Spring Boot Web Development With MySQL

1. Database Connectivity and SQL Operations

• Connection Setup: Requires adding the mysql-connector-j driver and configuring connection parameters in application.properties or application.yml (e.g., spring.datasource.url=jdbc:mysql://localhost:3306/dbname, username, and password).
• Connection Pooling: Spring Boot configures HikariCP by default, managing a pool of reusable connections to avoid the high overhead of establishing a new physical connection for every request.
• SQL Operations: Covers standard DDL and DML operations (such as SELECT, INSERT, UPDATE, and DELETE) along with transaction management via @Transactional to guarantee ACID compliance during execution.

2. JdbcTemplate

• Boilerplate Reduction: Eliminates repetitive tasks such as opening/closing connections, preparing statements, catching checked SQL exceptions, and managing transactions manually.
• Exception Translation: Converts generic JDBC SQLException instances into Spring’s informative, unchecked DataAccessException hierarchy.
• Execution Methods: Provides straightforward utility methods such as .query(), .queryForObject(), and .update() to execute queries and data modifications with parameterized inputs, preventing SQL injection vulnerabilities.

3. Row Mapping

• RowMapper<T> Interface: Allows custom column-by-column mapping logic by implementing the mapRow(ResultSet rs, int rowNum) method to construct a model object from the ResultSet.
• BeanPropertyRowMapper: A built-in implementation that automatically maps SQL column names (snake_case) to Java object fields (camelCase) by matching names, eliminating the need to write manual conversion code for standard models.

4. Multiple Database Support

• Explicit Bean Configuration: Bypasses default auto-configuration by manually defining multiple DataSource beans using @Configuration and @ConfigurationProperties (e.g., pointing to app.datasource.primary and app.datasource.secondary).
• Managing Beans: Uses @Primary on the default DataSource, JdbcTemplate, and TransactionManager, while using @Qualifier to inject non-primary data sources into specific repositories or services.
• Use Cases: Common in enterprise applications that require separating operational data from reporting/analytics, managing legacy system integrations, or implementing multi-tenant architectures.