How to Query a JSON Object in Snowflake

Snowflake, a powerful cloud-based data platform, allows for querying and managing JSON data with ease. When working with semi-structured data like JSON, Snowflake provides a variety of tools to extract, transform, and analyze the information stored in these objects. In this tutorial, we will walk you through how to query JSON data in Snowflake using SQL functions designed for working with JSON objects.

Understanding JSON in Snowflake

JSON data in Snowflake can be stored in a column with a VARIANT data type, which allows for handling different kinds of semi-structured data such as JSON, XML, and Avro. Snowflake’s support for JSON means that you can load JSON data into tables and query it with standard SQL syntax.

Querying JSON Data

Once your JSON data is loaded into Snowflake, you can use a variety of SQL functions to extract and query the JSON elements. Below are the most commonly used functions for querying JSON objects in Snowflake:

• PARSE_JSON: This function is used to parse a JSON string into a VARIANT type that can be queried. For example:

SELECT PARSE_JSON('{"name":"John", "age":30}') AS parsed_json;

• GET: The GET function allows you to access a specific key in a JSON object. For example, to get the "name" key from the parsed JSON:

SELECT parsed_json:Get('name') AS name FROM your_table;

• GET_PATH: This function is used to retrieve values from nested JSON structures. If the JSON object has nested objects, you can use GET_PATH to navigate through them:

SELECT parsed_json:Get_Path('address', 'city') AS city FROM your_table;

• FLATTEN: When working with arrays in JSON, the FLATTEN function helps in unpacking the array into separate rows. Here's an example:

SELECT f.value AS item FROM your_table, LATERAL FLATTEN(input => parsed_json:Get('items')) f;

Example: Querying Nested JSON

Imagine you have a table with JSON data containing information about employees and their departments. Here's how you can extract data from a nested JSON object:

SELECT 
    employee_data:Get('name') AS employee_name,
    employee_data:Get('department'):Get('name') AS department_name
FROM employees;

This query extracts the employee’s name and their department’s name from the JSON object stored in the employee_data column.

Conclusion

Snowflake makes it easy to work with JSON objects by providing powerful SQL functions that allow you to extract, manipulate, and query semi-structured data. By using functions such as PARSE_JSON, GET, and FLATTEN, you can unlock the value of your JSON data and incorporate it into your analytics pipeline. With Snowflake’s flexibility, you can easily manage complex datasets and perform advanced queries.