Transform/map json object array to primitive for GIN indexing

Say I have a table with a jsonb column that contains data structured like this:

{
  "records": [
    {
      "id": 1,
      "tag": "address"
    },{
      "id": 1,
      "tag": "receipt"
    }
  ]
}

I’d like to be able to index this column such that I can request “give me all rows where there is a record of type ‘receipt'”.

I’m trying to find an expression that would output a jsonb array that looks like

["address","receipt"]

so then I can plug that expression into

CREATE INDEX ON t1 USING GIN (expr)

I’ve been playing around with all different combinations of the JSONB functions, but I think I’m in over my head.

I wouldn’t store the data like that in the first place, if I could help it. Assuming that that ship has sailed, I would at least transform it to a native PostgreSQL array, not a JSON(B) array, as that would give you better statistics estimates and so probably better execution plans, as well as just plain faster execution.

Due to some arbitrary-seeming restrictions on the composition of set-returning functions with aggregations and expression indexes, I couldn’t find a way to do this without the help of some helper function (which is probably a good idea anyway).

CREATE OR REPLACE FUNCTION public.helper(jsonb)
 RETURNS text[]
 LANGUAGE sql
 IMMUTABLE
AS $function$
select array_agg(x) from
   (select jsonb_array_elements($1->'records')->>'tag') as f(x);
$function$

Followed by:

CREATE INDEX ON t1 USING GIN (public.helper(jsonb_colname));

And then:

select * from t1 where public.helper(x) && ARRAY['receipt'];

But taking a step back, you could do this directly using the built-in jsonb containment operators with no transformations or expressions at all (although the index will probably larger and slower than a tailored one):

create index on t1 using gin (jsonb_colname);
select * from t1 where jsonb_colname @> '{"records":[{"tag":"receipt"}]}';