Transactions and Concurrency Control
Index Selectivity
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Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
What if there were a tool that could automatically detect what caused performance issues in your JPA and Hibernate data access layer?
Wouldn’t it be awesome to have such a tool to watch your application and prevent performance issues during development, long before they affect production systems?
Well, 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 fixing performance issues in your production system on a Saturday night, you are better off using Hypersistence Optimizer to help you prevent those issues so that you can spend 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
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Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
What if there were a tool that could automatically detect what caused performance issues in your JPA and Hibernate data access layer?
Wouldn’t it be awesome to have such a tool to watch your application and prevent performance issues during development, long before they affect production systems?
Well, 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 fixing performance issues in your production system on a Saturday night, you are better off using Hypersistence Optimizer to help you prevent those issues so that you can spend 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
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Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
What if there were a tool that could automatically detect what caused performance issues in your JPA and Hibernate data access layer?
Wouldn’t it be awesome to have such a tool to watch your application and prevent performance issues during development, long before they affect production systems?
Well, 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 fixing performance issues in your production system on a Saturday night, you are better off using Hypersistence Optimizer to help you prevent those issues so that you can spend 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
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
What if there were a tool that could automatically detect what caused performance issues in your JPA and Hibernate data access layer?
Wouldn’t it be awesome to have such a tool to watch your application and prevent performance issues during development, long before they affect production systems?
Well, 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 fixing performance issues in your production system on a Saturday night, you are better off using Hypersistence Optimizer to help you prevent those issues so that you can spend 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.
The best way to use Spring Data JPA Stream methods
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Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
What if there were a tool that could automatically detect what caused performance issues in your JPA and Hibernate data access layer?
Wouldn’t it be awesome to have such a tool to watch your application and prevent performance issues during development, long before they affect production systems?
Well, 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 fixing performance issues in your production system on a Saturday night, you are better off using Hypersistence Optimizer to help you prevent those issues so that you can spend your time on the things that you love!
Introduction
In this article, we are going to see what is the best way to use Spring Data JPA Stream query methods.
When having to fetch a larger result set, the advantage of using a Java Stream is that the query result set could be fetched progressively instead of getting all the data at once.
Ten years of blogging
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Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
What if there were a tool that could automatically detect what caused performance issues in your JPA and Hibernate data access layer?
Wouldn’t it be awesome to have such a tool to watch your application and prevent performance issues during development, long before they affect production systems?
Well, 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 fixing performance issues in your production system on a Saturday night, you are better off using Hypersistence Optimizer to help you prevent those issues so that you can spend your time on the things that you love!
Ten years later!
Ten years ago today, I decided to start blogging and published this article about injecting a List of Spring beans using the @Autowired annotation.
How to find the source of an SQL query generated by Hibernate
Last modified:
Are you struggling with performance issues in your Spring, Jakarta EE, or Java EE application?
What if there were a tool that could automatically detect what caused performance issues in your JPA and Hibernate data access layer?
Wouldn’t it be awesome to have such a tool to watch your application and prevent performance issues during development, long before they affect production systems?
Well, 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 fixing performance issues in your production system on a Saturday night, you are better off using Hypersistence Optimizer to help you prevent those issues so that you can spend your time on the things that you love!
Introduction
In this article, we are going to see how we can find the source of an SQL query generated by Hibernate.
Knowing where a given SQL query originates from is very useful when trying to investigate performance issues caused by either long-running queries or queries that are executed excessively (e.g., N+1 query issues).