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How do PostgreSQL advisory locks work
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
Imagine having a tool that could automatically detect performance issues in your JPA and Hibernate data access layer long before pushing a problematic change into production!
With the widespread adoption of AI agents generating code in a heartbeat, having such a tool that can watch your back and prevent performance issues during development, long before they affect production systems, can save your company a lot of money and make you a hero!
Hypersistence Optimizer is that tool, and it works with Spring Boot, Spring Framework, Jakarta EE, Java EE, Quarkus, Micronaut, or Play Framework.
So, rather than allowing performance issues to annoy your customers, you are better off preventing those issues using Hypersistence Optimizer and enjoying spending your time on the things that you love!
Introduction
PostgreSQL, like many modern RDBMS, offers both MVCC (Multi-Version Concurrency Control) and explicit pessimistic locking for various use cases when you want a custom concurrency control mechanism.
However, PostgreSQL also offers advisory locks which are very convenient to implement application-level concurrency control patterns. In this article, we are going to explain how PostgreSQL advisory locks work and how you should use them.
How to get started with CockroachDB
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
Imagine having a tool that could automatically detect performance issues in your JPA and Hibernate data access layer long before pushing a problematic change into production!
With the widespread adoption of AI agents generating code in a heartbeat, having such a tool that can watch your back and prevent performance issues during development, long before they affect production systems, can save your company a lot of money and make you a hero!
Hypersistence Optimizer is that tool, and it works with Spring Boot, Spring Framework, Jakarta EE, Java EE, Quarkus, Micronaut, or Play Framework.
So, rather than allowing performance issues to annoy your customers, you are better off preventing those issues using Hypersistence Optimizer and enjoying spending your time on the things that you love!
Introduction
CockroachDB is a really interesting database system, getting the best of both RDBMS and NoSQL. It’s been developed by former Google developers, and it’s inspired by Google Spanner. However, unlike Google Spanner, which is offered as a service in Google Cloud, CockroachDB is an open-source database that can be installed on premise.
Also, CockroackDB allows you to use the PostgreSQL drivers as opposed to Spanner which only supports the gRPC protocol. So, you can practically reuse all the frameworks that have emerged in the Java ecosystem like connection pools, monitoring proxies (e.g. FlexyPool) or data access frameworks (e.g. Hibernate).
Unlike a typical RDBMS, CockroachDB is designed to be globally distributed and strongly resilient to disasters, hence its very unusual name. But what’s really exciting about CockroachDB is its non-locking timestamp ordering concurrency control mechanism which allows CockroachDB to run in Serializable isolation level, even if the database is massively distributed. Intriguing, right?
Why you should use the Hibernate ResultTransformer to customize result set mappings
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
Imagine having a tool that could automatically detect performance issues in your JPA and Hibernate data access layer long before pushing a problematic change into production!
With the widespread adoption of AI agents generating code in a heartbeat, having such a tool that can watch your back and prevent performance issues during development, long before they affect production systems, can save your company a lot of money and make you a hero!
Hypersistence Optimizer is that tool, and it works with Spring Boot, Spring Framework, Jakarta EE, Java EE, Quarkus, Micronaut, or Play Framework.
So, rather than allowing performance issues to annoy your customers, you are better off preventing those issues using Hypersistence Optimizer and enjoying spending your time on the things that you love!
Introduction
JPA queries allow you to fetch either entities or DTO projections. However, sometimes you want a combined result set as illustrated in this Hibernate forum question.
The best way to map a @OneToMany relationship with JPA and Hibernate
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
Imagine having a tool that could automatically detect performance issues in your JPA and Hibernate data access layer long before pushing a problematic change into production!
With the widespread adoption of AI agents generating code in a heartbeat, having such a tool that can watch your back and prevent performance issues during development, long before they affect production systems, can save your company a lot of money and make you a hero!
Hypersistence Optimizer is that tool, and it works with Spring Boot, Spring Framework, Jakarta EE, Java EE, Quarkus, Micronaut, or Play Framework.
So, rather than allowing performance issues to annoy your customers, you are better off preventing those issues using Hypersistence Optimizer and enjoying spending your time on the things that you love!
Introduction
While adding a @OneToMany relationship is very easy with JPA and Hibernate, knowing the right way to map such an association so that it generates very efficient SQL statements is definitely not a trivial thing to do.
In a relational database system, a one-to-many association links two tables based on a Foreign Key column so that the child table record references the Primary Key of the parent table row.
As straightforward as it might be in a relational database, when it comes to JPA, the one-to-many database association can be represented either through a @ManyToOne or a @OneToMany association since the OOP association can be either unidirectional or bidirectional.
The @ManyToOne annotation allows you to map the Foreign Key column in the child entity mapping so that the child has an entity object reference to its parent entity. This is the most natural way of mapping a database one-to-many database association, and, usually, the most efficient alternative too.
For convenience, to take advantage of the entity state transitions and the dirty checking mechanism, many developers choose to map the child entities as a collection in the parent object, and, for this purpose, JPA offers the @OneToMany annotation.
As I explained in my book, many times, you are better off replacing collections with a query, which is much more flexible in terms of fetching performance. However, there are times when mapping a collection is the right thing to do, and then you have two choices:
- a unidirectional
@OneToManyassociation - a bidirectional
@OneToManyassociation
The bidirectional association requires the child entity mapping to provide a @ManyToOne annotation, which is responsible for controlling the association.
On the other hand, the unidirectional @OneToMany association is simpler since it’s just the parent-side that defines the relationship. In this article, I’m going to explain the caveats of @OneToMany associations, and how you can overcome them.
There are many ways to map the @OneToMany association. We can use a List or a Set. We can also define the @JoinColumn annotation too. So, let’s see how all this works.
How to find which statement failed in a JDBC Batch Update
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
Imagine having a tool that could automatically detect performance issues in your JPA and Hibernate data access layer long before pushing a problematic change into production!
With the widespread adoption of AI agents generating code in a heartbeat, having such a tool that can watch your back and prevent performance issues during development, long before they affect production systems, can save your company a lot of money and make you a hero!
Hypersistence Optimizer is that tool, and it works with Spring Boot, Spring Framework, Jakarta EE, Java EE, Quarkus, Micronaut, or Play Framework.
So, rather than allowing performance issues to annoy your customers, you are better off preventing those issues using Hypersistence Optimizer and enjoying spending your time on the things that you love!
Introduction
Yesterday, my Danish friend, Flemming Harms, asked my a very interesting question related to when a JDBC batch update fails.
Basically, considering we are going to group several DML statements in a batch, we need a way to tell which statement is the cause of the failure. This post is going to answer this question in more detail.
The best way to soft delete with Hibernate
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
Imagine having a tool that could automatically detect performance issues in your JPA and Hibernate data access layer long before pushing a problematic change into production!
With the widespread adoption of AI agents generating code in a heartbeat, having such a tool that can watch your back and prevent performance issues during development, long before they affect production systems, can save your company a lot of money and make you a hero!
Hypersistence Optimizer is that tool, and it works with Spring Boot, Spring Framework, Jakarta EE, Java EE, Quarkus, Micronaut, or Play Framework.
So, rather than allowing performance issues to annoy your customers, you are better off preventing those issues using Hypersistence Optimizer and enjoying spending your time on the things that you love!
Introduction
Each database application is unique. While most of the time, deleting a record is the best approach, there are times when the application requirements demand that database records should never be physically deleted.
So who uses this technique?
For instance, StackOverflow does it for all Posts (e.g. Questions and Answers). The StackOverflow Posts table has a ClosedDate column which acts as a soft delete mechanism since it hides an Answer for all users who have less than 10k reputation.
If you’re using Oracle, you can take advantage of its Flashback capabilities, so you don’t need to change your application code to offer such a functionality. Another option is to use the SQL Server Temporal Table feature.
However, not all relational database systems support Flashback queries, or they allow you to recover a certain record without having to restore from a database backup. In this case, Hibernate allows you to simplify the implementation of soft deletes, and this article is going to explain the best way to implement the logical deletion mechanism.
If your entities are using the optimistic locking
@Versionproperty, then check out this article instead to see how you have to map your entities to include theversionproperty as well.
How does MVCC (Multi-Version Concurrency Control) work
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
Imagine having a tool that could automatically detect performance issues in your JPA and Hibernate data access layer long before pushing a problematic change into production!
With the widespread adoption of AI agents generating code in a heartbeat, having such a tool that can watch your back and prevent performance issues during development, long before they affect production systems, can save your company a lot of money and make you a hero!
Hypersistence Optimizer is that tool, and it works with Spring Boot, Spring Framework, Jakarta EE, Java EE, Quarkus, Micronaut, or Play Framework.
So, rather than allowing performance issues to annoy your customers, you are better off preventing those issues using Hypersistence Optimizer and enjoying spending your time on the things that you love!
Introduction
In this article, I’m going to explain how the MVCC (Multi-Version Concurrency Control) mechanism works using PostgreSQL as a reference implementation.
In Concurrency Control theory, there are two ways you can deal with conflicts:
- You can avoid them, by employing a pessimistic locking mechanism (e.g. Read/Write locks, Two-Phase Locking)
- You can allow conflicts to occur, but you need to detect them using an optimistic locking mechanism (e.g. logical clock, MVCC)
Because MVCC (Multi-Version Concurrency Control) is such a prevalent Concurrency Control technique (not only in relational database systems, in this article, I’m going to explain how it works.
How to encrypt and decrypt data with Hibernate
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
Imagine having a tool that could automatically detect performance issues in your JPA and Hibernate data access layer long before pushing a problematic change into production!
With the widespread adoption of AI agents generating code in a heartbeat, having such a tool that can watch your back and prevent performance issues during development, long before they affect production systems, can save your company a lot of money and make you a hero!
Hypersistence Optimizer is that tool, and it works with Spring Boot, Spring Framework, Jakarta EE, Java EE, Quarkus, Micronaut, or Play Framework.
So, rather than allowing performance issues to annoy your customers, you are better off preventing those issues using Hypersistence Optimizer and enjoying spending your time on the things that you love!
Introduction
Today, one of my Twitter followers sent me the following StackOverflow question, and, while answering it, I realized that it definitely deserves a post of its own.
In this post, I will explain how you can encrypt and decrypt data with Hibernate.