Eli Collins overviews how to build new applications with Hadoop and how to integrate Hadoop with existing applications, providing an update on the state of Hadoop ecosystem, frameworks and APIs.
Dean Wampler supports using Functional Programming and its core operations to process large amounts of data, explaining why Java’s dominance in Hadoop is harming Big Data’s progress.
Alex Robbins introduces Cascalog, a Clojure library for writing declarative Hadoop jobs.
Hairong Kuang explains how Facebook uses HDFS to store and analyze over 100PB of user log data.
Nikita Ivanov shows adding real-time capabilities to Hadoop through a demo application streaming word counting on a 2-nodes cluster.
Kathleen Ting details 8 misconfigurations that can bring ZooKeeper down.
Costin Leau discusses Big Data, current available tools for dealing with it, and how Spring can be used to create Big Data pipelines.
Nathan Marz introduces Twitter Storm, outlining its architecture and use cases, and takes a look at future features to be made available.
Rob Lancaster explains the steps made by Orbitz in order to bridge the gap between their data in the data warehouse and the data in Hadoop.
Eli Collins introduces Hadoop: why it came about, the benefits it produces, its history, its architecture, use cases and applications.
Dhruba Borthakur discusses the different types of data used by Facebook and how they are stored, including graph data, semi-OLTP data, immutable data for pictures, and Hadoop/Hive for analytics.
Yaniv Rodenski introduces Hadoop, then running Hadoop on Azure and the available tools and frameworks.