# SUM Function

An aggregate function that returns the sum of a set of numbers. 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
`MIN`

are `NULL`

, `SUM`

returns `NULL`

.

**Syntax:**

`SUM([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:** `BIGINT`

for integer arguments, `DOUBLE`

for floating-point
arguments

**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 (Impala 2.3 or higher only) 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:**

The following example shows how to use `SUM()`

to compute the total for all the values in the
table, a subset of values, or the sum for each combination of values in the `GROUP BY`

clause:

```
-- Total all the values for this column in the table.
select sum(c1) from t1;
-- Find the total for this column from a subset of the table.
select sum(c1) from t1 where month = 'January' and year = '2013';
-- Find the total from a set of numeric function results.
select sum(length(s)) from t1;
-- Often used with functions that return predefined values to compute a score.
select sum(case when grade = 'A' then 1.0 when grade = 'B' then 0.75 else 0) as class_honors from test_scores;
-- Can also be used in combination with DISTINCT and/or GROUP BY.
-- Return more than one result.
select month, year, sum(purchase_price) from store_stats group by month, year;
-- Filter the input to eliminate duplicates before performing the calculation.
select sum(distinct x) from t1;
```

`SUM()`

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

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

clause which condenses the result set.
`select x, property, sum(x) `**over (partition by property)** as sum from int_t where property in ('odd','even');
+----+----------+-----+
| x | property | sum |
+----+----------+-----+
| 2 | even | 30 |
| 4 | even | 30 |
| 6 | even | 30 |
| 8 | even | 30 |
| 10 | even | 30 |
| 1 | odd | 25 |
| 3 | odd | 25 |
| 5 | odd | 25 |
| 7 | odd | 25 |
| 9 | odd | 25 |
+----+----------+-----+

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 `SUM()`

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

clause) to produce a running total of all the even values,
then a running total 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,
sum(x) over (partition by property
```**order by x**) as 'cumulative total'
from int_t where property in ('odd','even');
+----+----------+------------------+
| x | property | cumulative total |
+----+----------+------------------+
| 2 | even | 2 |
| 4 | even | 6 |
| 6 | even | 12 |
| 8 | even | 20 |
| 10 | even | 30 |
| 1 | odd | 1 |
| 3 | odd | 4 |
| 5 | odd | 9 |
| 7 | odd | 16 |
| 9 | odd | 25 |
+----+----------+------------------+
select x, property,
sum(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 total |
+----+----------+------------------+
| 2 | even | 2 |
| 4 | even | 6 |
| 6 | even | 12 |
| 8 | even | 20 |
| 10 | even | 30 |
| 1 | odd | 1 |
| 3 | odd | 4 |
| 5 | odd | 9 |
| 7 | odd | 16 |
| 9 | odd | 25 |
+----+----------+------------------+
select x, property,
sum(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 total |
+----+----------+------------------+
| 2 | even | 2 |
| 4 | even | 6 |
| 6 | even | 12 |
| 8 | even | 20 |
| 10 | even | 30 |
| 1 | odd | 1 |
| 3 | odd | 4 |
| 5 | odd | 9 |
| 7 | odd | 16 |
| 9 | odd | 25 |
+----+----------+------------------+

Changing the direction of the `ORDER BY`

clause causes the intermediate
results of the cumulative total to be calculated in a different order:
`select sum(x) over (partition by property `**order by x desc**) as 'cumulative total'
from int_t where property in ('odd','even');
+----+----------+------------------+
| x | property | cumulative total |
+----+----------+------------------+
| 10 | even | 10 |
| 8 | even | 18 |
| 6 | even | 24 |
| 4 | even | 28 |
| 2 | even | 30 |
| 9 | odd | 9 |
| 7 | odd | 16 |
| 5 | odd | 21 |
| 3 | odd | 24 |
| 1 | odd | 25 |
+----+----------+------------------+

The following examples show how to construct a moving window, with a running total 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,
sum(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 | 6 |
| 4 | even | 12 |
| 6 | even | 18 |
| 8 | even | 24 |
| 10 | even | 18 |
| 1 | odd | 4 |
| 3 | odd | 9 |
| 5 | odd | 15 |
| 7 | odd | 21 |
| 9 | odd | 16 |
+----+----------+--------------+
-- Doesn't work because of syntax restriction on RANGE clause.
select x, property,
sum(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.

**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`

.

**Related information:**