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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
Article: The Schema Proliferation Problem in Kafka and Flink Pipelines: How to Solve It
Schema proliferation builds slowly and gets expensive fast. One schema per event type feels right until there are ten tables, union queries spanning all of them, and a single field rename touching every schema. Discriminator-based schema consolidation collapses that to two tables, turning multi-table unions into a single query, while new variants are additive and don't break existing consumers.
By Spoorthi BasuPresentation: From Legacy to Sovereignty: Driving the Future of Insurance through Platform Engineering
Sergiu Petean discusses the strategic journey of evolving DevOps into platform engineering within heavily regulated enterprise environments. He explains how to maximize efficiency using dynamic reference architectures, align platform KPIs directly with board-level business goals, reduce cognitive load via custom team topologies, and maintain innovation sovereignty through open-source technology.
By Sergiu PeteanPodcast: Chasing Efficient Java Development: From 1BRC to Developing Hardwood AI Natively
Gunnar Morling, technologist at Confluent and Java Champion, shares his experiences with building high-performance applications in Java, especially in the data space. He shares insights from experiments with building durable execution engines, bootstrapping, and AI natively developing Apache Hardwood - a minimal dependencies Java parser for Apache Parquet.
By Gunnar MorlingGemma 4 Multi-Token Prediction Delivers Up to ~3x Faster Token Generation
Gemma 4 can be paired with multi-token prediction (MTP) drafters that use speculative decoding to generate multiple tokens in parallel, allowing the model to verify them in a single pass and achieve up to ~3× faster inference without quality loss.
By Sergio De SimoneNodeJS Proposes Built-In Virtual File System, Sparking Debate Over AI-Generated Contributions
Matteo Collina has proposed a Virtual File System (VFS) for Node.js core through the node:vfs module. The proposal includes about 19,000 lines of code and addresses common workflow challenges. While it has community support, concerns have arisen regarding the use of AI in its development, prompting debates about its implications for code verification and necessity in the Node.js ecosystem.
By Daniel Curtis
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