Run mode() function of each value in INT ARRAY - sql

Question

I have a table that holds an INT ARRAY data type representing some features (this is done instead of having a separate boolean column for each feature). The column is called feature_ids. If a record has a specific feature, the ID of the feature will be present in the feature_ids column. The mapping of the feature_ids are for context understanding as follows:
1: Fast
2: Expensive
3: Colorfull
4: Deadly
So in other words, I would also have had 4 columns called is_fast, is_expensive, is_colorfull and is_deadly - but I don't since my real application have +100 features, and they change quite a bit.
Now back to the question: I wanna do an aggregate mode() on the records in the table returning what are the most "frequent" features to have (e.g. if it's more common to be "fast" than not etc.). I want it returned in the same format as the original feature_ids column, but where the ID of a feature is ONLY in represented, if it's more common to be there than not, within each group:
CREATE TABLE test (
id INT,
feature_ids integer[] DEFAULT '{}'::integer[],
age INT,
type character varying(255)
);
INSERT INTO test (id, age, feature_ids, type) VALUES (1, 10, '{1,2}', 'movie');
INSERT INTO test (id, age, feature_ids, type) VALUES (2, 2, '{1}', 'movie');
INSERT INTO test (id, age, feature_ids, type) VALUES (3, 9, '{1,2,4}', 'movie');
INSERT INTO test (id, age, feature_ids, type) VALUES (4, 11, '{1,2,3}', 'wine');
INSERT INTO test (id, age, feature_ids, type) VALUES (5, 12, '{1,2,4}', 'hat');
INSERT INTO test (id, age, feature_ids, type) VALUES (6, 12, '{1,2,3}', 'hat');
INSERT INTO test (id, age, feature_ids, type) VALUES (7, 8, '{1,4}', 'hat');
I wanna do a query something like this:
SELECT
type, avg(age) as avg_age, mode() within group (order by feature_ids) as most_frequent_features
from test group by "type"
The result I expect is:
type avg_age most_frequent_features
hat 10.6 [1,2,4]
movie 7.0 [1,2]
wine 11.0 [1,2,3]
I have made an example here: https://www.db-fiddle.com/f/rTP4w7264vDC5rqjef6Nai/1

Answer 1

I find this quite tricky. The following is a rather brute-force approach -- calculating the "mode" explicitly and then bringing in the other aggregates:
select tf.type, t.avg_age,
array_agg(feature_id) as features
from (select t.type, feature_id, count(*) as cnt,
dense_rank() over (partition by t.type order by count(*) desc) as seqnum
from test t cross join
unnest(feature_ids) feature_id
group by t.type, feature_id
) tf join
(select t.type, avg(age) as avg_age
from test t
group by t.type
) t
on tf.type = t.type
where seqnum <= 2
group by tf.type, t.avg_age;
Here is a db<>fiddle.