How to Parse JSON to Retrieve Item Names in Snowflake SQL

Learn how to effectively parse JSON data and retrieve item names and quantities using Snowflake SQL queries. Explore practical examples to enhance your SQL skills!
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How to Parse JSON to Retrieve Item Names in Snowflake SQL

When working with JSON data in Snowflake, one common challenge is extracting specific information, such as names and quantities of items. In this guide, we’ll explore how to efficiently parse JSON and retrieve the required data using Snowflake SQL.

Understanding the Problem

Let’s say we have the following JSON structure representing a list of items, each containing attributes like itemId, name, quantity, storeId, and type:

[[See Video to Reveal this Text or Code Snippet]]

You want to write a SQL query that retrieves all item names and quantities, organizing them in two separate columns.

The Solution

To extract the names and quantities from this JSON, we’ll use a combination of Snowflake SQL functions: PARSE_JSON, FLATTEN, and subselects. Here’s how to do it step-by-step.

Step 1: Utilize the PARSE_JSON Function

First, we need to parse the JSON string into a format that Snowflake can work with. This is done using the PARSE_JSON function.

Step 2: Employ the FLATTEN Function

The FLATTEN function allows us to transform the JSON array into a more accessible format, where we can easily select individual attributes.

Step 3: Write the SQL Query

Here’s the SQL query that combines these steps:

[[See Video to Reveal this Text or Code Snippet]]

Output

Upon executing this query, you will get a result set similar to the following:

NAMEQUANTITYA1b1C2D2Alternative Approach Using CTE

If you’d prefer to structure your SQL query for better readability, you can use a Common Table Expression (CTE) as shown below:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Parsing JSON in Snowflake SQL can be straightforward with the right functions. By utilizing PARSE_JSON and FLATTEN, you can extract specific attributes from a JSON array efficiently. With this guide, you should be able to apply these concepts in your projects and queries.

Happy querying!