How to Split JSON Array into Individual Objects in MuleSoft with DataWeave

Learn how to efficiently split a JSON array into multiple objects using DataWeave in MuleSoft. Follow our step-by-step guide for an easy solution!
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Splitting a JSON Array into Individual Objects in MuleSoft

If you're working with JSON data in MuleSoft, you might come across situations where you need to split a JSON array into individual objects. This is a common requirement, especially when processing data in applications where streamlined data structures are necessary. In this guide, we will walk you through the problem of extracting individual items from a nested JSON structure and how to solve it efficiently with DataWeave.

The Problem

Let's imagine you have a JSON payload that looks like this:

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

Your goal is to transform this payload into an array of objects that look like this:

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

However, the challenge arises when dealing with the cases where the specialtyIds array contains multiple elements. A common pitfall is using a method that improperly joins elements, leading to incorrect outputs, as was the experience for many when using expressions like:

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

This would yield results that are not well-structured, especially for arrays containing more than one element.

The Solution

Using DataWeave in MuleSoft

To properly extract the specialtyIds from each object in the data array, we can use the flatten function along with mapping to create a more streamlined transformation. Here’s how the DataWeave script would look:

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

Explanation of the Code

%dw 2.0: This specifies the version of DataWeave being used.

output application/json: This indicates that the output of the transformation is in JSON format.

map { id: $ }: This iterates over the flattened array and returns an object with the property id for each element.

How It Works

Flattening Data: The flatten function takes care of merging all the specialtyIds into a single list, ensuring we get each ID separately without duplicates.

Mapping Objects: By mapping each ID to an object with its corresponding property (id), we align the output with the desired structure.

Conclusion

This approach provides a clean and efficient way to convert your nested JSON arrays into individual object arrays. By leveraging the capabilities of DataWeave, you can streamline your data transformation processes and avoid the complexities that arise when handling nested structures with multiple elements.

If you're new to DataWeave or simply looking to refine your skills, this guide should offer you a robust starting point for working with JSON data in MuleSoft. With practice, these transformations will become second nature, enabling you to build more sophisticated integrations effortlessly.