Preventing Data Persistence on Retry Failure Calls with Spring Retry скачать в хорошем качестве

Preventing Data Persistence on Retry Failure Calls with Spring Retry

Discover how to manage `data persistence` efficiently when using Spring Retry with `@ Scheduled` methods to avoid unnecessary document creations. --- This video is based on the question https://stackoverflow.com/q/63243766/ asked by the user 'Alien' ( https://stackoverflow.com/u/6572971/ ) and on the answer https://stackoverflow.com/a/63246184/ provided by the user 'Alien' ( https://stackoverflow.com/u/6572971/ ) 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: Prevent data persist on retry failure call - Spring Retry 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. --- Preventing Data Persistence on Retry Failure Calls with Spring Retry In the world of microservices, we often encounter scenarios where our services interact with one another. However, when the service on the other end of an API call is down, retrying the call can create complications, especially in terms of data integrity. This article explores how to manage potential issues related to data persistence during failed retries in Spring applications, particularly when using the @ Scheduled and @ Retry annotations in Spring Boot. The Problem: Unwanted Duplicates Imagine you have a scheduled task in your application that generates documents and then calls an external service using RestTemplate. Due to the nature of this process, if the external service fails or is temporarily unavailable, your method will be retried. The downside? Every time the method is retried, it repeats the portions that save the document to the database, which can lead to multiple instances of the same document being created unnecessarily. This is not only inefficient but could also cause issues with data integrity. [[See Video to Reveal this Text or Code Snippet]] The Solution: Making Your Logic Idempotent To handle this problem effectively, we need to make our retry logic idempotent. This means that no matter how many times you execute the operation, the outcome will remain the same if the same input is provided. Let's break down the proposed solution: Step 1: Check for Document Existence Instead of saving the document every time the method is executed, we first check if the document already exists in the database. This way, we avoid creating duplicates during retries. Step 2: Fetch or Save the Document If the document exists, we can simply fetch it from the database instead of trying to save a new one. Only if it doesn’t exist should we proceed to save. This approach helps maintain a clean and consistent state in your database. Updated Method Implementation Here’s how you can implement the revised logic in your method: [[See Video to Reveal this Text or Code Snippet]] In this updated code: We still generate the excel document. We check for the document's existence in the database before attempting to save it. By avoiding redundant saves during retries, we ensure data consistency and integrity. Conclusion Managing data persistence effectively during retry failures can be challenging, but with the right approach, it can be done efficiently. By making the retry logic idempotent, you can prevent unnecessary duplicates and keep your database clean. This ultimately leads to a more reliable application that handles exceptions gracefully while interacting with external services. Keep this concept in mind as you develop more complex microservices, and avoid similar pitfalls in your applications!