# Aggregate Functions

Aggregate functions perform a calculation on a set of values and return a single value. Aggregate functions can be used as expressions only in the following:

- The select list of a SELECT statement (either a sub-query or an outer query).
- A HAVING clause.

## AVG

`avg(col)`

The average of the values in a group. The null values will be ignored.

## COUNT

```
count(*)
count(col)
```

The number of items in a group. The null values will be ignored.

## MAX

`max(col)`

The maximum value in a group. The null values will be ignored.

## MIN

`min(col)`

The minimum value in a group. The null values will be ignored.

## SUM

`sum(col)`

The sum of all the values in a group. The null values will be ignored.

## COLLECT

```
collect(*)
collect(col)
```

Returns an array with all columns or the whole record (when the parameter is *) values from the group.

### Examples

Get an array of column

`a`

of the current window. Assume the column`a`

is of an int type, the result will be like:`[{"r1":[32, 45]}]`

sql`SELECT collect(a) as r1 FROM test GROUP BY TumblingWindow(ss, 10)`

Get the whole array of the current window. The result will be like:

`[{"r1":[{"a":32, "b":"hello"}, {"a":45, "b":"world"}]}]`

sql`SELECT collect(*) as r1 FROM test GROUP BY TumblingWindow(ss, 10)`

Get the second element's column 'a' value within the current window. The result will be like:

`[{"r1":32}]`

sql`SELECT collect(*)[1]->a as r1 FROM test GROUP BY TumblingWindow(ss, 10)`

## LAST_VALUE

```
last_value(*, true)
last_value(col, false)
```

The last_value function is used to retrieve the value of the last row in a group for the specified column(s) or the entire message. It has two parameters, the first of which specifies the column(s) or the entire message, and the second of which specifies whether to ignore null values. If the second parameter is true, the function will only return the last non-null value. If there are no non-null values, the function will return null. If the second parameter is false, the function will return the last value, regardless of whether it is null or not.

## MERGE_AGG

```
merge_agg(*)
merge_agg(col)
```

Concatenate values from the group into a single value. It concatenates multiple objects by generating an object containing the union of their keys, taking the second object's value when there are duplicate keys. It does not operate recursively; only the top-level object structure is merged.

If the parameter is a column, the result will be an object containing the union of the keys of all the objects in the column. If the column contains only non-object values, the result will be an empty object.

### Examples

Given the following values in the group:

```
{
"a": {
"a": 2
},
"b": 2,
"c": 3
}
{
"a": {
"b": 2
},
"b": 5,
"d": 6
}
{
"a": {
"a": 3
},
"b": 8
}
```

Concat wildcard, the result will be:

`{"a": {"a": 3}, "b": 8, "c": 3, "d": 6}`

sql`SELECT merge_agg(*) as r1 FROM test GROUP BY TumblingWindow(ss, 10)`

Concat a specified object column, the result will be:

`{"a": 3, "b": 2}`

sql`SELECT merge_agg(a) as r1 FROM test GROUP BY TumblingWindow(ss, 10)`

Concat a specified non-object column, the result will be:

`{}`

sql`SELECT merge_agg(b) as r1 FROM test GROUP BY TumblingWindow(ss, 10)`

## DEDUPLICATE

`deduplicate(col, false)`

Returns the deduplicate results in the group, usually a window. The first argument is the column as the key to deduplicate; the second argument is whether to return all items or just the latest item which is not duplicate. If the latest item is a duplicate, the sink will receive an empty map.

Examples:

Get the whole array of the current window which is deduplicated by column

`a`

. The result will be like:`[{"r1":{"a":32, "b":"hello"}, {"a":45, "b":"world"}}]`

sql`SELECT deduplicate(a, true) as r1 FROM test GROUP BY TumblingWindow(ss, 10)`

Get the column

`a`

value which is not duplicate during the last hour. The result will be like:`[{"r1":32}]`

,`[{"r1":45}]`

and`[{}]`

if a duplicate value arrives. Use the omitIfEmpty sink property to filter out those empty results.sql`SELECT deduplicate(a, false)->a as r1 FROM demo GROUP BY SlidingWindow(hh, 1)`

## STDDEV

`stddev(col)`

Returns the population standard deviation of expression in the group, usually a window. The argument is the column as the key to stddev.

## STDDEVS

`stddevs(col)`

Returns the sample standard deviation of expression in the group, usually a window. The argument is the column as the key to stddevs.

## VAR

`var(col)`

Returns the population variance (square of the population standard deviation) of expression in the group, usually a window. The argument is the column as the key to var.

## VARS

`vars(col)`

Returns the sample variance (square of the sample standard deviation) of expression in the group, usually a window. The argument is the column as the key to vars.

## PERCENTILE

`percentile(col, percentile)`

Returns the percentile value based on a continuous distribution of expression in the group, usually a window. The first argument is the column as the key to percentile. The second argument is the percentile of the value that you want to find. The percentile must be a constant between 0.0 and 1.0.

## PERCENTILE_DISC

`percentile_disc(col, percentile)`

Returns the percentile value based on a discrete distribution of expression in the group, usually a window. The first argument is the column as the key to percentile_disc. The second argument is the percentile of the value that you want to find. The percentile must be a constant between 0.0 and 1.0.

## LAST_AGG_HIT_COUNT

`last_agg_hit_count()`

Returns the number of times the function had been called and passed. The function is usually used to get the accumulated trigger count of an aggregate rule. If the function is used in `HAVING`

clause, it will only update the count when the condition is true.

To use the similar functionality in a non-aggregate rule, use the last_hit_count function.

## LAST_AGG_HIT_TIME

`last_agg_hit_time()`

Returns the int64 timestamp of the last **event** time the function had been called and passed. The function is usually used to get the last trigger time of an aggregate rule. If the function is used in `HAVING`

clause, it will only update the timestamp when the condition is true.

To use the similar functionality in a non-aggregate rule, use the last_hit_time function.