If you are looking to enhance your Spring Data JDBC experience and execute complex SQL operations seamlessly, Spring JDBC Plus is a solid choice! In this guide, we’ll explore how to set up Spring JDBC Plus, write efficient SQL queries, and troubleshoot potential issues.

What is Spring JDBC Plus?

Spring JDBC Plus is an extension built on top of Spring Data JDBC. It adds essential features that allow developers to execute more complex SQL queries beyond the capabilities of the standard CrudRepository. With Spring JDBC Plus, you can combine persistence features with advanced SQL execution.

Key Features of Spring JDBC Plus

• Support for executing custom SQL SELECT statements
• Provides various parameter source types like BeanParameterSource and MapParameterSource
• Mapping support for complex table joins
• AggregateResultSet for mapping 1:N result data
• JdbcRepository for insert and update operations
• Support for reactive programming with Flux/Mono return types

Getting Started

To begin using Spring JDBC Plus, you’ll need to add the dependency in your Gradle or Maven projects. Here’s how to set it up:

1. Using Gradle

buildscript {
    repositories {
        mavenCentral()
        mavenLocal()
        maven { url "https://repo.spring.io/milestone" }
    }
    dependencies {
        classpath("org.springframework.boot:spring-boot-gradle-plugin:3.3.4")
    }
}
dependencies {
    implementation("org.springframework.boot:spring-boot-starter-data-jdbc")
    implementation("com.navercorp.spring:spring-boot-starter-data-jdbc-plus-sql:3.3.4")
}

2. Using Maven

<parent>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-parent</artifactId>
    <version>3.3.4</version>
</parent>

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-jdbc</artifactId>
</dependency>

<dependency>
    <groupId>com.navercorp.spring</groupId>
    <artifactId>spring-boot-starter-data-jdbc-plus-sql</artifactId>
    <version>3.3.4</version>
</dependency>

3. Example Java Code

Let’s create an entity class for our orders and define a method to find orders by the purchaser number:

@Table("n_order")
@Data
public class Order {
    @Id
    @Column("order_no")
    private Long orderNo;
    @Column("price")
    private long price;
    @Column("purchaser_no")
    private String purchaserNo;
}

public interface OrderRepository extends CrudRepository, OrderRepositoryCustom {}

public interface OrderRepositoryCustom {
    List findByPurchaserNo(String purchaserNo);
}

public class OrderRepositoryImpl extends JdbcRepositorySupport implements OrderRepositoryCustom {
    private final OrderSql sqls;

    public OrderRepositoryImpl(EntityJdbcProvider entityJdbcProvider) {
        super(Order.class, entityJdbcProvider);
        this.sql = sqls(OrderSql::new);
    }

    @Override
    public List findByPurchaserNo(String purchaserNo) {
        String sql = this.sql.selectByPurchaserNo();
        return find(sql, mapParameterSource().addValue("purchaserNo", purchaserNo));
    }
}

Understanding the Code: A Bakery Analogy

Imagine you are a baker with a great passion for making various types of pastries (your database entities). You need a special recipe book (the SQL commands) to create these pastries efficiently.

• The Order class represents a type of pastry – let’s say a chocolate croissant. Each croissant has its unique ingredients (properties) like order number, price, and purchaser number.
• The OrderRepository acts like a manager who retrieves and stores orders in your bakery. It knows how to get specific croissants based on who ordered them.
• The OrderRepositoryImpl is like a skilled chef who executes the recipe perfectly by following the custom SQL instructions.
• Finally, the findByPurchaserNo method is a specialized recipe that allows the chef to find and retrieve all chocolate croissants ordered by a specific customer.

Cautions When Writing SQL

Just as a skilled baker must avoid mixing old and new ingredients to prevent a failed batch, you should also be careful with SQL syntax:

• Always use named parameters when passing values to SQL to prevent SQL injection vulnerabilities.
• Avoid string concatenation for parameter values. Use named parameters instead.

Troubleshooting Tips

If you encounter issues during setup or execution, consider the following:

• Make sure you are using the correct version of Spring JDBC Plus. Avoid using version 3.3.3.
• Double-check your SQL commands for any syntactical errors.
• If parameters aren’t being passed correctly, ensure you are using named parameters properly.

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Additional Resources

For more detailed information, refer to the User Guide or visit Reporting Issues for help.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.