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

QCon SF: Database-Backed Workflow Orchestration Challenges Traditional Architecture

During QCon SF, Jeremy Edberg and Qian Li from DBOS presented a non-conventional architectural approach to workflow orchestration: treating PostgreSQL not just as a data store, but as the orchestration layer itself. Their talk addressed a persistent problem in distributed systems: workflows frequently fail, recovery mechanisms are complex, and visibility into workflow state remains challenging.

By Eran Stiller

AI-Generated Code Creates New Wave of Technical Debt, Report Finds

AI-generated code is “highly functional but systematically lacking in architectural judgment”, a new report from Ox Security has found. In a report released in late October called Army of Juniors: The AI Code Security Crisis, AI application security (AppSec) company Ox Security outlined 10 architecture and security anti-patterns that are commonly found in AI-generated code.

By Patrick Farry

CameraX 1.5 Brings Advanced Video Recording and Image Capture to Android

CameraX 1.5 introduces support for capturing slow-motion and high frame-rate videos as well as unprocessed, uncompressed still images. These capabilities are enabled by the new SessionConfig API, which streamlines camera setup and configuration.

By Sergio De Simone

First Keynote at QCon San Francisco 2025: Reducing Friction by Nicole Forsgren

At QCon SF 2025, Dr. Nicole Forsgren highlighted how AI accelerates code generation but reveals deployment bottlenecks, urging a strategic pivot to optimizing Developer Experience (DevEx). With 31% of developer time lost to friction, focusing on effective feedback loops, flow state, and cognitive load management is vital for competitive survival and retention.

By Steef-Jan Wiggers

New IBM Granite 4 Models to Reduce AI Costs with Inference-Efficient Hybrid Mamba-2 Architecture

IBM recently announced the Granite 4.0 family of small language models. The model family aims to deliver faster speeds and significantly lower operational costs at acceptable accuracy vs. larger models. Granite 4.0 features a new hybrid Mamba/transformer architecture that largely reduces memory requirements, enabling Granite to run on significantly cheaper GPUs and at significantly reduced costs.

By Bruno Couriol

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