COUNT

Counts the number of rows or not NULL values.

Syntax

COUNT([ DISTINCT ] <expression>)

Parameters

Parameter	Description	Supported input types
<expression>	The expression to count	Any

Valid values for the input expression include column names or functions that return a column name. When DISTINCT is being used, only the unique number of rows with no NULL values are counted. COUNT(*) returns a total count of all rows in the table, while COUNT(<column_name>) returns a count of non-null rows in the specified <column_name>.

By default, COUNT(DISTINCT) returns exact results. If you do not require a precise result and want to have faster performance, consider using the APPROX_COUNT_DISTINCT function. See below for examples and considerations.

Return Type

NUMERIC

Example

For this example, see the following table tournaments:

name	totalprizedollars
The Drifting Thunderdome	24768
The Lost Track Showdown	5336
The Acceleration Championship	19274
The Winter Wilderness Rally	21560
The Circuit Championship	9739
The Singapore Grand Prix	19274

Doing a regular COUNT returns the total number of rows in the column. As the tournaments table contains 6 rows, this will be the returned value.

SELECT
	COUNT(name)
FROM
	tournaments;

Returns: 6

A COUNT(DISTINCT) function on the same column returns the number of unique rows. When applied to the totalprizedollars column, the value returned is 5, as there is a repeated number in the column.

SELECT
	COUNT(DISTINCT totalprizedollars)
FROM
	tournaments;

Returns: 5

Example of COUNT(DISTINCT) vs. APPROX_COUNT_DISTINCT

To understand the difference between COUNT(DISTINCT pk) with exact precision enabled and using default approximation, consider a table, count_test with 8,388,608 unique pk values. The APPROX_COUNT_DISTINCT function returns the same approximate results as the COUNT(DISTINCT) function with exact precision disabled, so we can see the difference between these methods with the following example.

SELECT
	COUNT(DISTINCT pk) as count_distinct,
	APPROX_COUNT_DISTINCT(pk) as approx_count
FROM
	count_test;

Returns:

Assuming 8,388,608 unique pk values, we will see results like:

' +----------------+--------------+
' | count_distinct | approx_count |
' +----------------+--------------+
' |      8,388,608 |    8,427,387 |
' +----------------+--------------+