Carol McDonald
  • Female
  • Jacksonville, Florida
  • United States
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Carol McDonald's Discussions

Some Java Concurrency Tips

Started Sep 18, 2009

Java Enterprise Tech Tips: Locking and Concurrency in Java Persistence 2.0

Started Sep 14, 2009

Comparing Tomcat and Glassfish

Started Mar 6, 2009

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Profile Information

What are your main interests in software development?
Java, Web, Ajax, Java EE, Spring, Seam, JPA, Web Services
Do you have a website?
http://weblogs.java.net/blog/caroljmcdonald/
Anything else you'd like to add? Where do you live? (optional!)
Je parle Francais. Ich kann Deutsch.

Carol McDonald's Blog

movie recommendations with Spark machine learning

Posted on August 4, 2015 at 11:15am 0 Comments

Tutorial on Apache Spark, movie recommendations with machine learning 

This post discusses building a recommendation model from movie ratings using an iterative algorithm and parallel processing with Apache Spark MLlib.

https://dzone.com/links/parallel-and-iterative-processing-for-machine-lear.html

An Inside Look at the Components of a Recommendation Engine

Posted on April 13, 2015 at 9:14am 1 Comment

Recommendation engines help narrow your choices to those that best meet your particular needs.  In this post, we’re going to take a closer look at how all the different components of a recommendation engine work together. We’re going to use collaborative filtering on movie ratings data to recommend movies. The key components are a collaborative filtering algorithm in Apache Mahout to build and train a machine learning model,…

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screencast about MySQL for Developers

Posted on March 30, 2009 at 10:30am 0 Comments

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… Continue

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

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InfoQ Reading List

MySQL 9.6 Changes Foreign Key Constraints and Cascade Handling

MySQL is changing the way foreign key constraints and cascades are managed. Starting with MySQL 9.6, foreign key validation and cascade actions are handled by the SQL layer rather than the InnoDB storage engine. This will improve change tracking, replication accuracy, and data consistency, making MySQL more reliable for CDC pipelines, mixed-database environments, and analytics workloads.

By Renato Losio

Vercel Releases React Best Practices Skill with 40+ Performance Rules for AI Agents

Vercel has launched "react-best-practices," an open-source repository featuring 40+ performance optimization rules for React and Next.js apps. Tailored for AI coding agents yet valuable for developers, it categorizes rules based on impact, assisting in enhancing performance, bundle size, and architectural decisions.

By Daniel Curtis

Kubernetes Introduces Node Readiness Controller to Improve Pod Scheduling Reliability

The Kubernetes project recently announced a new core controller called the Node Readiness Controller, designed to enhance scheduling reliability and cluster health by making the API server’s view of node readiness more accurate.

By Craig Risi

Presentation: Platforms for Secure API Connectivity With Architecture as Code

Jim Gough discusses the transition from accidental architect to API program leader, explaining how to manage the complexity of secure API connectivity. He shares the Common Architecture Language Model (CALM), a framework designed to bridge the developer-security gap. By leveraging architecture patterns, engineering leaders can move from six-month review cycles to two-hour automated deployments.

By Jim Gough

Microsoft Open Sources Evals for Agent Interop Starter Kit to Benchmark Enterprise AI Agents

Microsoft's Evals for Agent Interop is an open-source starter kit that enables developers to evaluate AI agents in realistic work scenarios. It features curated scenarios, datasets, and an evaluation harness to assess agent performance across tools like email and calendars.

By Edin Kapić