Overview

An aggregate function performs a calculation on a set of values and returns a single scalar value.

DISTINCT

All aggregate functions support the use of the set quantifier DISTINCT to deduplicate values before aggregation.

Null Values

Rows containing null values are ignored by all aggregate functions.

Example Graph

The following examples run against this graph:

avg()

Computes the average of a set of numeric values.

find().nodes() as n
return avg(n.score)

Result:

collect()

Collects a set of values into a list.

find().nodes() as n
return collect(n.title)

Result:

count()

Returns the number of records in the input.

find().nodes() as n
return count(n)

Result:

uncollect [1, "a", "2", "b3", null] as item
return count(item)

Result:

count(DISTINCT)

You can include the set quantifier DISTINCT in count() to return the number of distinct records in the input.

uncollect [1, 1, "a", "2", "b3", null] as item
return count(DISTINCT item)

Result:

max()

Returns the maximum value in a set of values.

find().nodes() as n
return max(n.score)

Result:

uncollect [1, "a", "2.1", "b3"] as item
return max(item)

Result:

min()

Returns the minimum value in a set of values.

find().nodes() as n
return min(n.score)

Result:

uncollect [1, "a", "2.1", "b3"] as item
return min(item)

Result:

stddev_pop()

Computes the population standard deviation of a set of numeric values.

find().nodes() as n
return stddev_pop(n.score)

Result:

stddev_samp()

Computes the sample standard deviation of a set of numeric values.

find().nodes() as n
return stddev_samp(n.score)

Result:

sum()

Computes the sum of a set of values.

find().nodes() as n
return sum(n.score)

Result: