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Carol McDonald
- Female
- Jacksonville, Florida
- United States
- Blog Posts (3)
- Discussions (4)
- Events
- Groups (9)
- Photos
- Photo Albums
- Videos
Carol McDonald's Groups
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Community Corral
23 members
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iPhone Development
40 members
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Database SIG
13 members
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JEE Town
28 members
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Spring Town
47 members
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
Gifts Received
Carol McDonald has not received any gifts yet
Carol McDonald's Page
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 1 Like
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 0 Likes
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,…
Continuescreencast about MySQL for Developers
Posted on March 30, 2009 at 10:30am 0 Comments 0 Likes
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
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.
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
OpenCode: an Open-source AI Coding Agent Competing with Claude Code and Copilot
Open-source AI coding tool OpenCode features a native terminal-based UI, multi-session support, and compatibility with over 75 models, including Claude, OpenAI, Gemini, and local models. In addition to its CLI tool, OpenCode is also available as a desktop app and and an IDE extension for VS Code, Cursor, and other tools.
By Sergio De SimoneGetting Feedback from Test-Driven Development and Testing in Production
Teams rely on strong unit and integration tests instead of end-to-end tests. Using TDD, pair programming, and good design, they ship small changes often, test in production for real feedback, and use feature toggles to reduce risk, Ola Hast and Asgaut Mjølne Söderbom mentioned in their talk about continuous delivery with pair programming.
By Ben LindersGoogle Pushes for gRPC Support in Model Context Protocol
Google Cloud is bridging a critical gap for enterprises by introducing a gRPC transport package for the Model Context Protocol (MCP), enhancing integration for businesses already using gRPC. This game-changer reduces development friction, ensuring AI agents seamlessly connect with existing services while boosting performance and efficiency. Join the evolving landscape of AI integration!
By Steef-Jan WiggersLinkedIn Re-Architects Service Discovery: Replacing Zookeeper with Kafka and xDS at Scale
LinkedIn's engineering team successfully upgraded its legacy ZooKeeper service discovery platform to enhance scalability and performance. By leveraging Apache Kafka and the xDS protocol, the new architecture enables eventual consistency, supports multiple languages, and allows migration without downtime. Post-upgrade, latency vastly improved, facilitating hundreds of thousands of app instances.
By Patrick FarryPresentation: Beyond the Warehouse: Why BigQuery Alone Won’t Solve Your Data Problems
Sarah Usher discusses the architectural "breaking point" where warehouses like BigQuery struggle with latency and cost. She explains the necessity of a conceptual data lifecycle (Raw, Curated, Use Case) to regain control over lineage and innovation. She shares practical strategies to design a single source of truth that empowers both ML teams and analytics without bottlenecking scale.
By Sarah Usher
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