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

OpenTofu 1.12 The Feature Terraform Never Shipped

The OpenTofu community released version 1.12.0 on May 14, 2026. This update isn’t a complete rewrite, but it does resolve some issues that infrastructure teams have faced for a while.

By Claudio Masolo

With Android CLI, Google is Making the Android Toolchain Agent-Friendly

Google introduced new Android development tools that enable building apps up to 3x faster by using AI agents, including a redesigned Android command-line interface (CLI), structured skills", and an integrated knowledge base. These tools are designed to support agent-driven workflows and are compatible with third-party agents such as Claude Code and Codex, in addition to Google Gemini.

By Sergio De Simone

Article: The Mathematics of Backlogs: Capacity Planning for Queue Recovery

Backlogs in distributed systems are arithmetic problems, not mysteries. This article provides practical formulas for calculating backlog drain time, sizing consumer headroom, and setting auto-scaling triggers. It covers key failure modes — retry amplification, metastable states, and cascading pipeline bottlenecks — plus when to shed load instead of draining.

By Rajesh Kumar Pandey

Designing a Multi-Agent System for Engineering Support at Scale: A Case Study From Grab

Grab’s Central Data Team built a multi-agent AI system to automate repetitive engineering support tasks across its data warehouse platform. The system separates investigation and enhancement workflows using specialized agents coordinated via an orchestration layer. It reduces operational load, improves resolution speed, and shifts engineering effort from firefighting to platform engineering work.

By Leela Kumili

Presentation: The AI Gateway: Scaling Centralized Inference Across Decentralized Teams

Meryem Arik discusses why modern engineering teams face "inference chaos" and how AI model gateways provide a critical control layer. She explains the balance between empowering decentralized teams to choose the best models and maintaining centralized oversight for security, RBAC, and cost control. Explore open-source solutions like LiteLLM and Doubleword to streamline your AI infra.

By Meryem Arik

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