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Adds JSON_TABLE() support, and SQL/JSON constructor/query functions tests (#7816) 

DESCRIPTION: Adds JSON_TABLE() support

PG17 has added basic `JSON_TABLE()` functionality
`JSON_TABLE()` allows `JSON` data to be converted into a relational view
and thus used, for example, in a `FROM` clause, like other tabular data.

We treat `JSON_TABLE` the same as correlated functions (e.g., recurring
tuples). In the end, for multi-shard `JSON_TABLE` commands, we apply the
same restrictions as reference tables (e.g., cannot perform a lateral
outer join when a distributed subquery references a (reference
table)/(json table) etc.)

Relevant PG17 commits:
[basic JSON
table](https://github.com/postgres/postgres/commit/de3600452), [nested
paths in json
table](https://github.com/postgres/postgres/commit/bb766cde6)

Onder had previously added json table support for PG15BETA1, but we
reverted that commit because json table was reverted in PG15.
ce7f1a530f
Previous relevant PG15Beta1 commit:
https://github.com/postgres/postgres/commit/4e34747c8
Therefore, I referred to Onder's commit for this commit as well, with a
few changes due to some differences between PG15/PG17:

1) In PG15Beta1, we had also `PLAN` clauses for `JSON_TABLE`
https://github.com/postgres/postgres/commit/fadb48b00, and Onder's
commit includes tests for those as well. However, `PLAN` nodes are _not_
added in PG17. Therefore, I didn't include the `json_table_select_only`
test, which had mostly queries involving `PLAN`. I only included the
last query from that test.

2) In PG15 timeline (Citus 11.1), we didn't support outer joins where
the outer rel is a recurring one and the inner one is a non-recurring
one. However, [Onur added support for that one in Citus
11.2](https://github.com/citusdata/citus/pull/6512), therefore I updated
the tests from Onder's commit accordingly.

3) PG17 json table has nested paths and columns, therefore I added a
test
with a distributed table, which is exactly the same as the one in
sqljson_jsontable in PG17.
https://github.com/postgres/postgres/commit/bb766cde6

This pull request also adds some basic tests on validation of SQL/JSON
constructor functions JSON(), JSON_SCALAR(), and JSON_SERIALIZE(),
and also SQL/JSON query functions JSON_EXISTS(), JSON_QUERY(), and
JSON_VALUE(). The relevant PG commits are the following:
[JSON(), JSON_SCALAR(),
JSON_SERIALIZE()](https://github.com/postgres/postgres/commit/03734a7fe)
[JSON_EXISTS(), JSON_VALUE(),
JSON_QUERY()](https://github.com/postgres/postgres/commit/6185c9737)
pull/7822/head
Naisila Puka 2024-12-30 19:19:07 +03:00 committed by GitHub
parent 8a8b2f9a6d
commit 9e3c3297fc
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
7 changed files with 1031 additions and 6 deletions
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3
src/backend/distributed/planner/multi_logical_planner.c
View File

@ -1170,7 +1170,8 @@ HasComplexRangeTableType(Query *queryTree)
if (rangeTableEntry->rtekind != RTE_RELATION &&
rangeTableEntry->rtekind != RTE_SUBQUERY &&
rangeTableEntry->rtekind != RTE_FUNCTION &&
rangeTableEntry->rtekind != RTE_VALUES)
rangeTableEntry->rtekind != RTE_VALUES &&
!IsJsonTableRTE(rangeTableEntry))
{
hasComplexRangeTableType = true;
}

56
src/backend/distributed/planner/query_pushdown_planning.c
View File

@ -61,7 +61,8 @@ typedef enum RecurringTuplesType
RECURRING_TUPLES_FUNCTION,
RECURRING_TUPLES_EMPTY_JOIN_TREE,
RECURRING_TUPLES_RESULT_FUNCTION,
RECURRING_TUPLES_VALUES
RECURRING_TUPLES_VALUES,
RECURRING_TUPLES_JSON_TABLE
} RecurringTuplesType;
/*
@ -347,7 +348,8 @@ IsFunctionOrValuesRTE(Node *node)
RangeTblEntry *rangeTblEntry = (RangeTblEntry *) node;
if (rangeTblEntry->rtekind == RTE_FUNCTION ||
rangeTblEntry->rtekind == RTE_VALUES)
rangeTblEntry->rtekind == RTE_VALUES ||
IsJsonTableRTE(rangeTblEntry))
{
return true;
}
@ -700,6 +702,13 @@ DeferErrorIfFromClauseRecurs(Query *queryTree)
"the FROM clause contains VALUES", NULL,
NULL);
}
else if (recurType == RECURRING_TUPLES_JSON_TABLE)
{
return DeferredError(ERRCODE_FEATURE_NOT_SUPPORTED,
"correlated subqueries are not supported when "
"the FROM clause contains JSON_TABLE", NULL,
NULL);
}
/*
@ -1204,7 +1213,8 @@ DeferErrorIfUnsupportedTableCombination(Query *queryTree)
*/
if (rangeTableEntry->rtekind == RTE_RELATION ||
rangeTableEntry->rtekind == RTE_SUBQUERY ||
rangeTableEntry->rtekind == RTE_RESULT)
rangeTableEntry->rtekind == RTE_RESULT ||
IsJsonTableRTE(rangeTableEntry))
{
/* accepted */
}
@ -1372,6 +1382,13 @@ DeferErrorIfUnsupportedUnionQuery(Query *subqueryTree)
"VALUES is not supported within a "
"UNION", NULL);
}
else if (recurType == RECURRING_TUPLES_JSON_TABLE)
{
return DeferredError(ERRCODE_FEATURE_NOT_SUPPORTED,
"cannot push down this subquery",
"JSON_TABLE is not supported within a "
"UNION", NULL);
}
return NULL;
}
@ -1477,6 +1494,11 @@ RecurringTypeDescription(RecurringTuplesType recurType)
return "a VALUES clause";
}
case RECURRING_TUPLES_JSON_TABLE:
{
return "a JSON_TABLE";
}
case RECURRING_TUPLES_INVALID:
{
/*
@ -1673,7 +1695,8 @@ DeferredErrorIfUnsupportedLateralSubquery(PlannerInfo *plannerInfo,
* strings anyway.
*/
if (recurType != RECURRING_TUPLES_VALUES &&
recurType != RECURRING_TUPLES_RESULT_FUNCTION)
recurType != RECURRING_TUPLES_RESULT_FUNCTION &&
recurType != RECURRING_TUPLES_JSON_TABLE)
{
recurTypeDescription = psprintf("%s (%s)", recurTypeDescription,
recurringRangeTableEntry->eref->
@ -1750,6 +1773,26 @@ ContainsRecurringRangeTable(List *rangeTable, RecurringTuplesType *recurType)
}
/*
* IsJsonTableRTE checks whether the RTE refers to a JSON_TABLE
* table function, which was introduced in PostgreSQL 17.
*/
bool
IsJsonTableRTE(RangeTblEntry *rte)
{
#if PG_VERSION_NUM >= PG_VERSION_17
if (rte == NULL)
{
return false;
}
return (rte->rtekind == RTE_TABLEFUNC &&
rte->tablefunc->functype == TFT_JSON_TABLE);
#endif
return false;
}
/*
* HasRecurringTuples returns whether any part of the expression will generate
* the same set of tuples in every query on shards when executing a distributed
@ -1811,6 +1854,11 @@ HasRecurringTuples(Node *node, RecurringTuplesType *recurType)
*recurType = RECURRING_TUPLES_VALUES;
return true;
}
else if (IsJsonTableRTE(rangeTableEntry))
{
*recurType = RECURRING_TUPLES_JSON_TABLE;
return true;
}
return false;
}

1
src/include/distributed/query_pushdown_planning.h
View File

@ -46,6 +46,7 @@ extern DeferredErrorMessage * DeferErrorIfCannotPushdownSubquery(Query *subquery
bool
outerMostQueryHasLimit);
extern DeferredErrorMessage * DeferErrorIfUnsupportedUnionQuery(Query *queryTree);
extern bool IsJsonTableRTE(RangeTblEntry *rte);
#endif /* QUERY_PUSHDOWN_PLANNING_H */

578
src/test/regress/expected/pg17_json.out Normal file
View File

@ -0,0 +1,578 @@
--
-- PG17_JSON
-- PG17 has added basic JSON_TABLE() functionality
-- JSON_TABLE() allows JSON data to be converted into a relational view
-- and thus used, for example, in a FROM clause, like other tabular
-- data. We treat JSON_TABLE the same as correlated functions (e.g., recurring tuples).
-- In the end, for multi-shard JSON_TABLE commands, we apply the same
-- restrictions as reference tables (e.g., cannot perform a lateral outer join
-- when a distributed subquery references a (reference table)/JSON_TABLE etc.)
-- Relevant PG commit:
-- https://github.com/postgres/postgres/commit/de3600452
--
SHOW server_version \gset
SELECT substring(:'server_version', '\d+')::int >= 17 AS server_version_ge_17
\gset
\if :server_version_ge_17
\else
\q
\endif
CREATE SCHEMA pg17_json;
SET search_path TO pg17_json;
SET citus.next_shard_id TO 1687000;
CREATE TABLE test_table(id bigserial, value text);
SELECT create_distributed_table('test_table', 'id');
create_distributed_table
---------------------------------------------------------------------
(1 row)
INSERT INTO test_table (value) SELECT i::text FROM generate_series(0,100)i;
CREATE TABLE my_films(id bigserial, js jsonb);
SELECT create_distributed_table('my_films', 'id');
create_distributed_table
---------------------------------------------------------------------
(1 row)
INSERT INTO my_films(js) VALUES (
'{ "favorites" : [
{ "kind" : "comedy", "films" : [ { "title" : "Bananas", "director" : "Woody Allen"},
{ "title" : "The Dinner Game", "director" : "Francis Veber" } ] },
{ "kind" : "horror", "films" : [{ "title" : "Psycho", "director" : "Alfred Hitchcock" } ] },
{ "kind" : "thriller", "films" : [{ "title" : "Vertigo", "director" : "Alfred Hitchcock" } ] },
{ "kind" : "drama", "films" : [{ "title" : "Yojimbo", "director" : "Akira Kurosawa" } ] }
] }');
INSERT INTO my_films(js) VALUES (
'{ "favorites" : [
{ "kind" : "comedy", "films" : [ { "title" : "Bananas2", "director" : "Woody Allen"},
{ "title" : "The Dinner Game2", "director" : "Francis Veber" } ] },
{ "kind" : "horror", "films" : [{ "title" : "Psycho2", "director" : "Alfred Hitchcock" } ] },
{ "kind" : "thriller", "films" : [{ "title" : "Vertigo2", "director" : "Alfred Hitchcock" } ] },
{ "kind" : "drama", "films" : [{ "title" : "Yojimbo2", "director" : "Akira Kurosawa" } ] }
] }');
-- a router query
SELECT jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt
WHERE my_films.id = 1
ORDER BY 1,2,3,4;
id | kind | title | director
---------------------------------------------------------------------
1 | comedy | Bananas | Woody Allen
1 | comedy | The Dinner Game | Francis Veber
2 | horror | Psycho | Alfred Hitchcock
3 | thriller | Vertigo | Alfred Hitchcock
4 | drama | Yojimbo | Akira Kurosawa
(5 rows)
-- router query with an explicit LATEREL SUBQUERY
SELECT sub.*
FROM my_films,
lateral(SELECT * FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt) as sub
WHERE my_films.id = 1;
id | kind | title | director
---------------------------------------------------------------------
1 | comedy | Bananas | Woody Allen
1 | comedy | The Dinner Game | Francis Veber
2 | horror | Psycho | Alfred Hitchcock
3 | thriller | Vertigo | Alfred Hitchcock
4 | drama | Yojimbo | Akira Kurosawa
(5 rows)
-- router query with an explicit LATEREL SUBQUERY and LIMIT
SELECT sub.*
FROM my_films,
lateral(SELECT * FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt ORDER BY id DESC LIMIT 1) as sub
WHERE my_films.id = 1;
id | kind | title | director
---------------------------------------------------------------------
4 | drama | Yojimbo | Akira Kurosawa
(1 row)
-- set it DEBUG1 in case the plan changes
-- we can see details
SET client_min_messages TO DEBUG1;
-- a mult-shard query
SELECT jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt
ORDER BY 1,2,3,4;
id | kind | title | director
---------------------------------------------------------------------
1 | comedy | Bananas | Woody Allen
1 | comedy | Bananas2 | Woody Allen
1 | comedy | The Dinner Game | Francis Veber
1 | comedy | The Dinner Game2 | Francis Veber
2 | horror | Psycho | Alfred Hitchcock
2 | horror | Psycho2 | Alfred Hitchcock
3 | thriller | Vertigo | Alfred Hitchcock
3 | thriller | Vertigo2 | Alfred Hitchcock
4 | drama | Yojimbo | Akira Kurosawa
4 | drama | Yojimbo2 | Akira Kurosawa
(10 rows)
-- recursively plan subqueries that has JSON_TABLE
SELECT count(*) FROM
(
SELECT jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt
LIMIT 1) as sub_with_json, test_table
WHERE test_table.id = sub_with_json.id;
DEBUG: push down of limit count: 1
DEBUG: generating subplan XXX_1 for subquery SELECT jt.id, jt.kind, jt.title, jt.director FROM pg17_json.my_films, LATERAL JSON_TABLE(my_films.js, '$."favorites"[*]' AS json_table_path_0 COLUMNS (id FOR ORDINALITY, kind text PATH '$."kind"', NESTED PATH '$."films"[*]' AS json_table_path_1 COLUMNS (title text PATH '$."title"', director text PATH '$."director"'))) jt LIMIT 1
DEBUG: Plan XXX query after replacing subqueries and CTEs: SELECT count(*) AS count FROM (SELECT intermediate_result.id, intermediate_result.kind, intermediate_result.title, intermediate_result.director FROM read_intermediate_result('XXX_1'::text, 'binary'::citus_copy_format) intermediate_result(id integer, kind text, title text, director text)) sub_with_json, pg17_json.test_table WHERE (test_table.id OPERATOR(pg_catalog.=) sub_with_json.id)
count
---------------------------------------------------------------------
1
(1 row)
-- multi-shard query with an explicit LATEREL SUBQUERY
SELECT sub.*
FROM my_films JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true)
ORDER BY 1,2,3,4;
id | kind | title | director
---------------------------------------------------------------------
1 | comedy | Bananas | Woody Allen
1 | comedy | Bananas2 | Woody Allen
1 | comedy | The Dinner Game | Francis Veber
1 | comedy | The Dinner Game2 | Francis Veber
2 | horror | Psycho | Alfred Hitchcock
2 | horror | Psycho2 | Alfred Hitchcock
3 | thriller | Vertigo | Alfred Hitchcock
3 | thriller | Vertigo2 | Alfred Hitchcock
4 | drama | Yojimbo | Akira Kurosawa
4 | drama | Yojimbo2 | Akira Kurosawa
(10 rows)
-- JSON_TABLE can be on the inner part of an outer joion
SELECT sub.*
FROM my_films LEFT JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true)
ORDER BY 1,2,3,4;
id | kind | title | director
---------------------------------------------------------------------
1 | comedy | Bananas | Woody Allen
1 | comedy | Bananas2 | Woody Allen
1 | comedy | The Dinner Game | Francis Veber
1 | comedy | The Dinner Game2 | Francis Veber
2 | horror | Psycho | Alfred Hitchcock
2 | horror | Psycho2 | Alfred Hitchcock
3 | thriller | Vertigo | Alfred Hitchcock
3 | thriller | Vertigo2 | Alfred Hitchcock
4 | drama | Yojimbo | Akira Kurosawa
4 | drama | Yojimbo2 | Akira Kurosawa
(10 rows)
-- we can pushdown this correlated subquery in WHERE clause
SELECT count(*)
FROM my_films WHERE
(SELECT count(*) > 0
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000);
count
---------------------------------------------------------------------
2
(1 row)
-- we can pushdown this correlated subquery in SELECT clause
SELECT (SELECT count(*) > 0
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt)
FROM my_films;
?column?
---------------------------------------------------------------------
t
t
(2 rows)
-- multi-shard query with an explicit LATEREL SUBQUERY
-- along with other tables
SELECT sub.*
FROM my_films JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true) JOIN test_table ON(my_films.id = test_table.id)
ORDER BY 1,2,3,4;
id | kind | title | director
---------------------------------------------------------------------
1 | comedy | Bananas | Woody Allen
1 | comedy | Bananas2 | Woody Allen
1 | comedy | The Dinner Game | Francis Veber
1 | comedy | The Dinner Game2 | Francis Veber
2 | horror | Psycho | Alfred Hitchcock
2 | horror | Psycho2 | Alfred Hitchcock
3 | thriller | Vertigo | Alfred Hitchcock
3 | thriller | Vertigo2 | Alfred Hitchcock
4 | drama | Yojimbo | Akira Kurosawa
4 | drama | Yojimbo2 | Akira Kurosawa
(10 rows)
-- non-colocated join fails
SELECT sub.*
FROM my_films JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true) JOIN test_table ON(my_films.id != test_table.id)
ORDER BY 1,2,3,4;
ERROR: complex joins are only supported when all distributed tables are co-located and joined on their distribution columns
-- JSON_TABLE can be in the outer part of the join
-- as long as there is a distributed table
SELECT sub.*
FROM my_films JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true) LEFT JOIN test_table ON(my_films.id = test_table.id)
ORDER BY 1,2,3,4;
id | kind | title | director
---------------------------------------------------------------------
1 | comedy | Bananas | Woody Allen
1 | comedy | Bananas2 | Woody Allen
1 | comedy | The Dinner Game | Francis Veber
1 | comedy | The Dinner Game2 | Francis Veber
2 | horror | Psycho | Alfred Hitchcock
2 | horror | Psycho2 | Alfred Hitchcock
3 | thriller | Vertigo | Alfred Hitchcock
3 | thriller | Vertigo2 | Alfred Hitchcock
4 | drama | Yojimbo | Akira Kurosawa
4 | drama | Yojimbo2 | Akira Kurosawa
(10 rows)
-- JSON_TABLE can be on the outer side of the join
-- We support outer joins where the outer rel is a recurring one
-- and the inner one is a non-recurring one if we don't reference the outer from the inner
-- https://github.com/citusdata/citus/pull/6512
SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (id FOR ORDINALITY, column_a int4 PATH '$.a', column_b int4 PATH '$.b', a int4, b int4, c text))
LEFT JOIN LATERAL
(SELECT *
FROM my_films) AS foo on(foo.id = a);
DEBUG: recursively planning right side of the left join since the outer side is a recurring rel
DEBUG: recursively planning the distributed subquery since it is part of a distributed join node that is outer joined with a recurring rel
DEBUG: generating subplan XXX_1 for subquery SELECT id, js FROM pg17_json.my_films
DEBUG: Plan XXX query after replacing subqueries and CTEs: SELECT "json_table".id, "json_table".column_a, "json_table".column_b, "json_table".a, "json_table".b, "json_table".c, foo.id, foo.js FROM (JSON_TABLE('[{"a": 10, "b": 20}, {"a": 30, "b": 40}]'::jsonb, '$[*]' AS json_table_path_0 COLUMNS (id FOR ORDINALITY, column_a integer PATH '$."a"', column_b integer PATH '$."b"', a integer PATH '$."a"', b integer PATH '$."b"', c text PATH '$."c"')) LEFT JOIN LATERAL (SELECT intermediate_result.id, intermediate_result.js FROM read_intermediate_result('XXX_1'::text, 'binary'::citus_copy_format) intermediate_result(id bigint, js jsonb)) foo ON ((foo.id OPERATOR(pg_catalog.=) "json_table".a)))
id | column_a | column_b | a | b | c | id | js
---------------------------------------------------------------------
1 | 10 | 20 | 10 | 20 | | |
2 | 30 | 40 | 30 | 40 | | |
(2 rows)
-- However we don't support
-- when we reference the JSON_TABLE from the non-recurring distributed table subquery
SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (json_id FOR ORDINALITY, column_a int4 PATH '$.a', column_b int4 PATH '$.b', a int4, b int4, c text))
LEFT JOIN LATERAL
(SELECT *
FROM my_films WHERE id::text LIKE c) AS foo on(foo.id = a);
DEBUG: recursively planning right side of the left join since the outer side is a recurring rel
DEBUG: recursively planning the distributed subquery since it is part of a distributed join node that is outer joined with a recurring rel
ERROR: cannot perform a lateral outer join when a distributed subquery references a JSON_TABLE
-- JSON_TABLE cannot be on the FROM clause alone
SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (json_id FOR ORDINALITY, column_a int4 PATH '$.a', column_b int4 PATH '$.b', a int4, b int4, c text)) as foo
WHERE b >
(SELECT count(*)
FROM my_films WHERE id = foo.a);
ERROR: correlated subqueries are not supported when the FROM clause contains JSON_TABLE
-- we can recursively plan json_tables on set operations
(SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (id FOR ORDINALITY)) ORDER BY id ASC LIMIT 1)
UNION
(SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (id FOR ORDINALITY)) ORDER BY id ASC LIMIT 1)
UNION
(SELECT id FROM test_table ORDER BY id ASC LIMIT 1);
DEBUG: generating subplan XXX_1 for subquery SELECT id FROM JSON_TABLE('[{"a": 10, "b": 20}, {"a": 30, "b": 40}]'::jsonb, '$[*]' AS json_table_path_0 COLUMNS (id FOR ORDINALITY)) ORDER BY id LIMIT 1
DEBUG: generating subplan XXX_2 for subquery SELECT id FROM JSON_TABLE('[{"a": 10, "b": 20}, {"a": 30, "b": 40}]'::jsonb, '$[*]' AS json_table_path_0 COLUMNS (id FOR ORDINALITY)) ORDER BY id LIMIT 1
DEBUG: push down of limit count: 1
DEBUG: generating subplan XXX_3 for subquery SELECT id FROM pg17_json.test_table ORDER BY id LIMIT 1
DEBUG: Plan XXX query after replacing subqueries and CTEs: SELECT intermediate_result.id FROM read_intermediate_result('XXX_1'::text, 'binary'::citus_copy_format) intermediate_result(id integer) UNION SELECT intermediate_result.id FROM read_intermediate_result('XXX_2'::text, 'binary'::citus_copy_format) intermediate_result(id integer) UNION SELECT intermediate_result.id FROM read_intermediate_result('XXX_3'::text, 'binary'::citus_copy_format) intermediate_result(id bigint)
id
---------------------------------------------------------------------
1
(1 row)
-- LIMIT in subquery not supported when json_table exists
SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (id FOR ORDINALITY, column_a int4 PATH '$.a', column_b int4 PATH '$.b', a int4, b int4, c text))
JOIN LATERAL
(SELECT *
FROM my_films WHERE json_table.id = a LIMIT 1) as foo ON (true);
ERROR: cannot push down this subquery
DETAIL: Limit clause is currently unsupported when a lateral subquery references a column from a JSON_TABLE
RESET client_min_messages;
-- we can use JSON_TABLE in modification queries as well
-- use log level such that we can see trace changes
SET client_min_messages TO DEBUG1;
--the JSON_TABLE subquery is recursively planned
UPDATE test_table SET VALUE = 'XXX' FROM(
SELECT jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt) as foo WHERE foo.id = test_table.id;
DEBUG: generating subplan XXX_1 for subquery SELECT jt.id, jt.kind, jt.title, jt.director FROM pg17_json.my_films, LATERAL JSON_TABLE(my_films.js, '$."favorites"[*]' AS json_table_path_0 COLUMNS (id FOR ORDINALITY, kind text PATH '$."kind"', NESTED PATH '$."films"[*]' AS json_table_path_1 COLUMNS (title text PATH '$."title"', director text PATH '$."director"'))) jt
DEBUG: Plan XXX query after replacing subqueries and CTEs: UPDATE pg17_json.test_table SET value = 'XXX'::text FROM (SELECT intermediate_result.id, intermediate_result.kind, intermediate_result.title, intermediate_result.director FROM read_intermediate_result('XXX_1'::text, 'binary'::citus_copy_format) intermediate_result(id integer, kind text, title text, director text)) foo WHERE (foo.id OPERATOR(pg_catalog.=) test_table.id)
-- Subquery with JSON table can be pushed down because two distributed tables
-- in the query are joined on distribution column
UPDATE test_table SET VALUE = 'XXX' FROM (
SELECT my_films.id, jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt) as foo WHERE foo.id = test_table.id;
-- we can pushdown with CTEs as well
WITH json_cte AS
(SELECT my_films.id, jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt)
UPDATE test_table SET VALUE = 'XYZ' FROM json_cte
WHERE json_cte.id = test_table.id;
-- we can recursively with CTEs as well
WITH json_cte AS
(SELECT my_films.id as film_id, jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
id FOR ORDINALITY,
title text PATH '$.title',
director text PATH '$.director'))) AS jt ORDER BY jt.id LIMIT 1)
UPDATE test_table SET VALUE = 'XYZ' FROM json_cte
WHERE json_cte.film_id = test_table.id;
DEBUG: generating subplan XXX_1 for CTE json_cte: SELECT my_films.id AS film_id, jt.kind, jt.id, jt.title, jt.director FROM pg17_json.my_films, LATERAL JSON_TABLE(my_films.js, '$."favorites"[*]' AS json_table_path_0 COLUMNS (kind text PATH '$."kind"', NESTED PATH '$."films"[*]' AS json_table_path_1 COLUMNS (id FOR ORDINALITY, title text PATH '$."title"', director text PATH '$."director"'))) jt ORDER BY jt.id LIMIT 1
DEBUG: push down of limit count: 1
DEBUG: Plan XXX query after replacing subqueries and CTEs: UPDATE pg17_json.test_table SET value = 'XYZ'::text FROM (SELECT intermediate_result.film_id, intermediate_result.kind, intermediate_result.id, intermediate_result.title, intermediate_result.director FROM read_intermediate_result('XXX_1'::text, 'binary'::citus_copy_format) intermediate_result(film_id bigint, kind text, id integer, title text, director text)) json_cte WHERE (json_cte.film_id OPERATOR(pg_catalog.=) test_table.id)
-- JSON_TABLE NESTED
-- JSON_TABLE: plan execution
-- Check output with Postgres table in sqljson_jsontable test
-- https://github.com/postgres/postgres/blob/REL_17_0/src/test/regress/expected/sqljson_jsontable.out#L776-L814
CREATE TABLE jsonb_table_test (id bigserial, js jsonb);
DEBUG: CREATE TABLE will create implicit sequence "jsonb_table_test_id_seq" for serial column "jsonb_table_test.id"
SELECT create_distributed_table('jsonb_table_test', 'id');
create_distributed_table
---------------------------------------------------------------------
(1 row)
INSERT INTO jsonb_table_test
VALUES (1,
'[
{"a": 1, "b": [], "c": []},
{"a": 2, "b": [1, 2, 3], "c": [10, null, 20]},
{"a": 3, "b": [1, 2], "c": []},
{"x": "4", "b": [1, 2], "c": 123}
]'
);
select
jt.*
from
jsonb_table_test jtt,
json_table (
jtt.js,'strict $[*]' as p
columns (
n for ordinality,
a int path 'lax $.a' default -1 on empty,
nested path 'strict $.b[*]' as pb columns (b_id for ordinality, b int path '$' ),
nested path 'strict $.c[*]' as pc columns (c_id for ordinality, c int path '$' )
)
) jt;
n | a | b_id | b | c_id | c
---------------------------------------------------------------------
1 | 1 | | | |
2 | 2 | 1 | 1 | |
2 | 2 | 2 | 2 | |
2 | 2 | 3 | 3 | |
2 | 2 | | | 1 | 10
2 | 2 | | | 2 |
2 | 2 | | | 3 | 20
3 | 3 | 1 | 1 | |
3 | 3 | 2 | 2 | |
4 | -1 | 1 | 1 | |
4 | -1 | 2 | 2 | |
(11 rows)
-- test some utility functions on the target list & where clause: json_exists()
select jsonb_path_exists(js, '$.favorites') from my_films;
jsonb_path_exists
---------------------------------------------------------------------
t
t
(2 rows)
select bool_and(JSON_EXISTS(js, '$.favorites.films.title')) from my_films;
bool_and
---------------------------------------------------------------------
t
(1 row)
SELECT count(*) FROM my_films WHERE jsonb_path_exists(js, '$.favorites');
count
---------------------------------------------------------------------
2
(1 row)
SELECT count(*) FROM my_films WHERE JSON_EXISTS(js, '$.favorites.films.title');
count
---------------------------------------------------------------------
2
(1 row)
-- check constraint with json_exists, use json_scalar also
SET citus.shard_replication_factor TO 1;
create table user_profiles (
id bigserial,
addresses jsonb,
anyjson jsonb,
serialized bytea,
check (json_exists( addresses, '$.main' )) -- we should insert a key named main
);
DEBUG: CREATE TABLE will create implicit sequence "user_profiles_id_seq" for serial column "user_profiles.id"
select create_distributed_table('user_profiles', 'id');
create_distributed_table
---------------------------------------------------------------------
(1 row)
insert into user_profiles (addresses) VALUES (JSON_SCALAR('1'));
ERROR: new row for relation "user_profiles_1687012" violates check constraint "user_profiles_addresses_check"
DETAIL: Failing row contains (1, "1", null, null).
CONTEXT: while executing command on localhost:xxxxx
insert into user_profiles (addresses, anyjson) VALUES ('{"main":"value"}', JSON_SCALAR('1')) RETURNING *;
id | addresses | anyjson | serialized
---------------------------------------------------------------------
2 | {"main": "value"} | "1" |
(1 row)
-- use json() - we cannot insert because WITH UNIQUE KEYS
insert into user_profiles (addresses) VALUES (JSON ('{"main":"value", "main":"value"}' WITH UNIQUE KEYS));
ERROR: duplicate JSON object key value
-- we can insert with
insert into user_profiles (addresses) VALUES (JSON ('{"main":"value", "main":"value"}' WITHOUT UNIQUE KEYS)) RETURNING *;
id | addresses | anyjson | serialized
---------------------------------------------------------------------
4 | {"main": "value"} | |
(1 row)
-- JSON predicates
TRUNCATE user_profiles;
INSERT INTO user_profiles (anyjson) VALUES ('12'), ('"abc"'), ('[1,2,3]'), ('{"a":12}');
select anyjson, anyjson is json array as json_array, anyjson is json object as json_object, anyjson is json scalar as json_scalar,
anyjson is json with UNIQUE keys
from user_profiles WHERE anyjson IS NOT NULL ORDER BY 1;
anyjson | json_array | json_object | json_scalar | ?column?
---------------------------------------------------------------------
"abc" | f | f | t | t
12 | f | f | t | t
[1, 2, 3] | t | f | f | t
{"a": 12} | f | t | f | t
(4 rows)
-- use json_serialize
-- it is evaluated in the worker
SELECT JSON_SERIALIZE('{ "a" : 1 } ' RETURNING bytea);
json_serialize
---------------------------------------------------------------------
\x7b20226122203a2031207d20
(1 row)
SET citus.log_remote_commands TO on;
INSERT INTO user_profiles (serialized) VALUES (JSON_SERIALIZE('{ "a" : 1 } ' RETURNING bytea)) RETURNING *;
NOTICE: issuing INSERT INTO pg17_json.user_profiles_1687015 (id, serialized) VALUES ('9'::bigint, JSON_SERIALIZE('{ "a" : 1 } '::text RETURNING bytea)) RETURNING id, addresses, anyjson, serialized
DETAIL: on server postgres@localhost:xxxxx connectionId: xxxxxxx
id | addresses | anyjson | serialized
---------------------------------------------------------------------
9 | | | \x7b20226122203a2031207d20
(1 row)
RESET citus.log_remote_commands;
-- use json_query
SELECT i,
json_query('[{"x": "aaa"},{"x": "bbb"},{"x": "ccc"}]'::JSONB, '$[$i].x' passing id AS i RETURNING text omit quotes)
FROM generate_series(0, 3) i
JOIN my_films ON(id = i) ORDER BY 1;
i | json_query
---------------------------------------------------------------------
1 | bbb
2 | ccc
(2 rows)
-- use json_value
-- check output with sqljson_queryfuncs test
-- https://github.com/postgres/postgres/blob/REL_17_0/src/test/regress/expected/sqljson_queryfuncs.out#L439-L455
SELECT i,
JSON_VALUE(
jsonb '{"a": 1, "b": 2}',
'$.* ? (@ > $i)' PASSING id AS i
RETURNING int
DEFAULT -1 ON EMPTY
DEFAULT -2 ON ERROR
)
FROM generate_series(0, 3) i
JOIN my_films ON(id = i) ORDER BY 1;
i | json_value
---------------------------------------------------------------------
1 | 2
2 | -1
(2 rows)
SET client_min_messages TO ERROR;
DROP SCHEMA pg17_json CASCADE;

18
src/test/regress/expected/pg17_json_0.out Normal file
View File

@ -0,0 +1,18 @@
--
-- PG17_JSON
-- PG17 has added basic JSON_TABLE() functionality
-- JSON_TABLE() allows JSON data to be converted into a relational view
-- and thus used, for example, in a FROM clause, like other tabular
-- data. We treat JSON_TABLE the same as correlated functions (e.g., recurring tuples).
-- In the end, for multi-shard JSON_TABLE commands, we apply the same
-- restrictions as reference tables (e.g., cannot perform a lateral outer join
-- when a distributed subquery references a (reference table)/JSON_TABLE etc.)
-- Relevant PG commit:
-- https://github.com/postgres/postgres/commit/de3600452
--
SHOW server_version \gset
SELECT substring(:'server_version', '\d+')::int >= 17 AS server_version_ge_17
\gset
\if :server_version_ge_17
\else
\q

2
src/test/regress/multi_schedule
View File

@ -66,7 +66,7 @@ test: pg14
test: pg15
test: pg15_jsonpath detect_conn_close
test: pg16
test: pg17
test: pg17 pg17_json
test: drop_column_partitioned_table
test: tableam

379
src/test/regress/sql/pg17_json.sql Normal file
View File

@ -0,0 +1,379 @@
--
-- PG17_JSON
-- PG17 has added basic JSON_TABLE() functionality
-- JSON_TABLE() allows JSON data to be converted into a relational view
-- and thus used, for example, in a FROM clause, like other tabular
-- data. We treat JSON_TABLE the same as correlated functions (e.g., recurring tuples).
-- In the end, for multi-shard JSON_TABLE commands, we apply the same
-- restrictions as reference tables (e.g., cannot perform a lateral outer join
-- when a distributed subquery references a (reference table)/JSON_TABLE etc.)
-- Relevant PG commit:
-- https://github.com/postgres/postgres/commit/de3600452
--
SHOW server_version \gset
SELECT substring(:'server_version', '\d+')::int >= 17 AS server_version_ge_17
\gset
\if :server_version_ge_17
\else
\q
\endif
CREATE SCHEMA pg17_json;
SET search_path TO pg17_json;
SET citus.next_shard_id TO 1687000;
CREATE TABLE test_table(id bigserial, value text);
SELECT create_distributed_table('test_table', 'id');
INSERT INTO test_table (value) SELECT i::text FROM generate_series(0,100)i;
CREATE TABLE my_films(id bigserial, js jsonb);
SELECT create_distributed_table('my_films', 'id');
INSERT INTO my_films(js) VALUES (
'{ "favorites" : [
{ "kind" : "comedy", "films" : [ { "title" : "Bananas", "director" : "Woody Allen"},
{ "title" : "The Dinner Game", "director" : "Francis Veber" } ] },
{ "kind" : "horror", "films" : [{ "title" : "Psycho", "director" : "Alfred Hitchcock" } ] },
{ "kind" : "thriller", "films" : [{ "title" : "Vertigo", "director" : "Alfred Hitchcock" } ] },
{ "kind" : "drama", "films" : [{ "title" : "Yojimbo", "director" : "Akira Kurosawa" } ] }
] }');
INSERT INTO my_films(js) VALUES (
'{ "favorites" : [
{ "kind" : "comedy", "films" : [ { "title" : "Bananas2", "director" : "Woody Allen"},
{ "title" : "The Dinner Game2", "director" : "Francis Veber" } ] },
{ "kind" : "horror", "films" : [{ "title" : "Psycho2", "director" : "Alfred Hitchcock" } ] },
{ "kind" : "thriller", "films" : [{ "title" : "Vertigo2", "director" : "Alfred Hitchcock" } ] },
{ "kind" : "drama", "films" : [{ "title" : "Yojimbo2", "director" : "Akira Kurosawa" } ] }
] }');
-- a router query
SELECT jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt
WHERE my_films.id = 1
ORDER BY 1,2,3,4;
-- router query with an explicit LATEREL SUBQUERY
SELECT sub.*
FROM my_films,
lateral(SELECT * FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt) as sub
WHERE my_films.id = 1;
-- router query with an explicit LATEREL SUBQUERY and LIMIT
SELECT sub.*
FROM my_films,
lateral(SELECT * FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt ORDER BY id DESC LIMIT 1) as sub
WHERE my_films.id = 1;
-- set it DEBUG1 in case the plan changes
-- we can see details
SET client_min_messages TO DEBUG1;
-- a mult-shard query
SELECT jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt
ORDER BY 1,2,3,4;
-- recursively plan subqueries that has JSON_TABLE
SELECT count(*) FROM
(
SELECT jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt
LIMIT 1) as sub_with_json, test_table
WHERE test_table.id = sub_with_json.id;
-- multi-shard query with an explicit LATEREL SUBQUERY
SELECT sub.*
FROM my_films JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true)
ORDER BY 1,2,3,4;
-- JSON_TABLE can be on the inner part of an outer joion
SELECT sub.*
FROM my_films LEFT JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true)
ORDER BY 1,2,3,4;
-- we can pushdown this correlated subquery in WHERE clause
SELECT count(*)
FROM my_films WHERE
(SELECT count(*) > 0
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000);
-- we can pushdown this correlated subquery in SELECT clause
SELECT (SELECT count(*) > 0
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt)
FROM my_films;
-- multi-shard query with an explicit LATEREL SUBQUERY
-- along with other tables
SELECT sub.*
FROM my_films JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true) JOIN test_table ON(my_films.id = test_table.id)
ORDER BY 1,2,3,4;
-- non-colocated join fails
SELECT sub.*
FROM my_films JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true) JOIN test_table ON(my_films.id != test_table.id)
ORDER BY 1,2,3,4;
-- JSON_TABLE can be in the outer part of the join
-- as long as there is a distributed table
SELECT sub.*
FROM my_films JOIN
lateral
(SELECT *
FROM JSON_TABLE (js, '$.favorites[*]' COLUMNS (id FOR ORDINALITY,
kind text PATH '$.kind', NESTED PATH '$.films[*]'
COLUMNS (title text PATH '$.title', director text PATH '$.director'))) AS jt
LIMIT 1000) AS sub ON (true) LEFT JOIN test_table ON(my_films.id = test_table.id)
ORDER BY 1,2,3,4;
-- JSON_TABLE can be on the outer side of the join
-- We support outer joins where the outer rel is a recurring one
-- and the inner one is a non-recurring one if we don't reference the outer from the inner
-- https://github.com/citusdata/citus/pull/6512
SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (id FOR ORDINALITY, column_a int4 PATH '$.a', column_b int4 PATH '$.b', a int4, b int4, c text))
LEFT JOIN LATERAL
(SELECT *
FROM my_films) AS foo on(foo.id = a);
-- However we don't support
-- when we reference the JSON_TABLE from the non-recurring distributed table subquery
SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (json_id FOR ORDINALITY, column_a int4 PATH '$.a', column_b int4 PATH '$.b', a int4, b int4, c text))
LEFT JOIN LATERAL
(SELECT *
FROM my_films WHERE id::text LIKE c) AS foo on(foo.id = a);
-- JSON_TABLE cannot be on the FROM clause alone
SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (json_id FOR ORDINALITY, column_a int4 PATH '$.a', column_b int4 PATH '$.b', a int4, b int4, c text)) as foo
WHERE b >
(SELECT count(*)
FROM my_films WHERE id = foo.a);
-- we can recursively plan json_tables on set operations
(SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (id FOR ORDINALITY)) ORDER BY id ASC LIMIT 1)
UNION
(SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (id FOR ORDINALITY)) ORDER BY id ASC LIMIT 1)
UNION
(SELECT id FROM test_table ORDER BY id ASC LIMIT 1);
-- LIMIT in subquery not supported when json_table exists
SELECT *
FROM json_table('[{"a":10,"b":20},{"a":30,"b":40}]'::JSONB, '$[*]'
COLUMNS (id FOR ORDINALITY, column_a int4 PATH '$.a', column_b int4 PATH '$.b', a int4, b int4, c text))
JOIN LATERAL
(SELECT *
FROM my_films WHERE json_table.id = a LIMIT 1) as foo ON (true);
RESET client_min_messages;
-- we can use JSON_TABLE in modification queries as well
-- use log level such that we can see trace changes
SET client_min_messages TO DEBUG1;
--the JSON_TABLE subquery is recursively planned
UPDATE test_table SET VALUE = 'XXX' FROM(
SELECT jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
id FOR ORDINALITY,
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt) as foo WHERE foo.id = test_table.id;
-- Subquery with JSON table can be pushed down because two distributed tables
-- in the query are joined on distribution column
UPDATE test_table SET VALUE = 'XXX' FROM (
SELECT my_films.id, jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt) as foo WHERE foo.id = test_table.id;
-- we can pushdown with CTEs as well
WITH json_cte AS
(SELECT my_films.id, jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
title text PATH '$.title',
director text PATH '$.director'))) AS jt)
UPDATE test_table SET VALUE = 'XYZ' FROM json_cte
WHERE json_cte.id = test_table.id;
-- we can recursively with CTEs as well
WITH json_cte AS
(SELECT my_films.id as film_id, jt.* FROM
my_films,
JSON_TABLE ( js, '$.favorites[*]' COLUMNS (
kind text PATH '$.kind',
NESTED PATH '$.films[*]' COLUMNS (
id FOR ORDINALITY,
title text PATH '$.title',
director text PATH '$.director'))) AS jt ORDER BY jt.id LIMIT 1)
UPDATE test_table SET VALUE = 'XYZ' FROM json_cte
WHERE json_cte.film_id = test_table.id;
-- JSON_TABLE NESTED
-- JSON_TABLE: plan execution
-- Check output with Postgres table in sqljson_jsontable test
-- https://github.com/postgres/postgres/blob/REL_17_0/src/test/regress/expected/sqljson_jsontable.out#L776-L814
CREATE TABLE jsonb_table_test (id bigserial, js jsonb);
SELECT create_distributed_table('jsonb_table_test', 'id');
INSERT INTO jsonb_table_test
VALUES (1,
'[
{"a": 1, "b": [], "c": []},
{"a": 2, "b": [1, 2, 3], "c": [10, null, 20]},
{"a": 3, "b": [1, 2], "c": []},
{"x": "4", "b": [1, 2], "c": 123}
]'
);
select
jt.*
from
jsonb_table_test jtt,
json_table (
jtt.js,'strict $[*]' as p
columns (
n for ordinality,
a int path 'lax $.a' default -1 on empty,
nested path 'strict $.b[*]' as pb columns (b_id for ordinality, b int path '$' ),
nested path 'strict $.c[*]' as pc columns (c_id for ordinality, c int path '$' )
)
) jt;
-- test some utility functions on the target list & where clause: json_exists()
select jsonb_path_exists(js, '$.favorites') from my_films;
select bool_and(JSON_EXISTS(js, '$.favorites.films.title')) from my_films;
SELECT count(*) FROM my_films WHERE jsonb_path_exists(js, '$.favorites');
SELECT count(*) FROM my_films WHERE JSON_EXISTS(js, '$.favorites.films.title');
-- check constraint with json_exists, use json_scalar also
SET citus.shard_replication_factor TO 1;
create table user_profiles (
id bigserial,
addresses jsonb,
anyjson jsonb,
serialized bytea,
check (json_exists( addresses, '$.main' )) -- we should insert a key named main
);
select create_distributed_table('user_profiles', 'id');
insert into user_profiles (addresses) VALUES (JSON_SCALAR('1'));
insert into user_profiles (addresses, anyjson) VALUES ('{"main":"value"}', JSON_SCALAR('1')) RETURNING *;
-- use json() - we cannot insert because WITH UNIQUE KEYS
insert into user_profiles (addresses) VALUES (JSON ('{"main":"value", "main":"value"}' WITH UNIQUE KEYS));
-- we can insert with
insert into user_profiles (addresses) VALUES (JSON ('{"main":"value", "main":"value"}' WITHOUT UNIQUE KEYS)) RETURNING *;
-- JSON predicates
TRUNCATE user_profiles;
INSERT INTO user_profiles (anyjson) VALUES ('12'), ('"abc"'), ('[1,2,3]'), ('{"a":12}');
select anyjson, anyjson is json array as json_array, anyjson is json object as json_object, anyjson is json scalar as json_scalar,
anyjson is json with UNIQUE keys
from user_profiles WHERE anyjson IS NOT NULL ORDER BY 1;
-- use json_serialize
-- it is evaluated in the worker
SELECT JSON_SERIALIZE('{ "a" : 1 } ' RETURNING bytea);
SET citus.log_remote_commands TO on;
INSERT INTO user_profiles (serialized) VALUES (JSON_SERIALIZE('{ "a" : 1 } ' RETURNING bytea)) RETURNING *;
RESET citus.log_remote_commands;
-- use json_query
SELECT i,
json_query('[{"x": "aaa"},{"x": "bbb"},{"x": "ccc"}]'::JSONB, '$[$i].x' passing id AS i RETURNING text omit quotes)
FROM generate_series(0, 3) i
JOIN my_films ON(id = i) ORDER BY 1;
-- use json_value
-- check output with sqljson_queryfuncs test
-- https://github.com/postgres/postgres/blob/REL_17_0/src/test/regress/expected/sqljson_queryfuncs.out#L439-L455
SELECT i,
JSON_VALUE(
jsonb '{"a": 1, "b": 2}',
'$.* ? (@ > $i)' PASSING id AS i
RETURNING int
DEFAULT -1 ON EMPTY
DEFAULT -2 ON ERROR
)
FROM generate_series(0, 3) i
JOIN my_films ON(id = i) ORDER BY 1;
SET client_min_messages TO ERROR;
DROP SCHEMA pg17_json CASCADE;