Codetown
Codetown ::: a software developer's community
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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
Advance Your Socio-Technical Architecture Skills with InfoQ’s New Online Cohorts
Enhance your architectural leadership with InfoQ’s new online cohorts starting April 15, May 7, and June 10, 2026. Led by Luca Mezzalira, this 5-week program focuses on socio-technical skills like ADRs, platform engineering, and AI trade-offs. Senior practitioners can apply frameworks to live projects, earn ICSAET certification, and contribute to the InfoQ community.
By Ian RobinsMaking Retrospectives Effective with Small Concrete Actions and Rotating Facilitators
Teams can run regular retrospectives that focus on 1–2 concrete weekly actions to avoid complaint circles, Natan Žabkar Nordberg mentioned at QCon London. You can rotate facilitators to build ownership, with each one bringing their own unique perspective. He suggested framing bigger changes as 4–6 week experiments, then vote to keep, tweak, or revert, ensuring learning and continuous improvement.
By Ben LindersAWS Launches Strands Labs for Experimental AI Agent Projects
Amazon Web Services has introduced Strands Labs, a new GitHub organization created to host experimental projects related to agent-based AI development.
By Daniel DominguezClaude Opus 4.6 Introduces Adaptive Reasoning and Context Compaction for Long-Running Agents
Anthropic’s Claude Opus 4.6 introduces "Adaptive Thinking" and a "Compaction API" to solve context rot in long-running agents. The model supports a 1M token context window with 76% multi-needle retrieval accuracy. While leading benchmarks in agentic coding, independent tests show a 49% detection rate for binary backdoors, highlighting the gap between SOTA claims and production security.
By Steef-Jan WiggersRunning Ray at Scale on AKS
The Azure Kubernetes Service (AKS) team at Microsoft has shared guidance for running Anyscale's managed Ray service at scale. They focus on three key issues: GPU capacity limits, scattered ML storage, and problems with credential expiry.
By Claudio Masolo
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