-
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.
-
CQRS for Enterprise Web Development: What's in it for Business?
With a focus on the business case for a CQRS architecture, this article covers the core concepts of Command Query Responsibility Segregation, and contrasts them with a common, n-tier architecture. Benefits including scalability and maintainability are highlighted, which can reduce the total cost of ownership, and lead to an improved return on investment when choosing a CQRS architecture.
-
Java 9, OSGi and the Future of Modularity
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.
Polymorphism of MVC-esque Web Architecture: Classification
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.
Pros and Cons of Cross-Platform Mobile App Development
One of the most challenging situations for app developers is whether to develop a native mobile app or go for cross-platform. This article discussed the pros and cons of cross-platform development. 6
Spark GraphX in Action Book Review and Interview
InfoQ spoke with authors of Spark GraphX in Action book, Apache Spark framework and what's coming up in the area of graph data processing and analytics.
Two Mistakes You Need to Avoid When Integrating Services
Often enterprises assume adopting patterns like ESB help in developing with services. However, hidden challenges with these patterns can present dangers which go unnoticed until the system is live.
Continuous Delivery Coding Patterns: Latent-to-Live Code & Forward Compatible Interim Versions
Learn two novel practices for continuous delivery to increase speed and reliability of software development and reduce risks: Latent-to-live code pattern and Forward compatible interim versions.
Technical Practices as a Hack on Consciousness: Why to Hack Yourself
Software developers can raise their consciousness through the use of disciplined technical practices. A knowledgeable developer can influence an ever-increasing portion of the world.
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
Christine Doig on Data Science as a Team Discipline
Christine Doig spoke at OSCON Conference about data science as a team discipline and how to navigate data science Python ecosystem. InfoQ spoke with Christine about challenges of data science teams.
Virtual Panel: Current State of NoSQL Databases
NoSQL databases have been around for several years and have become a preferred choice for managing unstructured data. InfoQ spoke with four panelists about the current state of NoSQL databases. 1
