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: Building a Global Caching System at Netflix: A Deep Dive to Global Replication

Netflix's EVCache system handles 400M ops/second across 22,000 servers, managing 14.3 PB of data. This infrastructure ensures global availability and resilience through intelligent data routing and flexible replication strategies. By implementing batch compression and switching to DNS-based discovery, Netflix optimizes efficiency, reduces bandwidth usage and significantly lowers operational costs.

By Sriram Rangarajan, Prudhviraj Karumanchi

Podcast: The Ongoing Challenges of DevSecOps Transformation and Improving Developer Experience

In this podcast Shane Hastie, Lead Editor for Culture & Methods, spoke to Adam Kentosh about the ongoing challenges organisations face in their DevOps, DevSecOps and digital transformation journeys.

By Adam Kentosh

Maybe WebAssembly Is the Next Evolutionary Step From Containers: Fermyon at InfoQ DevSummit Munich

During her presentation at the inaugural edition of the InfoQ Dev Summit Munich, Danielle Lancashire, principal software engineer at Fermyon and co-chair of the CNCF wasm-wg, hinted at WebAssembly containers as a greener alternative and a potential evolution from the current containerised approach to serverless computing.

By Olimpiu Pop

NVIDIA Unveils NVLM 1.0: Open-Source Multimodal LLM with Improved Text and Vision Capabilities

NVIDIA unveiled NVLM 1.0, an open-source multimodal large language model (LLM) that performs strongly on both vision-language and text-only tasks. NVLM 1.0 shows improvements in text-based tasks after multimodal training, standing out among current models. The model weights are now available on Hugging Face, with the training code set to be released shortly.

By Robert Krzaczyński

InfoQ Dev Summit Munich: How to Optimize Java for the 1BRC

Java applications passed the 1 Billion Row Challenge (1BRC) in 1.5 seconds. 1BRC creator Gunnar Morling detailed their optimizations at the InfoQ Dev Summit Munich 2024. General optimizations applicable to all Java applications cut the runtime from 290 seconds to 20 seconds. Getting to 1.5 seconds required niche optimizations that most Java applications should forego, except for possibly GraalVM.

By Karsten Silz

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