Summary: json_extract_path_text(from_json json, VARIADIC path_elems text[]) navigates a JSON value by a variadic path of text keys and array indexes, returning the result cast to TEXT rather than JSON. Use this function instead of json_extract_path when the extracted value will be compared, concatenated, or joined as a string, since the text cast avoids an extra explicit conversion. For binary jsonb columns, prefer jsonb_extract_path_text, which offers the same interface with better index support.

Extracts a JSON sub-object at the specified path as text

The json_extract_path_text function is designed to simplify extracting text from JSON data in Postgres. This function is similar to json_extract_path; it also produces the value at the specified path from a JSON object but casts it to plain text before returning. This makes it more straightforward for text manipulation and comparison operations.

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json_extract_path_text(from_json json, VARIADIC path_elems text[]) -> TEXT

The function accepts a JSON object and a variadic list of elements that specify the path to the desired value.

Let's consider a users table with a JSON column named profile containing various user details.

Here's how we can create the table and insert some sample data:

CREATE TABLE users (
    id INT,
    profile JSON
);

INSERT INTO users (id, profile)
VALUES
    (1, '{"name": "Alice", "contact": {"email": "alice@example.com", "phone": "1234567890"}, "hobbies": ["reading", "cycling", "hiking"]}'),
    (2, '{"name": "Bob", "contact": {"email": "bob@example.com", "phone": "0987654321"}, "hobbies": ["gaming", "cooking"]}');

To extract and view the email addresses of all users, we can run the following query:

SELECT id, json_extract_path_text(profile, 'contact', 'email') as email
FROM users;

This query returns the following:

| id | email              |
|----|--------------------|
| 1  | alice@example.com  |
| 2  | bob@example.com    |

Let's say we have another table, hobbies, that includes additional information such as difficulty level and the average cost to practice each hobby.

We can create the hobbies table with some sample data with the following statements:

CREATE TABLE hobbies (
   hobby_id SERIAL PRIMARY KEY,
   hobby_name VARCHAR(255),
   difficulty_level VARCHAR(50),
   average_cost VARCHAR(50)
);

INSERT INTO hobbies (hobby_name, difficulty_level, average_cost)
VALUES
    ('Reading', 'Easy', 'Low'),
    ('Cycling', 'Moderate', 'Medium'),
    ('Gaming', 'Variable', 'High'),
    ('Cooking', 'Variable', 'Low');

The users table we created previously has a JSON column named profile that contains information about each user's preferred hobbies. A fun exercise could be to find if a user has any hobbies that are easy to get started with. Then we can recommend they engage with it more often.

To fetch this list, we can run the query below.

SELECT
  json_extract_path_text(u.profile, 'name') as user_name,
  h.hobby_name
FROM users u
JOIN hobbies h
ON json_extract_path_text(u.profile, 'hobbies') LIKE '%' || lower(h.hobby_name) || '%'
WHERE h.difficulty_level = 'Easy';

We use json_extract_path_text to extract the list of hobbies for each user, and then check if the name of an easy hobby is present in the list.

This query returns the following:

| user_name | hobby_name |
|-----------|------------|
| Alice     | Reading    |

json_extract_path_text can also be used to extract values from JSON arrays.

For instance, to extract the first and second hobbies for everyone, we can run the following query:

SELECT
    json_extract_path_text(profile, 'name') as name,
    json_extract_path_text(profile, 'hobbies', '0') as first_hobby,
    json_extract_path_text(profile, 'hobbies', '1') as second_hobby
FROM users;

This query returns the following:

| name  | first_hobby | second_hobby |
|-------|-------------|--------------|
| Alice | reading     | cycling      |
| Bob   | gaming      | cooking      |

Performance considerations for json_extract_path_text are similar to those for json_extract_path. It is efficient for extracting data but can be impacted by large JSON objects or complex queries. Indexing JSON fields can improve performance in some cases.

• json_extract_path - This is a similar function that can extract data from a JSON object at the specified path. The difference is that it returns a JSON object, while json_extract_path_text always returns text. The right function to use depends on what you want to use the output data for.
• jsonb_extract_path_text - This is a similar function that can extract data from a JSON object at the specified path. It is more efficient but works only with data of the type JSONB.

• PostgreSQL Documentation: JSON Functions and Operators
• PostgreSQL Documentation: JSON Types

• array_to_json
• json
• json_agg
• json_array_elements
• json_build_object
• json_each
• json_exists
• json_extract_path
• json_object
• json_populate_record
• json_query
• json_scalar
• json_serialize
• json_table
• json_to_record
• json_value
• jsonb_array_elements
• jsonb_each
• jsonb_extract_path
• jsonb_extract_path_text
• jsonb_object
• jsonb_populate_record
• jsonb_to_record

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