COUNT([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             |
+-------------+-------+-----+------+-----------+----------------+---------------+

-- How many rows total are in the table, regardless of NULL values?
select count(*) from t1;
-- How many rows are in the table with non-NULL values for a column?
select count(c1) from t1;
-- Count the rows that meet certain conditions.
-- Again, * includes NULLs, so COUNT(*) might be greater than COUNT(col).
select count(*) from t1 where x > 10;
select count(c1) from t1 where x > 10;
-- Can also be used in combination with DISTINCT and/or GROUP BY.
-- Combine COUNT and DISTINCT to find the number of unique values.
-- Must use column names rather than * with COUNT(DISTINCT ...) syntax.
-- Rows with NULL values are not counted.
select count(distinct c1) from t1;
-- Rows with a NULL value in _either_ column are not counted.
select count(distinct c1, c2) from t1;
-- Return more than one result.
select month, year, count(distinct visitor_id) from web_stats group by month, year;

The following examples show how to use COUNT() in an analytic context. They use a table containing integers from 1 to 10. Notice how the COUNT() is reported for each input value, as opposed to the GROUP BY clause which condenses the result set.

select x, property, count(x) over (partition by property) as count from int_t where property in ('odd','even');
+----+----------+-------+
| x  | property | count |
+----+----------+-------+
| 2  | even     | 5     |
| 4  | even     | 5     |
| 6  | even     | 5     |
| 8  | even     | 5     |
| 10 | even     | 5     |
| 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 COUNT() in an analytic context (that is, with an OVER() clause) to produce a running count of all the even values, then a running count 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,
  count(x) over (partition by property order by x) as 'cumulative count'
  from int_t where property in ('odd','even');
+----+----------+------------------+
| x  | property | cumulative count |
+----+----------+------------------+
| 2  | even     | 1                |
| 4  | even     | 2                |
| 6  | even     | 3                |
| 8  | even     | 4                |
| 10 | even     | 5                |
| 1  | odd      | 1                |
| 3  | odd      | 2                |
| 5  | odd      | 3                |
| 7  | odd      | 4                |
| 9  | odd      | 5                |
+----+----------+------------------+

select x, property,
  count(x) over
  (
    partition by property
    order by x
    range between unbounded preceding and current row
  ) as 'cumulative total'
from int_t where property in ('odd','even');
+----+----------+------------------+
| x  | property | cumulative count |
+----+----------+------------------+
| 2  | even     | 1                |
| 4  | even     | 2                |
| 6  | even     | 3                |
| 8  | even     | 4                |
| 10 | even     | 5                |
| 1  | odd      | 1                |
| 3  | odd      | 2                |
| 5  | odd      | 3                |
| 7  | odd      | 4                |
| 9  | odd      | 5                |
+----+----------+------------------+

select x, property,
  count(x) over
  (
    partition by property
    order by x
    rows between unbounded preceding and current row
  ) as 'cumulative total'
  from int_t where property in ('odd','even');
+----+----------+------------------+
| x  | property | cumulative count |
+----+----------+------------------+
| 2  | even     | 1                |
| 4  | even     | 2                |
| 6  | even     | 3                |
| 8  | even     | 4                |
| 10 | even     | 5                |
| 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 count 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). Therefore, the count is consistently 3 for rows in the middle of the window, and 2 for rows near the ends of the window, where there is no preceding or no following row in the partition. 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,
  count(x) over
  (
    partition by property
    order by x
    rows between 1 preceding and 1 following
  ) as 'moving total'
  from int_t where property in ('odd','even');
+----+----------+--------------+
| x  | property | moving total |
+----+----------+--------------+
| 2  | even     | 2            |
| 4  | even     | 3            |
| 6  | even     | 3            |
| 8  | even     | 3            |
| 10 | even     | 2            |
| 1  | odd      | 2            |
| 3  | odd      | 3            |
| 5  | odd      | 3            |
| 7  | odd      | 3            |
| 9  | odd      | 2            |
+----+----------+--------------+

-- Doesn't work because of syntax restriction on RANGE clause.
select x, property,
  count(x) over
  (
    partition by property
    order by x
    range between 1 preceding and 1 following
  ) as 'moving total'
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.

select v1.c1 result1, v2.c1 result2 from
  (select count(distinct col1) as c1 from t1) v1 
    cross join
  (select count(distinct col2) as c1 from t1) v2;