Performance oriented Spring Data JPA & Hibernate by Maciej Walkowiak

Optimize yourSpring Data JPA and Hibernate performance with expert tips on query optimization, connection pooling, lazy loading, entity mapping, and more.

Key takeaways

Optimizing queries is crucial for performance, and Hibernate provides tools to achieve this.
Using JPQL instead of HQL can improve performance by reducing the number of queries.
Connection pooling is essential for managing database connections, and tools like Hikari CP can help optimize it.
Dynamic update can be used to update only the changed fields of an entity.
Entity graphs can be used to specify which associations to fetch.
Lazy loading can be used to improve performance by reducing the number of queries.
JPQL queries can be optimized by using fetch joins and batch updating.
N+1 problem can occur when fetching related entities, and can be avoided by using fetch joins and batch updating.
Versioning can be used to track changes to entities.
Hibernate provides tools for logging and debugging, such as logging and tracing tools.
Distributed tracing can be used to track and analyze queries and database connections.
Performance issues can be caused by poorly written queries, unclosed connections, and incorrect configuration.
Connection pooling can help improve performance by reusing connections and reducing overhead.
Entity mapping can be used to optimize queries and improve performance.
Spring Data JPA provides tools for simplifying database operations and improving performance.
Hibernate provides tools for optimizing queries and improving performance, such as entity graphs and dynamic update.
Lazy loading can be used to improve performance by reducing the number of queries.
Connection pooling can help improve performance by reusing connections and reducing overhead.

Performance oriented Spring Data JPA & Hibernate by Maciej Walkowiak

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