`	`Prologue`	::=	`( BaseDecl \| PrefixDecl \| VersionDecl )*`
`[5]`	`BaseDecl`	::=	`'BASE' IRIREF`
`[6]`	`PrefixDecl`	::=	`'PREFIX' PNAME_NS IRIREF`
`[7]`	`VersionDecl`	::=	`'VERSION' VersionSpecifier`
`[8]`	`VersionSpecifier`	::=	`STRING_LITERAL1 \| STRING_LITERAL2`
`[9]`	`SelectQuery`	::=	`SelectClause DatasetClause * WhereClause SolutionModifier`
`[10]`	`SubSelect`	::=	`SelectClause WhereClause SolutionModifier ValuesClause`
`[11]`	`SelectClause`	::=	`'SELECT' ( 'DISTINCT' \| 'REDUCED' )? ( ( Var \| ( '(' Expression 'AS' Var ')' ) )+ \| '*' )`
`[12]`	`ConstructQuery`	::=	`'CONSTRUCT' ( ConstructTemplate DatasetClause * WhereClause SolutionModifier \| DatasetClause * 'WHERE' '{' TriplesTemplate ? '}' SolutionModifier )`
`[13]`	`DescribeQuery`	::=	`'DESCRIBE' ( VarOrIri + \| '' ) DatasetClause WhereClause ? SolutionModifier`
`[14]`	`AskQuery`	::=	`'ASK' DatasetClause * WhereClause SolutionModifier`
`[15]`	`DatasetClause`	::=	`'FROM' ( DefaultGraphClause \| NamedGraphClause )`
`[16]`	`DefaultGraphClause`	::=	`SourceSelector`
`[17]`	`NamedGraphClause`	::=	`'NAMED' SourceSelector`
`[18]`	`SourceSelector`	::=	`iri`
`[19]`	`WhereClause`	::=	`'WHERE' ? GroupGraphPattern`
`[20]`	`SolutionModifier`	::=	`GroupClause ? HavingClause ? OrderClause ? LimitOffsetClauses ?`
`[21]`	`GroupClause`	::=	`'GROUP' 'BY' GroupCondition +`
`[22]`	`GroupCondition`	::=	`BuiltInCall \| FunctionCall \| '(' Expression ( 'AS' Var )? ')' \| Var`
`[23]`	`HavingClause`	::=	`'HAVING' HavingCondition +`
`[24]`	`HavingCondition`	::=	`Constraint`
`[25]`	`OrderClause`	::=	`'ORDER' 'BY' OrderCondition +`
`[26]`	`OrderCondition`	::=	`( ( 'ASC' \| 'DESC' ) BrackettedExpression ) \| ( Constraint \| Var )`
`[27]`	`LimitOffsetClauses`	::=	`LimitClause OffsetClause ? \| OffsetClause LimitClause ?`
`[28]`	`LimitClause`	::=	`'LIMIT' INTEGER`
`[29]`	`OffsetClause`	::=	`'OFFSET' INTEGER`
`[30]`	`ValuesClause`	::=	`( 'VALUES' DataBlock )?`
`[31]`	`Update`	::=	`Prologue ( Update1 ( ';' Update )? )?`
`[32]`	`Update1`	::=	`Load \| Clear \| Drop \| Add \| Move \| Copy \| Create \| DeleteWhere \| Modify \| InsertData \| DeleteData`
`[33]`	`Load`	::=	`'LOAD' 'SILENT' ? iri ( 'INTO' GraphRef )?`
`[34]`	`Clear`	::=	`'CLEAR' 'SILENT' ? GraphRefAll`
`[35]`	`Drop`	::=	`'DROP' 'SILENT' ? GraphRefAll`
`[36]`	`Create`	::=	`'CREATE' 'SILENT' ? GraphRef`
`[37]`	`Add`	::=	`'ADD' 'SILENT' ? GraphOrDefault 'TO' GraphOrDefault`
`[38]`	`Move`	::=	`'MOVE' 'SILENT' ? GraphOrDefault 'TO' GraphOrDefault`
`[39]`	`Copy`	::=	`'COPY' 'SILENT' ? GraphOrDefault 'TO' GraphOrDefault`
`[40]`	`InsertData`	::=	`'INSERT DATA' QuadData`
`[41]`	`DeleteData`	::=	`'DELETE DATA' QuadData`
`[42]`	`DeleteWhere`	::=	`'DELETE WHERE' QuadPattern`
`[43]`	`Modify`	::=	`( 'WITH' iri )? ( DeleteClause InsertClause ? \| InsertClause ) UsingClause * 'WHERE' GroupGraphPattern`
`[44]`	`DeleteClause`	::=	`'DELETE' QuadPattern`
`[45]`	`InsertClause`	::=	`'INSERT' QuadPattern`
`[46]`	`UsingClause`	::=	`'USING' ( iri \| 'NAMED' iri )`
`[47]`	`GraphOrDefault`	::=	`'DEFAULT' \| 'GRAPH' ? iri`
`[48]`	`GraphRef`	::=	`'GRAPH' iri`
`[49]`	`GraphRefAll`	::=	`GraphRef \| 'DEFAULT' \| 'NAMED' \| 'ALL'`
`[50]`	`QuadPattern`	::=	`'{' Quads '}'`
`[51]`	`QuadData`	::=	`'{' Quads '}'`
`[52]`	`Quads`	::=	`TriplesTemplate ? ( QuadsNotTriples '.' ? TriplesTemplate ? )*`
`[53]`	`QuadsNotTriples`	::=	`'GRAPH' VarOrIri '{' TriplesTemplate ? '}'`
`[54]`	`TriplesTemplate`	::=	`TriplesSameSubject ( '.' TriplesTemplate ? )?`
`[55]`	`GroupGraphPattern`	::=	`'{' ( SubSelect \| GroupGraphPatternSub ) '}'`
`[56]`	`GroupGraphPatternSub`	::=	`TriplesBlock ? ( GraphPatternNotTriples '.' ? TriplesBlock ? )*`
`[57]`	`TriplesBlock`	::=	`TriplesSameSubjectPath ( '.' TriplesBlock ? )?`
`[58]`	`ReifiedTripleBlock`	::=	`ReifiedTriple PropertyList`
`[59]`	`ReifiedTripleBlockPath`	::=	`ReifiedTriple PropertyListPath`
`[60]`	`GraphPatternNotTriples`	::=	`GroupOrUnionGraphPattern \| OptionalGraphPattern \| MinusGraphPattern \| GraphGraphPattern \| ServiceGraphPattern \| Filter \| Bind \| InlineData`
`[61]`	`OptionalGraphPattern`	::=	`' OPTIONAL ' GroupGraphPattern`
`[62]`	`GraphGraphPattern`	::=	`'GRAPH' VarOrIri GroupGraphPattern`
`[63]`	`ServiceGraphPattern`	::=	`'SERVICE' 'SILENT' ? VarOrIri GroupGraphPattern`
`[64]`	`Bind`	::=	`'BIND' '(' Expression 'AS' Var ')'`
`[65]`	`InlineData`	::=	`'VALUES' DataBlock`
`[66]`	`DataBlock`	::=	`InlineDataOneVar \| InlineDataFull`
`[67]`	`InlineDataOneVar`	::=	`Var '{' DataBlockValue * '}'`
`[68]`	`InlineDataFull`	::=	`( NIL \| '(' Var * ')' ) '{' ( '(' DataBlockValue * ')' \| NIL )* '}'`
`[69]`	`DataBlockValue`	::=	`iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| 'UNDEF' \| TripleTermData`
`[70]`	`Reifier`	::=	`'~' VarOrReifierId ?`
`[71]`	`VarOrReifierId`	::=	`Var \| iri \| BlankNode`
`[72]`	`MinusGraphPattern`	::=	`'MINUS' GroupGraphPattern`
`[73]`	`GroupOrUnionGraphPattern`	::=	`GroupGraphPattern ( 'UNION' GroupGraphPattern )*`
`[74]`	`Filter`	::=	`'FILTER' Constraint`
`[75]`	`Constraint`	::=	`BrackettedExpression \| BuiltInCall \| FunctionCall`
`[76]`	`FunctionCall`	::=	`iri ArgList`
`[77]`	`ArgList`	::=	`NIL \| '(' 'DISTINCT' ? Expression ( ',' Expression )* ')'`
`[78]`	`ExpressionList`	::=	`NIL \| '(' Expression ( ',' Expression )* ')'`
`[79]`	`ConstructTemplate`	::=	`'{' ConstructTriples ? '}'`
`[80]`	`ConstructTriples`	::=	`TriplesSameSubject ( '.' ConstructTriples ? )?`
`[81]`	`TriplesSameSubject`	::=	`VarOrTerm PropertyListNotEmpty \| TriplesNode PropertyList \| ReifiedTripleBlock`
`[82]`	`PropertyList`	::=	`PropertyListNotEmpty ?`
`[83]`	`PropertyListNotEmpty`	::=	`Verb ObjectList ( ';' ( Verb ObjectList )? )*`
`[84]`	`Verb`	::=	`VarOrIri \| 'a'`
`[85]`	`ObjectList`	::=	`Object ( ',' Object )*`
`[86]`	`Object`	::=	`GraphNode Annotation`
`[87]`	`TriplesSameSubjectPath`	::=	`VarOrTerm PropertyListPathNotEmpty \| TriplesNodePath PropertyListPath \| ReifiedTripleBlockPath`
`[88]`	`PropertyListPath`	::=	`PropertyListPathNotEmpty ?`
`[89]`	`PropertyListPathNotEmpty`	::=	`( VerbPath \| VerbSimple ) ObjectListPath ( ';' ( ( VerbPath \| VerbSimple ) ObjectListPath )? )*`
`[90]`	`VerbPath`	::=	`Path`
`[91]`	`VerbSimple`	::=	`Var`
`[92]`	`ObjectListPath`	::=	`ObjectPath ( ',' ObjectPath )*`
`[93]`	`ObjectPath`	::=	`GraphNodePath AnnotationPath`
`[94]`	`Path`	::=	`PathAlternative`
`[95]`	`PathAlternative`	::=	`PathSequence ( '\|' PathSequence )*`
`[96]`	`PathSequence`	::=	`PathEltOrInverse ( '/' PathEltOrInverse )*`
`[97]`	`PathElt`	::=	`PathPrimary PathMod ?`
`[98]`	`PathEltOrInverse`	::=	`PathElt \| '^' PathElt`
`[99]`	`PathMod`	::=	`'?' \| '*' \| '+'`
`[100]`	`PathPrimary`	::=	`iri \| 'a' \| '!' PathNegatedPropertySet \| '(' Path ')'`
`[101]`	`PathNegatedPropertySet`	::=	`PathOneInPropertySet \| '(' ( PathOneInPropertySet ( '\|' PathOneInPropertySet )* )? ')'`
`[102]`	`PathOneInPropertySet`	::=	`iri \| 'a' \| '^' ( iri \| 'a' )`
`[103]`	`TriplesNode`	::=	`Collection \| BlankNodePropertyList`
`[104]`	`BlankNodePropertyList`	::=	`'[' PropertyListNotEmpty ']'`
`[105]`	`TriplesNodePath`	::=	`CollectionPath \| BlankNodePropertyListPath`
`[106]`	`BlankNodePropertyListPath`	::=	`'[' PropertyListPathNotEmpty ']'`
`[107]`	`Collection`	::=	`'(' GraphNode + ')'`
`[108]`	`CollectionPath`	::=	`'(' GraphNodePath + ')'`
`[109]`	`AnnotationPath`	::=	`( Reifier \| AnnotationBlockPath )*`
`[110]`	`AnnotationBlockPath`	::=	`'{\|' PropertyListPathNotEmpty '\|}'`
`[111]`	`Annotation`	::=	`( Reifier \| AnnotationBlock )*`
`[112]`	`AnnotationBlock`	::=	`'{\|' PropertyListNotEmpty '\|}'`
`[113]`	`GraphNode`	::=	`VarOrTerm \| TriplesNode \| ReifiedTriple`
`[114]`	`GraphNodePath`	::=	`VarOrTerm \| TriplesNodePath \| ReifiedTriple`
`[115]`	`VarOrTerm`	::=	`Var \| iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| BlankNode \| NIL \| TripleTerm`
`[116]`	`ReifiedTriple`	::=	`'<<' ReifiedTripleSubject Verb ReifiedTripleObject Reifier ? '>>'`
`[117]`	`ReifiedTripleSubject`	::=	`Var \| iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| BlankNode \| ReifiedTriple \| TripleTerm`
`[118]`	`ReifiedTripleObject`	::=	`Var \| iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| BlankNode \| ReifiedTriple \| TripleTerm`
`[119]`	`TripleTerm`	::=	`'<<(' TripleTermSubject Verb TripleTermObject ')>>'`
`[120]`	`TripleTermSubject`	::=	`Var \| iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| BlankNode \| TripleTerm`
`[121]`	`TripleTermObject`	::=	`Var \| iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| BlankNode \| TripleTerm`
`[122]`	`TripleTermData`	::=	`'<<(' TripleTermDataSubject ( iri \| 'a' ) TripleTermDataObject ')>>'`
`[123]`	`TripleTermDataSubject`	::=	`iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| TripleTermData`
`[124]`	`TripleTermDataObject`	::=	`iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| TripleTermData`
`[125]`	`VarOrIri`	::=	`Var \| iri`
`[126]`	`Var`	::=	`VAR1 \| VAR2`
`[127]`	`Expression`	::=	`ConditionalOrExpression`
`[128]`	`ConditionalOrExpression`	::=	`ConditionalAndExpression ( '\|\|' ConditionalAndExpression )*`
`[129]`	`ConditionalAndExpression`	::=	`ValueLogical ( '&&' ValueLogical )*`
`[130]`	`ValueLogical`	::=	`RelationalExpression`
`[131]`	`RelationalExpression`	::=	`NumericExpression ( '=' NumericExpression \| '!=' NumericExpression \| '<' NumericExpression \| '>' NumericExpression \| '<=' NumericExpression \| '>=' NumericExpression \| 'IN' ExpressionList \| 'NOT' 'IN' ExpressionList )?`
`[132]`	`NumericExpression`	::=	`AdditiveExpression`
`[133]`	`AdditiveExpression`	::=	`MultiplicativeExpression ( '+' MultiplicativeExpression \| '-' MultiplicativeExpression \| ( NumericLiteralPositive \| NumericLiteralNegative ) ( ( '' UnaryExpression ) \| ( '/' UnaryExpression ) ) )*`
`[134]`	`MultiplicativeExpression`	::=	`UnaryExpression ( '' UnaryExpression \| '/' UnaryExpression )`
`[135]`	`UnaryExpression`	::=	`'!' PrimaryExpression \| '+' PrimaryExpression \| '-' PrimaryExpression \| PrimaryExpression`
`[136]`	`PrimaryExpression`	::=	`BrackettedExpression \| BuiltInCall \| iriOrFunction \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| Var \| ExprTripleTerm`
`[137]`	`ExprTripleTerm`	::=	`'<<(' ExprTripleTermSubject Verb ExprTripleTermObject ')>>'`
`[138]`	`ExprTripleTermSubject`	::=	`iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| Var \| ExprTripleTerm`
`[139]`	`ExprTripleTermObject`	::=	`iri \| RDFLiteral \| NumericLiteral \| BooleanLiteral \| Var \| ExprTripleTerm`
`[140]`	`BrackettedExpression`	::=	`'(' Expression ')'`
`[141]`	`BuiltInCall`	::=	Aggregate \| 'STR' '(' Expression ')' \| 'LANG' '(' Expression ')' \| 'LANGMATCHES' '(' Expression ',' Expression ')' \| 'LANGDIR' '(' Expression ')' \| 'DATATYPE' '(' Expression ')' \| 'BOUND' '(' Var ')' \| 'IRI' '(' Expression ')' \| 'URI' '(' Expression ')' \| 'BNODE' ( '(' Expression ')' \| NIL ) \| 'RAND' NIL \| 'ABS' '(' Expression ')' \| 'CEIL' '(' Expression ')' \| 'FLOOR' '(' Expression ')' \| 'ROUND' '(' Expression ')' \| 'CONCAT' ExpressionList \| SubstringExpression \| 'STRLEN' '(' Expression ')' \| StrReplaceExpression \| 'UCASE' '(' Expression ')' \| 'LCASE' '(' Expression ')' \| 'ENCODE_FOR_URI' '(' Expression ')' \| 'CONTAINS' '(' Expression ',' Expression ')' \| 'STRSTARTS' '(' Expression ',' Expression ')' \| 'STRENDS' '(' Expression ',' Expression ')' \| 'STRBEFORE' '(' Expression ',' Expression ')' \| 'STRAFTER' '(' Expression ',' Expression ')' \| 'YEAR' '(' Expression ')' \| 'MONTH' '(' Expression ')' \| 'DAY' '(' Expression ')' \| 'HOURS' '(' Expression ')' \| 'MINUTES' '(' Expression ')' \| 'SECONDS' '(' Expression ')' \| 'TIMEZONE' '(' Expression ')' \| 'TZ' '(' Expression ')' \| 'NOW' NIL \| 'UUID' NIL \| 'STRUUID' NIL \| 'MD5' '(' Expression ')' \| 'SHA1' '(' Expression ')' \| 'SHA256' '(' Expression ')' \| 'SHA384' '(' Expression ')' \| 'SHA512' '(' Expression ')' \| 'COALESCE' ExpressionList \| 'IF' '(' Expression ',' Expression ',' Expression ')' \| 'STRLANG' '(' Expression ',' Expression ')' \| 'STRLANGDIR' '(' Expression ',' Expression ',' Expression ')' \| 'STRDT' '(' Expression ',' Expression ')' \| 'sameTerm' '(' Expression ',' Expression ')' \| 'isIRI' '(' Expression ')' \| 'isURI' '(' Expression ')' \| 'isBLANK' '(' Expression ')' \| 'isLITERAL' '(' Expression ')' \| 'isNUMERIC' '(' Expression ')' \| 'hasLANG' '(' Expression ')' \| 'hasLANGDIR' '(' Expression ')' \| RegexExpression \| ExistsFunc \| NotExistsFunc \| 'isTRIPLE' '(' Expression ')' \| 'TRIPLE' '(' Expression ',' Expression ',' Expression ')' \| 'SUBJECT' '(' Expression ')' \| 'PREDICATE' '(' Expression ')' \| 'OBJECT' '(' Expression ')'
`[142]`	`RegexExpression`	::=	`'REGEX' '(' Expression ',' Expression ( ',' Expression )? ')'`
`[143]`	`SubstringExpression`	::=	`'SUBSTR' '(' Expression ',' Expression ( ',' Expression )? ')'`
`[144]`	`StrReplaceExpression`	::=	`'REPLACE' '(' Expression ',' Expression ',' Expression ( ',' Expression )? ')'`
`[145]`	`ExistsFunc`	::=	`'EXISTS' GroupGraphPattern`
`[146]`	`NotExistsFunc`	::=	`'NOT' 'EXISTS' GroupGraphPattern`
`[147]`	`Aggregate`	::=	`'COUNT' '(' 'DISTINCT' ? ( '*' \| Expression ) ')' \| 'SUM' '(' 'DISTINCT' ? Expression ')' \| 'MIN' '(' 'DISTINCT' ? Expression ')' \| 'MAX' '(' 'DISTINCT' ? Expression ')' \| 'AVG' '(' 'DISTINCT' ? Expression ')' \| 'SAMPLE' '(' 'DISTINCT' ? Expression ')' \| 'GROUP_CONCAT' '(' 'DISTINCT' ? Expression ( ';' 'SEPARATOR' '=' String )? ')'`
`[148]`	`iriOrFunction`	::=	`iri ArgList ?`
`[149]`	`RDFLiteral`	::=	`String ( LANG_DIR \| '^^' iri )?`
`[150]`	`NumericLiteral`	::=	`NumericLiteralUnsigned \| NumericLiteralPositive \| NumericLiteralNegative`
`[151]`	`NumericLiteralUnsigned`	::=	`INTEGER \| DECIMAL \| DOUBLE`
`[152]`	`NumericLiteralPositive`	::=	`INTEGER_POSITIVE \| DECIMAL_POSITIVE \| DOUBLE_POSITIVE`
`[153]`	`NumericLiteralNegative`	::=	`INTEGER_NEGATIVE \| DECIMAL_NEGATIVE \| DOUBLE_NEGATIVE`
`[154]`	`BooleanLiteral`	::=	`'true' \| 'false'`
`[155]`	`String`	::=	`STRING_LITERAL1 \| STRING_LITERAL2 \| STRING_LITERAL_LONG1 \| STRING_LITERAL_LONG2`
`[156]`	`iri`	::=	`IRIREF \| PrefixedName`
`[157]`	`PrefixedName`	::=	`PNAME_LN \| PNAME_NS`
`[158]`	`BlankNode`	::=	`BLANK_NODE_LABEL \| ANON`

Productions for terminals:

`[159]`	`IRIREF`	::=	'<' ([^<>"{}\|^`\]-[#x00-#x20])* '>'
`[160]`	`PNAME_NS`	::=	`PN_PREFIX ? ':'`
`[161]`	`PNAME_LN`	::=	`PNAME_NS PN_LOCAL`
`[162]`	`BLANK_NODE_LABEL`	::=	`'_:' ( PN_CHARS_U \| [0-9] ) (( PN_CHARS \|'.')* PN_CHARS )?`
`[163]`	`VAR1`	::=	`'?' VARNAME`
`[164]`	`VAR2`	::=	`'$' VARNAME`
`[165]`	`LANG_DIR`	::=	`'@' [a-zA-Z]+ ('-' [a-zA-Z0-9]+)* ('--' [a-zA-Z]+)?`
`[166]`	`INTEGER`	::=	`[0-9]+`
`[167]`	`DECIMAL`	::=	`[0-9]* '.' [0-9]+`
`[168]`	`DOUBLE`	::=	`( ([0-9]+ ('.'[0-9]*)? ) \| ( '.' ([0-9])+ ) ) EXPONENT`
`[169]`	`EXPONENT`	::=	`[eE] [+-]? [0-9]+`
`[170]`	`INTEGER_POSITIVE`	::=	`'+' INTEGER`
`[171]`	`DECIMAL_POSITIVE`	::=	`'+' DECIMAL`
`[172]`	`DOUBLE_POSITIVE`	::=	`'+' DOUBLE`
`[173]`	`INTEGER_NEGATIVE`	::=	`'-' INTEGER`
`[174]`	`DECIMAL_NEGATIVE`	::=	`'-' DECIMAL`
`[175]`	`DOUBLE_NEGATIVE`	::=	`'-' DOUBLE`
`[176]`	`STRING_LITERAL1`	::=	`"'" ( ([^#x27#x5C#xA#xD]) \| ECHAR )* "'"`
`[177]`	`STRING_LITERAL2`	::=	`'"' ( ([^#x22#x5C#xA#xD]) \| ECHAR )* '"'`
`[178]`	`STRING_LITERAL_LONG1`	::=	`"'''" ( ( "'" \| "''" )? ( [^'\] \| ECHAR ) )* "'''"`
`[179]`	`STRING_LITERAL_LONG2`	::=	`'"""' ( ( '"' \| '""' )? ( [^"\] \| ECHAR ) )* '"""'`
`[180]`	`ECHAR`	::=	`'\' [tbnrf\"']`
`[181]`	`NIL`	::=	`'(' WS * ')'`
`[182]`	`WS`	::=	`#x20 \| #x9 \| #xD \| #xA`
`[183]`	`ANON`	::=	`'[' WS * ']'`
`[184]`	`PN_CHARS_BASE`	::=	`[A-Z] \| [a-z] \| [#x00C0-#x00D6] \| [#x00D8-#x00F6] \| [#x00F8-#x02FF] \| [#x0370-#x037D] \| [#x037F-#x1FFF] \| [#x200C-#x200D] \| [#x2070-#x218F] \| [#x2C00-#x2FEF] \| [#x3001-#xD7FF] \| [#xF900-#xFDCF] \| [#xFDF0-#xFFFD] \| [#x10000-#xEFFFF]`
`[185]`	`PN_CHARS_U`	::=	`PN_CHARS_BASE \| '_'`
`[186]`	`VARNAME`	::=	`( PN_CHARS_U \| [0-9] ) ( PN_CHARS_U \| [0-9] \| #x00B7 \| [#x0300-#x036F] \| [#x203F-#x2040] )*`
`[187]`	`PN_CHARS`	::=	`PN_CHARS_U \| '-' \| [0-9] \| #x00B7 \| [#x0300-#x036F] \| [#x203F-#x2040]`
`[188]`	`PN_PREFIX`	::=	`PN_CHARS_BASE (( PN_CHARS \|'.')* PN_CHARS )?`
`[189]`	`PN_LOCAL`	::=	`( PN_CHARS_U \| ':' \| [0-9] \| PLX ) (( PN_CHARS \| '.' \| ':' \| PLX )* ( PN_CHARS \| ':' \| PLX ) )?`
`[190]`	`PLX`	::=	`PERCENT \| PN_LOCAL_ESC`
`[191]`	`PERCENT`	::=	`'%' HEX HEX`
`[192]`	`HEX`	::=	`[0-9] \| [A-F] \| [a-f]`
`[193]`	`PN_LOCAL_ESC`	::=	`'\' ( '_' \| '~' \| '.' \| '-' \| '!' \| '$' \| '&' \| "'" \| '(' \| ')' \| '*' \| '+' \| ',' \| ';' \| '=' \| '/' \| '?' \| '#' \| '@' \| '%' )`

A text version of this grammar is available here .

As well as sections marked as non-normative, all authoring guidelines, diagrams, examples, and notes in this specification are non-normative. Everything else in this specification is normative.

The key words MAY , MUST , MUST NOT , OPTIONAL , and SHOULD in this document are to be interpreted as described in BCP 14 [ RFC2119 ] [ RFC8174 ] when, and only when, they appear in all capitals, as shown here.

See Section 19 SPARQL Grammar regarding conformance of SPARQL query strings , and section 16 Query Forms for conformance of query results. See section 22. Internet Media Type for conformance to the application/sparql-query media type.

This specification is intended for use in conjunction with the SPARQL 1.1 Protocol [ SPARQL11-PROTOCOL ], the SPARQL Query Results XML Format (Second Edition) [ RDF-SPARQL-XMLRES ], the SPARQL 1.1 Query Results JSON Format [ SPARQL11-RESULTS-JSON ] and the SPARQL 1.1 Query Results CSV and TSV Formats [ SPARQL11-RESULTS-CSV-TSV ]. See those specifications for their conformance criteria.

Note that the SPARQL protocol describes a means for conveying SPARQL queries to an SPARQL query processing service and returning the query results to the entity that requested them.

The Internet Media Type (formerly known as MIME Type) for the SPARQL Query Language is " application/sparql-query ".

It is recommended that sparql query files have the extension ".rq" (lowercase) on all platforms.

It is recommended that sparql query files stored on Macintosh HFS file systems be given a file type of "TEXT".

Type name:: application
Subtype name:: sparql-query
Required parameters:: None
Optional parameters:: None
Encoding considerations:: The syntax of the SPARQL Query Language is expressed over code points in Unicode [ UNICODE ]. The encoding is always UTF-8 [ RFC3629 ].; Unicode code points may also be expressed using an \uXXXX (U+0 to U+FFFF) or \UXXXXXXXX syntax (for U+10000 onwards) where X is a hexadecimal digit [0-9A-F]
Security considerations:: See SPARQL Query appendix C, Security Considerations as well as UTF-8, a transformation format of ISO 10646 [ RFC3629 ] section 7, Security Considerations.
Interoperability considerations:: There are no known interoperability issues.
Published specification:: This specification.
Applications which use this media type:: No known applications currently use this media type.
Additional information:
Magic number(s):: A SPARQL query may have the string 'PREFIX' (case independent) near the beginning of the document.
File extension(s):: ".rq"
Base URI:: The SPARQL 'BASE <IRIref>' term can change the current base URI for relative IRIrefs in the query language that are used sequentially later in the document.
Macintosh file type code(s):: "TEXT"
Person & email address to contact for further information:: public-rdf-dawg-comments@w3.org
Intended usage:: COMMON
Restrictions on usage:: None
Author/Change controller:: The SPARQL 1.2 specification is a work product of the World Wide Web Consortium's RDF-star Working Group. The W3C has change control over these specifications.

TODO

SPARQL queries using FROM, FROM NAMED, or GRAPH may cause the specified URI to be dereferenced. This may cause additional use of network, disk or CPU resources along with associated secondary issues such as denial of service. The security issues of Uniform Resource Identifier (URI): Generic Syntax [ RFC3986 ] Section 7 should be considered. In addition, the contents of file: URIs can in some cases be accessed, processed and returned as results, providing unintended access to local resources.

SPARQL requests may cause additional requests to be issued from the SPARQL endpoint, such as FROM NAMED. The endpoint is potentially within an organisations firewall or DMZ, and so such queries may be a source of indirection attacks.

The SPARQL language permits extensions, which will have their own security implications.

Multiple IRIs may have the same appearance. Characters in different scripts may look similar (a Cyrillic "о" may appear similar to a Latin "o"). A character followed by combining characters may have the same visual representation as another character (LATIN SMALL LETTER E followed by COMBINING ACUTE ACCENT has the same visual representation as LATIN SMALL LETTER E WITH ACUTE). Users of SPARQL must take care to construct queries with IRIs that match the IRIs in the data. Further information about matching of similar characters can be found in Unicode Security Considerations [ UTR36 ] and Internationalized Resource Identifiers (IRIs) [ RFC3987 ] Section 8.

TODO

argument compatible §17.4.3
SPARQL Query §18.1.8
SPARQL query string §19.1
SPARQL string §19.1
SPARQL update string §19.1
string literal §17.4.3

[ CURIE ] defines the following:
- CURIE
[ I18N-GLOSSARY ] defines the following:
- surrogate code points
- Unicode code points
- Unicode scalar values
[ RDF12-CONCEPTS ] defines the following:
- base direction
- blank node
- blank node identifier
- datatype IRI
- equal as blank nodes
- equal as literal terms
- equal as triple terms
- graph name
- ill-typed
- IRI
- IRI
- IRIs
- language tag
- lexical form
- lexical space
- literal
- object type
- part of SPARQL and RDF concrete serializations
- predicate
- RDF Dataset
- RDF string
- RDF term
- RDF terms
- RDF triple
- same as IRIs
- same RDF term
- simple literal
- subject
- triple term
[ RDF12-SEMANTICS ] defines the following:
- lean
- RDF collections
- RDF instance mapping
- RDF interpolation lemma
- RDF merge
[ RDF12-XML ] defines the following:
- RDF/XML
[ SPARQL11-PROTOCOL ] defines the following:
- specified in a SPARQL protocol request
[ SPARQL11-QUERY ] defines the following:
- solution mapping
[ SPARQL11-UPDATE ] defines the following:
- SPARQL update request
[ VCARD-RDF ] defines the following:
- vCard vocabulary
[ WEBARCH ] defines the following:
- further details
[ XML-NAMES11 ] defines the following:
- XML local names
[ XML11 ] defines the following:
- Notation
[ XMLSCHEMA11-2 ] defines the following:
- atomic datatype
- XML Schema Regular Expressions
- xsd:boolean
- xsd:byte
- xsd:dateTime
- xsd:decimal
- xsd:double
- xsd:float
- xsd:int
- xsd:integer
- xsd:long
- xsd:negativeInteger
- xsd:nonNegativeInteger
- xsd:nonPositiveInteger
- xsd:positiveInteger
- xsd:short
- xsd:string
- xsd:unsignedByte
- xsd:unsignedInt
- xsd:unsignedLong
- xsd:unsignedShort
[ XPATH-31 ] defines the following:
- numeric type promotions
- string value
- subtype substitution
- typed value
- XPath Operator Mapping
[ XPATH-DATAMODEL-31 ] defines the following:
- XDM
[ XPATH-FUNCTIONS-31 ] defines the following:
- 19.1 Casting from primitive types to primitive types
- defined by XPath
- defined by XQuery and XPath Functions and Operators
- fn:boolean
- fn:compare
- fn:concat
- fn:contains
- fn:day-from-dateTime
- fn:encode-for-uri
- fn:ends-with
- fn:hours-from-dateTime
- fn:lower-case
- fn:matches
- fn:minutes-from-dateTime
- fn:month-from-dateTime
- fn:not
- fn:numeric-abs
- fn:numeric-ceil
- fn:numeric-floor
- fn:numeric-round
- fn:replace
- fn:seconds-from-dateTime
- fn:starts-with
- fn:string-length
- fn:substring
- fn:substring-after
- fn:substring-before
- fn:timezone-from-dateTime
- fn:upper-case
- fn:year-from-dateTime
- op:boolean-equal
- op:boolean-greater-than
- op:boolean-less-than
- op:dateTime-equal
- op:dateTime-greater-than
- op:dateTime-less-than
- op:numeric-add
- op:numeric-divide
- op:numeric-equal
- op:numeric-greater-than
- op:numeric-less-than
- op:numeric-multiply
- op:numeric-subtract
- op:numeric-unary-minus
- op:numeric-unary-plus
[ XQUERY-31 ] defines the following:
- 2.3.1, Kinds of Errors
- Effective Boolean Value
- Expression Processing
- Operator Mapping

[BCP47]: Tags for Identifying Languages . A. Phillips, Ed.; M. Davis, Ed. IETF. September 2009. Best Current Practice. URL: https://www.rfc-editor.org/rfc/rfc5646
[CBD]: CBD - Concise Bounded Description . Patrick Stickler, Nokia. W3C. 3 June 2005. W3C Member Submission. URL: https://www.w3.org/Submission/CBD/
[CURIE]: CURIE Syntax 1.0 . Mark Birbeck; Shane McCarron. W3C. 16 December 2010. W3C Working Group Note. URL: https://www.w3.org/TR/curie/
[I18N-GLOSSARY]: Internationalization Glossary . Richard Ishida; Addison Phillips. W3C. 17 October 2024. W3C Working Group Note. URL: https://www.w3.org/TR/i18n-glossary/
[RDF-DAWG-UC]: RDF Data Access Use Cases and Requirements . Kendall Clark. W3C. 25 March 2005. W3C Working Draft. URL: https://www.w3.org/TR/rdf-dawg-uc/
[RDF-SPARQL-XMLRES]: SPARQL Query Results XML Format (Second Edition) . Dave Beckett; Jeen Broekstra. W3C. 21 March 2013. W3C Recommendation. URL: https://www.w3.org/TR/rdf-sparql-XMLres/
[RDF12-CONCEPTS]: RDF 1.2 Concepts and Abstract Syntax . Olaf Hartig; Pierre-Antoine Champin; Gregg Kellogg; Andy Seaborne. W3C. 7 August 2025. W3C Working Draft. URL: https://www.w3.org/TR/rdf12-concepts/
[RDF12-SEMANTICS]: RDF 1.2 Semantics . Peter Patel-Schneider; Dörthe Arndt; Enrico Franconi. W3C. 12 August 2025. W3C Working Draft. URL: https://www.w3.org/TR/rdf12-semantics/
[RDF12-XML]: RDF 1.2 XML Syntax . Gregg Kellogg. W3C. 26 June 2025. W3C Working Draft. URL: https://www.w3.org/TR/rdf12-xml/
[RFC2119]: Key words for use in RFCs to Indicate Requirement Levels . S. Bradner. IETF. March 1997. Best Current Practice. URL: https://www.rfc-editor.org/rfc/rfc2119
[RFC3629]: UTF-8, a transformation format of ISO 10646 . F. Yergeau. IETF. November 2003. Internet Standard. URL: https://www.rfc-editor.org/rfc/rfc3629
[RFC3986]: Uniform Resource Identifier (URI): Generic Syntax . T. Berners-Lee; R. Fielding; L. Masinter. IETF. January 2005. Internet Standard. URL: https://www.rfc-editor.org/rfc/rfc3986
[RFC3987]: Internationalized Resource Identifiers (IRIs) . M. Duerst; M. Suignard. IETF. January 2005. Proposed Standard. URL: https://www.rfc-editor.org/rfc/rfc3987
[RFC4122]: A Universally Unique IDentifier (UUID) URN Namespace . P. Leach; M. Mealling; R. Salz. IETF. July 2005. Proposed Standard. URL: https://www.rfc-editor.org/rfc/rfc4122
[RFC4647]: Matching of Language Tags . A. Phillips, Ed.; M. Davis, Ed. IETF. September 2006. Best Current Practice. URL: https://www.rfc-editor.org/rfc/rfc4647
[RFC8174]: Ambiguity of Uppercase vs Lowercase in RFC 2119 Key Words . B. Leiba. IETF. May 2017. Best Current Practice. URL: https://www.rfc-editor.org/rfc/rfc8174
[SPARQL-FEATURES]: SPARQL New Features and Rationale . Kjetil Kjernsmo; Alexandre Passant. W3C. 2 July 2009. W3C Working Draft. URL: https://www.w3.org/TR/sparql-features/
[SPARQL11-ENTAILMENT]: SPARQL 1.1 Entailment Regimes . Birte Glimm; Chimezie Ogbuji. W3C. 21 March 2013. W3C Recommendation. URL: https://www.w3.org/TR/sparql11-entailment/
[SPARQL11-FEDERATED-QUERY]: SPARQL 1.1 Federated Query . Eric Prud'hommeaux; Carlos Buil Aranda. W3C. 21 March 2013. W3C Recommendation. URL: https://www.w3.org/TR/sparql11-federated-query/
[SPARQL11-PROTOCOL]: SPARQL 1.1 Protocol . Lee Feigenbaum; Gregory Williams; Kendall Clark; Elias Torres. W3C. 21 March 2013. W3C Recommendation. URL: https://www.w3.org/TR/sparql11-protocol/
[SPARQL11-QUERY]: SPARQL 1.1 Query Language . Steven Harris; Andy Seaborne. W3C. 21 March 2013. W3C Recommendation. URL: https://www.w3.org/TR/sparql11-query/
[SPARQL11-RESULTS-CSV-TSV]: SPARQL 1.1 Query Results CSV and TSV Formats . Andy Seaborne. W3C. 21 March 2013. W3C Recommendation. URL: https://www.w3.org/TR/sparql11-results-csv-tsv/
[SPARQL11-RESULTS-JSON]: SPARQL 1.1 Query Results JSON Format . Andy Seaborne. W3C. 21 March 2013. W3C Recommendation. URL: https://www.w3.org/TR/sparql11-results-json/
[SPARQL11-UPDATE]: SPARQL 1.1 Update . Paula Gearon; Alexandre Passant; Axel Polleres. W3C. 21 March 2013. W3C Recommendation. URL: https://www.w3.org/TR/sparql11-update/
[TURTLE]: RDF 1.1 Turtle . Eric Prud'hommeaux; Gavin Carothers. W3C. 25 February 2014. W3C Recommendation. URL: https://www.w3.org/TR/turtle/
[UAX31]: Unicode Identifiers and Syntax . Mark Davis; Robin Leroy. Unicode Consortium. 2 September 2024. Unicode Standard Annex #31. URL: https://www.unicode.org/reports/tr31/tr31-41.html
[UNICODE]: The Unicode Standard . Unicode Consortium. URL: https://www.unicode.org/versions/latest/
[UTR36]: Unicode Security Considerations . Mark Davis; Michel Suignard. Unicode Consortium. 19 September 2014. Unicode Technical Report #36. URL: https://www.unicode.org/reports/tr36/tr36-15.html
[vcard-rdf]: vCard Ontology - for describing People and Organizations . Renato Iannella; James McKinney. W3C. 22 May 2014. W3C Working Group Note. URL: https://www.w3.org/TR/vcard-rdf/
[WEBARCH]: Architecture of the World Wide Web, Volume One . Ian Jacobs; Norman Walsh. W3C. 15 December 2004. W3C Recommendation. URL: https://www.w3.org/TR/webarch/
[XML-NAMES11]: Namespaces in XML 1.1 (Second Edition) . Tim Bray; Dave Hollander; Andrew Layman; Richard Tobin et al. W3C. 16 August 2006. W3C Recommendation. URL: https://www.w3.org/TR/xml-names11/
[XML11]: Extensible Markup Language (XML) 1.1 (Second Edition) . Tim Bray; Jean Paoli; Michael Sperberg-McQueen; Eve Maler; François Yergeau; John Cowan et al. W3C. 16 August 2006. W3C Recommendation. URL: https://www.w3.org/TR/xml11/
[XMLSCHEMA11-2]: W3C XML Schema Definition Language (XSD) 1.1 Part 2: Datatypes . David Peterson; Sandy Gao; Ashok Malhotra; Michael Sperberg-McQueen; Henry Thompson; Paul V. Biron et al. W3C. 5 April 2012. W3C Recommendation. URL: https://www.w3.org/TR/xmlschema11-2/
[XPATH-31]: XML Path Language (XPath) 3.1 . Jonathan Robie; Michael Dyck; Josh Spiegel. W3C. 21 March 2017. W3C Recommendation. URL: https://www.w3.org/TR/xpath-31/
[XPATH-DATAMODEL-31]: XQuery and XPath Data Model 3.1 . Norman Walsh; John Snelson; Andrew Coleman. W3C. 21 March 2017. W3C Recommendation. URL: https://www.w3.org/TR/xpath-datamodel-31/
[XPATH-FUNCTIONS-31]: XPath and XQuery Functions and Operators 3.1 . Michael Kay. W3C. 21 March 2017. W3C Recommendation. URL: https://www.w3.org/TR/xpath-functions-31/
[XQUERY-31]: XQuery 3.1: An XML Query Language . Jonathan Robie; Michael Dyck; Josh Spiegel. W3C. 21 March 2017. W3C Recommendation. URL: https://www.w3.org/TR/xquery-31/

[SPARQL12-CONCEPTS]: SPARQL 1.2 Concepts . The W3C RDF & SPARQL Working Group. W3C. W3C Working Draft. URL: https://w3c.github.io/sparql-concepts/spec/
[SPARQL12-ENTAILMENT]: SPARQL 1.2 Entailment Regimes . Peter Patel-Schneider. W3C. 19 December 2024. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-entailment/
[SPARQL12-FEDERATED-QUERY]: SPARQL 1.2 Federated Query . Ruben Taelman; Gregory Williams. W3C. 5 May 2025. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-federated-query/
[SPARQL12-GRAPH-STORE-PROTOCOL]: SPARQL 1.2 Graph Store Protocol . Andy Seaborne; Thomas Pellissier Tanon. W3C. 19 December 2024. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-graph-store-protocol/
[SPARQL12-NEW]: What’s New in SPARQL 1.2 . The W3C RDF & SPARQL Working Group. W3C. W3C Working Draft. URL: https://w3c.github.io/sparql-new/spec/
[SPARQL12-PROTOCOL]: SPARQL 1.2 Protocol . Andy Seaborne; Ruben Taelman; Gregory Williams; Thomas Pellissier Tanon. W3C. 24 June 2025. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-protocol/
[SPARQL12-RESULTS-CSV-TSV]: SPARQL 1.2 Query Results CSV and TSV Formats . Ruben Taelman; Gregory Williams; Thomas Pellissier Tanon. W3C. 19 December 2024. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-results-csv-tsv/
[SPARQL12-RESULTS-JSON]: SPARQL 1.2 Query Results JSON Format . Andy Seaborne; Ruben Taelman; Gregory Williams; Thomas Pellissier Tanon. W3C. 8 May 2025. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-results-json/
[SPARQL12-RESULTS-XML]: SPARQL 1.2 Query Results XML Format . Ruben Taelman; Dominik Tomaszuk; Thomas Pellissier Tanon. W3C. 27 December 2024. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-results-xml/
[SPARQL12-SERVICE-DESCRIPTION]: SPARQL 1.2 Service Description . Ruben Taelman; Gregory Williams. W3C. 19 December 2024. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-service-description/
[SPARQL12-UPDATE]: SPARQL 1.2 Update . Ruben Taelman; Andy Seaborne; Thomas Pellissier Tanon. W3C. 6 February 2025. W3C Working Draft. URL: https://www.w3.org/TR/sparql12-update/

SPARQL 1.2 Query Language

Abstract

Status of This Document

Set of Documents

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 Identifiers 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

4.3 Version Announcement

5. Graph Patterns

5.1 Basic Graph Patterns

5.1.1 Blank Node Identifiers

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

12.1 Example

13. RDF Dataset