Is it a good practice to create many DTO for a model?

user_11772287 0
Viewed 1481

Assuming I have a class User with many fields:

public class User {
    public Integer id;
    public String name;
    public String username;
    public Integer age;
    public Address address;
    public String phoneNumber;
    public String email;
}

But I will not always need all User attributes in frontend. Each screen needs only some of User's fields. Is it a good practice to make DTO classes for each screen, since they access different attributes? Like this:

class UserToScreenADTO implements Serializable {
    public String name;
    public String email;
}

class UserToScreenBDTO implements Serializable {
    public String phoneNumber;
    public Address address;
}

class UserToScreenCDTO implements Serializable {
    public Integer id;
    public String username;
    public String email;
}
dto serializable hibernate java
3 Answers

I would create just one DTO class but e.g. pass to its constructor
the list of the fields which I want to be pulled and set by the backend.
All other fields will be null.

The list of fields will be passed in by the front-end.

I find this approach pretty flexible/dynamic.

It also avoids multiple classes to maintain.

I don't know if this approach matches any best practices or enterprise patterns
but creating multiple DTO classes definitely sounds worse.

user_23005970

Since OP said that the system is used from the same frontend and in the same context, I would consider it bad practice and not recommend using different DTOs.

Reasoning:

Modern frontends normally manage a store of all entites received by the backend. So the frontend can look up entities in the store and - depending on caching policies - load them from the store rather than requesting them from the server. Thus, instead of fetching users part-by-part, the user is transmitted once. This can be further improved by using ETags. While the usage of Etags will hardly improve latency, it can improve network load since the response to a matching ETag is a 304/Not Modified without a body (!) rather than a 200/OK with body. While ETags can be used with many Dto-Objects, more (partial) updates might occur. If, for example, the email and the phone number of a user changes, and the frontend first requests the UserToScreenADTO, it would get a response body that - among other things - contains the new email. When it then later requests a UserToScreenBDTO, it would - again - receive a response body containing the new phone number. With only one DTO, the frontend will receive one updated representation on the first request, and all successive request (made with the matching ETag) will result in a 304/Not Modified.

Furthermore, more classes normally mean higher complexity. Thus, I would recommend to keep the number of classes reasonably small. If using an ETag is not wanted and/or the frontend does not keep a store of server-sent entities, I would recommend the approach described in peter petrov's answer.

The representation should only change if the context changes. If the representations differ drastically between, for example, a user-frontend and an admin-frontend, then different DTOs may be justified.

user_42166410

Using "just" one DTO or the entity directly comes with a high cost that you usually only pay later, so I would recommend anyone to create a DTO per use case just like you did here.

Here are some of the reasons/costs for this:

  • If the user of the API sees accessors for state that isn't loaded this will trigger lazy loading which will either result in bad performance or lazy initialization exceptions. If objects are passed through a session, you might lose the context how the object came to be, so you might not always be able to tell which state is loaded.
  • It might be inefficient to load all data all the time. If you have some text columns that contain lots of data this has to be transferred over the wire and materialized as Java Objects etc. If you don't use the data, it's just pointless to load it at all. One might say this is negligible, but it depends on your use case. The worst that can happen? The DBMS does a full table scan or a less efficient index scan rather than index only scan because you instruct the DBMS to load the value for a column.
  • Not all the state that you want to provide for a client should be in the relational representation. If you do aggregations or use expressions for e.g. concatenating columns together, you need a DTO.

Having said that, this is a perfect use case for Blaze-Persistence Entity Views.

I created the library to allow easy mapping between JPA models and custom interface or abstract class defined models, something like Spring Data Projections on steroids. The idea is that you define your target structure(domain model) the way you like and map attributes(getters) via JPQL expressions to the entity model.

A DTO model for your use case could look like the following with Blaze-Persistence Entity-Views:

@EntityView(User.class)
public interface UserToScreenADTO extends Serializable {
    String getName();
    String getEmail();
}

@EntityView(User.class)
public interface UserToScreenBDTO extends Serializable {
    String getPhoneNumber();
    Address getAddress();
}

@EntityView(User.class)
public interface UserToScreenCDTO extends Serializable {
    Integer getId();
    String getUsername();
    String getEmail();
}

Querying is a matter of applying the entity view to a query, the simplest being just a query by id.

UserToScreenADTO u = entityViewManager.find(entityManager, UserToScreenADTO.class, id);

The Spring Data integration allows you to use it almost like Spring Data Projections: https://persistence.blazebit.com/documentation/entity-view/manual/en_US/index.html#spring-data-features

user_4124460
Related