How to Transform Array Object to a Nested Array Object in DataWeave

Learn how to effectively `transform array objects` into a nested structure in DataWeave, complete with example and step-by-step instructions.
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Transforming Array Objects to Nested Array Objects in DataWeave

In the world of data processing, especially when working with MuleSoft’s DataWeave, you may encounter scenarios where you need to transform flat array objects into nested array structures. A common challenge for developers is to reorganize data from flat formats, such as those sourced from CSV files, into a more hierarchical representation that reflects relationships between various elements of the data.

The Problem: Data Structure Transformation

Imagine you have a dataset in JSON format that represents sales records. Each record includes details like sold, org, soNo, sku, and qty. However, your goal is to transform this flat list into a nested array where sold and soNo serve as unique keys with associated details grouped accordingly.

Example Dataset

Here’s an example of what the input data might look like:

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

What you truly desire is an output structure like this:

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

The Solution: Using DataWeave for Transformation

To achieve this transformation, the key is to utilize the groupBy method in DataWeave, which allows us to group data based on specific keys and then map the relevant information into the desired structure.

Step-by-Step Implementation

Here’s how you can accomplish this transformation using DataWeave 2.x syntax:

Use groupBy: This function will group the records based on the combination of sold, soNo, and org keys.

Map the Output: Once grouped, you can use the pluck operator to create a new object for each group, while excluding the sku and qty fields from the main object.

DataWeave Code Example

The following code snippet demonstrates how to implement this transformation:

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

Explanation of the Code

payload groupBy: This command groups the input payload based on the unique keys.

pluck: This method extracts the necessary fields to create a new object format.

($[0] - "sku" - "qty"): Here, we're taking the first occurrence of the group and removing sku and qty, which will be handled separately.

items: ($ map ($ - "sold" - "soNo" - "org")): This part maps over the grouped items, extracting the sku and qty into a nested items array.

Conclusion

With the above approach, transforming your flat array objects into a nested array structure becomes straightforward and efficient. Utilizing DataWeave’s powerful features allows you to manipulate and reshape data, making it fit your needs perfectly.

This method effectively organizes your data into a more interpretable format, ensuring that your sales records can be utilized efficiently in downstream processes.

Make sure to understand each component of the code provided and adapt it as needed for different datasets. Happy coding in DataWeave!