Preface
Requirements
Throughout this book, we will explore Cascading and related open source projects in the context of brief programming examples. Familiarity with Java programming is required. We’ll show additional code in Clojure, Scala, SQL, and R. The sample apps are all available in source code repositories on GitHub. These sample apps are intended to run on a laptop (Linux, Unix, and Mac OS X, but not Windows) using Apache Hadoop in standalone mode. Each example is built so that it will run efficiently with a large data set on a large cluster, but setting new world records on Hadoop isn’t our agenda. Our intent here is to introduce a new way of thinking about how Enterprise apps get designed. We will show how to get started with Cascading and discuss best practices for Enterprise data workflows.
Enterprise Data Workflows
Cascading provides an open source API for writing Enterprise-scale apps on top of Apache Hadoop and other Big Data frameworks. In production use now for five years (as of 2013Q1), Cascading apps run at hundreds of different companies and in several verticals, which include finance, retail, health care, and transportation. Case studies have been published about large deployments at Williams-Sonoma, Twitter, Etsy, Airbnb, Square, The Climate Corporation, Nokia, Factual, uSwitch, Trulia, Yieldbot, and the Harvard School of Public Health. Typical use cases for Cascading include large extract/transform/load (ETL) jobs, reporting, web crawlers, anti-fraud classifiers, ...
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