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

Article: Change as Metrics: Measuring System Reliability Through Change Delivery Signals

System changes are the primary driver of production incidents, making change-related metrics essential reliability signals. A minimal metric set of Change Lead Time, Change Success Rate, and Incident Leakage Rate assesses delivery efficiency and reliability, supported by actionable technical metrics and an event-centric data warehouse for unified change observability.

By Peihao Yuan

Microsoft Launches MCP C# SDK v1.0, Bringing Full Support for Latest Protocol Specification

Microsoft has released version 1.0 of the official MCP C# SDK, bringing full support for the 2025-11-25 MCP Specification. The release introduces enhanced authorization flows, icon support for tools and resources, incremental scope consent, URL mode elicitation, tool calling in sampling, and improved handling of long-running HTTP requests.

By Almir Vuk

Rspress 2.0: AI-Native Documentation, Faster Startup and a Redesigned Theme

Rspress 2.0 has launched with a revamped theme, boosted performance, and innovative AI features, transforming developer documentation. With enhanced build speeds and a new Static Site Generation to Markdown (SSG-MD) capability, Rspress empowers developers with customizable styling options while simplifying content management. Experience superior documentation with lightning-fast efficiency!

By Daniel Curtis

Google BigQuery Previews Cross-Region SQL Queries for Distributed Data

Google Cloud has recently announced the preview of a global queries feature for BigQuery. The new option lets developers run SQL queries across data stored in different geographic regions without first moving or copying the data to aggregate the results.

By Renato Losio

Scaling Human Judgment: How Dropbox Uses LLMs to Improve Labeling for RAG Systems

To improve the relevance of responses produced by Dropbox Dash, Dropbox engineers began using LLMs to augment human labelling, which plays a crucial role in identifying the documents that should be used to generate the responses. Their approach offers useful insights for any system built on retrieval-augmented generation (RAG).

By Sergio De Simone

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