Hibernate StatelessSession Upsert
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 Hibernate StatelessSession Upsert method works.
As I explained in this article, the UPSERT operation allows you to INSERT a record if there is no such record matching the filtering criteria or to UPDATE it in case the record exists.
While many relational database systems offer the standard MERGE command to execute the UPSERT command, the syntax may differ slightly from one database to the other. Therefore, it’s great that Hibernate provides a portable way to achieve this goal.
The best way to map multiple entities on the same table
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 map multiple entities on the same table.
There are several advantages to mapping multiple entities on the same database table:
- To avoid loading large columns (e.g., JSON)
- To avoid N+1 query issues for bidirectional
@OneToOneassociations
Before we start investigating the best way to map multiple entities on the same table, if you wonder why you even need to use one-to-one table relationships, then check out this article first.
Spring Load-Time Weaving
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 Spring load-time weaving works so that you can apply the Hibernate bytecode enhancement mechanism at runtime.
Traditionally, the bytecode enhancement mechanism is applied when the project is built using a Maven or Gradle plugin. For more details about the build-time approach, check out this article.
Index Selectivity
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 Index Selectivity works in relational database systems and why the database Optimizer might choose to avoid using an index if the number of matching records is large.
Index selectivity is inversely proportional to the number of index entries matched by a given value. So, a unique index has the highest selectivity because only a single entry can be matched by any given value.
On the other hand, if column values are skewed, then a column value matching a large number of table records is going to have a low selectivity.
Table partitioning 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 how we can implement a table partitioning solution when using Spring and Hibernate.
The goal of table partitioning is to split a large table into multiple smaller partition tables so that the associated table and index records can fit into the in-memory Buffer Pool, therefore allowing a more efficient seek or scan.
How to cascade DELETE unidirectional associations with Spring Data JPA
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 cascade DELETE the unidirectional associations with Spring Data JPA when we cannot rely on the CascadeType mechanism that propagates state transitions from parent to child entities.
How to batch INSERT statements with MySQL 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 how we can batch INSERT statements when using MySQL and Hibernate.
While Hibernate has long supported automated JDBC batch inserts, this feature doesn’t work when using the IDENTITY identifier generator strategy. Unfortunately, MySQL doesn’t support SEQUENCE objects, so using IDENTITY is the only reasonable option.
Therefore, I’m going to show you a technique you can use to get Hibernate batch INSERT statements for entities that use the IDENTITY generator.
