Amazon Redshift will no longer support the creation of new Python UDFs starting November 1, 2025.
If you would like to use Python UDFs, create the UDFs prior to that date.
Existing Python UDFs will continue to function as normal. For more information, see the
blog post
IS_VALID_JSON function
Note
CAN_JSON_PARSE and its associated functions parse JSON values as SUPER, which Amazon Redshift parses more efficiently than VARCHAR.
Instead of using IS_VALID_JSON, we recommend that you validate your JSON strings using the CAN_JSON_PARSE function.
The IS_VALID_JSON function validates a JSON string. The function returns Boolean
true if the string is properly formed JSON or
false if the string is malformed. To validate a JSON
array, use IS_VALID_JSON_ARRAY function
For more information, see JSON functions.
Syntax
IS_VALID_JSON('json_string')
Arguments
- json_string
-
A string or expression that evaluates to a JSON string.
Return type
BOOLEAN
Examples
To create a table and insert JSON strings for testing, use the following example.
CREATE TABLE test_json(id int IDENTITY(0,1), json_strings VARCHAR); -- Insert valid JSON strings -- INSERT INTO test_json(json_strings) VALUES ('{"a":2}'), ('{"a":{"b":{"c":1}}}'), ('{"a": [1,2,"b"]}'); -- Insert invalid JSON strings -- INSERT INTO test_json(json_strings) VALUES ('{{}}'), ('{1:"a"}'), ('[1,2,3]');
To validate the strings in the preceding example, use the following example.
SELECT id, json_strings, IS_VALID_JSON(json_strings) FROM test_json ORDER BY id;+----+---------------------+---------------+ | id | json_strings | is_valid_json | +----+---------------------+---------------+ | 0 | {"a":2} | true | | 4 | {"a":{"b":{"c":1}}} | true | | 8 | {"a": [1,2,"b"]} | true | | 12 | {{}} | false | | 16 | {1:"a"} | false | | 20 | [1,2,3] | false | +----+---------------------+---------------+
