Aggregators in MuleSoft Integration

The Aggregator module offered by MuleSoft is a helpful tool used within integration flows to bring together different messages. Imagine you have various bits of information coming from different sources or undergoing different processing steps, and you want to combine them into one cohesive message for further handling. That's where the Aggregator module steps in.

Now, let's explore its benefits:

1. Data Consolidation: One of the primary advantages is its ability to consolidate data from multiple messages into a single one. This proves particularly useful when you're dealing with parallel processing or when your integration flow branches out into multiple pathways, and you need to gather all the results into one stream for easier management.

2. Efficient Parallel Processing: Another benefit is the capability to design integration flows where different parts of message processing can occur simultaneously. Once these parallel processing tasks are complete, the Aggregator module steps in to bring together all the results. This not only helps streamline the overall process but also enhances efficiency.

3. Dynamic Aggregation Strategies: MuleSoft provides the flexibility to define dynamic aggregation strategies based on specific conditions. This means you can tailor the aggregation logic according to the unique requirements of your integration flow. It's like having the ability to customize how different pieces of information are assembled based on what makes sense for your particular scenario.

Now, let's delve into how the Aggregator module functions:

• Storage and Release Mechanism: At its core, the Aggregator module serves as a mechanism for storing and releasing values. It collects these values until a specified condition is met. Once that condition is satisfied, it triggers the execution of a processor's chain of components, utilizing the aggregated elements as the payload.

• Different Types of Aggregators: Within the Aggregators Module, you'll find various types of aggregators, each with predefined configurations to suit different needs. These include:

  • Size Based Aggregator: Aggregates messages based on their size.
  • Time Based Aggregator: Aggregates messages based on time intervals.
  • Group Based Aggregator: Aggregates messages based on predefined groups.

• Configuration: Setting up an aggregator involves specifying what values to aggregate (usually obtained through expression evaluation from the message), defining the conditions for completion of aggregation, and determining the processor chain that activates upon meeting those conditions.

It's important to note that while the Aggregator module facilitates the aggregation process, it primarily serves as a pass-through router. This means that the data received by an aggregator scope undergoes processing by subsequent components in the flow. Any changes made to the data are minimal, with the primary focus being on routing and organizing the information efficiently.

To better understand how these aggregators work in practice, let's explore them through a sample MuleSoft application. Size Based Aggregator

The Size-Based Aggregator Scope is a tool that gathers elements together until they reach a certain size, signaling that the aggregation is complete.

To use this scope, you first need to download the aggregator module from Exchange. You can locate the aggregator module in the Mule palette.

Then Drag and drop the HTTP listener in the canvas and configure the HTTP listener to run in a local environment.

Add a transform message to the flow after the HTTP listener and set up the payload.

%dw 2.0
output application/json
---
{
"Source Name" : "abc",
"Source Id" : uuid()
}

Then add size based aggregator and setup according to your requirements. Configure the size based aggregator as per the image.

Once the Mule application is deployed and running, you can use Postman to send HTTP requests to it. If you send five HTTP requests, you should see the following response logged:

Time Based Aggregator

The Time-Based Aggregator Scope in the Aggregators module enables you to group elements within a defined time frame. Setting up a Time-Based Aggregator is much like configuring a Size-Based Aggregator.

Set up the HTTP listener and add the Transform message as per image. Then set up a below payload.

%dw 2.0
output application/json
---
{
“Source Name”: “mulecraft time-based”,
“Source ID”: (random() as String)
}

Then add the time based aggregator module and configure the parameters as per the image.

Run and Deploy the application. Hit the Postman too.
You could see only three payload is processed and completed for the given specific time period.

Group Based Aggregator

The Group-Based Aggregator Scope in the Aggregators module lets you combine elements by categorizing them into different groups using designated group IDs.

The setup is similar to the Time based aggregator. You need to add the transform message with the below payload.

%dw 2.0

output application/json

- — -

{

“Source Name”: “mulecraft-group-based”,

“GroupId”: message.attributes[‘queryParams’].groupId,

“Source ID”: (random() as String)
}

Set a group based aggregator flow and configure the parameters as per image.

Hit the postman with the queryParams- groupId with values 1 and 2.

According to the group size, you could find the response in logs.