A practical guide to designing, testing, and implementing complex MapReduce applications in ScalaAbout This Book
- Develop MapReduce applications using a functional development language in a lightweight, high-performance, and testable way
- Recognize the Scalding capabilities to communicate with external data stores and perform machine learning operations
- Full of illustrations and diagrams, practical examples, and tips for deeper understanding of MapReduce application development
Who This Book Is For
This book is for developers who are willing to discover how to effectively develop MapReduce applications. Prior knowledge of Hadoop or Scala is not required; however, investing some time on those topics would certainly be beneficial.
What You Will Learn
- Set up an environment to execute jobs in local and Hadoop mode
- Preview the complete Scalding API through examples and illustrations
- Learn about Scalding capabilities, testing, and pipelining jobs
- Understand the concepts of MapReduce patterns and the applications of its ecosystem
- Implement logfile analysis and ad-targeting applications using best practices
- Apply a test-driven development (TDD) methodology and structure Scalding applications in a modular and testable way
- Interact with external NoSQL and SQL data stores from Scalding
- Deploy, schedule, monitor, and maintain production systems
In Detail
Programming MapReduce with Scalding is a practical guide to setting up a development environment and implementing simple and complex MapReduce transformations in Scalding, using a test-driven development methodology and other best practices.
This book will first introduce you to how the Cascading framework allows for higher abstraction reasoning over MapReduce applications and then dive into how Scala DSL Scalding enables us to develop elegant and testable applications. It will then teach you how to test Scalding jobs and how to define specifications and behavior-driven development (BDD) with Scalding. This book will also demonstrate how to monitor and maintain cluster stability and efficiently access SQL, NoSQL, and search platforms.
Programming MapReduce with Scalding provides hands-on information starting from proof of concept applications and progressing to production-ready implementations.
Antonios Chalkiopoulos
Antonios Chalkiopoulos is a developer living in London and a professional working with Hadoop and Big Data technologies. He completed a number of complex MapReduce applications in Scalding into 40-plus production nodes HDFS Cluster. He is a contributor to Scalding and other open source projects, and he is interested in cloud technologies, NoSQL databases, distributed real-time computation systems, and machine learning. He was involved in a number of Big Data projects before discovering Scala and Scalding. Most of the content of this book comes from his experience and knowledge accumulated while working with a great team of engineers.
