Firebird Query Tuning Techniques in Spring Boot

Optimizing queries in Firebird is key to faster Spring Boot applications. This guide shows practical tuning techniques you can apply right away.

1. Enable Query Logging

First, turn on SQL logging to see what Hibernate or JPA generates:

spring.jpa.show-sql=true
spring.jpa.properties.hibernate.format_sql=true

This helps identify slow or redundant queries directly in your console.

Firebird performs best when queries use indexed columns. Check your queries and create indexes for frequent filters or joins:

CREATE INDEX idx_employee_name ON employee(name);

Avoid over-indexing; it can slow down inserts and updates.

Keep JOIN operations simple and use explicit joins in your JPA queries:

@Query("SELECT e FROM Employee e JOIN e.department d WHERE d.name = :name")
List<Employee> findByDepartment(@Param("name") String name);

Ensure that joined columns are indexed for efficient lookups.

Never fetch unnecessary data. Always use pagination or projections when querying large tables:

Page<Employee> findAll(Pageable pageable);

This minimizes memory use and reduces database load.

For analytical or aggregated data, write optimized native SQL queries:

@Query(value = "SELECT dept_id, AVG(salary) FROM employee GROUP BY dept_id", nativeQuery = true)
List<Object[]> averageSalaryByDept();

Firebird executes raw SQL faster than complex ORM mappings for large datasets.

Set batch sizes and fetch strategies wisely:

spring.jpa.properties.hibernate.jdbc.batch_size=30
spring.jpa.properties.hibernate.default_batch_fetch_size=20

Batching reduces round trips between Spring Boot and Firebird, improving insert and fetch performance.

Use Firebird’s EXPLAIN PLAN to see how the engine executes your query:

SET PLAN ON;
SELECT * FROM employee WHERE department_id = 2;

Review the plan and adjust indexes or filters based on results.

Choose appropriate data types in Firebird tables. For example, use INTEGER instead of BIGINT when possible to save memory and disk I/O.

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