![]() One way of solving this challenge in our Spring-Data enabled application, is by using Spring’sĮnabling transaction management across both data sources can roughly be thought of as a three stage process: That the order is either successfully persisted to both DBs or neither. In order to avert any of these – admittedly, somewhat artificial – scenarios, the retailer’s application needs to make sure Shipping the items ordered, or shipping items without having received payment. This would result in either the company processing a payment and never Note: The demo application on github does not implement the REST Controllerįrom a business perspective, it would be an absolute disaster if a new order were saved to only one of the two DBs,ĭue to one system being temporarily unavailable or different failures, such as a constraint violation orĪ bug in your code. The two DBs are completely separate from one another, and they have different views on ![]() The app does this by writing directly into the respectiveĭepartment’s database instance. AccFin, which handles the payment, and the.The retailer’s application then forwards the received order to two different departments: Let’s start by defining a simple – albeit slightly artificial – business case, that we’ll use to guide ourselves alongĪ customer places an order with our Fictitious Online Retailer, by invoking a service with their Some basic knowledge of JPA – particularly JPA entities – is also necessary. PrerequisitesĪ decent level of familiarity with the Spring Framework in general is required if you want toĭelve into the technical intricacies of this tutorial. The code opening the code in a window parallel to this will make cross-referencing information a lot easier. Once you’ve read this text, you should be able to easily understand ![]() Hand in hand with the explanations provided in this post. The source code can be found here, on github and goes Step-by-step guide with the solution to this challenge. In order to spare others and my future self the misery of having to do this painstaking research again, I’ve put together a Transaction handling libraries, through configuration alone. One of the databases fail, then the system had to be rolled back to its previous state – in both databases.Īs it turns out, this issue is rather easily tackled using Spring and its assorted data and This posed a slight problem regarding data consistency: should any write operation to either I was recently confronted with a scenario that required a Spring BootĪpplication to manipulate information spanning two different SQL databases: this meant that one business entity lived For the validation of the chained transaction logic via Unit test, have a look at OrderProcessorServiceTransactionHandlingTest. You’re in a hurry to set up your chained transaction manager and have no time to go through this tutorial? Just read the code,Īs an entry point.
0 Comments
Leave a Reply. |