Expressions

Enterprise Edition

The query language is a highly composable expression language. Each expression in the query language returns zero or more data model instances. There are three major kinds of expressions. At the topmost level, an expression can be an OperatorExpression (similar to a mathematical expression) or a QuantifiedExpression (which yields a boolean value). Each will be detailed as we explore the full grammar of the language.

Expression ::= OperatorExpression | QuantifiedExpression

Note that in the following text, words enclosed in angle brackets denote keywords that are not case-sensitive.

Operator Expressions

Operators perform a specific operation on the input values or expressions. The syntax of an operator expression is as follows:

OperatorExpression ::= PathExpression
                       | Operator OperatorExpression
                       | OperatorExpression Operator (OperatorExpression)?
                       | OperatorExpression <BETWEEN> OperatorExpression <AND> OperatorExpression

The language provides a full set of operators that you can use within its statements. Here are the categories of operators:

Arithmetic Operators, to perform basic mathematical operations;
Collection Operators, to evaluate expressions on collections or objects;
Comparison Operators, to compare two expressions;
Logical Operators, to combine operators using Boolean logic.

The following table summarizes the precedence order (from higher to lower) of the major unary and binary operators:

Operator	Operation
EXISTS, NOT EXISTS	Collection emptiness testing
^	Exponentiation
*, /, DIV, MOD (%)	Multiplication, division, modulo
+, -	Addition, subtraction
\|\|	String concatenation
IS NULL, IS NOT NULL, IS MISSING, IS NOT MISSING, IS UNKNOWN, IS NOT UNKNOWN, IS VALUED, IS NOT VALUED	Unknown value comparison
BETWEEN, NOT BETWEEN	Range comparison (inclusive on both sides)
=, !=, <>, <, >, <=, >=, LIKE, NOT LIKE, IN, NOT IN	Comparison
NOT	Logical negation
AND	Conjunction
OR	Disjunction

Operator

Operation

EXISTS, NOT EXISTS

Collection emptiness testing

Exponentiation

*, /, DIV, MOD (%)

Multiplication, division, modulo

+, -

Addition, subtraction

String concatenation

IS NULL, IS NOT NULL, IS MISSING, IS NOT MISSING,
IS UNKNOWN, IS NOT UNKNOWN, IS VALUED, IS NOT VALUED

Unknown value comparison

BETWEEN, NOT BETWEEN

Range comparison (inclusive on both sides)

=, !=, <>, <, >, <=, >=, LIKE, NOT LIKE, IN, NOT IN

Comparison

NOT

Logical negation

AND

Conjunction

Disjunction

In general, if any operand evaluates to a MISSING value, the enclosing operator will return MISSING; if none of operands evaluates to a MISSING value but there is an operand evaluates to a NULL value, the enclosing operator will return NULL. However, there are a few exceptions listed in comparison operators and logical operators.

Arithmetic Operators

Arithmetic operators are used to exponentiate, add, subtract, multiply, and divide numeric values, or concatenate string values.

Operator Purpose Example

Operator	Purpose	Example
+, -	As unary operators, they denote a positive or negative expression	SELECT VALUE -1;
+, -	As binary operators, they add or subtract	SELECT VALUE 1 + 2;
*	Multiply	SELECT VALUE 4 * 2;
/	Divide (returns a value of type `double` if both operands are integers)	SELECT VALUE 5 / 2;
DIV	Divide (returns an integer value if both operands are integers)	SELECT VALUE 5 DIV 2;
MOD (%)	Modulo	SELECT VALUE 5 % 2;
^	Exponentiation	SELECT VALUE 2^3;
\|\|	String concatenation	SELECT VALUE "ab"\|\|"c"\|\|"d";

+, -

As unary operators, they denote a
positive or negative expression

SELECT VALUE -1;

+, -

As binary operators, they add or subtract

SELECT VALUE 1 + 2;

Multiply

SELECT VALUE 4 * 2;

Divide (returns a value of type double if both operands are integers)

SELECT VALUE 5 / 2;

DIV

Divide (returns an integer value if both operands are integers)

SELECT VALUE 5 DIV 2;

MOD (%)

Modulo

SELECT VALUE 5 % 2;

Exponentiation

SELECT VALUE 2^3;

String concatenation

SELECT VALUE "ab"||"c"||"d";

Collection Operators

Collection operators are used for membership tests (IN, NOT IN) or empty collection tests (EXISTS, NOT EXISTS).

Operator	Purpose	Example
IN	Membership test	SELECT * FROM ChirpMessages cm WHERE cm.user.lang IN ["en", "de"];
NOT IN	Non-membership test	SELECT * FROM ChirpMessages cm WHERE cm.user.lang NOT IN ["en"];
EXISTS	Check whether a collection is not empty	SELECT * FROM ChirpMessages cm WHERE EXISTS cm.referredTopics;
NOT EXISTS	Check whether a collection is empty	SELECT * FROM ChirpMessages cm WHERE NOT EXISTS cm.referredTopics;

Operator

Purpose

Example

Membership test

SELECT * FROM ChirpMessages cm
WHERE cm.user.lang IN ["en", "de"];

NOT IN

Non-membership test

SELECT * FROM ChirpMessages cm
WHERE cm.user.lang NOT IN ["en"];

EXISTS

Check whether a collection is not empty

SELECT * FROM ChirpMessages cm
WHERE EXISTS cm.referredTopics;

NOT EXISTS

Check whether a collection is empty

SELECT * FROM ChirpMessages cm
WHERE NOT EXISTS cm.referredTopics;

Comparison Operators

Comparison operators are used to compare values. The comparison operators fall into one of two sub-categories: missing value comparisons and regular value comparisons. The query language (and JSON) has two ways of representing missing information in a object - the presence of the field with a NULL for its value (as in SQL), and the absence of the field (which JSON permits). For example, the first of the following objects represents Jack, whose friend is Jill. In the other examples, Jake is friendless a la SQL, with a friend field that is NULL, while Joe is friendless in a more natural (for JSON) way, i.e., by not having a friend field.

Examples

{"name": "Jack", "friend": "Jill"}

{"name": "Jake", "friend": NULL}

{"name": "Joe"}

The following table enumerates all of the query language’s comparison operators.

Operator	Purpose	Example
IS NULL	Test if a value is NULL	SELECT * FROM ChirpMessages cm WHERE cm.user.name IS NULL;
IS NOT NULL	Test if a value is not NULL	SELECT * FROM ChirpMessages cm WHERE cm.user.name IS NOT NULL;
IS MISSING	Test if a value is MISSING	SELECT * FROM ChirpMessages cm WHERE cm.user.name IS MISSING;
IS NOT MISSING	Test if a value is not MISSING	SELECT * FROM ChirpMessages cm WHERE cm.user.name IS NOT MISSING;
IS UNKNOWN	Test if a value is NULL or MISSING	SELECT * FROM ChirpMessages cm WHERE cm.user.name IS UNKNOWN;
IS NOT UNKNOWN	Test if a value is neither NULL nor MISSING	SELECT * FROM ChirpMessages cm WHERE cm.user.name IS NOT UNKNOWN;
IS KNOWN (IS VALUED)	Test if a value is neither NULL nor MISSING	SELECT * FROM ChirpMessages cm WHERE cm.user.name IS KNOWN;
IS NOT KNOWN (IS NOT VALUED)	Test if a value is NULL or MISSING	SELECT * FROM ChirpMessages cm WHERE cm.user.name IS NOT KNOWN;
BETWEEN	Test if a value is between a start value and a end value. The comparison is inclusive to both start and end values.	SELECT * FROM ChirpMessages cm WHERE cm.chirpId BETWEEN 10 AND 20;
=	Equality test	SELECT * FROM ChirpMessages cm WHERE cm.chirpId=10;
!=	Inequality test	SELECT * FROM ChirpMessages cm WHERE cm.chirpId!=10;
<>	Inequality test	SELECT * FROM ChirpMessages cm WHERE cm.chirpId<>10;
<	Less than	SELECT * FROM ChirpMessages cm WHERE cm.chirpId<10;
>	Greater than	SELECT * FROM ChirpMessages cm WHERE cm.chirpId>10;
<=	Less than or equal to	SELECT * FROM ChirpMessages cm WHERE cm.chirpId<=10;
>=	Greater than or equal to	SELECT * FROM ChirpMessages cm WHERE cm.chirpId>=10;
LIKE	Test if the left side matches a pattern defined on the right side; in the pattern, "%" matches any string while "_" matches any character.	SELECT * FROM ChirpMessages cm WHERE cm.user.name LIKE "%Giesen%";
NOT LIKE	Test if the left side does not match a pattern defined on the right side; in the pattern, "%" matches any string while "_" matches any character.	SELECT * FROM ChirpMessages cm WHERE cm.user.name NOT LIKE "%Giesen%";

Operator

Purpose

Example

IS NULL

Test if a value is NULL

SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NULL;

IS NOT NULL

Test if a value is not NULL

SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NOT NULL;

IS MISSING

Test if a value is MISSING

SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS MISSING;

IS NOT MISSING

Test if a value is not MISSING

SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NOT MISSING;

IS UNKNOWN

Test if a value is NULL or MISSING

SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS UNKNOWN;

IS NOT UNKNOWN

Test if a value is neither NULL nor MISSING

SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NOT UNKNOWN;

IS KNOWN (IS VALUED)

Test if a value is neither NULL nor MISSING

SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS KNOWN;

IS NOT KNOWN (IS NOT VALUED)

Test if a value is NULL or MISSING

SELECT * FROM ChirpMessages cm
WHERE cm.user.name IS NOT KNOWN;

BETWEEN

Test if a value is between a start value and
a end value. The comparison is inclusive
to both start and end values.

SELECT * FROM ChirpMessages cm
WHERE cm.chirpId BETWEEN 10 AND 20;

Equality test

SELECT * FROM ChirpMessages cm
WHERE cm.chirpId=10;

Inequality test

SELECT * FROM ChirpMessages cm
WHERE cm.chirpId!=10;

Inequality test

SELECT * FROM ChirpMessages cm
WHERE cm.chirpId<>10;

Less than

SELECT * FROM ChirpMessages cm
WHERE cm.chirpId<10;

Greater than

SELECT * FROM ChirpMessages cm
WHERE cm.chirpId>10;

Less than or equal to

SELECT * FROM ChirpMessages cm
WHERE cm.chirpId<=10;

Greater than or equal to

SELECT * FROM ChirpMessages cm
WHERE cm.chirpId>=10;

Test if the left side matches a
pattern defined on the right
side; in the pattern, "%" matches
any string while "_" matches
any character.

SELECT * FROM ChirpMessages cm
WHERE cm.user.name LIKE "%Giesen%";

NOT LIKE

Test if the left side does not
match a pattern defined on the right
side; in the pattern, "%" matches
any string while "_" matches
any character.

SELECT * FROM ChirpMessages cm
WHERE cm.user.name NOT LIKE "%Giesen%";

The following table summarizes how the missing value comparison operators work.

Operator	Non-NULL/Non-MISSING value	NULL	MISSING
IS NULL	FALSE	TRUE	MISSING
IS NOT NULL	TRUE	FALSE	MISSING
IS MISSING	FALSE	FALSE	TRUE
IS NOT MISSING	TRUE	TRUE	FALSE
IS UNKNOWN	FALSE	TRUE	TRUE
IS NOT UNKNOWN	TRUE	FALSE	FALSE
IS KNOWN (IS VALUED)	TRUE	FALSE	FALSE
IS NOT KNOWN (IS NOT VALUED)	FALSE	TRUE	TRUE

Operator

Non-NULL/Non-MISSING value

NULL

MISSING

IS NULL

FALSE

TRUE

MISSING

IS NOT NULL

TRUE

FALSE

MISSING

IS MISSING

FALSE

TRUE

IS NOT MISSING

TRUE

FALSE

IS UNKNOWN

FALSE

TRUE

IS NOT UNKNOWN

TRUE

FALSE

IS KNOWN (IS VALUED)

TRUE

FALSE

IS NOT KNOWN (IS NOT VALUED)

FALSE

TRUE

Logical Operators

Logical operators perform logical NOT, AND, and OR operations over Boolean values (TRUE and FALSE) plus NULL and MISSING.

Operator	Purpose	Example
NOT	Returns true if the following condition is false, otherwise returns false	SELECT VALUE NOT TRUE;
AND	Returns true if both branches are true, otherwise returns false	SELECT VALUE TRUE AND FALSE;
OR	Returns true if one branch is true, otherwise returns false	SELECT VALUE FALSE OR FALSE;

Operator

Purpose

Example

NOT

Returns true if the following condition is false, otherwise returns false

SELECT VALUE NOT TRUE;

AND

Returns true if both branches are true, otherwise returns false

SELECT VALUE TRUE AND FALSE;

Returns true if one branch is true, otherwise returns false

SELECT VALUE FALSE OR FALSE;

The following table is the truth table for AND and OR.

A	B	A AND B	A OR B
TRUE	TRUE	TRUE	TRUE
TRUE	FALSE	FALSE	TRUE
TRUE	NULL	NULL	TRUE
TRUE	MISSING	MISSING	TRUE
FALSE	FALSE	FALSE	FALSE
FALSE	NULL	FALSE	NULL
FALSE	MISSING	FALSE	MISSING
NULL	NULL	NULL	NULL
NULL	MISSING	MISSING	NULL
MISSING	MISSING	MISSING	MISSING

A AND B

A OR B

TRUE

FALSE

TRUE

NULL

TRUE

MISSING

TRUE

FALSE

NULL

FALSE

NULL

FALSE

MISSING

FALSE

MISSING

NULL

MISSING

NULL

MISSING

The following table demonstrates the results of NOT on all possible inputs.

A	NOT A
TRUE	FALSE
FALSE	TRUE
NULL	NULL
MISSING	MISSING

NOT A

TRUE

FALSE

TRUE

NULL

MISSING

Quantified Expressions

QuantifiedExpression ::= ( (<ANY>|<SOME>) | <EVERY> ) Variable <IN> Expression ( "," Variable "in" Expression )*
                         <SATISFIES> Expression (<END>)?

Quantified expressions are used for expressing existential or universal predicates involving the elements of a collection.

The following pair of examples illustrate the use of a quantified expression to test that every (or some) element in the set [1, 2, 3] of integers is less than three. The first example yields FALSE and second example yields TRUE.

It is useful to note that if the set were instead the empty set, the first expression would yield TRUE ("every" value in an empty set satisfies the condition) while the second expression would yield FALSE (since there isn’t "some" value, as there are no values in the set, that satisfies the condition).

A quantified expression will return a NULL (or MISSING) if the first expression in it evaluates to NULL (or MISSING). A type error will be raised if the first expression in a quantified expression does not return a collection.

Examples

EVERY x IN [ 1, 2, 3 ] SATISFIES x < 3
SOME x IN [ 1, 2, 3 ] SATISFIES x < 3

Path Expressions

PathExpression  ::= PrimaryExpression ( Field | Index )*
Field           ::= "." Identifier
Index           ::= "[" Expression "]"

Components of complex types in the data model are accessed via path expressions. Path access can be applied to the result of a query expression that yields an instance of a complex type, for example, a object or array instance. For objects, path access is based on field names. For arrays, path access is based on (zero-based) array-style indexing. Attempts to access non-existent fields or out-of-bound array elements produce the special value MISSING. For multisets path access is also zero-based and returns an arbitrary multiset element if the index is within the size of the multiset or MISSING otherwise. Type errors will be raised for inappropriate use of a path expression, such as applying a field accessor to a numeric value.

The following examples illustrate field access for a object, index-based element access for an array, and also a composition thereof.

Examples

({"name": "MyABCs", "array": [ "a", "b", "c"]}).array

(["a", "b", "c"])[2]

({"name": "MyABCs", "array": [ "a", "b", "c"]}).array[2]

Primary Expressions

PrimaryExpr ::= Literal
              | VariableReference
              | ParameterReference
              | ParenthesizedExpression
              | FunctionCallExpression
              | CaseExpression
              | Constructor

The most basic building block for any expression in the query langauge is PrimaryExpression. This can be a simple literal (constant) value, a reference to a query variable that is in scope, a parenthesized expression, a function call, or a newly constructed instance of the data model (such as a newly constructed object, array, or multiset of data model instances).

Literals

Literal        ::= StringLiteral
                   | IntegerLiteral
                   | FloatLiteral
                   | DoubleLiteral
                   | <NULL>
                   | <MISSING>
                   | <TRUE>
                   | <FALSE>
StringLiteral  ::= "\"" (
                             <EscapeQuot>
                           | <EscapeBslash>
                           | <EscapeSlash>
                           | <EscapeBspace>
                           | <EscapeFormf>
                           | <EscapeNl>
                           | <EscapeCr>
                           | <EscapeTab>
                           | ~["\"","\\"])*
                    "\""
                    | "\'"(
                             <EscapeApos>
                           | <EscapeBslash>
                           | <EscapeSlash>
                           | <EscapeBspace>
                           | <EscapeFormf>
                           | <EscapeNl>
                           | <EscapeCr>
                           | <EscapeTab>
                           | ~["\'","\\"])*
                      "\'"
<ESCAPE_Apos>  ::= "\\\'"
<ESCAPE_Quot>  ::= "\\\""
<EscapeBslash> ::= "\\\\"
<EscapeSlash>  ::= "\\/"
<EscapeBspace> ::= "\\b"
<EscapeFormf>  ::= "\\f"
<EscapeNl>     ::= "\\n"
<EscapeCr>     ::= "\\r"
<EscapeTab>    ::= "\\t"

IntegerLiteral ::= <DIGITS>
<DIGITS>       ::= ["0" - "9"]+
FloatLiteral   ::= <DIGITS> ( "f" | "F" )
                 | <DIGITS> ( "." <DIGITS> ( "f" | "F" ) )?
                 | "." <DIGITS> ( "f" | "F" )
DoubleLiteral  ::= <DIGITS> "." <DIGITS>
                   | "." <DIGITS>

Literals (constants) in a query can be strings, integers, floating point values, double values, boolean constants, or special constant values like NULL and MISSING. The NULL value is like a NULL in SQL; it is used to represent an unknown field value. The special value MISSING is only meaningful in the context of field accesses; it occurs when the accessed field simply does not exist at all in a object being accessed.

The following are some simple examples of literals.

Examples

'a string'
"test string"
42

Different from standard SQL, double quotes play the same role as single quotes and may be used for string literals in queries as well.

Variable References

VariableReference     ::= <IDENTIFIER> | <DelimitedIdentifier>
<IDENTIFIER>          ::= (<LETTER> | "_") (<LETTER> | <DIGIT> | "_" | "$")*
<LETTER>              ::= ["A" - "Z", "a" - "z"]
DelimitedIdentifier   ::= "`" (<EscapeQuot>
                                | <EscapeBslash>
                                | <EscapeSlash>
                                | <EscapeBspace>
                                | <EscapeFormf>
                                | <EscapeNl>
                                | <EscapeCr>
                                | <EscapeTab>
                                | ~["`","\\"])*
                          "`"

A variable in a query can be bound to any legal data model value. A variable reference refers to the value to which an in-scope variable is bound. (E.g., a variable binding may originate from one of the FROM, WITH or LET clauses of a SELECT statement or from an input parameter in the context of a function body.) Backticks, for example, id, are used for delimited identifiers. Delimiting is needed when a variable’s desired name clashes with a keyword or includes characters not allowed in regular identifiers. More information on exactly how variable references are resolved can be found in the appendix section on Variable Resolution.

Examples

tweet
id
`SELECT`
`my-function`

Parameter References

ParameterReference              ::= NamedParameterReference | PositionalParameterReference
NamedParameterReference         ::= "$" (<IDENTIFIER> | <DelimitedIdentifier>)
PositionalParameterReference    ::= ("$" <DIGITS>) | "?"

A statement parameter is an external variable which value is provided through the statement execution API. An error will be raised if the parameter is not bound at the query execution time. Positional parameter numbering starts at 1. "?" parameters are interpreted as $1, .. $N in the order in which they appear in the statement.

Examples

$id
$1
?

Parenthesized Expressions

ParenthesizedExpression ::= "(" Expression ")" | Subquery

An expression can be parenthesized to control the precedence order or otherwise clarify a query. For composability, a subquery is also an parenthesized expression.

The following expression evaluates to the value 2.

Example

( 1 + 1 )

Function Call Expressions

FunctionCallExpression ::= FunctionName "(" ( Expression ( "," Expression )* )? ")"

Functions are included in the query language, like most languages, as a way to package useful functionality or to componentize complicated or reusable computations. A function call is a legal query expression that represents the value resulting from the evaluation of its body expression with the given parameter bindings; the parameter value bindings can themselves be any expressions in the query language.

The following example is a (built-in) function call expression whose value is 8.

Example

length('a string')

Case Expressions

CaseExpression ::= SimpleCaseExpression | SearchedCaseExpression
SimpleCaseExpression ::= <CASE> Expression ( <WHEN> Expression <THEN> Expression )+ ( <ELSE> Expression )? <END>
SearchedCaseExpression ::= <CASE> ( <WHEN> Expression <THEN> Expression )+ ( <ELSE> Expression )? <END>

In a simple CASE expression, the query evaluator searches for the first WHEN … THEN pair in which the WHEN expression is equal to the expression following CASE and returns the expression following THEN. If none of the WHEN … THEN pairs meet this condition, and an ELSE branch exists, it returns the ELSE expression. Otherwise, NULL is returned.

In a searched CASE expression, the query evaluator searches from left to right until it finds a WHEN expression that is evaluated to TRUE, and then returns its corresponding THEN expression. If no condition is found to be TRUE, and an ELSE branch exists, it returns the ELSE expression. Otherwise, it returns NULL.

The following example illustrates the form of a case expression.

Example

CASE (2 < 3) WHEN true THEN "yes" ELSE "no" END

Constructors

Constructor              ::= ArrayConstructor | MultisetConstructor | ObjectConstructor
ArrayConstructor         ::= "[" ( Expression ( "," Expression )* )? "]"
MultisetConstructor      ::= "{{" ( Expression ( "," Expression )* )? "}}"
ObjectConstructor        ::= "{" ( FieldBinding ( "," FieldBinding )* )? "}"
FieldBinding             ::= Expression ":" Expression

A major feature of the query language is its ability to construct new data model instances. This is accomplished using its constructors for each of the model’s complex object structures, namely arrays, multisets, and objects. Arrays are like JSON arrays, while multisets have bag semantics. Objects are built from fields that are field-name/field-value pairs, again like JSON.

The following examples illustrate how to construct a new array with 4 items and a new object with 2 fields respectively. Array elements can be homogeneous (as in the first example), which is the common case, or they may be heterogeneous (as in the second example). The data values and field name values used to construct arrays, multisets, and objects in constructors are all simply query expressions. Thus, the collection elements, field names, and field values used in constructors can be simple literals or they can come from query variable references or even arbitrarily complex query expressions (subqueries). Type errors will be raised if the field names in an object are not strings, and duplicate field errors will be raised if they are not distinct.

Examples

[ 'a', 'b', 'c', 'c' ]

[ 42, "forty-two!", { "rank" : "Captain", "name": "America" }, 3.14159 ]

{
  'project name': 'Hyracks',
  'project members': [ 'vinayakb', 'dtabass', 'chenli', 'tsotras', 'tillw' ]
}