avg aggregate function

  • Article

Applies to: check marked yes Databricks SQL check marked yes Databricks Runtime

Returns the mean calculated from values of a group. This function is a synonym for mean aggregate function.

Syntax

avg( [ALL | DISTINCT] expr) [FILTER ( WHERE cond ) ]

This function can also be invoked as a window function using the OVER clause.

Arguments

  • expr: An expression that evaluates to a numeric or an interval.
  • cond: An optional boolean expression filtering the rows used for aggregation.

Returns

The result type is computed as for the arguments:

  • DECIMAL(p, s): The result type is a DECIMAL(p + 4, s + 4). If the maximum precision for DECIMAL is reached the increase in scale will be limited to avoid loss of significant digits.
  • year-month interval: The result is an INTERVAL YEAR TO MONTH.
  • day-time interval: The result is an INTERVAL DAY TO SECOND.
  • In all other cases the result is a DOUBLE.

Nulls within the group are ignored. If a group is empty or consists only of nulls, the result is NULL.

If DISTINCT is specified the average is computed after duplicates have been removed.

If the result overflows the result type, Azure Databricks raises an ARITHMETIC_OVERFLOW error. To return a NULL instead use try_avg.

Warning

In Databricks Runtime, if spark.sql.ansi.enabled is false, an overflow returns NULL instead of an error.

Examples

> SELECT avg(col) FROM VALUES (1), (2), (3) AS tab(col);
 2.0

> SELECT avg(DISTINCT col) FROM VALUES (1), (1), (2) AS tab(col);
 1.5

> SELECT avg(col) FROM VALUES (1), (2), (NULL) AS tab(col);
 1.5

> SELECT avg(col) FROM VALUES (INTERVAL '1' YEAR), (INTERVAL '2' YEAR) AS tab(col);
 1-6

-- Overflow results in NULL for try_avg()
> SELECT try_avg(col) FROM VALUES (5e37::DECIMAL(38, 0)), (5e37::DECIMAL(38, 0)) AS tab(col);
 NULL

-- Overflow causes error for avg() in ANSI mode.
> SELECT avg(col) FROM VALUES (5e37::DECIMAL(38, 0)), (5e37::DECIMAL(38, 0)) AS tab(col);
 Error: CANNOT_CHANGE_DECIMAL_PRECISION