Carol McDonald
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  • 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

Airbnb Implements Context-Aware Identity Model to Support Privacy-First Social Features

Airbnb has redesigned its identity system to support privacy-first social features in Experiences. The platform introduces context-specific profiles that separate global user identity from externally visible profiles, preventing cross-context linkage. The migration leveraged automated auditing, manual validation, and AI-assisted refactoring to enforce correct identity usage across services.

By Leela Kumili

JEP 533 Tightens Exception Handling in Java's Structured Concurrency for JDK 27

JEP 533, Structured Concurrency, has reached integrated status for JDK 27. It refines exception handling and type safety in its API, particularly focusing on exception flow with a new ExecutionException type. Changes include an updated Joiner interface and a new open overload for easier configuration. The steady evolution signals ongoing development as feedback shapes the API.

By A N M Bazlur Rahman

Presentation: What I Learned Building Multi-Agent Systems From Scratch

Paulo Arruda discusses Shopify’s evolution in AI adoption, moving from simple chat tools to a sophisticated swarm of specialized agents. He explains the transition from massive "all-in-one" prompts to lean, narrow-focused agent microservices that slash task times from hours to minutes. He also shares a future-looking hypothesis on using filesystem-based adapters to solve context bloat.

By Paulo Arruda

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

Grafana's Pyroscope 2.0 Makes Continuous Profiling Practical at Scale

Grafana Labs has launched Pyroscope 2.0, a rearchitected open-source continuous profiling database. This version improves storage costs, query performance, and operational complexity. Key changes include single write paths for profiles, stateless query processing, and enhanced capabilities for profiling data. It supports the OpenTelemetry Protocol, aligning with current trends in observability.

By Matt Saunders

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