Solve JPA N+1 Problem: Understand Fetch Join & EntityGraph

Overview of JPA N+1 Problem

JPA (Java Persistence API) is a standard that supports the use of relational databases in Java applications. However, one of the common problems encountered when using JPA is the N+1 problem.

The N+1 problem refers to performance degradation issues that occur when retrieving associated entities. For example, consider the case of retrieving information about a single user and the posts written by that user. First, one query is needed to retrieve the user's information, and N more queries are needed to retrieve the posts of each user, resulting in a total of N+1 queries being executed.

When many unnecessary queries are executed, the performance of the database can be degraded, and the processing speed of the application can be slowed down. Therefore, it's important to effectively resolve the N+1 problem.

Causes of JPA N+1 Problem

The JPA N+1 problem is primarily related to lazy loading. Lazy loading is a JPA loading strategy that retrieves associated entities only when they are actually used, with the advantage of loading only the necessary data, but this increases the likelihood of the occurrence of the N+1 problem.

According to the lazy loading strategy, after retrieving the parent entity with the first query, additional queries are executed to retrieve individual child entities. When there are N parent-child relationships, N+1 queries are executed, causing performance problems.

Using eager loading to prevent the N+1 problem can cause other issues. Eager loading is a loading strategy that pre-fetches all associated entities, and always loads all the related data, which can result in unnecessarily large data transfer volumes.

Therefore, it's necessary to solve the N+1 problem using appropriate methods. The next section introduces solutions using Fetch Join and EntityGraph.

Solution 1: Using Fetch Join

Fetch Join is a method that retrieves associated entities along with the main entity when using JOIN keyword in JPQL (Java Persistence Query Language). This method allows you to retrieve all necessary data using a single query that joins the child entity to the parent entity's query.

Fetch Join can be implemented using the 'fetch' keyword in JPQL, as shown below:

// Original query
String jpql = "select u from User u";
// Query with Fetch Join applied
String fetchJoinJpql = "select u from User u join fetch u.posts";

Using Fetch Join can reduce the number of queries but may result in duplicate data in the joined results. To resolve this, you can use the 'distinct' keyword in JPQL to remove duplicate results.

String distinctFetchJoinJpql = "select distinct u from User u join fetch u.posts";

Using Fetch Join allows you to retrieve necessary data in a single query and solve the N+1 problem. However, be cautious when using it for large-volume data. In such cases, consider using EntityGraph, which is explained in the next section.

Solution 2: Using EntityGraph

EntityGraph is a feature introduced in JPA 2.1 that allows you to dynamically load associated entities. By using EntityGraph, you can specify the loading strategy at the data retrieval point, effectively solving the N+1 problem and reducing data transfer volume.

EntityGraph can be applied in two ways: Named Entity Graph and Dynamic Entity Graph. Named Entity Graph is defined using the @NamedEntityGraph annotation in the entity class, while Dynamic Entity Graph can be created dynamically using the API.

First, let's take a look at how to use the Named Entity Graph. In the following example, we create an EntityGraph that retrieves the User entity and the associated Post entity together.

@Entity
@NamedEntityGraph(name = "User.posts", attributeNodes = @NamedAttributeNode("posts"))
public class User {
    // ... omitted ...
}

To use the Named Entity Graph defined above, you can apply it to the query like this:

EntityGraph<User> entityGraph = em.createEntityGraph(User.class);
entityGraph.addAttributeNodes("posts");
List<User> users = em.createQuery("select u from User u", User.class)
    .setHint("javax.persistence.fetchgraph", entityGraph)
    .getResultList();

Dynamic Entity Graph is a method of creating an EntityGraph dynamically without using annotations on the entity class. The implementation is as follows:

EntityGraph<User> entityGraph = em.createEntityGraph(User.class);
entityGraph.addAttributeNodes("posts");
List<User> users = em.createQuery("select u from User u", User.class)
    .setHint("javax.persistence.loadgraph", entityGraph)
    .getResultList();

Using EntityGraph, you can reduce duplicate data and the number of queries to execute, thereby solving the N+1 problem unlike using Fetch Join. This can improve query performance.

Conclusion and Summary

The N+1 problem is a major cause of performance degradation that many developers face while using JPA. Various methods can be used to resolve the N+1 problem.

Fetch Join is a method in JPQL that allows you to retrieve associated entities together, preventing performance degradation. This method allows you to retrieve necessary data in a single query, but it can result in a lot of duplicate data in the joined results. Therefore, it should be used cautiously with large-volume data.

EntityGraph is a feature introduced in JPA 2.1 that allows you to dynamically load associated entities. This method allows you to specify the loading strategy during data retrieval, effectively solving both the N+1 problem and the data transfer volume issue. Moreover, EntityGraph can be applied using two methods - Named Entity Graph and Dynamic Entity Graph.

By appropriately using the methods introduced above, you can solve the JPA N+1 problem, enhance database performance, and improve the processing speed of your application. It's important to select the appropriate method based on the situation to achieve optimal performance.