Aggregation on fixed size JSONB array in PostgreSQL - postgresql

Question

I'm struggling doing aggregations on a JSONB field in a PostgreSQL database. This is probably easier explained with an example so if create and populate a table called analysis with 2 columns (id and analysis) as follows: -
create table analysis (
id serial primary key,
analysis jsonb
);
insert into analysis
(id, analysis) values
(1, '{"category" : "news", "results" : [1, 2, 3, 4, 5 , 6, 7, 8, 9, 10, 11, 12, 13, 14, null, null]}'),
(2, '{"category" : "news", "results" : [11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, null, 26]}'),
(3, '{"category" : "news", "results" : [31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]}'),
(4, '{"category" : "sport", "results" : [51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66]}'),
(5, '{"category" : "sport", "results" : [71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86]}'),
(6, '{"category" : "weather", "results" : [91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106]}');
As you can see the analysis JSONB field always contains 2 attributes category and results. The results attribute will always contain an fixed length array of size 16. I've used various functions such as jsonb_array_elements but what I'm trying to do is the following: -
Group by analysis->'category'
Average of each array element
When I want is a statement to return 3 rows grouped by category (i.e. news, sport and weather) and a 16 fixed length array containing averages. To further complicate things, if there are nulls in the array then we should ignore them (i.e. we are not simply summing and averaging by the number of rows). The result should look something like the following: -
category | analysis_average
-----------+--------------------------------------------------------------------------------------------------------------
"news" | [14.33, 15.33, 16.33, 17.33, 18.33, 19.33, 20.33, 21.33, 22.33, 23.33, 24.33, 25.33, 26.33, 27.33, 45, 36]
"sport" | [61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76]
"weather" | [91, 92, 93, 94, 95, 96, 97, 98, 99, 00, 101, 102, 103, 104, 105, 106]
NOTE: Notice the 45 and 36 in the last 2 array itmes on the 1st row which illustrates ignoring the nullss.
I had considered creating a view which exploded the array into 16 columns i.e.
create view analysis_view as
select a.*,
(a.analysis->'results'->>0)::int as result0,
(a.analysis->'results'->>1)::int as result1
/* ... etc for all 16 array entries .. */
from analysis a;
This seems extremely inelegant to me and removes the advantages of using an array in the first place but could probably hack something together using that approach.
Any pointers or tips will be most appreciated!
Also performance is really important here so the higher the performance the better!

Answer 1

This will work for any array length
select category, array_agg(average order by subscript) as average
from (
select
a.analysis->>'category' category,
subscript,
avg(v)::numeric(5,2) as average
from
analysis a,
lateral unnest(
array(select jsonb_array_elements_text(analysis->'results')::int)
) with ordinality s(v,subscript)
group by 1, 2
) s
group by category
;
category | average
----------+----------------------------------------------------------------------------------------------------------
news | {14.33,15.33,16.33,17.33,18.33,19.33,20.33,21.33,22.33,23.33,24.33,25.33,26.33,27.33,45.00,36.00}
sport | {61.00,62.00,63.00,64.00,65.00,66.00,67.00,68.00,69.00,70.00,71.00,72.00,73.00,74.00,75.00,76.00}
weather | {91.00,92.00,93.00,94.00,95.00,96.00,97.00,98.00,99.00,100.00,101.00,102.00,103.00,104.00,105.00,106.00}
table functions - with ordinality
lateral

Answer 2

Because the array is always of the same length, you can use generate_series instead of typing the index of every array element yourself. You CROSS JOIN with that generated series so the index is applied to every category and you can get every element at position s from the array. Then it is just aggregating the data using GROUP BY.
The query then becomes:
SELECT category, array_agg(val ORDER BY s) analysis_average
FROM (
SELECT analysis->'category' category, s, AVG((analysis->'results'->>s)::numeric) val
FROM analysis
CROSS JOIN generate_series(0, 15) s
GROUP BY category,s
) q
GROUP BY category
15 is in this case the last index of the array (16-1).

Answer 3

It can be done in more traditional way like
select
(t.analysis->'category')::varchar,
array_math_avg(array(select jsonb_array_elements_text(t.analysis->'results')::int))::numeric(9,2)[]
from
analysis t
group by 1 order by 1;
but we need to do some preparation:
create type t_array_math_agg as(
c int[],
a numeric[]
);
create or replace function array_math_sum_f(in t_array_math_agg, in numeric[]) returns t_array_math_agg as $$
declare
r t_array_math_agg;
i int;
begin
if $2 is null then
return $1;
end if;
r := $1;
for i in array_lower($2,1)..array_upper($2,1) loop
if coalesce(r.a[i],$2[i]) is null then
r.a[i] := null;
else
r.a[i] := coalesce(r.a[i],0) + coalesce($2[i],0);
r.c[i] := coalesce(r.c[i],0) + 1;
end if;
end loop;
return r;
end; $$ immutable language plpgsql;
create or replace function array_math_avg_final(in t_array_math_agg) returns numeric[] as $$
declare
r numeric[];
i int;
begin
if array_lower($1.a, 1) is null then
return null;
end if;
for i in array_lower($1.a,1)..array_upper($1.a,1) loop
r[i] := $1.a[i] / $1.c[i];
end loop;
return r;
end; $$ immutable language plpgsql;
create aggregate array_math_avg(numeric[]) (
sfunc=array_math_sum_f,
finalfunc=array_math_avg_final,
stype=t_array_math_agg,
initcond='({},{})'
);