Operators in GoogleSQL

GoogleSQL for Spanner supports operators. Operators are represented by special characters or keywords; they don't use function call syntax. An operator manipulates any number of data inputs, also called operands, and returns a result.

Common conventions:

Unless otherwise specified, all operators return NULL when one of the operands is NULL.
All operators will throw an error if the computation result overflows.
For all floating point operations, +/-inf and NaN may only be returned if one of the operands is +/-inf or NaN. In other cases, an error is returned.

When Spanner runs an operator, the operator is treated as a function. Because of this, if an operator produces an error, the error message might use the term function when referencing an operator.

Operator precedence

The following table lists all GoogleSQL operators from highest to lowest precedence, i.e., the order in which they will be evaluated within a statement.

Order of Precedence	Operator	Input Data Types	Name	Operator Arity
1	Field access operator	`STRUCT` `PROTO` `JSON`	Field access operator	Binary
	Array subscript operator	`ARRAY`	Array position. Must be used with `OFFSET` or `ORDINAL`—see Array Functions .	Binary
	JSON subscript operator	`JSON`	Field name or array position in JSON.	Binary
2	`+`	All numeric types	Unary plus	Unary
	`-`	All numeric types	Unary minus	Unary
	`~`	Integer or `BYTES`	Bitwise not	Unary
3	`*`	All numeric types	Multiplication	Binary
	`/`	All numeric types	Division	Binary
	`\|\|`	`STRING`, `BYTES`, or `ARRAY<T>`	Concatenation operator	Binary
4	`+`	All numeric types , `INTERVAL`	Addition	Binary
	`-`	All numeric types , `INTERVAL`	Subtraction	Binary
5	`<<`	Integer or `BYTES`	Bitwise left-shift	Binary
	`>>`	Integer or `BYTES`	Bitwise right-shift	Binary
6	`&`	Integer or `BYTES`	Bitwise and	Binary
7	`^`	Integer or `BYTES`	Bitwise xor	Binary
8	`\|`	Integer or `BYTES`	Bitwise or	Binary
9 (Comparison Operators)	`=`	Any comparable type. See Data Types for a complete list.	Equal	Binary
	`<`	Any comparable type. See Data Types for a complete list.	Less than	Binary
	`>`	Any comparable type. See Data Types for a complete list.	Greater than	Binary
	`<=`	Any comparable type. See Data Types for a complete list.	Less than or equal to	Binary
	`>=`	Any comparable type. See Data Types for a complete list.	Greater than or equal to	Binary
	`!=`, `<>`	Any comparable type. See Data Types for a complete list.	Not equal	Binary
	`[NOT] LIKE`	`STRING` and `BYTES`	Value does [not] match the pattern specified	Binary
	`[NOT] BETWEEN`	Any comparable types. See Data Types for a complete list.	Value is [not] within the range specified	Binary
	`[NOT] IN`	Any comparable types. See Data Types for a complete list.	Value is [not] in the set of values specified	Binary
	`IS [NOT] NULL`	All	Value is [not] `NULL`	Unary
	`IS [NOT] TRUE`	`BOOL`	Value is [not] `TRUE`.	Unary
	`IS [NOT] FALSE`	`BOOL`	Value is [not] `FALSE`.	Unary
10	`NOT`	`BOOL`	Logical `NOT`	Unary
11	`AND`	`BOOL`	Logical `AND`	Binary
12	`OR`	`BOOL`	Logical `OR`	Binary

For example, the logical expression:

x OR y AND z

is interpreted as:

( x OR ( y AND z ) )

Operators with the same precedence are left associative. This means that those operators are grouped together starting from the left and moving right. For example, the expression:

x AND y AND z

is interpreted as:

( ( x AND y ) AND z )

The expression:

x * y / z

is interpreted as:

( ( x * y ) / z )

All comparison operators have the same priority, but comparison operators aren't associative. Therefore, parentheses are required to resolve ambiguity. For example:

(x < y) IS FALSE

Operator list

Name	Summary
Field access operator	Gets the value of a field.
Array subscript operator	Gets a value from an array at a specific position.
JSON subscript operator	Gets a value of an array element or field in a JSON expression.
Arithmetic operators	Performs arithmetic operations.
Datetime subtraction	Computes the difference between two datetimes as an interval.
Interval arithmetic operators	Adds an interval to a datetime or subtracts an interval from a datetime.
Bitwise operators	Performs bit manipulation.
Logical operators	Tests for the truth of some condition and produces `TRUE`, `FALSE`, or `NULL`.
Graph concatenation operator	Combines multiple graph paths into one and preserves the original order of the nodes and edges.
Graph logical operators	Tests for the truth of a condition in a graph and produces either `TRUE` or `FALSE`.
Graph predicates	Tests for the truth of a condition for a graph element and produces `TRUE`, `FALSE`, or `NULL`.
`ALL_DIFFERENT` predicate	In a graph, checks to see if the elements in a list are mutually distinct.
`IS DESTINATION` predicate	In a graph, checks to see if a node is or isn't the destination of an edge.
`IS LABELED` predicate	In a graph, checks to see if a node or edge label satisfies a label expression.
`IS SOURCE` predicate	In a graph, checks to see if a node is or isn't the source of an edge.
`PROPERTY_EXISTS` predicate	In a graph, checks to see if a property exists for an element.
`SAME` predicate	In a graph, checks if all graph elements in a list bind to the same node or edge.
Comparison operators	Compares operands and produces the results of the comparison as a `BOOL` value.
`EXISTS` operator	Checks if a subquery produces one or more rows.
`IN` operator	Checks for an equal value in a set of values.
`IS` operators	Checks for the truth of a condition and produces either `TRUE` or `FALSE`.
`LIKE` operator	Checks if values are like or not like one another.
`NEW` operator	Creates a protocol buffer.
Concatenation operator	Combines multiple values into one.
`WITH` expression	Creates variables for re-use and produces a result expression.

Field access operator

expression.fieldname[. ...]

Description

Gets the value of a field. Alternatively known as the dot operator. Can be used to access nested fields. For example, expression.fieldname1.fieldname2.

Input values:

STRUCT
PROTO
JSON
GRAPH_ELEMENT

Return type

For STRUCT: SQL data type of fieldname. If a field isn't found in the struct, an error is thrown.
For PROTO: SQL data type of fieldname. If a field isn't found in the protocol buffer, an error is thrown.
For JSON: JSON. If a field isn't found in a JSON value, a SQL NULL is returned.
For GRAPH_ELEMENT:
- Without dynamic properties: SQL data type of fieldname. If a field (property) isn't found in the graph element, an error is returned.
- With dynamic properties: SQL data type of fieldname if the field (property) is defined; JSON type if the field (property) is stored as a dynamic property and found in the graph element during query execution; SQL NULL is returned if the field (property) is not found in the graph element. See graph element type for more details about graph elements with dynamic properties.

Example

In the following example, the field access operations are .address and .country.

SELECT
  STRUCT(
    STRUCT('Yonge Street' AS street, 'Canada' AS country)
      AS address).address.country

/*---------*
 | country |
 +---------+
 | Canada  |
 *---------*/

Array subscript operator

array_expression "[" array_subscript_specifier "]"

array_subscript_specifier:
  position_keyword(index)

position_keyword:
  { OFFSET | SAFE_OFFSET | ORDINAL | SAFE_ORDINAL }

Description

Gets a value from an array at a specific position.

Input values:

array_expression: The input array.
position_keyword(index): Determines where the index for the array should start and how out-of-range indexes are handled. The index is an integer that represents a specific position in the array.
- OFFSET(index): The index starts at zero. Produces an error if the index is out of range. To produce NULL instead of an error, use SAFE_OFFSET(index).
- SAFE_OFFSET(index): The index starts at zero. Returns NULL if the index is out of range.
- ORDINAL(index): The index starts at one. Produces an error if the index is out of range. To produce NULL instead of an error, use SAFE_ORDINAL(index).
- SAFE_ORDINAL(index): The index starts at one. Returns NULL if the index is out of range.

Return type

T where array_expression is ARRAY<T>.

Examples

In following query, the array subscript operator is used to return values at specific position in item_array. This query also shows what happens when you reference an index (6) in an array that's out of range. If the SAFE prefix is included, NULL is returned, otherwise an error is produced.

SELECT
  ["coffee", "tea", "milk"] AS item_array,
  ["coffee", "tea", "milk"][OFFSET(0)] AS item_offset,
  ["coffee", "tea", "milk"][ORDINAL(1)] AS item_ordinal,
  ["coffee", "tea", "milk"][SAFE_OFFSET(6)] AS item_safe_offset

/*---------------------+-------------+--------------+------------------*
 | item_array          | item_offset | item_ordinal | item_safe_offset |
 +---------------------+-------------+--------------+------------------+
 | [coffee, tea, milk] | coffee      | coffee       | NULL             |
 *---------------------+-------------+--------------+------------------*/

When you reference an index that's out of range in an array, and a positional keyword that begins with SAFE isn't included, an error is produced. For example:

-- Error. Array index 6 is out of bounds.
SELECT ["coffee", "tea", "milk"][OFFSET(6)] AS item_offset

JSON subscript operator

json_expression "[" array_element_id "]"

json_expression "[" field_name "]"

Description

Gets a value of an array element or field in a JSON expression. Can be used to access nested data.

Input values:

JSON expression: The JSON expression that contains an array element or field to return.
[array_element_id]: An INT64 expression that represents a zero-based index in the array. If a negative value is entered, or the value is greater than or equal to the size of the array, or the JSON expression doesn't represent a JSON array, a SQL NULL is returned.
[field_name]: A STRING expression that represents the name of a field in JSON. If the field name isn't found, or the JSON expression isn't a JSON object, a SQL NULL is returned.

Return type

JSON

Example

In the following example:

json_value is a JSON expression.
.class is a JSON field access.
.students is a JSON field access.
[0] is a JSON subscript expression with an element offset that accesses the zeroth element of an array in the JSON value.
['name'] is a JSON subscript expression with a field name that accesses a field.

SELECT json_value.class.students[0]['name'] AS first_student
FROM
  UNNEST(
    [
      JSON '{"class" : {"students" : [{"name" : "Jane"}]}}',
      JSON '{"class" : {"students" : []}}',
      JSON '{"class" : {"students" : [{"name" : "John"}, {"name": "Jamie"}]}}'])
    AS json_value;

/*-----------------*
 | first_student   |
 +-----------------+
 | "Jane"          |
 | NULL            |
 | "John"          |
 *-----------------*/

Arithmetic operators

All arithmetic operators accept input of numeric type T, and the result type has type T unless otherwise indicated in the description below:

Name	Syntax
Addition	`X + Y`
Subtraction	`X - Y`
Multiplication	`X * Y`
Division	`X / Y`
Unary Plus	`+ X`
Unary Minus	`- X`

NOTE: Divide by zero operations return an error. To return a different result, consider the IEEE_DIVIDE or SAFE_DIVIDE functions.

Result types for Addition, Subtraction and Multiplication:

INPUT	`INT64`	`NUMERIC`	`FLOAT32`	`FLOAT64`
`INT64`	`INT64`	`NUMERIC`	`FLOAT64`	`FLOAT64`
`NUMERIC`	`NUMERIC`	`NUMERIC`	`FLOAT64`	`FLOAT64`
`FLOAT32`	`FLOAT64`	`FLOAT64`	`FLOAT64`	`FLOAT64`
`FLOAT64`	`FLOAT64`	`FLOAT64`	`FLOAT64`	`FLOAT64`

Result types for Division:

INPUT	`INT64`	`NUMERIC`	`FLOAT32`	`FLOAT64`
`INT64`	`FLOAT64`	`NUMERIC`	`FLOAT64`	`FLOAT64`
`NUMERIC`	`NUMERIC`	`NUMERIC`	`FLOAT64`	`FLOAT64`
`FLOAT32`	`FLOAT64`	`FLOAT64`	`FLOAT64`	`FLOAT64`
`FLOAT64`	`FLOAT64`	`FLOAT64`	`FLOAT64`	`FLOAT64`

Result types for Unary Plus:

INPUT	`INT64`	`NUMERIC`	`FLOAT32`	`FLOAT64`
OUTPUT	`INT64`	`NUMERIC`	`FLOAT32`	`FLOAT64`

Result types for Unary Minus:

INPUT	`INT64`	`NUMERIC`	`FLOAT32`	`FLOAT64`
OUTPUT	`INT64`	`NUMERIC`	`FLOAT32`	`FLOAT64`

Datetime subtraction

date_expression - date_expression
timestamp_expression - timestamp_expression

Description

Computes the difference between two datetime values as an interval.

Return Data Type

INTERVAL

Example

SELECT
  DATE "2021-05-20" - DATE "2020-04-19" AS date_diff,
  TIMESTAMP "2021-06-01 12:34:56.789" - TIMESTAMP "2021-05-31 00:00:00" AS time_diff

/*-------------------+------------------------*
 | date_diff         | time_diff              |
 +-------------------+------------------------+
 | 0-0 396 0:0:0     | 0-0 0 36:34:56.789     |
 *-------------------+------------------------*/

Interval arithmetic operators

Addition and subtraction


timestamp_expression + interval_expression = TIMESTAMP
timestamp_expression - interval_expression = TIMESTAMP

Description

Adds an interval to a datetime value or subtracts an interval from a datetime value.

Example

SELECT
  DATE "2021-04-20" + INTERVAL 25 HOUR AS date_plus,
  TIMESTAMP "2021-05-02 00:01:02.345" - INTERVAL 10 SECOND AS time_minus;

/*-------------------------+--------------------------------*
 | date_plus               | time_minus                     |
 +-------------------------+--------------------------------+
 | 2021-04-21 01:00:00     | 2021-05-02 00:00:52.345+00     |
 *-------------------------+--------------------------------*/

Multiplication and division

interval_expression * integer_expression = INTERVAL
interval_expression / integer_expression = INTERVAL

Description

Multiplies or divides an interval value by an integer.

Example

SELECT
  INTERVAL '1:2:3' HOUR TO SECOND * 10 AS mul1,
  INTERVAL 35 SECOND * 4 AS mul2,
  INTERVAL 10 YEAR / 3 AS div1,
  INTERVAL 1 MONTH / 12 AS div2

/*----------------+--------------+-------------+--------------*
 | mul1           | mul2         | div1        | div2         |
 +----------------+--------------+-------------+--------------+
 | 0-0 0 10:20:30 | 0-0 0 0:2:20 | 3-4 0 0:0:0 | 0-0 2 12:0:0 |
 *----------------+--------------+-------------+--------------*/

Bitwise operators

All bitwise operators return the same type and the same length as the first operand.

Name	Syntax	Input Data Type	Description
Bitwise not	`~ X`	Integer or `BYTES`	Performs logical negation on each bit, forming the ones' complement of the given binary value.
Bitwise or	`X \| Y`	`X`: Integer or `BYTES` `Y`: Same type as `X`	Takes two bit patterns of equal length and performs the logical inclusive `OR` operation on each pair of the corresponding bits. This operator throws an error if `X` and `Y` are bytes of different lengths.
Bitwise xor	`X ^ Y`	`X`: Integer or `BYTES` `Y`: Same type as `X`	Takes two bit patterns of equal length and performs the logical exclusive `OR` operation on each pair of the corresponding bits. This operator throws an error if `X` and `Y` are bytes of different lengths.
Bitwise and	`X & Y`	`X`: Integer or `BYTES` `Y`: Same type as `X`	Takes two bit patterns of equal length and performs the logical `AND` operation on each pair of the corresponding bits. This operator throws an error if `X` and `Y` are bytes of different lengths.
Left shift	`X << Y`	`X`: Integer or `BYTES` `Y`: `INT64`	Shifts the first operand `X` to the left. This operator returns `0` or a byte sequence of `b'\x00'` if the second operand `Y` is greater than or equal to the bit length of the first operand `X` (for example, `64` if `X` has the type `INT64`). This operator throws an error if `Y` is negative.
Right shift	`X >> Y`	`X`: Integer or `BYTES` `Y`: `INT64`	Shifts the first operand `X` to the right. This operator doesn't perform sign bit extension with a signed type (i.e., it fills vacant bits on the left with `0`). This operator returns `0` or a byte sequence of `b'\x00'` if the second operand `Y` is greater than or equal to the bit length of the first operand `X` (for example, `64` if `X` has the type `INT64`). This operator throws an error if `Y` is negative.

Logical operators

GoogleSQL supports the AND, OR, and NOT logical operators. Logical operators allow only BOOL or NULL input and use three-valued logic to produce a result. The result can be TRUE, FALSE, or NULL:

`x`	`y`	`x AND y`	`x OR y`
`TRUE`	`TRUE`	`TRUE`	`TRUE`
`TRUE`	`FALSE`	`FALSE`	`TRUE`
`TRUE`	`NULL`	`NULL`	`TRUE`
`FALSE`	`TRUE`	`FALSE`	`TRUE`
`FALSE`	`FALSE`	`FALSE`	`FALSE`
`FALSE`	`NULL`	`FALSE`	`NULL`
`NULL`	`TRUE`	`NULL`	`TRUE`
`NULL`	`FALSE`	`FALSE`	`NULL`
`NULL`	`NULL`	`NULL`	`NULL`

`x`	`NOT x`
`TRUE`	`FALSE`
`FALSE`	`TRUE`
`NULL`	`NULL`

Examples

The examples in this section reference a table called entry_table:

/*-------*
 | entry |
 +-------+
 | a     |
 | b     |
 | c     |
 | NULL  |
 *-------*/

SELECT 'a' FROM entry_table WHERE entry = 'a'

-- a => 'a' = 'a' => TRUE
-- b => 'b' = 'a' => FALSE
-- NULL => NULL = 'a' => NULL

/*-------*
 | entry |
 +-------+
 | a     |
 *-------*/

SELECT entry FROM entry_table WHERE NOT (entry = 'a')

-- a => NOT('a' = 'a') => NOT(TRUE) => FALSE
-- b => NOT('b' = 'a') => NOT(FALSE) => TRUE
-- NULL => NOT(NULL = 'a') => NOT(NULL) => NULL

/*-------*
 | entry |
 +-------+
 | b     |
 | c     |
 *-------*/

SELECT entry FROM entry_table WHERE entry IS NULL

-- a => 'a' IS NULL => FALSE
-- b => 'b' IS NULL => FALSE
-- NULL => NULL IS NULL => TRUE

/*-------*
 | entry |
 +-------+
 | NULL  |
 *-------*/

Graph concatenation operator

graph_path || graph_path [ || ... ]

Description

Combines multiple graph paths into one and preserves the original order of the nodes and edges.

Arguments:

graph_path: A GRAPH_PATH value that represents a graph path to concatenate.

Details

This operator produces an error if the last node in the first path isn't the same as the first node in the second path.

-- This successfully produces the concatenated path called `full_path`.
MATCH
  p=(src:Account)-[t1:Transfers]->(mid:Account),
  q=(mid)-[t2:Transfers]->(dst:Account)
LET full_path = p || q

-- This produces an error because the first node of the path to be concatenated
-- (mid2) isn't equal to the last node of the previous path (mid1).
MATCH
  p=(src:Account)-[t1:Transfers]->(mid1:Account),
  q=(mid2:Account)-[t2:Transfers]->(dst:Account)
LET full_path = p || q

The first node in each subsequent path is removed from the concatenated path.

-- The concatenated path called `full_path` contains these elements:
-- src, t1, mid, t2, dst.
MATCH
  p=(src:Account)-[t1:Transfers]->(mid:Account),
  q=(mid)-[t2:Transfers]->(dst:Account)
LET full_path = p || q

If any graph_path is NULL, produces NULL.

Example

In the following query, a path called p and q are concatenated. Notice that mid is used at the end of the first path and at the beginning of the second path. Also notice that the duplicate mid is removed from the concatenated path called full_path:

GRAPH FinGraph
MATCH
  p=(src:Account)-[t1:Transfers]->(mid:Account),
  q = (mid)-[t2:Transfers]->(dst:Account)
LET full_path = p || q
RETURN
  JSON_QUERY(TO_JSON(full_path)[0], '$.labels') AS element_a,
  JSON_QUERY(TO_JSON(full_path)[1], '$.labels') AS element_b,
  JSON_QUERY(TO_JSON(full_path)[2], '$.labels') AS element_c,
  JSON_QUERY(TO_JSON(full_path)[3], '$.labels') AS element_d,
  JSON_QUERY(TO_JSON(full_path)[4], '$.labels') AS element_e,
  JSON_QUERY(TO_JSON(full_path)[5], '$.labels') AS element_f

/*-------------------------------------------------------------------------------------*
 | element_a   | element_b     | element_c   | element_d     | element_e   | element_f |
 +-------------------------------------------------------------------------------------+
 | ["Account"] | ["Transfers"] | ["Account"] | ["Transfers"] | ["Account"] |           |
 | ...         | ...           | ...         | ...           | ...         | ...       |
 *-------------------------------------------------------------------------------------/*

The following query produces an error because the last node for p must be the first node for q:

-- Error: `mid1` and `mid2` aren't equal.
GRAPH FinGraph
MATCH
  p=(src:Account)-[t1:Transfers]->(mid1:Account),
  q=(mid2:Account)-[t2:Transfers]->(dst:Account)
LET full_path = p || q
RETURN TO_JSON(full_path) AS results

The following query produces an error because the path called p is NULL:

-- Error: a graph path is NULL.
GRAPH FinGraph
MATCH
  p=NULL,
  q=(mid:Account)-[t2:Transfers]->(dst:Account)
LET full_path = p || q
RETURN TO_JSON(full_path) AS results

Graph logical operators

GoogleSQL supports the following logical operators in element pattern label expressions:

Name	Syntax	Description
`NOT`	`!X`	Returns `TRUE` if `X` isn't included, otherwise, returns `FALSE`.
`OR`	`X \| Y`	Returns `TRUE` if either `X` or `Y` is included, otherwise, returns `FALSE`.
`AND`	`X & Y`	Returns `TRUE` if both `X` and `Y` are included, otherwise, returns `FALSE`.

Graph predicates

GoogleSQL supports the following graph-specific predicates in graph expressions. A predicate can produce TRUE, FALSE, or NULL.

ALL_DIFFERENT predicate
PROPERTY_EXISTS predicate
IS SOURCE predicate
IS DESTINATION predicate
IS LABELED predicate
SAME predicate

`ALL_DIFFERENT` predicate

ALL_DIFFERENT(element, element[, ...])

Description

In a graph, checks to see if the elements in a list are mutually distinct. Returns TRUE if the elements are distinct, otherwise FALSE.

Definitions

element: The graph pattern variable for a node or edge element.

Details

Produces an error if element is NULL.

Return type

BOOL

Examples

GRAPH FinGraph
MATCH
  (a1:Account)-[t1:Transfers]->(a2:Account)-[t2:Transfers]->
  (a3:Account)-[t3:Transfers]->(a4:Account)
WHERE a1.id < a4.id
RETURN
  ALL_DIFFERENT(t1, t2, t3) AS results

/*---------+
 | results |
 +---------+
 | FALSE   |
 | TRUE    |
 | TRUE    |
 +---------*/

`IS DESTINATION` predicate

node IS [ NOT ] DESTINATION [ OF ] edge

Description

In a graph, checks to see if a node is or isn't the destination of an edge. Can produce TRUE, FALSE, or NULL.

Arguments:

node: The graph pattern variable for the node element.
edge: The graph pattern variable for the edge element.

Examples

GRAPH FinGraph
MATCH (a:Account)-[transfer:Transfers]-(b:Account)
WHERE a IS DESTINATION of transfer
RETURN a.id AS a_id, b.id AS b_id

/*-------------+
 | a_id | b_id |
 +-------------+
 | 16   | 7    |
 | 16   | 7    |
 | 20   | 16   |
 | 7    | 20   |
 | 16   | 20   |
 +-------------*/

GRAPH FinGraph
MATCH (a:Account)-[transfer:Transfers]-(b:Account)
WHERE b IS DESTINATION of transfer
RETURN a.id AS a_id, b.id AS b_id

/*-------------+
 | a_id | b_id |
 +-------------+
 | 7    | 16   |
 | 7    | 16   |
 | 16   | 20   |
 | 20   | 7    |
 | 20   | 16   |
 +-------------*/

`IS LABELED` predicate

element IS [ NOT ] LABELED label_expression

Description

In a graph, checks to see if a node or edge label satisfies a label expression. Can produce TRUE, FALSE, or NULL if element is NULL.

Arguments:

element: The graph pattern variable for a graph node or edge element.
label_expression: The label expression to verify. For more information, see Label expression definition.

Examples

GRAPH FinGraph
MATCH (a)
WHERE a IS LABELED Account | Person
RETURN a.id AS a_id, LABELS(a) AS labels

/*----------------+
 | a_id | labels  |
 +----------------+
 | 1    | Person  |
 | 2    | Person  |
 | 3    | Person  |
 | 7    | Account |
 | 16   | Account |
 | 20   | Account |
 +----------------*/

GRAPH FinGraph
MATCH (a)-[e]-(b:Account)
WHERE e IS LABELED Transfers | Owns
RETURN a.Id as a_id, Labels(e) AS labels, b.Id as b_id
ORDER BY a_id, b_id

/*------+-----------------------+------+
 | a_id | labels                | b_id |
 +------+-----------------------+------+
 |    1 | [owns]                |    7 |
 |    2 | [owns]                |   20 |
 |    3 | [owns]                |   16 |
 |    7 | [transfers]           |   16 |
 |    7 | [transfers]           |   16 |
 |    7 | [transfers]           |   20 |
 |   16 | [transfers]           |    7 |
 |   16 | [transfers]           |    7 |
 |   16 | [transfers]           |   20 |
 |   16 | [transfers]           |   20 |
 |   20 | [transfers]           |    7 |
 |   20 | [transfers]           |   16 |
 |   20 | [transfers]           |   16 |
 +------+-----------------------+------*/

GRAPH FinGraph
MATCH (a:Account {Id: 7})
OPTIONAL MATCH (a)-[:OWNS]->(b)
RETURN a.Id AS a_id, b.Id AS b_id, b IS LABELED Account AS b_is_account

/*------+-----------------------+
 | a_id | b_id   | b_is_account |
 +------+-----------------------+
 | 7    | NULL   | NULL         |
 +------+-----------------------+*/

`IS SOURCE` predicate

node IS [ NOT ] SOURCE [ OF ] edge

Description

In a graph, checks to see if a node is or isn't the source of an edge. Can produce TRUE, FALSE, or NULL.

Arguments:

node: The graph pattern variable for the node element.
edge: The graph pattern variable for the edge element.

Examples

GRAPH FinGraph
MATCH (a:Account)-[transfer:Transfers]-(b:Account)
WHERE a IS SOURCE of transfer
RETURN a.id AS a_id, b.id AS b_id

/*-------------+
 | a_id | b_id |
 +-------------+
 | 20   | 7    |
 | 7    | 16   |
 | 7    | 16   |
 | 20   | 16   |
 | 16   | 20   |
 +-------------*/

GRAPH FinGraph
MATCH (a:Account)-[transfer:Transfers]-(b:Account)
WHERE b IS SOURCE of transfer
RETURN a.id AS a_id, b.id AS b_id

/*-------------+
 | a_id | b_id |
 +-------------+
 | 7    | 20   |
 | 16   | 7    |
 | 16   | 7    |
 | 16   | 20   |
 | 20   | 16   |
 +-------------*/

`PROPERTY_EXISTS` predicate

PROPERTY_EXISTS(element, element_property)

Description

In a graph, checks to see if a property exists for an element. Can produce TRUE, FALSE, or NULL.

Arguments:

element: The graph pattern variable for a node or edge element.
element_property: The name of the property to look for in element. The property name must refer to a property in the graph. If the property doesn't exist in the graph, an error is produced. The property name is resolved in a case-insensitive manner.

Example

GRAPH FinGraph
MATCH (n:Person|Account WHERE PROPERTY_EXISTS(n, name))
RETURN n.name

/*------+
 | name |
 +------+
 | Alex |
 | Dana |
 | Lee  |
 +------*/

`SAME` predicate

SAME (element, element[, ...])

Description

In a graph, checks if all graph elements in a list bind to the same node or edge. Returns TRUE if the elements bind to the same node or edge, otherwise FALSE.

Arguments:

element: The graph pattern variable for a node or edge element.

Details

Produces an error if element is NULL.

Example

The following query checks to see if a and b aren't the same person.

GRAPH FinGraph
MATCH (src:Account)<-[transfer:Transfers]-(dest:Account)
WHERE NOT SAME(src, dest)
RETURN src.id AS source_id, dest.id AS destination_id

/*----------------------------+
 | source_id | destination_id |
 +----------------------------+
 | 7         | 20             |
 | 16        | 7              |
 | 16        | 7              |
 | 16        | 20             |
 | 20        | 16             |
 +----------------------------*/

Comparison operators

Compares operands and produces the results of the comparison as a BOOL value. These comparison operators are available:

Name	Syntax	Description
Less Than	`X < Y`	Returns `TRUE` if `X` is less than `Y`.
Less Than or Equal To	`X <= Y`	Returns `TRUE` if `X` is less than or equal to `Y`.
Greater Than	`X > Y`	Returns `TRUE` if `X` is greater than `Y`.
Greater Than or Equal To	`X >= Y`	Returns `TRUE` if `X` is greater than or equal to `Y`.
Equal	`X = Y`	Returns `TRUE` if `X` is equal to `Y`.
Not Equal	`X != Y` `X <> Y`	Returns `TRUE` if `X` isn't equal to `Y`.
`BETWEEN`	`X [NOT] BETWEEN Y AND Z`	Returns `TRUE` if `X` is [not] within the range specified. The result of `X BETWEEN Y AND Z` is equivalent to `Y <= X AND X <= Z` but `X` is evaluated only once in the former.
`LIKE`	`X [NOT] LIKE Y`	See the `LIKE` operator for details.
`IN`	Multiple	See the `IN` operator for details.

The following rules apply to operands in a comparison operator:

The operands must be comparable.
A comparison operator generally requires both operands to be of the same type.
If the operands are of different types, and the values of those types can be converted to a common type without loss of precision, they are generally coerced to that common type for the comparison.
A literal operand is generally coerced to the same data type of a non-literal operand that's part of the comparison.
Struct operands support only these comparison operators: equal (=), not equal (!= and <>), and IN.

The following rules apply when comparing these data types:

Floating point: All comparisons with NaN return FALSE, except for != and <>, which return TRUE.
BOOL: FALSE is less than TRUE.
STRING: Strings are compared codepoint-by-codepoint, which means that canonically equivalent strings are only guaranteed to compare as equal if they have been normalized first.
JSON: You can't compare JSON, but you can compare the values inside of JSON if you convert the values to SQL values first. For more information, see JSON functions.
NULL: Any operation with a NULL input returns NULL.

STRUCT: When testing a struct for equality, it's possible that one or more fields are NULL. In such cases:

If all non-NULL field values are equal, the comparison returns NULL.
If any non-NULL field values aren't equal, the comparison returns FALSE.

The following table demonstrates how STRUCT data types are compared when they have fields that are NULL valued.

Struct1	Struct2	Struct1 = Struct2
`STRUCT(1, NULL)`	`STRUCT(1, NULL)`	`NULL`
`STRUCT(1, NULL)`	`STRUCT(2, NULL)`	`FALSE`
`STRUCT(1,2)`	`STRUCT(1, NULL)`	`NULL`

`EXISTS` operator

EXISTS( subquery )

Description

Returns TRUE if the subquery produces one or more rows. Returns FALSE if the subquery produces zero rows. Never returns NULL. To learn more about how you can use a subquery with EXISTS, see EXISTS subqueries.

Examples

In this example, the EXISTS operator returns FALSE because there are no rows in Words where the direction is south:

WITH Words AS (
  SELECT 'Intend' as value, 'east' as direction UNION ALL
  SELECT 'Secure', 'north' UNION ALL
  SELECT 'Clarity', 'west'
 )
SELECT EXISTS( SELECT value FROM Words WHERE direction = 'south' ) as result;

/*--------*
 | result |
 +--------+
 | FALSE  |
 *--------*/

`IN` operator

The IN operator supports the following syntax:

search_value [NOT] IN value_set

value_set:
  {
    (expression[, ...])
    | (subquery)
    | UNNEST(array_expression)
  }

Description

Checks for an equal value in a set of values. Semantic rules apply, but in general, IN returns TRUE if an equal value is found, FALSE if an equal value is excluded, otherwise NULL. NOT IN returns FALSE if an equal value is found, TRUE if an equal value is excluded, otherwise NULL.

search_value: The expression that's compared to a set of values.
value_set: One or more values to compare to a search value.
- (expression[, ...]): A list of expressions.
- (subquery): A subquery that returns a single column. The values in that column are the set of values. If no rows are produced, the set of values is empty.
- UNNEST(array_expression): An UNNEST operator that returns a column of values from an array expression. This is equivalent to:
```
IN (SELECT element FROM UNNEST(array_expression) AS element)
```

This operator generally supports collation, however, [NOT] IN UNNEST doesn't support collation.

Semantic rules

When using the IN operator, the following semantics apply in this order:

Returns FALSE if value_set is empty.
Returns NULL if search_value is NULL.
Returns TRUE if value_set contains a value equal to search_value.
Returns NULL if value_set contains a NULL.
Returns FALSE.

When using the NOT IN operator, the following semantics apply in this order:

Returns TRUE if value_set is empty.
Returns NULL if search_value is NULL.
Returns FALSE if value_set contains a value equal to search_value.
Returns NULL if value_set contains a NULL.
Returns TRUE.

The semantics of:

x IN (y, z, ...)

are defined as equivalent to:

(x = y) OR (x = z) OR ...

and the subquery and array forms are defined similarly.

x NOT IN ...

is equivalent to:

NOT(x IN ...)

The UNNEST form treats an array scan like UNNEST in the FROM clause:

x [NOT] IN UNNEST(<array expression>)

This form is often used with array parameters. For example:

x IN UNNEST(@array_parameter)

See the Arrays topic for more information on how to use this syntax.

IN can be used with multi-part keys by using the struct constructor syntax. For example:

(Key1, Key2) IN ( (12,34), (56,78) )
(Key1, Key2) IN ( SELECT (table.a, table.b) FROM table )

See the Struct Type topic for more information.

Return Data Type

BOOL

Examples

You can use these WITH clauses to emulate temporary tables for Words and Items in the following examples:

WITH Words AS (
  SELECT 'Intend' as value UNION ALL
  SELECT 'Secure' UNION ALL
  SELECT 'Clarity' UNION ALL
  SELECT 'Peace' UNION ALL
  SELECT 'Intend'
 )
SELECT * FROM Words;

/*----------*
 | value    |
 +----------+
 | Intend   |
 | Secure   |
 | Clarity  |
 | Peace    |
 | Intend   |
 *----------*/

WITH
  Items AS (
    SELECT STRUCT('blue' AS color, 'round' AS shape) AS info UNION ALL
    SELECT STRUCT('blue', 'square') UNION ALL
    SELECT STRUCT('red', 'round')
  )
SELECT * FROM Items;

/*----------------------------*
 | info                       |
 +----------------------------+
 | {blue color, round shape}  |
 | {blue color, square shape} |
 | {red color, round shape}   |
 *----------------------------*/

Example with IN and an expression:

SELECT * FROM Words WHERE value IN ('Intend', 'Secure');

/*----------*
 | value    |
 +----------+
 | Intend   |
 | Secure   |
 | Intend   |
 *----------*/

Example with NOT IN and an expression:

SELECT * FROM Words WHERE value NOT IN ('Intend');

/*----------*
 | value    |
 +----------+
 | Secure   |
 | Clarity  |
 | Peace    |
 *----------*/

Example with IN, a scalar subquery, and an expression:

SELECT * FROM Words WHERE value IN ((SELECT 'Intend'), 'Clarity');

/*----------*
 | value    |
 +----------+
 | Intend   |
 | Clarity  |
 | Intend   |
 *----------*/

Example with IN and an UNNEST operation:

SELECT * FROM Words WHERE value IN UNNEST(['Secure', 'Clarity']);

/*----------*
 | value    |
 +----------+
 | Secure   |
 | Clarity  |
 *----------*/

Example with IN and a struct:

SELECT
  (SELECT AS STRUCT Items.info) as item
FROM
  Items
WHERE (info.shape, info.color) IN (('round', 'blue'));

/*------------------------------------*
 | item                               |
 +------------------------------------+
 | { {blue color, round shape} info } |
 *------------------------------------*/

`IS` operators

IS operators return TRUE or FALSE for the condition they are testing. They never return NULL, even for NULL inputs, unlike the IS_INF and IS_NAN functions defined in Mathematical Functions. If NOT is present, the output BOOL value is inverted.

Function Syntax	Input Data Type	Result Data Type	Description
`X IS TRUE`	`BOOL`	`BOOL`	Evaluates to `TRUE` if `X` evaluates to `TRUE`. Otherwise, evaluates to `FALSE`.
`X IS NOT TRUE`	`BOOL`	`BOOL`	Evaluates to `FALSE` if `X` evaluates to `TRUE`. Otherwise, evaluates to `TRUE`.
`X IS FALSE`	`BOOL`	`BOOL`	Evaluates to `TRUE` if `X` evaluates to `FALSE`. Otherwise, evaluates to `FALSE`.
`X IS NOT FALSE`	`BOOL`	`BOOL`	Evaluates to `FALSE` if `X` evaluates to `FALSE`. Otherwise, evaluates to `TRUE`.
`X IS NULL`	Any value type	`BOOL`	Evaluates to `TRUE` if `X` evaluates to `NULL`. Otherwise evaluates to `FALSE`.
`X IS NOT NULL`	Any value type	`BOOL`	Evaluates to `FALSE` if `X` evaluates to `NULL`. Otherwise evaluates to `TRUE`.
`X IS UNKNOWN`	`BOOL`	`BOOL`	Evaluates to `TRUE` if `X` evaluates to `NULL`. Otherwise evaluates to `FALSE`.
`X IS NOT UNKNOWN`	`BOOL`	`BOOL`	Evaluates to `FALSE` if `X` evaluates to `NULL`. Otherwise, evaluates to `TRUE`.

`LIKE` operator

expression_1 [NOT] LIKE expression_2

Description

LIKE returns TRUE if the string in the first operand expression_1 matches a pattern specified by the second operand expression_2, otherwise returns FALSE.

NOT LIKE returns TRUE if the string in the first operand expression_1 doesn't match a pattern specified by the second operand expression_2, otherwise returns FALSE.

Expressions can contain these characters:

A percent sign (%) matches any number of characters or bytes.
An underscore (_) matches a single character or byte.
You can escape \, _, or % using two backslashes. For example, \\%. If you are using raw strings, only a single backslash is required. For example, r'\%'.

Return type

BOOL

Examples

The following examples illustrate how you can check to see if the string in the first operand matches a pattern specified by the second operand.

-- Returns TRUE
SELECT 'apple' LIKE 'a%';

-- Returns FALSE
SELECT '%a' LIKE 'apple';

-- Returns FALSE
SELECT 'apple' NOT LIKE 'a%';

-- Returns TRUE
SELECT '%a' NOT LIKE 'apple';

-- Produces an error
SELECT NULL LIKE 'a%';

-- Produces an error
SELECT 'apple' LIKE NULL;

The following example illustrates how to search multiple patterns in an array to find a match with the LIKE operator:

WITH Words AS
 (SELECT 'Intend with clarity.' as value UNION ALL
  SELECT 'Secure with intention.' UNION ALL
  SELECT 'Clarity and security.')
SELECT value
FROM Words
WHERE ARRAY_INCLUDES(['%ity%', '%and%'], pattern->(Words.value LIKE pattern));

/*------------------------+
 | value                  |
 +------------------------+
 | Intend with clarity.   |
 | Clarity and security.  |
 +------------------------*/

`NEW` operator

The NEW operator only supports protocol buffers and uses the following syntax:

NEW protocol_buffer {...}: Creates a protocol buffer using a map constructor.

NEW protocol_buffer {
  field_name: literal_or_expression
  field_name { ... }
  repeated_field_name: [literal_or_expression, ... ]
}

NEW protocol_buffer (...): Creates a protocol buffer using a parenthesized list of arguments.
```
NEW protocol_buffer(field [AS alias], ...field [AS alias])
```

Examples

The following example uses the NEW operator with a map constructor:

NEW Universe {
  name: "Sol"
  closest_planets: ["Mercury", "Venus", "Earth" ]
  star {
    radius_miles: 432,690
    age: 4,603,000,000
  }
  constellations: [{
    name: "Libra"
    index: 0
  }, {
    name: "Scorpio"
    index: 1
  }]
  all_planets: (SELECT planets FROM SolTable)
}

The following example uses the NEW operator with a parenthesized list of arguments:

SELECT
  key,
  name,
  NEW googlesql.examples.music.Chart(key AS rank, name AS chart_name)
FROM
  (SELECT 1 AS key, "2" AS name);

To learn more about protocol buffers in GoogleSQL, see Work with protocol buffers.

Concatenation operator

The concatenation operator combines multiple values into one.

Function Syntax	Input Data Type	Result Data Type
`STRING \|\| STRING [ \|\| ... ]`	`STRING`	`STRING`
`BYTES \|\| BYTES [ \|\| ... ]`	`BYTES`	`BYTES`
`ARRAY<T> \|\| ARRAY<T> [ \|\| ... ]`	`ARRAY<T>`	`ARRAY<T>`

`WITH` expression

WITH(variable_assignment[, ...], result_expression)

variable_assignment:
  variable_name AS expression

Description

Create one or more variables. Each variable can be used in subsequent expressions within the WITH expression. Returns the value of result_expression.

variable_assignment: Introduces a variable. The variable name must be unique within a given WITH expression. Each expression can reference the variables that come before it. For example, if you create variable a, then follow it with variable b, you can reference a inside of b's expression.
- variable_name: The name of the variable.
- expression: The value to assign to the variable.
result_expression: An expression that's the WITH expression's result. result_expression can use all of the variables defined before it.

Return Type

The type of the result_expression.

Requirements and Caveats

A given variable may only be assigned once in a given WITH clause.
Variables created during WITH may not be used in aggregate function arguments. For example, WITH(a AS ..., SUM(a)) produces an error.
Volatile expressions behave as if they are evaluated only once.

Examples

The following example first concatenates variable a with b, then variable b with c:

SELECT WITH(a AS '123',               -- a is '123'
            b AS CONCAT(a, '456'),    -- b is '123456'
            c AS '789',               -- c is '789'
            CONCAT(b, c)) AS result;  -- b + c is '123456789'

/*-------------*
 | result      |
 +-------------+
 | '123456789' |
 *-------------*/

Aggregate function results can be stored in variables. In this example, an average is computed:

SELECT WITH(s AS SUM(input), c AS COUNT(input), s/c)
FROM UNNEST([1.0, 2.0, 3.0]) AS input;

/*---------*
 | result  |
 +---------+
 | 2.0     |
 *---------*/

Variables can't be used in aggregate function call arguments:

SELECT WITH(diff AS a - b, AVG(diff))
FROM UNNEST([
              STRUCT(1 AS a, 2 AS b),
              STRUCT(3 AS a, 4 AS b),
              STRUCT(5 AS a, 6 AS b),
            ]);

-- ERROR: WITH variables like 'diff' can't be used in aggregate or analytic
-- function arguments.

Operators in GoogleSQL Stay organized with collections Save and categorize content based on your preferences.

Operator precedence

Operator list

Field access operator

Array subscript operator

JSON subscript operator

Arithmetic operators

Datetime subtraction

Interval arithmetic operators

Bitwise operators

Logical operators

Graph concatenation operator

Graph logical operators

Graph predicates

ALL_DIFFERENT predicate

IS DESTINATION predicate

IS LABELED predicate

IS SOURCE predicate

PROPERTY_EXISTS predicate

SAME predicate

Comparison operators

EXISTS operator

IN operator

IS operators

LIKE operator

NEW operator

Concatenation operator

WITH expression

Operators in GoogleSQL

`ALL_DIFFERENT` predicate

`IS DESTINATION` predicate

`IS LABELED` predicate

`IS SOURCE` predicate

`PROPERTY_EXISTS` predicate

`SAME` predicate

`EXISTS` operator

`IN` operator

`IS` operators

`LIKE` operator

`NEW` operator

`WITH` expression