The book is structured as a journey, typically divided into logical parts that build upon each other:
hibernate.jdbc.batch_size=20 hibernate.order_inserts=true hibernate.order_updates=true Use code with caution. high-performance java persistence pdf 20
A common misconception is that adding more connections linearly increases database performance. In reality, too many concurrent connections lead to context switching and disk contention. The optimal pool size often aligns closely with the formula: The book is structured as a journey, typically
The journey to a high-performance data access layer begins with deep knowledge and ends with powerful, measurable results. Vlad Mihalcea's High-Performance Java Persistence is more than a book—it's an essential companion for any developer serious about their craft. The optimal pool size often aligns closely with
Keep database transactions as short as possible. Hold connections only when executing SQL commands.
Database connections are expensive to create, maintain, and tear down. Every connection requires physical network overhead, memory allocation on the database server, and thread synchronization.
Java developers primarily rely on the Java Persistence API (JPA) and Hibernate to interact with databases. While these object-relational mapping (ORM) frameworks accelerate development, they abstract away the underlying SQL. This abstraction can obscure the performance costs of daily operations. The Impedance Mismatch