Hadoop is hard. There’s just no way around that. Setting up and running a cluster is hard, and so is developing applications that make sense of, and create value from, big data. What Hadoop really ...

The Apache Hadoop framework consists of three major components: HDFS – HDFS follows a master/slave architecture. Each HDFS cluster has a solitary NameNode that serves as a master server and a number ...

Figure 1. YARN-Based Architecture of Hadoop 2 Refactoring of resource management from the programming model of MapReduce makes Hadoop clusters more generic. Under YARN, MapReduce is one type of ...

Yahoo’s main internal cluster for research, user data, production workloads across its many brands and services (search, ad delivery, Flickr, email), and now deep learning is all based on a mature ...

Hadoop’s distributed architecture creates an environment that is highly vulnerable to attack at multiple points, as opposed to the centralized repositories that are monolithic and easier to secure.

This Spark+MPI architecture enables CaffeOnSpark to achieve similar performance as dedicated deep learning clusters. The Tesla K80s (four per node) and some purpose-built GPU servers sit in the same ...

A technology like Hadoop alone doesn’t deliver the business benefits promised by big data. For big data to become more than just promise we’ll need advances in the skill sets of IT professionals, ...

Hortonworks is unveiling the Open Hybrid Architecture initiative for transforming Hadoop into a cloud-native platform, and as part of it, has announced partnerships with IBM and Red Hat to make it ...

Storm, a top-level Apache project, is a Java framework designed to help programmers write real-time applications that run on Hadoop clusters. Designed at Twitter, Storm excels at processing high ...