Wim Bertels schrieb am 17.03.2023 um 11:05:
> what would be the general idea: "easily" convert an hierarchical
> structure like json or xml to a table; for example creating columns by
> appending the key-names when going doing down the three, using null for
> empty values, adding more columns as needed by the given structure.
> (1-way operation)
>
> a few conceptual gists:
> jsonX=
> {
> "glossary": {
> "title": "example glossary",
> "GlossDiv": {
> "title": "S",
> "GlossList": {
> "GlossEntry": {
> "ID": "SGML",
> "SortAs": "SGML",
> "GlossTerm": "Sta..";
> "Acronym": "SGML",
> "Abbrev": "ISO 8879:1986",
> "GlossDef": {
> "para": "A meta-m..",
> "GlossSeeAlso":
> ["GML", "XML"]
> },
> "GlossSee": "markup"
> }
> }
> }
> }
> }
>
> select *
> from json_to_table('jsonX');
> -- generated columns with no data/only nulls could be removed..
> -- arrays could be unnested in the process as well
>
> glossary | glossary.title | glossary.title.GlossDiv.title | ..
> -------------------------------------------------------------
> null | example glossary | S |
> ..
>
> the last column: glossary.title.GlossDiv.GlossList.GlossEntry.GlossSee
> with value "markup"
>
> ---
>
> what if there are different structures that need to be combined?
> (they could be added in the same manner as before)
>
> jsonY=
> {
> s1:[{
> "f1": "a",
> "f2": "b",
> "f3": { "f3.1": "c",
> "f3.2": "d"}
> },
> {
> "f1": "e",
> "f4": "g"
> }
> ]
> }
>
> select *
> from json_to_table('jsonY');
> -- generated columns with no data/only nulls could be removed..
> -- separator sign is untrusted
>
> s1 | s1.f1 | s1.f2 | s1.f3 | s1.f3.f3.1 | s1.f3.f3.2 | s1.f4
> -------------------------------------------------------------
> null| a | b | null | c | d | null
> null| e | null | null | null | null | g
You can't have a function that returns a different set of columns each time you
call it
(without specifying the output columns - which you don't want).
I have once written a function to flatten a JSON hierarchy to multiple rows.
Applied to your first example it would return the following:
path | key | value
-------------------------------------------------+--------------+-----------------
/glossary | title | example
glossary
/glossary/GlossDiv | title | S
/glossary/GlossDiv/GlossList/GlossEntry | ID | SGML
/glossary/GlossDiv/GlossList/GlossEntry | Abbrev | ISO 8879:1986
/glossary/GlossDiv/GlossList/GlossEntry | SortAs | SGML
/glossary/GlossDiv/GlossList/GlossEntry | Acronym | SGML
/glossary/GlossDiv/GlossList/GlossEntry | GlossSee | markup
/glossary/GlossDiv/GlossList/GlossEntry | GlossTerm | Sta..
/glossary/GlossDiv/GlossList/GlossEntry/GlossDef | para | A meta-m..
/glossary/GlossDiv/GlossList/GlossEntry/GlossDef | GlossSeeAlso | ["GML", "XML"]
And the following for the second example:
path | key | value
-------+------+------
/s1 | f1 | a
/s1 | f2 | b
/s1/f3 | f3.1 | c
/s1/f3 | f3.2 | d
/s1 | f1 | e
/s1 | f4 | g
Thomas
create or replace function flatten(p_input jsonb, p_path text)
returns table(path text, key text, value text)
as
$$
begin
if jsonb_typeof(p_input) = 'array' then
return query
select f.*
from jsonb_array_elements(p_input) as a(element)
cross join flatten(a.element, p_path) f;
else
return query
select p_path, e.key, e.value #>> '{}'
from jsonb_each(p_input) as e(key, value)
where jsonb_typeof(e.value) not in ('object', 'array')
or (jsonb_typeof(e.value) = 'array' and jsonb_typeof(e.value -> 0) <>
'object')
union all
select f.*
from jsonb_each(p_input) as t(key,value)
cross join flatten(t.value, p_path||'/'||t.key) as f
where jsonb_typeof(t.value) = 'object'
union all
select f.*
from jsonb_each(p_input) as t(key,value)
cross join jsonb_array_elements(t.value) as a(element)
cross join flatten(a.element, p_path||'/'||t.key) as f
where jsonb_typeof(t.value) = 'array'
and jsonb_typeof(t.value -> 0) = 'object';
end if;
end;
$$
language plpgsql
immutable
parallel safe
;
create or replace function flatten(p_input jsonb)
returns table(path text, key text, value text)
as
$$
select *
from flatten(p_input, '');
$$
language sql
immutable
parallel safe
;
