MuleSoft Training Session 4: Database Connector with Batch Processing | Parallel Processing

In this video, we have implemented a use-case that makes use of Batch processing, file connector, and database connector to handle valid and invalid records. It also collects batch processing matrix data and persists in the database as a transaction summary. I have explained about groupBy(), orderBy() and pluck() DW::Core functions to get desired output. I have also explained about $, $$, $$$ inbuilt variables in detail with example.

Batch Processing in Mule 4:
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Mule allows you to process messages in batches.
Within an application, you can initiate a Batch Job scope, which splits messages into individual records, performs actions upon each record, and then reports on the results and potentially pushes the processed output to other systems or queues.

For example, you can use batch processing when:
- Synchronizing data sets between business applications, such as syncing contacts between NetSuite and Salesforce.
- Extracting, transforming and loading (ETL) information into a target system, such as uploading data from a flat file (CSV) to Hadoop.
- Handling large quantities of incoming data from an API into a legacy system.

Thanks for watching this video!!!

Note: Batch processing is exclusive to Mule Enterprise runtimes.

References:
https://docs.mulesoft.com/mule-runtime/4.4/batch-processing-concept

CSV File:
https://drive.google.com/file/d/1BBGdZX9Ur328S9jV4EHVR_UsbD9ihIoO/view?usp=sharing

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