
Configure the project with spring batch dependencies, including the spring boot starter batch that pulls in core and infrastructure libraries, plus the test library; verify the build.
Configure a Spring Batch step with the step builder factory, defining a reader, processor, and writer, and implement a simple tasklet that prints hello world, and chunk oriented processing.
Launch a spring batch job via a rest controller at /job, wiring the job launcher and parameters, including a CSV file name for validation and successful execution feedback.
Update the step for chunking in Spring Batch by adding an item reader, processor, and writer. Configure a chunk size of 2 and adapt the job step and batch configuration.
Unit test an item processor in a batch job by applying its Java function to a patient record, producing a patient entity, and verifying results with assertions and step-scoped listeners.
Define the patient database schema by adding a liquibase changelog that maps table columns to the patient entity, update the master changelog, and verify the changes load correctly.
At the core of batch processing is an understanding of the basic concepts and patterns common to most batch products. In this course, you will learn these concepts and patterns in the context of one of the oldest and most mature open source batch frameworks available. First, you will learn about why you may need batch processing, including its benefits and drawbacks. Next, you will explore the foundation of Spring Batch terminology and offerings. Finally, you will follow along in a demonstration of building a full, production-ready Spring Batch job that reads input from a file, processes, and then outputs the information to a database. When you are finished with the course, you should have the basic knowledge needed to start building your own batch jobs using the Spring Batch framework.