Скачать или смотреть How to Use MapStruct for One-to-Many Relationships in Java: Creating a DTO Row by Row

Learn how to effectively use `MapStruct` to handle one-to-many relationships in Java, and generate DTOs seamlessly from your entities.
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This video is based on the question https://stackoverflow.com/q/71788571/ asked by the user 'microwth' ( https://stackoverflow.com/u/1498827/ ) and on the answer https://stackoverflow.com/a/71812484/ provided by the user 'GJohannes' ( https://stackoverflow.com/u/10254476/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Understanding the Problem: One-to-Many Mapping with DTOs

In Java applications that utilize Hibernate and MapStruct, handling relationships between entities can sometimes be tricky. A common scenario arises when you have a one-to-many relationship, for instance, between a Customer entity and its associated Address entities. In this example, a Customer can have multiple Addresses, and each Address contains an Email field.

Let's consider a situation where we have a customer with a list of addresses. For example,

Customer ID = 6 with two addresses:

Address 1: john@ gmail.com

Address 2: john2@ gmail.com

The question here is how to map this relationship into a DTO (Data Transfer Object) format, where we want to extract the Customer ID and the Email from each address, resulting in two rows as follows:

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The challenge is figuring out whether this can be achieved without additional SQL queries, and utilizing MapStruct alone for the mapping process.

The Solution: Using Java Streams and DTO Mapping

While MapStruct is powerful for mapping data between different object types, in this scenario, it falls short of satisfying our requirement because it doesn't support applying logic directly during the mapping process. However, we can leverage Java Streams along with a well-structured code implementation to achieve our goal efficiently.

Step-by-Step Implementation

The following is an in-depth guide on how to implement this solution in Java using the given entities and logic:

1. Define Your Entities and DTO

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2. Create a Customer and Its Addresses

Here we initialize a Customer object with a list of Address objects.

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3. Map the Addresses to the ResultingDTO

We can use Java Stream API to map through the addresses and transform them into the desired DTO format.

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4. Handling Multiple Customers

If you need to filter and map multiple customers by ID, you can do so by using additional stream operations.

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5. Output the Results

Finally, after running the code, you will get two rows of DTOs that reflect the mappings accurately.

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Conclusion

Although MapStruct might not directly support complex transformations involving conditional logic or collections, by utilizing Java Streams, we can achieve our objective of handling one-to-many relationships efficiently. This method allows us to map our entities to DTOs seamlessly and ensures that our code remains clean and readable. By following this structured approach, you can easily adapt it to your own use cases as required.

Feel free to reach out with any further questions about implementing MapStruct or working with Hibernate relationships in Java!