Preface

Big data is the new "must have" of this century. Suddenly, everyone wants to manage huge amounts of data and find patterns in it, which they did not see before. The problem, however, is that big data is not one, but a whole slew of technologies, which work together to produce the desired outcome. New technologies are emerging, and existing ones are evolving very quickly. The design and development of big data systems is very complex, with an incredibly steep learning curve and not a whole lot of prior experience and best practices to rely on. This is where Cascading comes in. Cascading sits on top of the core big data frameworks and makes design and development of big data applications intuitive and fun! Cascading significantly simplifies and streamlines application development, job creation, and job scheduling. Cascading is an open source software, and many large organizations prefer to use it to manage their big data systems over more complicated solutions, such as MapReduce.

We discovered Cascading after our applications started to get to the level of complexity when pure MapReduce turned into a blood-pressure-raising nightmare. Needless to say, we fell in love with Cascading. Now, we train other developers on it, and evangelize it every chance we get. So, this is how our book came about. Our vision was to provide a book to the Cascading user community that will help them accelerate the development of complex, workflow-based Cascading applications, while still keeping their sanity intact so that they can enjoy life.

This book will teach you how to quickly develop practical Cascading applications, starting with the basics and gradually progressing into more complex topics. We start with a look "under the hood", how Cascading relates to core big data technologies, such as Hadoop MapReduce, and future emerging technologies, such as Tez, Spark, Storm, and others. Having gained an understanding of underlying technologies, we follow with a comprehensive introduction to the Cascading paradigm and components using well-tested code examples that go beyond the ones in the open domain that exist today. Throughout this book, you will receive expert advice on how to use the portions of a product that are undocumented or have limited documentation. To deepen your knowledge and experience with Cascading, you will work with a real-life case study using Natural Language Processing to perform text analysis and search large volumes of unstructured text. We conclude with a look to the future, and how Cascading will soon run on additional big data fabrics, such as Spark and Tez.

Cascading has rapidly gained popularity, and obtaining development skills in this product is a very marketable feature for a big data professional. With in-depth instructions and hands-on practical approaches, Learning Cascading will ensure your mastery of Cascading.