Expressions
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, |
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 |
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 |
---|---|---|
+, - |
As unary operators, they denote a |
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 |
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 |
NOT IN |
Non-membership test |
SELECT * FROM ChirpMessages cm |
EXISTS |
Check whether a collection is not empty |
SELECT * FROM ChirpMessages cm |
NOT EXISTS |
Check whether a collection is empty |
SELECT * FROM ChirpMessages cm |
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 |
IS NOT NULL |
Test if a value is not NULL |
SELECT * FROM ChirpMessages cm |
IS MISSING |
Test if a value is MISSING |
SELECT * FROM ChirpMessages cm |
IS NOT MISSING |
Test if a value is not MISSING |
SELECT * FROM ChirpMessages cm |
IS UNKNOWN |
Test if a value is NULL or MISSING |
SELECT * FROM ChirpMessages cm |
IS NOT UNKNOWN |
Test if a value is neither NULL nor MISSING |
SELECT * FROM ChirpMessages cm |
IS KNOWN (IS VALUED) |
Test if a value is neither NULL nor MISSING |
SELECT * FROM ChirpMessages cm |
IS NOT KNOWN (IS NOT VALUED) |
Test if a value is NULL or MISSING |
SELECT * FROM ChirpMessages cm |
BETWEEN |
Test if a value is between a start value and |
SELECT * FROM ChirpMessages cm |
= |
Equality test |
SELECT * FROM ChirpMessages cm |
!= |
Inequality test |
SELECT * FROM ChirpMessages cm |
<> |
Inequality test |
SELECT * FROM ChirpMessages cm |
< |
Less than |
SELECT * FROM ChirpMessages cm |
> |
Greater than |
SELECT * FROM ChirpMessages cm |
<= |
Less than or equal to |
SELECT * FROM ChirpMessages cm |
>= |
Greater than or equal to |
SELECT * FROM ChirpMessages cm |
LIKE |
Test if the left side matches a |
SELECT * FROM ChirpMessages cm |
NOT LIKE |
Test if the left side does not |
SELECT * FROM ChirpMessages cm |
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 |
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; |
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 |
The following table demonstrates the results of NOT
on all possible inputs.
A | NOT A |
---|---|
TRUE |
FALSE |
FALSE |
TRUE |
NULL |
NULL |
MISSING |
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.
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.
({"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.
'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> | "_" | "$")* <LETTER> ::= ["A" - "Z", "a" - "z"] DelimitedIdentifier ::= "`" (<EscapeQuot> | <EscapeBslash> | <EscapeSlash> | <EscapeBspace> | <EscapeFormf> | <EscapeNl> | <EscapeCr> | <EscapeTab> | ~["`","\\"])* "`"
A variable in a query can be bound to any legal data model value.
A variable reference refers to the value to which an in-scope variable is bound.
(E.g., a variable binding may originate from one of the FROM
, WITH
or LET
clauses of a SELECT
statement or from
an input parameter in the context of a function body.)
Backticks, for example, id
, are used for delimited identifiers.
Delimiting is needed when a variable’s desired name clashes with a keyword or includes characters not allowed in regular
identifiers.
More information on exactly how variable references are resolved can be found in the appendix section on Variable
Resolution.
tweet id `SELECT` `my-function`
Parameter References
ParameterReference ::= NamedParameterReference | PositionalParameterReference NamedParameterReference ::= "$" (<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.
$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.
( 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.
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.
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.
[ 'a', 'b', 'c', 'c' ] [ 42, "forty-two!", { "rank" : "Captain", "name": "America" }, 3.14159 ] { 'project name': 'Hyracks', 'project members': [ 'vinayakb', 'dtabass', 'chenli', 'tsotras', 'tillw' ] }