1. Structure of a Spring Boot Project

The typical structure of a Spring Boot project looks like this:

Explanations of the Structure:

• src/main/java: This is where all the Java code resides.
• com/example: The base package name, usually reflecting the company’s domain name.
• controller/: Contains the REST controllers that handle HTTP requests.
• service/: Business logic is implemented here.
• repository/: Data access objects that interact with the database.
• Application.java: The main application class that contains the main method and starts Spring Boot.
• src/main/resources: This is where resources like configuration files and static files are located.
• application.properties: Configuration file for Spring Boot.
• static/: Static resources like CSS, JS, and images.
• templates/: Templates for rendering views (e.g., Thymeleaf).
• src/test/java: This is where the tests for the application are located.
• pom.xml: Maven project file that defines dependencies and plugins.

2. AOP Concepts (Aspect-Oriented Programming)

AOP allows you to separate cross-cutting concerns like logging, transactions, and security from business logic. Important terms include:

• Aspect: A modular unit of cross-cutting logic.
• Join Point: A specific point in the program flow where an aspect can be applied.
• Advice: The code that is executed at a Join Point.
• Pointcut: An expression that defines the Join Points where Advice is applied.

Example:

import org.aspectj.lang.annotation.Aspect;
import org.aspectj.lang.annotation.Before;
import org.springframework.stereotype.Component;

@Aspect
@Component
public class LoggingAspect {

    @Before("execution(* com.example.service.*.*(..))")
    public void logBeforeMethod() {
        System.out.println("A method is being called.");
    }
}

3. Database Access in Spring Boot

JDBC Template Example

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.stereotype.Repository;

import java.util.List;
import java.util.Map;

@Repository
public class UserRepository {

    @Autowired
    private JdbcTemplate jdbcTemplate;

    public Map<String, Object> getUserById(int id) {
        String sql = "SELECT * FROM users WHERE id = ?";
        return jdbcTemplate.queryForMap(sql, id);
    }

    public List<Map<String, Object>> getAllUsers() {
        String sql = "SELECT * FROM users";
        return jdbcTemplate.queryForList(sql);
    }
}

Difference between queryForMap and queryForList

• queryForMap: Returns a single row as a Map, using column names as keys.
• queryForList: Returns a list of rows, with each row represented as a Map.

JdbcTemplate supports batch processing, which allows us to execute multiple SQL statements in a single batch. This can significantly improve performance when inserting or updating large amounts of

public void batchAddUsers(List<User> users) {
    String sql = "INSERT INTO users (name, email) VALUES (?, ?)";
    jdbcTemplate.batchUpdate(sql, new BatchPreparedStatementSetter() {
        @Override
        public void setValues(PreparedStatement ps, int i) throws SQLException {
            ps.setString(1, users.get(i).getName());
            ps.setString(2, users.get(i).getEmail());
        }

        @Override
        public int getBatchSize() {
            return users.size();
        }
    });
}

To convert rows of the result set into custom objects, we can implement the RowMapper interface. This is especially useful for queries that return multiple rows.

public List<User> getAllUsers() {
    String sql = "SELECT * FROM users";
    return jdbcTemplate.query(sql, new UserRowMapper());
}

When performing multiple operations that need to be executed as a single unit of work, we can manage transactions using Spring’s @Transactional annotation.

@Transactional
public void createUserAndProfile(User user, Profile profile) {
    addUser(user.getName(), user.getEmail());
    // Insert profile logic here
}

4. Spring Data JDBC

Spring Data JDBC is a part of the Spring Data project that provides a simplified way to access relational databases using plain JDBC. It focuses on a more straightforward approach to data access by leveraging the concepts of repositories and entities, while maintaining a close relationship with the underlying database.

Key Features of Spring Data JDBC:

1. Entity Mapping: Maps Java objects directly to database tables without the complexity of ORM (Object-Relational Mapping).
2. Repository Support: Provides a repository abstraction, allowing you to perform CRUD operations without writing boilerplate code.
3. Simplicity: Offers a simpler programming model compared to JPA, making it easier to understand and use for straightforward use cases.

Here’s a simple example of using Spring Data JDBC:

import org.springframework.data.annotation.Id;
import org.springframework.data.jdbc.core.mapping.Table;
import org.springframework.data.repository.CrudRepository;
import org.springframework.stereotype.Repository;

import java.util.List;

@Table("users")
public class User {
    @Id
    private Long id;
    private String name;
    private String email;

    // Getters and Setters
}

@Repository
public interface UserRepository extends CrudRepository<User, Long> {
    List<User> findByName(String name);
}

In this example:

• The User class represents a table in the database, with fields mapped to columns.
• The UserRepository interface extends CrudRepository, providing methods to perform CRUD operations without additional implementation.

5. Spring Data JPA

What is JPA?

Java Persistence API (JPA) is a specification for managing relational data in Java applications. Spring Data JPA simplifies the implementation of JPA-based repositories.

Concrete Example

import org.springframework.data.jpa.repository.JpaRepository;
import org.springframework.stereotype.Repository;

@Repository
public interface UserRepository extends JpaRepository<User, Integer> {
    List<User> findByLastName(String lastName);
}

Dynamic Finder Methods (supported keywords)

• findBy: Searches by a specific attribute.
• findByFirstNameAndLastName: Searches by multiple attributes.
• findByAgeGreaterThan: Searches for values greater than a specific value.

Advantages of JPA

• Simplicity: Less boilerplate code compared to JDBC.
• Abstraction: Hides the complexity of database interaction.
• Flexibility: Supports different databases without changes to the code.

5. Comparison: JDBC, JdbcTemplate, and JPA

Fazit

• JDBC is suitable for low-level database access where performance is critical, but it requires a lot of boilerplate code.
• JdbcTemplate simplifies JDBC usage by handling resource management and providing utility methods, making it easier to work with databases.
• JPA is ideal for applications that require complex object-relational mapping and a higher level of abstraction, but it comes with additional overhead.

Choosing between these options depends on the specific requirements of our application, including complexity, performance, and ease of use.

6. Transactions in Spring

Spring provides support for declarative transactions, allowing us to manage transactions through annotations.

Example of Transactions

import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;

@Service
public class UserService {

    @Autowired
    private UserRepository userRepository;

    @Transactional
    public void createUser(User user) {
        userRepository.save(user);
        // Additional operations that are part of the transaction
    }
}

Conclusion

This tutorial gives us an overview of the structure of a Spring Boot project, AOP, database access, Spring Data JPA, and transactions.