JDBC Profiling with VisualVM
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, we are going to see how we can do JDBC profiling using the VisualVM tool to find slow-running SQL queries or discover N+1 query issues.
Soft delete and JPA version property
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, we are going to see how we can implement a soft delete mechanism when the JPA entity features a version property.
If you are not using a version property for optimistic locking, then you can implement the soft delete strategy, as explained in this article.
How to customize the HibernateTypesContributor from Hypersistence Utils
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, we are going to see how to customize the HibernateTypesContributor from Hypersistence Utils so that we can disable all or filter out certain Types.
Spring Data Query By Example
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, we are going to see how the Spring Data JPA Query By Example (QBE) feature works, when you should use it, and what limitations it has.
While Spring Data JPA already provides a wide range of options to query data:
- query methods or the
@Queryannotation - Spring Data JPA Specification
- custom Repository query methods
The Spring Data Query By Example feature is meant to offer a way to decouple the data filtering logic from the query processing engine so that you can allow the data access layer clients to define the filtering criteria using a generic API that doesn’t depend on the JPA Criteria API.
How to fetch multiple to-many relationships with jOOQ MULTISET
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, we are going to see how we can fetch multiple to-many relationships with jOOQ MULTISET so that we avoid bumping into an unintentional Cartesian Product.
The approach taken by jOOQ is truly revolutionary since it offers a solution that allows you to fetch multiple to-many relationships using a single type-safe query.
The best way to use one-to-one table relationships
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, we are going to see what is the best way to use one-to-one table relationships.
I decided to write this article after reading this Tweet:
The goal of one-to-one table relationships is to separate data that doesn't change in sync. The separation provides better concurrency (less locking and more optimistic locking versions, better cache hits, and better data integrity as if the child association is optional, you…
— Vlad Mihalcea (@vlad_mihalcea) June 12, 2023
The best way to validate the DDL schema with Spring and Hibernate
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, we are going to see what is the best way to validate the DDL schema and the JPA entity mappings when using Spring and Hibernate.
I decided to write this article after reading this Tweet:
Hi Vlad, shouldn't we set the value of spring.jpa.hibernate.ddl-auto=validate so that we are checking that flyway generated tables and our entities are in sync??
— Raja Dilip Kolli (@rajadilipkolli) June 5, 2023
Cache synchronization using jOOQ and PostgreSQL functions
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, we are going to see how we can achieve cache synchronization with the help of jOOQ and PostgreSQL functions.
By using Change Data Capture, we can track how table records change over time and synchronize the application-level cache entries that were built from the table records in question.
