# AVG function

An aggregate function that returns the average value from a set of numbers or
`TIMESTAMP`

values. Its single argument can be numeric column, or the numeric
result of a function or expression applied to the column value. Rows with a
`NULL`

value for the specified column are ignored. If the table is empty, or
all the values supplied to `AVG`

are `NULL`

, `AVG`

returns `NULL`

.

**Syntax:**

`AVG([DISTINCT | ALL] ``expression`) [OVER (`analytic_clause`)]

When the query contains a `GROUP BY`

clause, returns one value for each combination of
grouping values.

**Return type:** `DOUBLE`

for numeric values; `TIMESTAMP`

for
`TIMESTAMP`

values

**Complex type considerations:**

To access a column with a complex type (`ARRAY`

, `STRUCT`

, or `MAP`

)
in an aggregation function, you unpack the individual elements using join notation in the query,
and then apply the function to the final scalar item, field, key, or value at the bottom of any nested type hierarchy in the column.
See Complex types for details about using complex types in Impala.

`ARRAY`

of `STRUCT`

items).
The array is unpacked inside the query using join notation.
The array elements are referenced using the `ITEM`

pseudocolumn, and the structure fields inside the array elements
are referenced using dot notation.
Numeric values such as `SUM()`

and `AVG()`

are computed using the numeric `R_NATIONKEY`

field, and
the general-purpose `MAX()`

and `MIN()`

values are computed from the string `N_NAME`

field.
```
describe region;
+-------------+-------------------------+---------+
| name | type | comment |
+-------------+-------------------------+---------+
| r_regionkey | smallint | |
| r_name | string | |
| r_comment | string | |
| r_nations | array<struct< | |
| | n_nationkey:smallint, | |
| | n_name:string, | |
| | n_comment:string | |
| | >> | |
+-------------+-------------------------+---------+
select r_name, r_nations.item.n_nationkey
from region, region.r_nations as r_nations
order by r_name, r_nations.item.n_nationkey;
+-------------+------------------+
| r_name | item.n_nationkey |
+-------------+------------------+
| AFRICA | 0 |
| AFRICA | 5 |
| AFRICA | 14 |
| AFRICA | 15 |
| AFRICA | 16 |
| AMERICA | 1 |
| AMERICA | 2 |
| AMERICA | 3 |
| AMERICA | 17 |
| AMERICA | 24 |
| ASIA | 8 |
| ASIA | 9 |
| ASIA | 12 |
| ASIA | 18 |
| ASIA | 21 |
| EUROPE | 6 |
| EUROPE | 7 |
| EUROPE | 19 |
| EUROPE | 22 |
| EUROPE | 23 |
| MIDDLE EAST | 4 |
| MIDDLE EAST | 10 |
| MIDDLE EAST | 11 |
| MIDDLE EAST | 13 |
| MIDDLE EAST | 20 |
+-------------+------------------+
select
r_name,
count(r_nations.item.n_nationkey) as count,
sum(r_nations.item.n_nationkey) as sum,
avg(r_nations.item.n_nationkey) as avg,
min(r_nations.item.n_name) as minimum,
max(r_nations.item.n_name) as maximum,
ndv(r_nations.item.n_nationkey) as distinct_vals
from
region, region.r_nations as r_nations
group by r_name
order by r_name;
+-------------+-------+-----+------+-----------+----------------+---------------+
| r_name | count | sum | avg | minimum | maximum | distinct_vals |
+-------------+-------+-----+------+-----------+----------------+---------------+
| AFRICA | 5 | 50 | 10 | ALGERIA | MOZAMBIQUE | 5 |
| AMERICA | 5 | 47 | 9.4 | ARGENTINA | UNITED STATES | 5 |
| ASIA | 5 | 68 | 13.6 | CHINA | VIETNAM | 5 |
| EUROPE | 5 | 77 | 15.4 | FRANCE | UNITED KINGDOM | 5 |
| MIDDLE EAST | 5 | 58 | 11.6 | EGYPT | SAUDI ARABIA | 5 |
+-------------+-------+-----+------+-----------+----------------+---------------+
```

**Examples:**

```
-- Average all the non-NULL values in a column.
insert overwrite avg_t values (2),(4),(6),(null),(null);
-- The average of the above values is 4: (2+4+6) / 3. The 2 NULL values are ignored.
select avg(x) from avg_t;
-- Average only certain values from the column.
select avg(x) from t1 where month = 'January' and year = '2013';
-- Apply a calculation to the value of the column before averaging.
select avg(x/3) from t1;
-- Apply a function to the value of the column before averaging.
-- Here we are substituting a value of 0 for all NULLs in the column,
-- so that those rows do factor into the return value.
select avg(isnull(x,0)) from t1;
-- Apply some number-returning function to a string column and average the results.
-- If column s contains any NULLs, length(s) also returns NULL and those rows are ignored.
select avg(length(s)) from t1;
-- Can also be used in combination with DISTINCT and/or GROUP BY.
-- Return more than one result.
select month, year, avg(page_visits) from web_stats group by month, year;
-- Filter the input to eliminate duplicates before performing the calculation.
select avg(distinct x) from t1;
-- Filter the output after performing the calculation.
select avg(x) from t1 group by y having avg(x) between 1 and 20;
```

`AVG()`

in an analytic context. They use a table
containing integers from 1 to 10. Notice how the `AVG()`

is reported for each input value, as
opposed to the `GROUP BY`

clause which condenses the result set.
```
select x, property, avg(x) over (partition by property) as avg from int_t where property in ('odd','even');
+----+----------+-----+
| x | property | avg |
+----+----------+-----+
| 2 | even | 6 |
| 4 | even | 6 |
| 6 | even | 6 |
| 8 | even | 6 |
| 10 | even | 6 |
| 1 | odd | 5 |
| 3 | odd | 5 |
| 5 | odd | 5 |
| 7 | odd | 5 |
| 9 | odd | 5 |
+----+----------+-----+
```

Adding an `ORDER BY`

clause lets you experiment with results that are cumulative or apply to a moving
set of rows (the “window”). The following examples use `AVG()`

in an analytic context
(that is, with an `OVER()`

clause) to produce a running average of all the even values,
then a running average of all the odd values. The basic `ORDER BY x`

clause implicitly
activates a window clause of `RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW`

,
which is effectively the same as `ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW`

,
therefore all of these examples produce the same results:
```
select x, property,
avg(x) over (partition by property
```**order by x**) as 'cumulative average'
from int_t where property in ('odd','even');
+----+----------+--------------------+
| x | property | cumulative average |
+----+----------+--------------------+
| 2 | even | 2 |
| 4 | even | 3 |
| 6 | even | 4 |
| 8 | even | 5 |
| 10 | even | 6 |
| 1 | odd | 1 |
| 3 | odd | 2 |
| 5 | odd | 3 |
| 7 | odd | 4 |
| 9 | odd | 5 |
+----+----------+--------------------+
select x, property,
avg(x) over
(
partition by property
**order by x**
**range between unbounded preceding and current row**
) as 'cumulative average'
from int_t where property in ('odd','even');
+----+----------+--------------------+
| x | property | cumulative average |
+----+----------+--------------------+
| 2 | even | 2 |
| 4 | even | 3 |
| 6 | even | 4 |
| 8 | even | 5 |
| 10 | even | 6 |
| 1 | odd | 1 |
| 3 | odd | 2 |
| 5 | odd | 3 |
| 7 | odd | 4 |
| 9 | odd | 5 |
+----+----------+--------------------+
select x, property,
avg(x) over
(
partition by property
**order by x**
**rows between unbounded preceding and current row**
) as 'cumulative average'
from int_t where property in ('odd','even');
+----+----------+--------------------+
| x | property | cumulative average |
+----+----------+--------------------+
| 2 | even | 2 |
| 4 | even | 3 |
| 6 | even | 4 |
| 8 | even | 5 |
| 10 | even | 6 |
| 1 | odd | 1 |
| 3 | odd | 2 |
| 5 | odd | 3 |
| 7 | odd | 4 |
| 9 | odd | 5 |
+----+----------+--------------------+

The following examples show how to construct a moving window, with a running average taking into account 1 row before
and 1 row after the current row, within the same partition (all the even values or all the odd values).
Because of a restriction in the Impala `RANGE`

syntax, this type of
moving window is possible with the `ROWS BETWEEN`

clause but not the `RANGE BETWEEN`

clause:
```
select x, property,
avg(x) over
(
partition by property
```**order by x**
**rows between 1 preceding and 1 following**
) as 'moving average'
from int_t where property in ('odd','even');
+----+----------+----------------+
| x | property | moving average |
+----+----------+----------------+
| 2 | even | 3 |
| 4 | even | 4 |
| 6 | even | 6 |
| 8 | even | 8 |
| 10 | even | 9 |
| 1 | odd | 2 |
| 3 | odd | 3 |
| 5 | odd | 5 |
| 7 | odd | 7 |
| 9 | odd | 8 |
+----+----------+----------------+
-- Doesn't work because of syntax restriction on RANGE clause.
select x, property,
avg(x) over
(
partition by property
**order by x**
**range between 1 preceding and 1 following**
) as 'moving average'
from int_t where property in ('odd','even');
ERROR: AnalysisException: RANGE is only supported with both the lower and upper bounds UNBOUNDED or one UNBOUNDED and the other CURRENT ROW.

**Restrictions:**

Due to the way arithmetic on `FLOAT`

and `DOUBLE`

columns uses
high-performance hardware instructions, and distributed queries can perform these operations in different
order for each query, results can vary slightly for aggregate function calls such as `SUM()`

and `AVG()`

for `FLOAT`

and `DOUBLE`

columns, particularly on
large data sets where millions or billions of values are summed or averaged. For perfect consistency and
repeatability, use the `DECIMAL`

data type for such operations instead of
`FLOAT`

or `DOUBLE`

.