Postgres JSON_EXISTS() Function
newCheck for Values in JSON Data Using SQL/JSON Path Expressions
The JSON_EXISTS()
function in PostgreSQL 17 provides a powerful way to check for the existence of values within JSON
data using SQL/JSON
path expressions. This function is particularly useful for validating JSON
structure and implementing conditional logic based on the presence of specific JSON
elements.
Use JSON_EXISTS()
when you need to:
- Validate the presence of specific
JSON
paths - Implement conditional logic based on
JSON
content - Filter
JSON
data based on complex conditions - Verify
JSON
structure before processing
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Function signature
The JSON_EXISTS()
function uses the following syntax:
JSON_EXISTS(
context_item, -- JSON/JSONB input
path_expression -- SQL/JSON path expression
[ PASSING { value AS varname } [, ...] ]
[{ TRUE | FALSE | UNKNOWN | ERROR } ON ERROR ]
) → boolean
Parameters:
context_item
:JSON
orJSONB
input to evaluatepath_expression
:SQL/JSON
path expression to checkPASSING
: Optional clause to pass variables for use in the path expressionON ERROR
: Controls behavior when path evaluation fails (defaults toFALSE
)
Example usage
Let's explore various ways to use the JSON_EXISTS()
function with different scenarios and options.
Basic existence checks
-- Check if a simple key exists
SELECT JSON_EXISTS('{"name": "Alice", "age": 30}', '$.name');
# | json_exists
--------------
1 | t
-- Check for a nested key
SELECT JSON_EXISTS(
'{"user": {"details": {"email": "alice@example.com"}}}',
'$.user.details.email'
);
# | json_exists
--------------
1 | t
Array operations
-- Check if array contains any elements
SELECT JSON_EXISTS('{"numbers": [1,2,3,4,5]}', '$.numbers[*]');
# | json_exists
--------------
1 | t
-- Check for specific array element
SELECT JSON_EXISTS('{"tags": ["postgres", "json", "database"]}', '$.tags[3]');
# | json_exists
--------------
1 | f
Conditional checks
-- Check for values meeting a condition
SELECT JSON_EXISTS(
'{"scores": [85, 92, 78, 95]}',
'$.scores[*] ? (@ > 90)'
);
# | json_exists
--------------
1 | t
Using PASSING clause
-- Check using a variable
SELECT JSON_EXISTS(
'{"temperature": 25}',
'strict $.temperature ? (@ > $threshold)'
PASSING 30 AS threshold
);
# | json_exists
--------------
1 | f
Error handling
-- Default behavior (returns FALSE)
SELECT JSON_EXISTS(
'{"data": [1,2,3]}',
'strict $.data[5]'
);
# | json_exists
--------------
1 | f
-- Using ERROR ON ERROR
SELECT JSON_EXISTS(
'{"data": [1,2,3]}',
'strict $.data[5]'
ERROR ON ERROR
);
ERROR: jsonpath array subscript is out of bounds (SQLSTATE 22033)
-- Using UNKNOWN ON ERROR
SELECT JSON_EXISTS(
'{"data": [1,2,3]}',
'strict $.data[5]'
UNKNOWN ON ERROR
);
# | json_exists
--------------
1 |
Practical applications
Data validation
-- Validate required fields before insertion
CREATE TABLE user_profiles (
id SERIAL PRIMARY KEY,
data JSONB NOT NULL,
CONSTRAINT valid_profile CHECK (
JSON_EXISTS(data, '$.email') AND
JSON_EXISTS(data, '$.username')
)
);
-- This insert will succeed
INSERT INTO user_profiles (data) VALUES (
'{"email": "user@example.com", "username": "user123"}'::jsonb
);
-- This insert will fail
INSERT INTO user_profiles (data) VALUES (
'{"username": "user123"}'::jsonb
);
ERROR: new row for relation "user_profiles" violates check constraint "valid_profile" (SQLSTATE 23514)
Conditional queries
-- Filter records based on JSON content
SELECT *
FROM user_profiles
WHERE JSON_EXISTS(
data,
'$.preferences.notifications ? (@ == true)'
);
Best practices
-
Error handling:
- Use appropriate
ON ERROR
clauses based on your requirements - Consider
UNKNOWN ON ERROR
for nullable conditions - Use
ERROR ON ERROR
when validation is critical
- Use appropriate
-
Performance optimization:
- Create GIN indexes on
JSONB
columns for better performance - Use strict mode when path is guaranteed to exist
- Combine with other
JSON
functions for complex operations
- Create GIN indexes on
-
Path expressions:
- Use lax mode (default) for optional paths
- Leverage path variables with
PASSING
clause for dynamic checks