org.springframework.data.repository.config.RepositoryConfigurationDelegate -- Multiple Spring Data modules found, entering strict repository configuration mode

Understanding and Resolving the "Multiple Spring Data Modules Found" Issue

If you're a developer working with Spring Data, you may have encountered the warning message:

org.springframework.data.repository.config.RepositoryConfigurationDelegate -- Multiple Spring Data modules found, entering strict repository configuration mode

This message can be alarming, especially if you're aiming for smooth application performance. In this blog post, we’ll dive into what this issue means, why it occurs, and how to resolve it effectively.

What Does the Warning Mean?

When you see the warning about "multiple Spring Data modules," it indicates that your application has detected more than one Spring Data module on the classpath. Spring Data provides a consistent way to access various data stores, and while it supports many modules (like Spring Data JPA, Spring Data MongoDB, etc.), having multiple modules can sometimes lead to conflicts in repository configuration.

Why Is This a Problem?

1. Configuration Conflicts: Different Spring Data modules might have overlapping functionalities or configurations, leading to ambiguity in how repositories are managed.

2. Performance Issues: The strict repository configuration mode can lead to performance overhead as Spring Data takes extra steps to ensure that the repositories are correctly configured.

3. Runtime Exceptions: If the configurations conflict significantly, it might result in runtime exceptions, making debugging a hassle.

Identifying the Source of the Problem

To resolve the warning, you first need to identify the Spring Data modules included in your project. Here are some common scenarios that might lead to this issue:

• Multiple Dependencies: Check your pom.xml (for Maven) or build.gradle (for Gradle) files for multiple Spring Data dependencies.
• Transitive Dependencies: Sometimes, a library you depend on might pull in additional Spring Data modules. Use tools like mvn dependency:tree for Maven or gradle dependencies for Gradle to trace these transitive dependencies.

Solutions to Resolve the Issue

Once you’ve identified the cause, you can implement one or more of the following solutions:

1. Exclude Unnecessary Modules

If you’re using a specific Spring Data module, you can exclude other modules that are not needed. For instance, if you’re using Spring Data JPA and don’t need MongoDB, you can exclude it:

Maven Example

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-jpa</artifactId>
    <exclusions>
        <exclusion>
            <groupId>org.springframework.data</groupId>
            <artifactId>spring-data-mongodb</artifactId>
        </exclusion>
    </exclusions>
</dependency>

Gradle Example

implementation('org.springframework.boot:spring-boot-starter-data-jpa') {
    exclude group: 'org.springframework.data', module: 'spring-data-mongodb'
}

2. Use Spring Profiles

If your application requires different modules for different environments (e.g., development, testing), consider using Spring profiles. This allows you to specify which Spring Data modules to load based on the active profile.

3. Verify Spring Data Versions

Ensure that all Spring Data modules are compatible with each other. Using a consistent version across all Spring Data dependencies can help avoid conflicts. You can manage dependency versions using a Spring BOM (Bill of Materials):

Maven Example

<dependencyManagement>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-dependencies</artifactId>
            <version>2.6.3</version>
            <type>pom</type>
            <scope>import</scope>
        </dependency>
    </dependencies>
</dependencyManagement>

4. Adjust Repository Configuration

If the warning persists, you can configure your repositories explicitly. You may want to define custom configurations for each module in your application context.

Conclusion

Encountering the "Multiple Spring Data modules found" warning can be a nuisance, but with the right approach, you can resolve it effectively. By identifying unnecessary dependencies, managing versions, and configuring your repositories correctly, you can ensure smooth operation for your Spring Data application.

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Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'jpaSharedEM_entityManagerFactory': Cannot resolve reference to bean 'entityManagerFactory' while setting constructor argument

How to Resolve BeanCreationException After Upgrading to Spring Boot 3.3.3

Upgrading to the latest version of Spring Boot can sometimes introduce unexpected issues. One common error developers encounter is the BeanCreationException related to the entityManagerFactory. This blog post will guide you through understanding and resolving this issue.

Error Description

After upgrading to Spring Boot 3.3.3, you might see an error similar to the following:

Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'jpaSharedEM_entityManagerFactory': Cannot resolve reference to bean 'entityManagerFactory' while setting constructor argument
	at org.springframework.beans.factory.support.BeanDefinitionValueResolver.resolveReference(BeanDefinitionValueResolver.java:377) ~[spring-beans-6.1.12.jar:6.1.12]

This error indicates that Spring Boot is unable to create the entityManagerFactory bean, which is essential for JPA (Java Persistence API) operations.

Root Cause

The root cause of this issue is often related to changes in the configuration or dependencies that come with the new version of Spring Boot. Specifically, it can be due to:

1. Changes in Dependency Versions: Upgrading Spring Boot might also upgrade dependencies like Hibernate, which could introduce breaking changes.
2. Configuration Changes: Spring Boot 3.3.3 might have deprecated or changed certain configuration properties.

Solution

Here are the steps to resolve this issue:

1. Check Dependencies: Ensure that all your dependencies are compatible with Spring Boot 3.3.3. You can use the Spring Boot Dependency Management Plugin to manage versions.

   <dependencyManagement>
       <dependencies>
           <dependency>
               <groupId>org.springframework.boot</groupId>
               <artifactId>spring-boot-dependencies</artifactId>
               <version>3.3.3</version>
               <type>pom</type>
               <scope>import</scope>
           </dependency>
       </dependencies>
   </dependencyManagement>
   

2. Update Configuration: Review your application.properties or application.yml files for any deprecated properties. For example, ensure that your JPA configuration is up-to-date:

   spring.datasource.url=jdbc:mysql://localhost:3306/yourdb
   spring.datasource.username=root
   spring.datasource.password=yourpassword
   spring.jpa.hibernate.ddl-auto=update
   spring.jpa.show-sql=true
   

3. Use Spring Boot Properties Migrator: This tool helps in identifying and migrating deprecated properties. Add the following dependency to your project:

   <dependency>
       <groupId>org.springframework.boot</groupId>
       <artifactId>spring-boot-properties-migrator</artifactId>
       <scope>runtime</scope>
   </dependency>
   

   This will print diagnostics at startup and help you migrate properties.

4. Check Bean Definitions: Ensure that your entityManagerFactory bean is correctly defined. If you are using a custom configuration, make sure it aligns with the new version.

   @Bean
   public LocalContainerEntityManagerFactoryBean entityManagerFactory(
           EntityManagerFactoryBuilder builder, DataSource dataSource) {
       return builder
               .dataSource(dataSource)
               .packages("com.example.yourpackage")
               .persistenceUnit("yourPersistenceUnit")
               .build();
   }

By following these steps, you should be able to resolve the BeanCreationException and successfully upgrade to Spring Boot 3.3.3. Happy coding!

---

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¹: Spring Boot 3.0 Migration Guide

Implementing SSO with Keycloak in a Spring Boot Application

Introduction

Single Sign-On (SSO) is a powerful authentication mechanism that allows users to log in once and gain access to multiple applications. In this blog post, we’ll walk you through the steps to implement SSO using Keycloak in a Spring Boot application.

Step 1: Add Maven Dependencies

First, add the necessary dependencies to your pom.xml:

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-security</artifactId>
</dependency>
<dependency>
    <groupId>org.keycloak</groupId>
    <artifactId>keycloak-spring-boot-starter</artifactId>
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-oauth2-client</artifactId>
</dependency>

Step 2: Configure Keycloak

Create a keycloak.json file in your src/main/resources directory with the following content:

{
  "realm": "your-realm",
  "auth-server-url": "http://localhost:8080/auth",
  "ssl-required": "external",
  "resource": "your-client-id",
  "credentials": {
    "secret": "your-client-secret"
  },
  "confidential-port": 0
}

Step 3: Spring Security Configuration

Create a security configuration class to integrate Keycloak with Spring Security:

import org.keycloak.adapters.springsecurity.KeycloakConfiguration;
import org.keycloak.adapters.springsecurity.config.KeycloakWebSecurityConfigurerAdapter;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Bean;
import org.springframework.security.config.annotation.authentication.builders.AuthenticationManagerBuilder;
import org.springframework.security.config.annotation.web.builders.HttpSecurity;
import org.springframework.security.config.annotation.web.configuration.EnableWebSecurity;
import org.springframework.security.core.authority.mapping.SimpleAuthorityMapper;
import org.springframework.security.core.session.SessionRegistryImpl;
import org.springframework.security.web.authentication.session.RegisterSessionAuthenticationStrategy;
import org.springframework.security.web.authentication.session.SessionAuthenticationStrategy;

@KeycloakConfiguration
@EnableWebSecurity
public class SecurityConfig extends KeycloakWebSecurityConfigurerAdapter {

    @Autowired
    public void configureGlobal(AuthenticationManagerBuilder auth) {
        auth.authenticationProvider(keycloakAuthenticationProvider());
    }

    @Bean
    @Override
    protected SessionAuthenticationStrategy sessionAuthenticationStrategy() {
        return new RegisterSessionAuthenticationStrategy(new SessionRegistryImpl());
    }

    @Override
    protected void configure(HttpSecurity http) throws Exception {
        super.configure(http);
        http.authorizeRequests()
            .antMatchers("/public/**").permitAll()
            .anyRequest().authenticated();
    }
}

Step 4: Application Properties

Add the following properties to your application.properties file:

keycloak.realm=your-realm
keycloak.auth-server-url=http://localhost:8080/auth
keycloak.resource=your-client-id
keycloak.credentials.secret=your-client-secret
keycloak.ssl-required=external
keycloak.use-resource-role-mappings=true

Step 5: Create a Controller

Create a simple controller to test the SSO setup:

import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;

@RestController
public class TestController {

    @GetMapping("/public")
    public String publicEndpoint() {
        return "This is a public endpoint.";
    }

    @GetMapping("/private")
    public String privateEndpoint() {
        return "This is a private endpoint.";
    }
}

Conclusion

Run your Spring Boot application and navigate to the /private endpoint. You should be redirected to the Keycloak login page. After logging in, you will be able to access the private endpoint. This setup provides a basic SSO implementation using Keycloak with Spring Boot. Customize it further based on your specific requirements.

Happy coding! 🚀

---

Exploring Spring AI 1.0.0 M2: A Hands-On Guide with Code Samples

Welcome to our deep dive into Spring AI 1.0.0 M2, the latest release designed to simplify AI integration within the Spring framework. This update brings a host of enhancements that streamline the process of incorporating AI functionalities into your applications. In this post, we'll explore these new features and walk through a practical example of using Spring AI 1.0.0 M2 with a TensorFlow model.

What's New in Spring AI 1.0.0 M2?

Spring AI 1.0.0 M2 introduces several exciting updates:

• Simplified Configuration: Less boilerplate code and easier setup for AI components.
• Expanded AI Framework Support: Enhanced compatibility with TensorFlow, PyTorch, and other popular AI frameworks.
• Performance Enhancements: Improved efficiency and scalability for AI applications.
• Improved Documentation: Updated guides and examples for quicker implementation.

Getting Started with Spring AI 1.0.0 M2

To showcase the capabilities of Spring AI 1.0.0 M2, we'll create a simple Spring Boot application that uses TensorFlow for text classification. Follow these steps to get started:

1. Create a New Spring Boot Project

Generate a new Spring Boot project using Spring Initializr. Add the following dependencies:

• Spring Web
• Spring Boot DevTools
• Spring Data JPA (optional)

2. Add TensorFlow Dependency

Update your pom.xml file with the TensorFlow dependency:

<dependencies>
    <!-- Spring Boot Starter Web -->
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-web</artifactId>
    </dependency>
    
    <!-- TensorFlow Java Library -->
    <dependency>
        <groupId>org.tensorflow</groupId>
        <artifactId>tensorflow</artifactId>
        <version>2.11.0</version>
    </dependency>
</dependencies>

3. Build the AI Component

Create a service class to handle interactions with the TensorFlow model:

package com.example.springai.service;

import org.springframework.stereotype.Service;
import org.tensorflow.SavedModelBundle;
import org.tensorflow.Tensor;

@Service
public class TextClassificationService {

    private final SavedModelBundle model;

    public TextClassificationService() {
        // Load the pre-trained TensorFlow model
        this.model = SavedModelBundle.load("path/to/saved_model", "serve");
    }

    public String classifyText(String text) {
        try (Tensor<String> inputTensor = Tensor.create(text.getBytes("UTF-8"), String.class)) {
            // Run inference
            Tensor<?> result = model.session().runner()
                .feed("input_tensor_name", inputTensor)
                .fetch("output_tensor_name")
                .run()
                .get(0);

            // Process result
            float[][] output = result.copyTo(new float[1][1]);
            return output[0][0] > 0.5 ? "Positive" : "Negative";
        } catch (Exception e) {
            throw new RuntimeException("Error during text classification", e);
        }
    }
}

Note: Replace "path/to/saved_model", "input_tensor_name", and "output_tensor_name" with the actual paths and names used in your TensorFlow model.

4. Create a Controller

Add a REST controller to expose an API endpoint for text classification:

package com.example.springai.controller;

import com.example.springai.service.TextClassificationService;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;

@RestController
public class TextClassificationController {

    private final TextClassificationService classificationService;

    public TextClassificationController(TextClassificationService classificationService) {
        this.classificationService = classificationService;
    }

    @GetMapping("/classify")
    public String classify(@RequestParam String text) {
        return classificationService.classifyText(text);
    }
}

Running the Application

1. Build and Run Your Application

   Use Maven to build and run your Spring Boot application:

   mvn clean install
   mvn spring-boot:run
   

2. Test the API

   Open your browser or use a tool like curl or Postman to test the endpoint:

   
   curl "http://localhost:8080/classify?text=I%20love%20Spring%20AI"
   

   You should receive a response indicating whether the text is classified as "Positive" or "Negative."