Here is a screencast about MySQL for Developers

If you are a developer using MySQL, you should learn enough to take advantage of its strengths, because having an understanding of the database can help you develop better-performing applications. This session will talk about MySQL database design and SQL tuning for developers. Some topics include:

* MySQL Storage Engine Architecture
* Schema, the basic foundation of performance
* Think about performance when choosing Data Types
* Indexes and SQL tuning
* Understanding SQL Statements using EXPLAIN
* Scans and seeks
* Solving performance problems in your queries
* A Few Things to consider for JPA/Hibernate devlopers, Lazy loading and Optimistic locking


http://mediacast.sun.com/users/caroljmcdonald/media/mysqlproj.swf

You can download the slides here
https://techdayscode.dev.java.net/servlets/ProjectDocumentList?fold...

You can read more about this at
MySQL for Developers
GlassFish and MySQL, Part 4: Creating a RESTful Web Service and JavaFX Client
High Performance MySQL book
MySQL Pluggable Storage Engine Architecture
MySQL Storage Engine Architecture, Part 2: An In-Depth Look
Optimizing Queries with EXPLAIN
Java Persistence with Hibernate book
Jay Pipes blog
Colin Charles blog
mysql performance blog
Ronald Bradford blog
Taking JPA for a Test Drive
Pro EJB 3: Java Persistence API
Pro MySQL, Chapter 6: Benchmarking and Profiling

Views: 51

Comment

You need to be a member of Codetown to add comments!

Join Codetown

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

 

Enjoy the site? Support Codetown with your donation.



InfoQ Reading List

Pinterest Reduces Spark OOM Failures by 96% Through Auto Memory Retries

Pinterest Engineering cut Apache Spark out-of-memory failures by 96% using improved observability, configuration tuning, and automatic memory retries. Staged rollout, dashboards, and proactive memory adjustments stabilized data pipelines, reduced manual intervention, and lowered operational overhead across tens of thousands of daily jobs.

By Leela Kumili

Presentation: Duolingo's Kubernetes Leap

Franka Passing discusses the architectural shift of Duolingo’s 500+ backend services to Kubernetes. She explains the move toward GitOps with Argo CD, the transition to IPv6-only pods, and the "cellular architecture" used to isolate environments. She shares "reports from the trenches" on managing developer trust, navigating AWS rate limits, and productionizing early adopter services.

By Franka Passing

Article: A Better Alternative to Reducing CI Regression Test Suite Sizes

How can you focus in a sea of results from a large regression test suite? This article describes a stochastic approach that relies on some degree of redundancy in your CI regression test set. This approach does not guarantee you will catch every bug every time, but it gives you your best bet of not missing the subtle signatures of all the bugs uncovered by your CI regression test suite runs.

By James Bornefelt Westfall

Podcast: Context Engineering with Adi Polak

In this episode, Thomas Betts and Adi Polak talk about the need for context engineering when interacting with LLMs and designing agentic systems. Prompt engineering techniques work with a stateless approach, while context engineering allows AI systems to be stateful.

By Adi Polak

Dynamic Languages Faster and Cheaper in 13-Language Claude Code Benchmark

A 600-run benchmark by Ruby committer Yusuke Endoh tested Claude Code across 13 languages, implementing a simplified Git. Ruby, Python, and JavaScript were the fastest and cheapest, at $0.36- $0.39 per run. Statistically typed languages cost 1.4-2.6x more. Adding type checkers to dynamic languages imposed 1.6-3.2x slowdowns. Full dataset available on GitHub.

By Steef-Jan Wiggers

© 2026   Created by Michael Levin.   Powered by

Badges  |  Report an Issue  |  Terms of Service