The print version of High-Performance Java Persistence
One year after I published the first part of the High-Performance Java Persistence, I managed to publish the print version of the book. The book is printed on demand using Amazon CreateSpace, and it looks like as follows.
The best way to map a @OneToOne relationship with JPA and Hibernate
Introduction In this article, we are going to learn the best way to map a OneToOne association with JPA and Hibernate. While there are many ways you can map a one-to-one relationship with Hibernate, I’m going to demonstrate which mapping is the most efficient one from a database perspective.
14 High-Performance Java Persistence Tips
Introduction In this article, I’m going to show you various high-performance Java Persistence optimization tips that will help you get the most out of your data access layer. A high-performance data access layer requires a lot of knowledge about database internals, JDBC, JPA, Hibernate, and this post summarizes some of the most important techniques you can use to optimize your enterprise application. 1. SQL statement logging If you’re using a framework that generates statements on your behalf, you should always validate the effectiveness and efficiency of each executed statement. A testing-time assertion… Read More
High-Performance Java Persistence – Part Two
Another milestone has been reached The second part of High-Performance Java Persistence book is out. It’s been almost a year since I started writing this book, and seven months since I published the first part.
The Open Session In View Anti-Pattern
Introduction Open Session in View is an Anti-Pattern, and this post is going to demonstrate why it is so. First of all, let’s start with the Wikipedia definition of an Anti-Pattern: An anti-pattern (or antipattern) is a common response to a recurring problem that is usually ineffective and risks being highly counterproductive.
High-Performance Java Persistence – Chapter 16 – Caching
Part 2, Chapter 16 Every new chapter of my book is released right after it’s being completed, so the reader doesn’t have to wait for the whole part to be finished to get access to new material. Table of content This chapter explains how enterprise caching works, from database internal buffers, to application-level caching, and the second-level cache offered by Hibernate.
High-Performance Java Persistence – Chapter 15 – Fetching
Part 2, Chapter 15 Every new chapter of my book is released right after it’s being completed, so the reader doesn’t have to wait for the whole part to be finished to get access to new material. Table of content This chapter explains how fetching works in Hibernate.
High-Performance Java Persistence – Chapter 14 – Batching
Part 2, Chapter 14 Every new chapter of my book is released right after it’s being completed, so the reader doesn’t have to wait for the whole part to be finished to get access to new material. Table of content This chapter explains how batch updates work in Hibernate.
High-Performance Java Persistence – Chapter 13 – Flushing
Part 2, Chapter 13 Every new chapter of my book is released right after it’s being completed, so the reader doesn’t have to wait for the whole part to be finished to get access to new material. Table of content This chapter explains the inner-workings of the Hibernate Persistence Context implementation.
How to enable bytecode enhancement dirty checking in Hibernate
Introduction Hibernate runs the automatic dirty checking mechanism during flush-time, and any managed entity state change is translated into an UPDATE SQL statement. The default dirty checking mechanism uses Java reflection and goes through every property of every managed entity. If the Persistence Context has few entities, this process might go unnoticed, but, if we’re dealing with many entities or the entities have many properties (e.g. a legacy database Domain Model mapping), then the reflection-based dirty checking might have an associated performance impact.
