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AI, ML & Data Engineering

Big Data Processing with Apache Spark - Part 5: Spark ML Data Pipelines

With support for Machine Learning data pipelines, Apache Spark framework is a great choice for building a unified use case that combines ETL, batch analytics, streaming data analysis, and machine learning. In this fifth installment of Apache Spark article series, author Srini Penchikala discusses Spark ML package and how to use it to create and manage machine learning data pipelines.

Srini Penchikala
on Sep 24, 2016
Java

Java 9, OSGi and the Future of Modularity (Part 1)

The flagship feature of Java 9 will be the new Java Platform Module System (JPMS). Given the maturity of OSGi there were technical, political and commercial reasons why another Java module system will soon exist. In this article we compare the two from a technical perspective and see how JPMS and OSGi can work together.

Kai Hackbarth Neil Bartlett
on Sep 22, 2016
Web Development

Polymorphism of MVC-esque Web Architecture: Classification

The MVC architecture has a long and storied history, from its early days in the Smalltalk community to its modern implementation in JavaScript frameworks. In this article, Brent Chen explains the history of the MVC architecture and its different forms in modern applications, both on the client and on the server.

Brent Chen
on Sep 15, 2016
Mobile

Pros and Cons of Cross-Platform Mobile App Development

The world has gone mobile. One of the most challenging situations for app developers is whether to develop a native mobile app or go for cross-platform. This article discusses the pros and cons of cross-platform mobile app development.

Ritesh Patil
on Sep 13, 2016
AI, ML & Data Engineering

Spark GraphX in Action Book Review and Interview

“Spark GraphX in Action” book from Manning Publications, authored by Michael Malak and Robin East, provides a tutorial based coverage of Spark GraphX, the graph data processing library from Apache Spark framework. InfoQ spoke with authors about the book and Spark GraphX library as well as overall Spark framework and what's coming up in the area of graph data processing and analytics.

Srini Penchikala
on Sep 12, 2016
.NET

Designing with Exceptions in .NET

Exceptions are an integral part of working with .NET, but far too many developers don’t think about them from an API design perspective. Most of their work begins and ends with knowing which exceptions they need to catch and which should be allowed to hit the global logger. You can significantly reduce the time it takes to correct bugs if you design the API to use exceptions correctly.

Jonathan Allen
on Sep 09, 2016
Cloud

Introduction to SQL Server Containers

Containers are just around the corner for the Windows community, and this article takes a closer look at using SQL Server containers. The author discusses the value, use cases, and means for taking advantage of SQL Server containers today.

Paul Stanton
on Sep 08, 2016
Architecture & Design

Two Mistakes You Need to Avoid When Integrating Services

With SOA, businesses moved from monolithic applications to heterogeneous designs by decomposing functionality into services. However, architects must be careful when integrating services. Often enterprises assume adopting patterns like ESB can help. Unfortunately, there are hidden challenges with these patterns. The danger is they go unnoticed during development but surface when a system is live.

Pamod Sylvester
on Sep 07, 2016
AI, ML & Data Engineering

Book Review: Cathy O’Neil’s Weapons of Math Destruction

“Big Data has plenty of evangelists, but I’m not one of them,” writes Cathy O’Neil, a blogger (mathsbabe.org) and former quantitative analyst at the hedge fund DE Shaw who became sufficiently disillusioned with her hedge fund modelling that she joined the Occupy movement.

Charles Humble
on Sep 06, 2016
Culture & Methods

Technical Practices as a Hack on Consciousness: Why to Hack Yourself

Software technical practices are usually adopted as a means of creating better products. These practices can create and maintain a healthy human system. Technical practices raise the consciousness of individuals and the team as a whole. Technical practices hack consciousness giving us a quick, deep chute into depths of connection that improve our selves, our products, and our world.

Matthew Plavcan Jean Richardson
on Sep 01, 2016
Java

Using Templates to Transform Web Service Results into Markup

The HTTP-RPC open-source Java framework returns results in JSON by default, but can use the CTemplate system to respond with custom markup. In this article, Greg Brown shows how simple annotations can be used to automatically respond to a web service in any markup (HTML, XML, CSV, etc.).

Greg Brown
on Aug 31, 2016
AI, ML & Data Engineering

Chris Fregly on the PANCAKE STACK Workshop and Data Pipelines

InfoQ Interviews Chris Fregly, organizer for the 4000+ member Advanced Spark and TensorFlow Meetup about the PANCAKE STACK workshop, Spark and building data pipelines for a machine learning pipeline

Dylan Raithel
on Aug 29, 2016

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