Error
Error Code:
3665
MySQL Error 3665: Missing JSON_TABLE Column Value
Description
This error indicates that the `JSON_TABLE` function expected a value for a specific column derived from the JSON data, but no corresponding value was found at the specified path. It commonly occurs when the JSON path expression does not correctly point to an existing element, or the element's value is missing or null when a non-null value is required.
Error Message
Missing value for JSON_TABLE column '%s'
Known Causes
3 known causesIncorrect JSON Path
The JSON path expression used in the `JSON_TABLE` column definition does not correctly identify an existing element within the JSON document.
Missing JSON Key or Element
The source JSON document itself does not contain the expected key or element that the `JSON_TABLE` column definition is attempting to extract.
NULL Value Encountered
A `NULL` value or non-existent element is found for a `JSON_TABLE` column that implicitly or explicitly requires a `NOT NULL` value.
Solutions
3 solutions available1. Verify JSON Data Structure for Missing Values easy
Ensure your JSON data conforms to the expected structure for JSON_TABLE and contains values for all specified columns.
1
Examine the JSON document you are querying with `JSON_TABLE`. Identify the path specified for the column that is causing the error (indicated by `%s` in the error message).
2
For each row or object within the JSON that `JSON_TABLE` is attempting to process, confirm that the value exists at the specified path. If the path points to a nested object or array, ensure that the entire chain of keys/indices is present and has a non-null value.
3
If a value is genuinely missing, you have two options: either add the missing value to your JSON data or adjust your `JSON_TABLE` query to handle missing values gracefully.
4
Example: If your `JSON_TABLE` expects a 'name' field and your JSON has `{"age": 30}`, the 'name' field is missing. You would need to change the JSON to `{"name": "John Doe", "age": 30}` or modify the query.
2. Use `DEFAULT` Clause in JSON_TABLE for Optional Fields medium
Modify your `JSON_TABLE` definition to provide a default value for columns that might be missing in the JSON data.
1
Locate the `JSON_TABLE` function call in your SQL query.
2
For the column definition that is causing the error (identified by `%s`), add the `DEFAULT` clause with a suitable value. This value will be used if the corresponding path in the JSON document does not yield a value.
CREATE TABLE my_table (id INT, json_data JSON);
INSERT INTO my_table VALUES (1, '{"items": [{"name": "apple"}, {"price": 1.5}]}');
SELECT jt.*
FROM my_table, JSON_TABLE(my_table.json_data, '$.items[*]' COLUMNS (
name VARCHAR(50) PATH '$.name',
price DECIMAL(5,2) DEFAULT 0.0 PATH '$.price'
)) AS jt;
-- In the above example, if 'price' was missing for an item, it would default to 0.0.3
Consider the data type of the column when defining the `DEFAULT` value. For example, use `''` for strings, `0` for numbers, or `NULL` if appropriate and allowed by your schema.
3. Adjust JSON Path Expressions for Robustness medium
Refine your JSON path expressions to be more forgiving of variations or missing elements in the JSON structure.
1
Analyze the JSON path used for the problematic column in your `JSON_TABLE` definition. If the path is very specific and relies on every intermediate element existing, it can lead to this error.
2
Consider using more general path expressions or ensuring that your paths correctly handle arrays and objects that might be empty or missing.
3
For example, instead of `$.user.address.street`, if the `address` object might be missing, you might need to adjust your overall query structure or use conditional logic if possible within your SQL dialect (though `JSON_TABLE` itself expects a direct path). A common approach is to ensure the data source produces consistent JSON.
4
If you are querying an array and a specific element within that array might be missing, ensure your path correctly targets existing elements. For instance, if `$.data[*].value` is used and some objects in `data` lack a `value` key, this error can occur. You might need to check the existence of the parent object first or use a more robust method to extract data.