Carol McDonald
  • Female
  • Jacksonville, Florida
  • United States
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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

Presentation: Speed at Scale: Optimizing the Largest CX Platform Out There

Matheus Albuquerque shares strategies for optimizing a massive CX platform, moving from React 15 and Webpack 1 to modern standards. He discusses using AST-based codemods for large-scale migrations, implementing differential serving with module/nomodule, and leveraging Preact to shrink footprints. He explains how to balance cutting-edge performance with strict legacy browser constraints.

By Matheus Albuquerque

Article: Lakehouse Tower of Babel: Handling Identifier Resolution Rules Across Database Engines

Lakehouse architectures enable multiple engines to operate on shared data using open table formats such as Apache Iceberg. However, differences in SQL identifier resolution and catalog naming rules create interoperability failures. This article examines these behaviors and explains why enforcing consistent naming conventions and cross-engine validation is critical.

By Maninder Parmar

AWS Launches Agent Registry in Preview to Govern AI Agent Sprawl Across Enterprises

AWS released Agent Registry in preview as part of Amazon Bedrock AgentCore, providing a centralized catalog for discovering, governing, and reusing AI agents, tools, and MCP servers across organizations. The registry indexes agents regardless of where they run and supports both MCP and A2A protocols natively. Microsoft, Google Cloud, and the ACP Registry offer competing solutions.

By Steef-Jan Wiggers

AWS Introduces S3 Files, Bringing File System Access to S3 Buckets

AWS recently introduced S3 Files, which lets users mount an Amazon S3 bucket and access its data through a standard file system interface. Applications can read and write files using standard file operations, while the system automatically translates them into S3 requests, allowing compute services to work directly with data stored in S3.

By Renato Losio

Google Opens Gemma 4 Under Apache 2.0 with Multimodal and Agentic Capabilities

Google has announced the release of Gemma 4, a series of open-weight AI models, including variants with 2B, 4B, 26B, and 31B parameters, under the Apache 2.0 license. Key features include enhanced video and image processing, audio input on smaller models, and extended context windows up to 256K tokens.

By Hien Luu

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