Leveraging Stack Traces for SQL Performance Analysis in Spring Boot Applications

1. Spring Boot

   1 210 79,411 10.0 Java

   Spring Boot helps you to create Spring-powered, production-grade applications and services with absolute minimum fuss.

   

   Performance optimization in Spring Boot applications often requires deep visibility into database interactions. While traditional logging provides basic SQL query information, it frequently lacks the crucial context of where these queries originate in your codebase. This is especially important with lazy loading of Hibernate entities, where queries can be triggered unexpectedly throughout the application lifecycle. This article demonstrates how to implement a sophisticated logging solution that captures SQL execution stack traces, enabling developers to quickly identify and resolve performance bottlenecks.

2. Stream

   getstream.io featured

   Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.

   

3. Logback

   2 23 3,193 8.7 Java

   The reliable, generic, fast and flexible logging framework for Java.

   

   The solution involves creating a custom Logback layout that captures and filters stack traces for SQL operations, providing immediate visibility into the execution path. This approach combines Spring Boot's conditional configuration with Logback's extensible logging framework.

4. kotlin

   3 229 52,013 10.0 Kotlin

   The Kotlin Programming Language.

   

   All code examples in this article are written in Kotlin, leveraging its concise syntax, null safety, and seamless Java interoperability. Kotlin's expressive language features make the implementation more readable and maintainable compared to traditional Java approaches, while providing full compatibility with the Spring Boot ecosystem.

5. Hibernate

   4 37 6,373 10.0 Java

   Idiomatic persistence for Java and relational databases

   

   Performance optimization in Spring Boot applications often requires deep visibility into database interactions. While traditional logging provides basic SQL query information, it frequently lacks the crucial context of where these queries originate in your codebase. This is especially important with lazy loading of Hibernate entities, where queries can be triggered unexpectedly throughout the application lifecycle. This article demonstrates how to implement a sophisticated logging solution that captures SQL execution stack traces, enabling developers to quickly identify and resolve performance bottlenecks.

Suggest a related project