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

The following example demonstrates calls to several aggregation functions using values from a column containing nested complex types (an 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             |
+-------------+-------+-----+------+-----------+----------------+---------------+

-- 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;

The following examples show how to use 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.