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: 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

Java Explores Carrier Classes to Extend Data-Oriented Programming Beyond Records

The OpenJDK Amber project has published a new design note proposing “carrier classes” and “carrier interfaces” to extend record-style data modeling to more Java types. The proposal preserves concise state descriptions, derived methods, and pattern matching, while relaxing structural constraints that limit records.

By A N M Bazlur Rahman

Vercel Introduces Skills.sh, an Open Ecosystem for Agent Commands

Vercel has released Skills.sh, an open-source tool designed to provide AI agents with a standardized way to execute reusable actions, or skills, through the command line.

By Daniel Dominguez

Agent Trace: Cursor Proposes an Open Specification for AI Code Attribution

Cursor has published Agent Trace, a draft open specification aimed at standardizing how AI-generated code is attributed in software projects. Released as a Request for Comments (RFC), the proposal defines a vendor-neutral format for recording AI contributions alongside human authorship in version-controlled codebases.

By Robert Krzaczyński

Article: From Alert Fatigue to Agent-Assisted Intelligent Observability

As systems grow, observability becomes harder to maintain and incidents harder to diagnose. Agentic observability layers AI on existing tools, starting in read-only mode to detect anomalies and summarize issues. Over time, agents add context, correlate signals, and automate low-risk tasks. This approach frees engineers to focus on analysis and judgment.

By Rohit Dhawan

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