I'm facing an issue regarding using the JSON data type in PostgreSQL. I try to achieve storing a Java model denormalized in the DB. The model features lists of complex objects. Thus, I decided to model those as JSON in native PostgreSQL arrays.
This is a stripped down snippet of my table creation statement:
CREATE TABLE test.persons
(
id UUID,
firstName TEXT,
lastName TEXT,
communicationData JSON[],
CONSTRAINT pk_person PRIMARY KEY (id)
);
As you can see it is a person featuring a list of communication data objects in JSON. One of such objects might look like this:
{"value" : "03334/254147", "typeId" : "ea4e7d7e-7b87-4628-ba50-6a5f6e63dbf6"}
I can easily append such a JSON object to an array using PostgreSQL's array_append. However, I fail at removing a known value from the array. Consider f.e. this SQL statement:
UPDATE test.persons
SET communicationData = array_remove(
communicationData,
'{"value" : "03334/254147", "typeId" : "ea4e7d7e-7b87-4628-ba50-6a5f6e63dbf6"}'::JSON
)
WHERE id = 'f671eb6a-d603-11e3-bf6f-07ba007d953d';
This fails with ERROR: could not identify an equality operator for type json
. Do you have a hint how I could remove a known value from the JSON array? It would also be possible to remove by position in the array, as I know that one also...
PostgreSQL version is 9.3.4.
1 Answer 1
jsonb
in Postgres 9.4 or later
Consider the jsonb
data type in Postgres 9.4 or later. The 'b' at the end stands for 'binary'. Among other things, there is an equality operator (=
) for jsonb
. Most people will want to switch.
json
There is no =
operator defined for the data type json
, because there is no well defined method to establish equality for whole json
values. But see below.
You could cast to text
and then use the =
operator. This is short (and typically slow as it can't use a plain index), but only works if your text representation happens to match. Inherently unreliable, except for corner cases. See:
Or you can unnest
the array and use the ->>
operator to get the JSON object field as text
and compare individual fields.
Test table
Two rows, first like in the question, second with simple values.
CREATE TABLE tbl (
tbl_id int PRIMARY KEY
, jar json[]
);
INSERT INTO t VALUES
(1, '{"{\"value\" : \"03334/254146\", \"typeId\" : \"ea4e7d7e-7b87-4628-ba50-f5\"}"
,"{\"value\" : \"03334/254147\", \"typeId\" : \"ea4e7d7e-7b87-4628-ba50-f6\"}"
,"{\"value\" : \"03334/254148\", \"typeId\" : \"ea4e7d7e-7b87-4628-ba50-f7\"}"}')
, (2, '{"{\"value\" : \"a\", \"typeId\" : \"x\"}"
,"{\"value\" : \"b\", \"typeId\" : \"y\"}"
,"{\"value\" : \"c\", \"typeId\" : \"z\"}"}');
Demos
Demo 1
You could use array_remove()
with text
representations (unreliable).
SELECT tbl_id
, jar, array_length(jar, 1) AS jar_len
, jar::text[] AS t, array_length(jar::text[], 1) AS t_len
, array_remove(jar::text[], '{"value" : "03334/254147", "typeId" : "ea4e7d7e-7b87-4628-ba50-f6"}'::text) AS t_result
, array_remove(jar::text[], '{"value" : "03334/254147", "typeId" : "ea4e7d7e-7b87-4628-ba50-f6"}'::text)::json[] AS j_result
FROM tbl;
Demo 2
Unnest the array and test fields of individual elements.
SELECT tbl_id, array_agg(j) AS j_new
FROM tbl, unnest(jar) AS j -- LATERAL JOIN
WHERE j->>'value' <> '03334/254146'
AND j->>'typeId' <> 'ea4e7d7e-7b87-4628-ba50-6a5f6e63dbf5'
GROUP BY 1;
Demo 3
Alternative test with row type.
SELECT tbl_id, array_agg(j) AS j_new
FROM tbl, unnest(jar) AS j -- LATERAL JOIN
WHERE (j->>'value', j->>'typeId') NOT IN (
('03334/254146', 'ea4e7d7e-7b87-4628-ba50-6a5f6e63dbf5')
, ('a', 'x')
)
GROUP BY 1;
UPDATE
This is how you could implement your UPDATE
:
UPDATE tbl t
SET jar = j.jar
FROM tbl t1
CROSS JOIN LATERAL (
SELECT ARRAY(
SELECT j
FROM unnest(t1.jar) AS j -- LATERAL JOIN
WHERE j->>'value' <> 'a'
AND j->>'typeId' <> 'x'
) AS jar
) j
WHERE t1.tbl_id = 2 -- only relevant rows
AND t1.tbl_id = t.tbl_id;
About the implicit LATERAL JOIN
:
About unnesting arrays:
DB design
To simplify your situation consider an normalized schema: a separate table for the JSON values (instead of the array column), in a n:1 relationship to the main table.
-
It works like a charm. Yes, it would be easier with normalized data, but I'm in a 98% read, 2% write scenario. So I wanted to experiment with denormalization :-) Is there anything releated planned for Postgres 9.4 which might help with the original question?spa– spa2014年05月09日 09:01:21 +00:00Commented May 9, 2014 at 9:01
-
@spa: Actually, Postgres 9.4 will bring
jsonb
. I expect you'll love it. Added a chapter with links.Erwin Brandstetter– Erwin Brandstetter2014年05月09日 17:17:34 +00:00Commented May 9, 2014 at 17:17