Most SQL statements can contain *scalar expressions* that compute new
values from data. For example, in the query ```
SELECT ceil(price) FROM
items
```

, the expression `ceil(price)`

computes the rounded-up value of
the values from the `price`

column.

Scalar expressions produce values suitable to store in a single table cell (one column of one row). They can be contrasted with table expressions and selection queries, which produce results structured as a table.

The following sections provide details on each of these options.

## Constants

Constant expressions represent a simple value that doesn't change. They are described further in section SQL Constants.

## Column references

An expression in a query can refer to columns in the current data source in two ways:

Using the name of the column, e.g.,

`price`

in`SELECT price FROM items`

.- If the name of a column is also a
SQL keyword, the name
must be appropriately quoted. For example:
`SELECT "Default" FROM configuration`

. - If the name is ambiguous (e.g., when joining across multiple
tables), it is possible to disambiguate by prefixing the column
name by the table name. For example,
`SELECT items.price FROM items`

.

- If the name of a column is also a
SQL keyword, the name
must be appropriately quoted. For example:
Using the ordinal position of the column. For example,

`SELECT @1 FROM items`

selects the first column in`items`

.

*This is a CockroachDB SQL extension.*

## Unary and binary operations

An expression prefixed by a unary operator, or two expressions separated by a binary operator, form a new expression.

For a full list of CockroachDB operators, with details about their order of precedence and which data types are valid operands for each operator, see Functions and Operators.

### Value comparisons

The standard operators `<`

(smaller than), `>`

(greater than), `<=`

(lower than or equal to), `>=`

(greater than or equal to), `=`

(equals), `<>`

and `!=`

(not equal to), `IS`

(identical to), and ```
IS
NOT
```

(not identical to) can be applied to any pair of values from a
single data type, as well as some pairs of values from different data
types.

See also this section over which data types are valid operands for each operator.

The following special rules apply:

`NULL`

is always ordered smaller than every other value, even itself.`NULL`

is never equal to anything via`=`

, even`NULL`

. To check whether a value is`NULL`

, use the`IS`

operator or the conditional expression`IFNULL(..)`

.

See also NULLs and Ternary Logic.

#### Typing rule

All comparisons accept any combination of argument types and result in type `BOOL`

.

#### Comparison with `NaN`

CockroachDB recognizes the special value `NaN`

(Not-a-Number) for scalars of
type `FLOAT`

or `DECIMAL`

.

As per the IEEE 754
standard, `NaN`

is considered to be different from every other numeric
value in comparisons.

There are two exceptions however, made for compatibility with PostgreSQL:

`NaN`

is considered to be equal with itself in comparisons. IEEE 754 specifies that`NaN`

is different from itself.`NaN`

is considered to be smaller than every other value, including`-INFINITY`

. IEEE 754 specifies that`NaN`

does not order with any other value, i.e.,`x <= NaN`

and`x >= NaN`

are both false for every value of`x`

including infinities.

These exceptions exist so that the value `NaN`

can be used in `WHERE`

clauses and indexes.

For example:

```
> SELECT FLOAT 'NaN' < 1, 1 < FLOAT 'NaN', FLOAT 'NaN' < FLOAT 'NaN';
```

```
?column? | ?column? | ?column?
-----------+----------+-----------
true | false | false
(1 row)
```

```
> SELECT FLOAT 'NaN' = FLOAT 'NaN' AS result;
```

```
result
----------
true
(1 row)
```

```
> SELECT FLOAT 'NaN' < FLOAT '-INFINITY' AS result;
```

```
result
----------
true
(1 row)
```

### Multi-valued comparisons

Syntax:

```
<expr> <comparison> ANY <expr>
<expr> <comparison> SOME <expr>
<expr> <comparison> ALL <expr>
```

The value comparison operators `<`

, `>`

, `=`

, `<=`

, `>=`

, `<>`

and
`!=`

, as well as the pattern matching operators `[NOT] LIKE`

and
`[NOT] ILIKE`

, can be applied to compare a single value on the left to
multiple values on the right.

This is done by combining the operator using the keywords `ANY`

/`SOME`

or `ALL`

.

The right operand can be either an array, a tuple or subquery.

The result of the comparison is true if and only if:

- For
`ANY`

/`SOME`

, the comparison of the left value is true for any element on the right. - For
`ALL`

, the comparison of the left value is true for every element on the right.

For example:

```
> SELECT 12 = ANY (10, 12, 13);
```

```
?column?
------------
true
(1 row)
```

```
> SELECT 12 = ALL (10, 12, 13);
```

```
?column?
------------
false
(1 row)
```

```
> SELECT 1 = ANY ARRAY[2, 3, 1];
```

```
?column?
------------
true
(1 row)
```

#### Typing rule

The comparison between the type on the left and the element type of the right operand must be possible.

### Set membership

Syntax:

```
<expr> IN <expr>
<expr> IN ( ... subquery ... )
<expr> NOT IN <expr>
<expr> NOT IN ( ... subquery ... )
```

Returns `TRUE`

if and only if the value of the left operand is part of
the result of evaluating the right operand. In the subquery form, any
selection query can be used.

For example:

```
> SELECT a IN (1, 2, 3) FROM sometable;
```

```
> SELECT a IN (SELECT * FROM allowedvalues) FROM sometable;
```

```
> SELECT ('x', 123) IN (SELECT * FROM rows);
```

#### Typing rule

`IN`

requires its right operand to be a homogeneous tuple type and its left operand
to match the tuple element type. The result has type `BOOL`

.

### String pattern matching

Syntax:

```
<expr> LIKE <expr>
<expr> ILIKE <expr>
<expr> NOT LIKE <expr>
<expr> NOT ILIKE <expr>
```

Evaluates both expressions as strings, then tests whether the string on the left
matches the pattern given on the right. Returns `TRUE`

if a match is found
or `FALSE`

otherwise, or the inverted value for the `NOT`

variants.

Patterns can contain `_`

to match any single
character, or `%`

to match any sequence of zero or more characters.
`ILIKE`

causes the match to be tested case-insensitively.

For example:

```
> SELECT 'monday' LIKE '%day' AS a, 'tuesday' LIKE 'tue_day' AS b, 'wednesday' ILIKE 'W%' AS c;
```

```
a | b | c
-------+------+-------
true | true | true
(1 row)
```

#### Typing rule

The operands must be either both `STRING`

or both `BYTES`

. The result has type `BOOL`

.

### String matching using POSIX regular expressions

Syntax:

```
<expr> ~ <expr>
<expr> ~* <expr>
<expr> !~ <expr>
<expr> !~* <expr>
```

Evaluates both expressions as strings, then tests whether the string
on the left matches the pattern given on the right. Returns `TRUE`

if
a match is found or `FALSE`

otherwise, or the inverted value for the
`!`

variants.

The variants with an asterisk `*`

use case-insensitive matching;
otherwise the matching is case-sensitive.

The pattern is expressed using
POSIX regular expression syntax. Unlike
`LIKE`

patterns, a regular expression is allowed to match anywhere
inside a string, not only at the beginning.

For example:

```
> SELECT 'monday' ~ 'onday' AS a, 'tuEsday' ~ 't[uU][eE]sday' AS b, 'wednesday' ~* 'W.*y' AS c;
```

```
a | b | c
-------+------+-------
true | true | true
(1 row)
```

#### Typing rule

The operands must be either both `STRING`

or both `BYTES`

. The result has type `BOOL`

.

### String matching using SQL regular expressions

Syntax:

```
<expr> SIMILAR TO <expr>
<expr> NOT SIMILAR TO <expr>
```

Evaluates both expressions as strings, then tests whether the string on the left
matches the pattern given on the right. Returns `TRUE`

if a match is found
or `FALSE`

otherwise, or the inverted value for the `NOT`

variant.

The pattern is expressed using the SQL standard's definition of a regular expression.
This is a mix of SQL `LIKE`

patterns and POSIX regular expressions:

`_`

and`%`

denote any character or any string, respectively.`.`

matches specifically the period character, unlike in POSIX where it is a wildcard.- Most of the other POSIX syntax applies as usual.
- The pattern matches the entire string (as in
`LIKE`

, unlike POSIX regular expressions).

For example:

```
> SELECT 'monday' SIMILAR TO '_onday' AS a, 'tuEsday' SIMILAR TO 't[uU][eE]sday' AS b, 'wednesday' SIMILAR TO 'w%y' AS c;
```

```
a | b | c
-------+------+-------
true | true | true
(1 row)
```

#### Typing rule

The operands must be either both `STRING`

or both `BYTES`

. The result has type `BOOL`

.

## Function calls and SQL special forms

General syntax:

```
<name> ( <arguments...> )
```

A built-in function name followed by an opening parenthesis, followed by a comma-separated list of expressions, followed by a closing parenthesis.

This applies the named function to the arguments between parentheses. When the function's namespace is not prefixed, the name resolution rules determine which function is called.

See also the separate section on supported built-in functions.

In addition, the following SQL special forms are also supported:

Special form | Equivalent to |
---|---|

`AT TIME ZONE` |
`timezone()` |

`CURRENT_CATALOG` |
`current_catalog()` |

`COLLATION FOR` |
`pg_collation_for()` |

`CURRENT_DATE` |
`current_date()` |

`CURRENT_ROLE` |
`current_user()` |

`CURRENT_SCHEMA` |
`current_schema()` |

`CURRENT_TIMESTAMP` |
`current_timestamp()` |

`CURRENT_TIME` |
`current_time()` |

`CURRENT_USER` |
`current_user()` |

`EXTRACT(<part> FROM <value>)` |
`extract("<part>", <value>)` |

`EXTRACT_DURATION(<part> FROM <value>)` |
`extract_duration("<part>", <value>)` |

`OVERLAY(<text1> PLACING <text2> FROM <int1> FOR <int2>)` |
`overlay(<text1>, <text2>, <int1>, <int2>)` |

`OVERLAY(<text1> PLACING <text2> FROM <int>)` |
`overlay(<text1>, <text2>, <int>)` |

`POSITION(<text1> IN <text2>)` |
`strpos(<text2>, <text1>)` |

`SESSION_USER` |
`current_user()` |

`SUBSTRING(<text> FOR <int1> FROM <int2>)` |
`substring(<text>, <int2>, <int1>)` |

`SUBSTRING(<text> FOR <int>)` |
`substring(<text>, 1, <int>)` |

`SUBSTRING(<text> FROM <int1> FOR <int2>)` |
`substring(<text>, <int1>, <int2>)` |

`SUBSTRING(<text> FROM <int>)` |
`substring(<text>, <int>)` |

`TRIM(<text1> FROM <text2>)` |
`btrim(<text2>, <text1>)` |

`TRIM(<text1>, <text2>)` |
`btrim(<text1>, <text2>)` |

`TRIM(FROM <text>)` |
`btrim(<text>)` |

`TRIM(LEADING <text1> FROM <text2>)` |
`ltrim(<text2>, <text1>)` |

`TRIM(LEADING FROM <text>)` |
`ltrim(<text>)` |

`TRIM(TRAILING <text1> FROM <text2>)` |
`rtrim(<text2>, <text1>)` |

`TRIM(TRAILING FROM <text>)` |
`rtrim(<text>)` |

`USER` |
`current_user()` |

#### Typing rule

In general, a function call requires the arguments to be of the types accepted by the function, and returns a value of the type determined by the function.

However, the typing of function calls is complicated by the fact SQL supports function overloading. See our blog post for more details.

## Subscripted expressions

It is possible to access one item in an array value using the `[`

... `]`

operator.

For example, if the name `a`

refers to an array of 10
values, `a[3]`

will retrieve the 3rd value. The first value has index
1.

If the index is smaller or equal to 0, or larger than the size of the array, then
the result of the subscripted expression is `NULL`

.

#### Typing rule

The subscripted expression must have an array type; the index expression
must have type `INT`

. The result has the element type of the
subscripted expression.

## Conditional expressions

Expressions can test a conditional expression and, depending on whether or which condition is satisfied, evaluate to one or more additional operands.

These expression formats share the following property: some of their
operands are only evaluated if a condition is true. This matters
especially when an operand would be invalid otherwise. For example,
`IF(a=0, 0, x/a)`

returns 0 if `a`

is 0, and `x/a`

otherwise.

`IF`

expressions

Syntax:

```
IF ( <cond>, <expr1>, <expr2> )
```

Evaluates `<cond>`

, then evaluates `<expr1>`

if the condition is true,
or `<expr2>`

otherwise.

The expression corresponding to the case when the condition is false is not evaluated.

#### Typing rule

The condition must have type `BOOL`

, and the two remaining expressions
must have the same type. The result has the same type as the
expression that was evaluated.

### Simple `CASE`

expressions

Syntax:

```
CASE <cond>
WHEN <condval1> THEN <expr1>
[ WHEN <condvalx> THEN <exprx> ] ...
[ ELSE <expr2> ]
END
```

Evaluates `<cond>`

, then picks the `WHEN`

branch where `<condval>`

is
equal to `<cond>`

, then evaluates and returns the corresponding `THEN`

expression. If no `WHEN`

branch matches, the `ELSE`

expression is
evaluated and returned, if any. Otherwise, `NULL`

is returned.

Conditions and result expressions after the first match are not evaluated.

#### Typing rule

The condition and the `WHEN`

expressions must have the same type.
The `THEN`

expressions and the `ELSE`

expression, if any, must have the same type.
The result has the same type as the `THEN`

/`ELSE`

expressions.

### Searched `CASE`

expressions

Syntax:

```
CASE WHEN <cond1> THEN <expr1>
[ WHEN <cond2> THEN <expr2> ] ...
[ ELSE <expr> ]
END
```

In order, evaluates each `<cond>`

expression; at the first `<cond>`

expression that evaluates to `TRUE`

, returns the result of evaluating the
corresponding `THEN`

expression. If none of the `<cond>`

expressions
evaluates to true, then evaluates and returns the value of the `ELSE`

expression, if any, or `NULL`

otherwise.

Conditions and result expressions after the first match are not evaluated.

#### Typing rule

All the `WHEN`

expressions must have type `BOOL`

.
The `THEN`

expressions and the `ELSE`

expression, if any, must have the same type.
The result has the same type as the `THEN`

/`ELSE`

expressions.

`NULLIF`

expressions

Syntax:

```
NULLIF ( <expr1>, <expr2> )
```

Equivalent to: `IF ( <expr1> = <expr2>, NULL, <expr1> )`

#### Typing rule

Both operands must have the same type, which is also the type of the result.

`COALESCE`

and `IFNULL`

expressions

Syntax:

```
IFNULL ( <expr1>, <expr2> )
COALESCE ( <expr1> [, <expr2> [, <expr3> ] ...] )
```

`COALESCE`

evaluates the first expression first. If its value is not
`NULL`

, its value is returned directly. Otherwise, it returns the
result of applying `COALESCE`

on the remaining expressions. If all the
expressions are `NULL`

, `NULL`

is returned.

Arguments to the right of the first non-null argument are not evaluated.

`IFNULL(a, b)`

is equivalent to `COALESCE(a, b)`

.

#### Typing rule

The operands must have the same type, which is also the type of the result.

## Logical operators

The Boolean operators `AND`

, `OR`

and `NOT`

are available.

Syntax:

```
NOT <expr>
<expr1> AND <expr2>
<expr1> OR <expr2>
```

`AND`

and `OR`

are commutative. Moreover, the input to `AND`

and `OR`

is not evaluated in any particular order. Some operand may
not even be evaluated at all if the result can be fully ascertained using
only the other operand.

See also NULLs and Ternary Logic.

### Typing rule

The operands must have type `BOOL`

. The result has type `BOOL`

.

## Aggregate expressions

An aggregate expression has the same syntax as a function call, with a special
case for `COUNT`

:

```
<name> ( <arguments...> )
COUNT ( * )
```

The difference between aggregate expressions and function calls is
that the former use
aggregate functions
and can only appear in the list of rendered expressions in a
`SELECT`

clause.

An aggregate expression computes a combined value, depending on which aggregate function is used, across all the rows currently selected.

#### Typing rule

The operand and return types are determined like for regular function calls.

## Window function calls

A window function call has the syntax of a function call followed by an `OVER`

clause:

```
<name> ( <arguments...> ) OVER <window>
<name> ( * ) OVER <window>
```

It represents the application of a window or aggregate function over a subset ("window") of the rows selected by a query.

#### Typing rule

The operand and return types are determined like for regular function calls.

## Explicit type coercions

Syntax:

```
<expr> :: <type>
CAST (<expr> AS <type>)
```

Evaluates the expression and converts the resulting value to the specified type. An error is reported if the conversion is invalid.

For example: `CAST(now() AS DATE)`

Note that in many cases a type annotation is preferrable to a type coercion. See the section on type annotations below for more details.

#### Typing rule

The operand can have any type.
The result has the type specified in the `CAST`

expression.

As a special case, if the operand is a literal, a constant expression
or a placeholder, the `CAST`

type is used to guide the typing of the
operand. See our blog post for more details.

## Collation expressions

Syntax:

```
<expr> COLLATE <collation>
```

Evaluates the expression and converts its result to a collated string with the specified collation.

For example: `'a' COLLATE de`

#### Typing rule

The operand must have type `STRING`

. The result has type `COLLATEDSTRING`

.

## Array constructors

Syntax:

```
ARRAY[ <expr>, <expr>, ... ]
```

Evaluates to an array containing the specified values.

For example:

```
> SELECT ARRAY[1,2,3] AS a;
```

```
a
-----------
{1,2,3}
(1 row)
```

The data type of the array is inferred from the values of the provided expressions. All the positions in the array must have the same data type.

If there are no expressions specified (empty array), or
all the values are `NULL`

, then the type of the array must be
specified explicitly using a type annotation. For example:

```
> SELECT ARRAY[]:::int[];
```

`ARRAY(...)`

instead.`ARRAY(a, b, c)`

as an alias for `ARRAY[a, b, c]`

. This is an experimental, CockroachDB-specific SQL extension and may be removed in a later version of CockroachDB.#### Typing rule

The operands must all have the same type. The result has the array type with the operand type as element type.

## Tuple constructor

Syntax:

```
(<expr>, <expr>, ...)
ROW (<expr>, <expr>, ...)
```

Evaluates to a tuple containing the values of the provided expressions.

For example:

```
> SELECT ('x', 123, 12.3) AS a;
```

```
a
----------------
(x,123,12.3)
(1 row)
```

The data type of the resulting tuple is inferred from the values. Each position in a tuple can have a distinct data type.

New in v20.1: CockroachDB supports accessing the Nth element in a tuple as a single table cell using the syntax `(...).@N`

. For example:

```
> SELECT (t).@2 FROM (SELECT (1,'b',2.3) AS t);
```

```
?column?
------------
b
(1 row)
```

CockroachDB also supports expanding all elements of a tuple as a single row in a table with the `(<tuple>).*`

notation. This notation works as the inverse of the tuple-creating notation `(<table>.*)`

. For example:

```
> WITH tuples AS (SELECT (t.*) AS tuple FROM (SELECT 1,'b',2.3) AS t(x,y,z)) -- Build the tuples, with labels
SELECT (tuple).* FROM tuples; -- Expands the tuples and restore the column labels
```

```
x | y | z
----+---+------
1 | b | 2.3
(1 row)
```

#### Typing rule

The operands can have any type. The result has a tuple type whose item types are the types of the operands.

## Explicitly typed expressions

Syntax:

```
<expr>:::<type>
ANNOTATE_TYPE(<expr>, <type>)
```

Evaluates to the given expression, requiring the expression to have the given type. If the expression doesn't have the given type, an error is returned.

Type annotations are specially useful to guide the arithmetic on numeric values. For example:

```
> SELECT (1 / 0):::FLOAT;
```

```
ERROR: division by zero
SQLSTATE: 22012
```

```
> SELECT (1 / 0);
```

```
ERROR: division by zero
SQLSTATE: 22012
```

```
> SELECT (1 / 0)::FLOAT;
```

```
ERROR: division by zero
SQLSTATE: 22012
```

Type annotations are also different from cast expressions (see above) in
that they do not cause the value to be converted. For example,
`now()::DATE`

converts the current timestamp to a date value (and
discards the current time), whereas `now():::DATE`

triggers an error
message (that `now()`

does not have type `DATE`

).

Check our blog for more information about context-dependent typing.

#### Typing rule

The operand must be implicitly coercible to the given type. The result has the given type.

## Subquery expressions

### Scalar subqueries

Syntax:

```
( ... subquery ... )
```

Evaluates the subquery, asserts that it returns a single row and single column, and then evaluates to the value of that single cell. Any selection query can be used as subquery.

For example, the following query returns `TRUE`

if there are more rows in table `users`

than in table
`admins`

:

```
> SELECT (SELECT COUNT(*) FROM users) > (SELECT COUNT(*) FROM admins);
```

#### Typing rule

The operand must have a table type with only one column. The result has the type of that single column.

### Existence test on the result of subqueries

Syntax:

```
EXISTS ( ... subquery ... )
NOT EXISTS ( ... subquery ... )
```

Evaluates the subquery and then returns `TRUE`

or `FALSE`

depending on
whether the subquery returned any row (for `EXISTS`

) or didn't return
any row (for `NOT EXISTS`

). Any selection query
can be used as subquery.

#### Typing rule

The operand can have any table type. The result has type `BOOL`

.

### Conversion of subquery results to an array

Syntax:

```
ARRAY( ... subquery ... )
```

Evaluates the subquery and converts its results to an array. Any selection query can be used as subquery.

`ARRAY[...]`

instead.