Tag Archives: Java

@PrePersist and Friends: Five Lifecycle Callback Bugs You’ll Ship If You’re Not Careful

We had a callback that “audited every save” — except it silently skipped about half of them. The @PreUpdate on the AuditListener ran correctly for every web-layer save. It never ran for the nightly batch job. The batch used HQL bulk updates. Nobody remembered that bulk operations bypass the persistence context entirely, so lifecycle callbacks never fire for them. The audit log looked complete. It was missing six months of batch changes.

That is bug four in this list. Here are all five, each one a real failure mode with the code that produces it and the fix.

Technical Note: JPA vs. Hibernate Behavior

It is important to distinguish that all annotations discussed in this guide (like @PrePersist, @PostUpdate, etc.) are defined by the Jakarta Persistence API (JPA) specification. Hibernate 7 serves as the implementation provider. While the API is standard, specific behaviors such as dirty checking algorithms, the exact timing of the flush, and session state transitions are governed by Hibernate-specific logic.

The Problem: Fragmented Business Logic

In many legacy applications, developers scatter logic like password encryption, audit logging, and data normalization across various controllers and services.

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The Hibernate 7 Persistence Context: How Hibernate Tracks Your Entities (and Where It Gets Surprising)

Look at this Spring service. Eight lines, nothing exotic, no annotations missing as far as a junior reviewer can tell. Before reading on, predict what happens when something calls markActive(42) against a real database.

@Service
public class UserService {
    private final UserRepository userRepo;
    public UserService(UserRepository r) { this.userRepo = r; }

    public User markActive(Long id) {
        User u = userRepo.findById(id).orElseThrow();
        u.setStatus("ACTIVE");
        return u;
    }
}

If you said “an UPDATE statement fires”, you would be wrong. There is no @Transactional on the method, so Spring Data opens a session for the duration of findById, returns the entity, and closes the session. By the time u.setStatus("ACTIVE") runs, u is no longer managed. The mutation exists only in JVM memory. There is no flush, no dirty check, no UPDATE.

This is the kind of bug you can stare at for an hour, because the code is almost right. It would be right if Hibernate worked the way most people imagine it does. The actual mechanics are stranger and more interesting — and once you see them, a long list of mysterious behaviours suddenly make sense: phantom UPDATEs, missing UPDATEs, NonUniqueObjectException, LazyInitializationException, the JPQL query that fires SQL you didn’t expect.

This post is a deep-dive on the persistence context: the in-memory state machine that decides what gets written, when, and why.

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Bootstrapping EntityManager in Hibernate 7 (Jakarta Persistence 3.2) – XML vs Programmatic Guide

Are you struggling to bridge the gap between your Java objects and your relational database in the modern Jakarta EE era? If you’ve ever felt buried under boilerplate JDBC code or confused by the transition to Hibernate 7, you aren’t alone.

In modern Java development, bootstrapping EntityManager in Hibernate 7 is the foundational step for any robust data persistence layer. Hibernate 7 has fully embraced Jakarta Persistence 3.2, bringing stricter standards, better performance, and a move toward Java 17+ features. This version marks a significant milestone in the decoupling of Hibernate-specific logic from standard JPA interfaces.

TL;DR

  • 🚀 Requirements: Java 17+ and Jakarta Persistence 3.2 (complete jakarta.* namespace transition).
  • 🏗️ Architecture: EntityManagerFactory (EMF) is a thread-safe singleton; EntityManager (EM) is for short-lived units of work.
  • ⚙️ Configuration: Use XML (persistence.xml) for stability; use Programmatic (PersistenceConfiguration) for cloud-native/dynamic environments.
  • ⚠️ Critical Warning: Never create a new EntityManagerFactory per request. It leads to catastrophic Metaspace OOM errors.

The Problem: The Complexity of Manual Data Handling

Managing database connections manually is a developer’s nightmare. From opening connections and handling SQL exceptions to mapping result sets back into Java objects, the “traditional” JDBC way is error-prone and tedious. Without a properly bootstrapped EntityManager, your application lacks a unified way to manage entity lifecycles, leading to:

  • Memory Leaks: Connections that are never returned to the pool.
  • Data Inconsistency: Transactions that aren’t properly synchronized across operations.
  • Performance Bottlenecks: The infamous “N+1” query issues that arise when manual fetching isn’t optimized.
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Bootstrapping Hibernate 7: SessionFactory vs EntityManagerFactory vs Spring Boot Auto-Config — A Decision Guide

Most Spring Boot developers would struggle to answer the question: which Hibernate bootstrap path are you actually using? The answer is “the one Spring Boot chose for you”, which is the EntityManagerFactory path, built by HibernateJpaAutoConfiguration, wired to a HikariDataSource, reading from application.properties. You have never typed a single line of Hibernate bootstrap code.

That is fine for the common case. But when something breaks at startup — the wrong dialect is selected, HikariCP sizing is wrong, the schema validation fails — you need to know what is actually being configured and where. And for projects outside Spring Boot (command-line tools, framework libraries, Jakarta EE deployments), you need to choose a bootstrap path and implement it deliberately.

This post covers all three paths, when each makes sense, and the production failure that catches developers who autoconfig their way to production without understanding what they built.

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Hibernate 7 Hello World: A Working Project from Empty Folder to First Insert

Most Hibernate Hello World tutorials get you to a running INSERT in about 10 minutes. They also leave out three things that will bite you the moment you move past the trivial case.

First: the import packages. Hibernate 7 requires jakarta.persistence.*, not javax.persistence.*. Every tutorial written before 2022 uses the old namespace. If you copy the entity annotation from a pre-Hibernate 6 guide, the annotations will not be recognised and you will spend 30 minutes wondering why your table never appears.

Second: the persistence.xml location trap in Maven multi-module setups. The file belongs at src/main/resources/META-INF/persistence.xml in the module that contains your entity classes. Putting it in the wrong module produces a silent failure at bootstrap.

Third: the LazyInitializationException you will hit in your second example. The first example always works because you access everything inside one open session. The second example accesses an association after the session closes. This post calls that out explicitly so you see it coming.

Everything else is the standard step-by-step: Maven setup, entity, configuration, utility class, first insert. The code is complete and runs without modification on Java 17+.

Three Things This Guide Gets Right That Most Hello World Tutorials Skip

Hibernate 7 is not just a minor update; it’s optimized for modern environments like Jakarta EE 11 and Java 17/21/25+. It leverages the latest features of the JPA (Jakarta Persistence API) to provide a more type-safe and performant way to interact with your data.

High-Level Architecture Overview

Understanding the flow of data is crucial for mastering any ORM. Here is the architectural stack for this tutorial:

Java ApplicationHibernate SessionJPA Entity ManagerDialectDatabase (H2/MySQL)

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15 Common Problems During JUnit 5 to JUnit 6 Upgrade (And Proven Fixes to Get You Back on Track)

Upgrading your Java testing suite from JUnit 5 to JUnit 6? It’s a smart move—JUnit 6 brings a Java 17 baseline, cleaner APIs, unified versioning, and enhancements like improved CSV parsing with FastCSV. Released on September 30, 2025, this major update streamlines testing for modern Java projects, but it’s not without hurdles. If you’re searching for “JUnit 6 migration issues” or “breaking changes JUnit 5 to 6,” you’re in the right place.

As a seasoned Java developer who’s guided dozens of teams through framework upgrades, I’ve seen these pain points firsthand. In this post, we’ll dive into 15 common problems developers encounter during the JUnit 6 upgrade, complete with real-world explanations, code snippets, and step-by-step solutions. Whether you’re dealing with dependency clashes or sneaky API removals, these fixes will minimize downtime and keep your CI/CD pipeline humming.

By the end, you’ll have a migration checklist to tackle the upgrade confidently. Let’s jump in—your tests (and sanity) will thank you.


Why Upgrade to JUnit 6 Now?

Before we hit the issues, a quick note: JUnit 6 isn’t just a version bump. It mandates Java 17+ for better performance and security, deprecates legacy cruft, and aligns with Kotlin 2.2. Most JUnit 5 tests run unchanged, but ignoring these changes could lead to cryptic build failures. Pro tip: Start with a feature branch and use tools like OpenRewrite for automated refactors.

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JUnit 6 Deep Dive: What’s New, What Changed, and How to Migrate

Eight years after JUnit 5 shipped, the framework has a new major version. JUnit 6.0.0 released on September 30, 2025 — and unlike the painful JUnit 4 → 5 migration that rewrote the annotation model from scratch, this one is designed to be a calm, deliberate step forward. The current stable release is 6.0.3 (February 15, 2026), with 6.1.0 already in milestone preview.

JUnit 6 is not a revolution. It’s a maturation: a Java 17 baseline, unified versioning, first-class Kotlin coroutine support, null-safety annotations across the entire API, and a proper cancellation model for CI pipelines. If you’re already on JUnit 5.14 and Java 17+, the migration is mostly a version bump in your pom.xml. This guide covers what changed, what broke, and what the upgrade looks like in practice.

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