Avoid the temptation to set a massive pool size. A small pool of tightly managed connections often outperforms a large pool because it reduces database context switching and disk contention. Use the formula:
Tracked by the entity manager; changes sync automatically.
Instead of fetching full entities with all their relationships (which are then managed by the persistence context), use to select only necessary columns. High-performance Java Persistence.pdf
Before we dissect the content, let's address the format. Why are developers constantly searching for the PDF version of this book?
What is the primary performance issue you are facing ()? Share public link Avoid the temptation to set a massive pool size
Choosing the wrong primary key generation strategy can destroy batch processing performance.
or Entity Graphs are used to resolve N+1 query issues. Instead of fetching full entities with all their
Before blaming Hibernate for slow queries, look at the underlying mechanism: JDBC. A significant portion of latency in Java persistence comes not from the query execution itself, but from the data transfer between the application and the database.
by Vlad Mihalcea is widely considered the definitive guide for Java developers looking to bridge the gap between their application code and the underlying relational database. While many developers treat persistence frameworks like Hibernate as a "black box," this book unravels their inner workings to prevent the common performance bottlenecks that plague enterprise applications. High-Performance Java Persistence - Vlad Mihalcea