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Grouping
To group results by arbitrary criteria, AQL provides the COLLECT keyword.
COLLECT will perform a grouping, but no aggregation. Aggregation can still be
added in the query if required.
Ensuring uniqueness
COLLECT can be used to make a result set unique. The following query will return each distinct
age attribute value only once:
FOR u IN users
COLLECT age = u.age
RETURN age
This is grouping without tracking the group values, but just the group criterion (age) value.
Grouping can also be done on multiple levels using COLLECT:
FOR u IN users
COLLECT status = u.status, age = u.age
RETURN { status, age }
Alternatively RETURN DISTINCT can be used to make a result set unique.
RETURN DISTINCT supports a single criterion only:
FOR u IN users
RETURN DISTINCT u.age
RETURN DISTINCT does not change the order of results. For above query that
means the order is undefined because no particular order is guaranteed when
iterating over a collection without explicit SORT operation.
Fetching group values
To group users by age, and return the names of the users with the highest ages, we’ll issue a query like this:
FOR u IN users
FILTER u.active == true
COLLECT age = u.age INTO usersByAge
SORT age DESC LIMIT 0, 5
RETURN {
age,
users: usersByAge[*].u.name
}
[
{ "age": 37, "users": [ "John", "Sophia" ] },
{ "age": 36, "users": [ "Fred", "Emma" ] },
{ "age": 34, "users": [ "Madison" ] },
{ "age": 33, "users": [ "Chloe", "Michael" ] },
{ "age": 32, "users": [ "Alexander" ] }
]
The query will put all users together by their age attribute. There will be one
result document per distinct age value (let aside the LIMIT). For each group,
we have access to the matching document via the usersByAge variable introduced in
the COLLECT statement.
Variable Expansion
The usersByAge variable contains the full documents found, and as we’re only
interested in user names, we’ll use the expansion operator [*] to extract just the
name attribute of all user documents in each group:
usersByAge[*].u.name
The [*] expansion operator is just a handy short-cut. We could also write
a subquery:
( FOR temp IN usersByAge RETURN temp.u.name )
Grouping by multiple criteria
To group by multiple criteria, we’ll use multiple arguments in the COLLECT clause.
For example, to group users by ageGroup (a derived value we need to calculate first)
and then by gender, we’ll do:
FOR u IN users
FILTER u.active == true
COLLECT ageGroup = FLOOR(u.age / 5) * 5,
gender = u.gender INTO group
SORT ageGroup DESC
RETURN {
ageGroup,
gender
}
[
{ "ageGroup": 35, "gender": "f" },
{ "ageGroup": 35, "gender": "m" },
{ "ageGroup": 30, "gender": "f" },
{ "ageGroup": 30, "gender": "m" },
{ "ageGroup": 25, "gender": "f" },
{ "ageGroup": 25, "gender": "m" }
]
Counting group values
If the goal is to count the number of values in each group, AQL provides the special COLLECT WITH COUNT INTO syntax. This is a simple variant for grouping with an additional group length calculation:
FOR u IN users
FILTER u.active == true
COLLECT ageGroup = FLOOR(u.age / 5) * 5,
gender = u.gender WITH COUNT INTO numUsers
SORT ageGroup DESC
RETURN {
ageGroup,
gender,
numUsers
}
[
{ "ageGroup": 35, "gender": "f", "numUsers": 2 },
{ "ageGroup": 35, "gender": "m", "numUsers": 2 },
{ "ageGroup": 30, "gender": "f", "numUsers": 4 },
{ "ageGroup": 30, "gender": "m", "numUsers": 4 },
{ "ageGroup": 25, "gender": "f", "numUsers": 2 },
{ "ageGroup": 25, "gender": "m", "numUsers": 2 }
]
Aggregation
Adding further aggregation is also simple in AQL by using an AGGREGATE clause
in the COLLECT:
FOR u IN users
FILTER u.active == true
COLLECT ageGroup = FLOOR(u.age / 5) * 5,
gender = u.gender
AGGREGATE numUsers = LENGTH(1),
minAge = MIN(u.age),
maxAge = MAX(u.age)
SORT ageGroup DESC
RETURN {
ageGroup,
gender,
numUsers,
minAge,
maxAge
}
[
{
"ageGroup": 35,
"gender": "f",
"numUsers": 2,
"minAge": 36,
"maxAge": 39,
},
{
"ageGroup": 35,
"gender": "m",
"numUsers": 2,
"minAge": 35,
"maxAge": 39,
},
...
]
We have used the aggregate functions LENGTH here (it returns the length of an array).
This is the equivalent to SQL’s SELECT g, COUNT(*) FROM ... GROUP BY g. In addition to
LENGTH, AQL also provides MAX, MIN, SUM and AVERAGE, VARIANCE_POPULATION,
VARIANCE_SAMPLE, STDDEV_POPULATION, STDDEV_SAMPLE, UNIQUE, SORTED_UNIQUE and
COUNT_UNIQUE as basic aggregation functions.
In AQL all aggregation functions can be run on arrays only. If an aggregation function is run on anything that is not an array, a warning will be produced and the result will be null.
Using an AGGREGATE clause will ensure the aggregation is run while the groups are built
in the collect operation. This is normally more efficient than collecting all group values
for all groups and then doing a post-aggregation.
Post-aggregation
Aggregation can also be performed after a COLLECT operation using other AQL constructs,
though performance-wise this is often inferior to using COLLECT with AGGREGATE.
The same query as before can be turned into a post-aggregation query as shown below. Note that this query will build and pass on all group values for all groups inside the variable g, and perform the aggregation at the latest possible stage:
FOR u IN users
FILTER u.active == true
COLLECT ageGroup = FLOOR(u.age / 5) * 5,
gender = u.gender INTO g
SORT ageGroup DESC
RETURN {
ageGroup,
gender,
numUsers: LENGTH(g[*]),
minAge: MIN(g[*].u.age),
maxAge: MAX(g[*].u.age)
}
[
{
"ageGroup": 35,
"gender": "f",
"numUsers": 2,
"minAge": 36,
"maxAge": 39,
},
{
"ageGroup": 35,
"gender": "m",
"numUsers": 2,
"minAge": 35,
"maxAge": 39,
},
...
]
This is in contrast to the previous query that used an AGGREGATE clause to perform
the aggregation during the collect operation, at the earliest possible stage.
Post-filtering aggregated data
To filter the results of a grouping or aggregation operation (i.e. something
similar to HAVING in SQL), simply add another FILTER clause after the COLLECT
statement.
For example, to get the 3 ageGroups with the most users in them:
FOR u IN users
FILTER u.active == true
COLLECT ageGroup = FLOOR(u.age / 5) * 5 INTO group
LET numUsers = LENGTH(group)
FILTER numUsers > 2 /* group must contain at least 3 users in order to qualify */
SORT numUsers DESC
LIMIT 0, 3
RETURN {
"ageGroup": ageGroup,
"numUsers": numUsers,
"users": group[*].u.name
}
[
{
"ageGroup": 30,
"numUsers": 8,
"users": [
"Abigail",
"Madison",
"Anthony",
"Alexander",
"Isabella",
"Chloe",
"Daniel",
"Michael"
]
},
{
"ageGroup": 25,
"numUsers": 4,
"users": [
"Mary",
"Mariah",
"Jim",
"Diego"
]
},
{
"ageGroup": 35,
"numUsers": 4,
"users": [
"Fred",
"John",
"Emma",
"Sophia"
]
}
]
To increase readability, the repeated expression LENGTH(group) was put into a variable
numUsers. The FILTER on numUsers is the equivalent an SQL HAVING clause.
Aggregating data in local time
If you store datetimes in UTC in your collections and need to group data for
each day in your local timezone, you can use DATE_UTCTOLOCAL() and
DATE_TRUNC() to adjust for that.
Note: In the timezone Europe/Berlin daylight saving activated on 2020-03-29,
thus 2020-01-31T23:00:00Z is 2020-02-01 midnight in Germany and
2020-03-31T22:00:00Z is 2020-04-01 midnight in Germany.