Mastering JOLT Transformations: Separating JSON Lists into Objects with Conditional Values

Learn how to effectively apply JOLT transformations to JSON data, turning lists into individual objects and incorporating conditional boolean values for enhanced data analysis.
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Mastering JOLT Transformations: Separating JSON Lists into Objects with Conditional Values

In the world of data manipulation, transforming JSON structures to meet specific requirements is a common challenge. One such scenario involves taking a list of items in a JSON object and splitting them into individual objects, all while applying conditional logic to certain fields. This guide will walk you through a practical example of how to use JOLT transformations to achieve this.

Problem Overview

Imagine you are working with a JSON document that contains information about allergens, the doctors who diagnosed them, and the tests conducted. The challenge is to separate the allergens into individual JSON objects while also conditionally indicating whether they were diagnosed by specific types of healthcare providers and whether specific tests were performed.

Example Input JSON

Here is a quick look at the JSON input we will be working with:

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

Desired Output JSON

Our goal is to produce the following JSON output for each allergen:

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

Solution Using JOLT

To achieve the desired output, we will utilize JOLT's transformation capabilities. We will create a two-step transformation that shifts the data accordingly:

Step 1: Shifting and Conditional Conversion

This first transformation will break down the allergen list into individual objects, while applying conditional logic to fields derived from the doc_type and tests lists. Here is the JOLT transformation specification for this step:

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

Step 2: Removing Object Key Names

The second transformation specification is necessary to clean up the resulting structure by removing unwanted object key names. It looks like this:

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

Conclusion

By following the above two-step JOLT transformations, we can effectively separate a list of allergens into individual JSON objects while also applying conditional evaluations for specific fields. This approach enhances the usability of the resulting JSON by providing clear and actionable data. JOLT transformations can be a powerful tool in the hands of data engineers and developers alike, simplifying complex data structures with relative ease.

If you have any questions or need further assistance with JOLT specifications, feel free to get in touch or leave a comment below! Happy transforming!