Скачать или смотреть How to efficiently handle regular file loading with Spring Batch using restartable jobs

Discover how to handle frequent file uploads in Spring Batch, ensuring seamless processing and automatic recovery from errors with `restartable jobs`.
---
This video is based on the question https://stackoverflow.com/q/63726042/ asked by the user 'Amasta' ( https://stackoverflow.com/u/14092914/ ) and on the answer https://stackoverflow.com/a/63824627/ provided by the user 'Mahmoud Ben Hassine' ( https://stackoverflow.com/u/5019386/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How to load many files regularly and pick up where it left off?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Efficiently Handle Regular File Loading with Spring Batch

When dealing with a directory receiving numerous files to load regularly in Spring Batch, it can become cumbersome to manage errors effectively while ensuring that the loading process is seamless. If a file encounters an error, it’s crucial that the other files still get processed while allowing the failed file to pick up where it left off after correction. This guide will explore how to achieve that by using restartable jobs in Spring Batch.

Understanding the Problem

Imagine you have an external scheduler launching your Spring Batch Jar, and files are continuously arriving in a directory. Now, here are some challenges you might face:

If you use .incrementer(new RunIdIncrementer()), a new job is created every time your project runs, which means if there’s an error in any file, the process starts from the beginning rather than picking up from the point of failure.

Conversely, if you don’t use an incrementer, the job will correctly resume from where it left off. However, new files will not be loaded because the job doesn’t create a new instance for them.

So, how do you manage to load both existing and new files automatically while allowing for fault-tolerance?

Proposed Solution: Utilizing One Job Per File

The recommended approach to address these challenges is to ensure that each job processes one file at a time. This way, you can create a scheduled method that:

Reads the directory content.

Launches a job for each file with a unique identifying job parameter, such as the file name.

Moves successfully loaded files to another directory to separate them from the processing queue.

Advantages of This Approach

Scalability: Since you’re processing files individually, you can run multiple jobs in parallel effectively. The MultiResourceItemReader approach processes files serially, which can become a bottleneck.

Fault-tolerance: If a job fails, it won’t affect the loading of other files. During the next scheduled run, the job can restart processing the failed file where it left off.

No Need for an Incrementer: Since each job is unique to a file, there’s no requirement to use .incrementer(new RunIdIncrementer()), simplifying job management.

Steps to Implement the Solution

Schedule File Processing: Create a scheduled method to scan the directory for new files.

Launch Individual Jobs: For each identified file, launch a Spring Batch job that processes only that file. In this job configuration:

Define the reader, processor, and writer to handle the file content.

Employ unique job parameters per file, which would aid in tracking job execution states effectively.

Success and Failure Handling:

Upon successful processing, move the file to a “processed” directory.

If there’s a failure, log the error and ensure the job can resume on the next run without manual intervention.

Conclusion

Adopting this method of utilizing a single job for each file simplifies error handling and enhances file processing efficiency in your Spring Batch application. By structuring jobs this way, you ensure smooth operation while taking full advantage of Spring Batch's capabilities for managing file loads effectively and automatically.

Feel free to implement this strategy in your projects, and enjoy the benefits of scalable, fault-tolerant file loading with Spring Batch.