Chapter 9. Making Development Easier
In this chapter, we will look at how, depending on use cases and end goals, application development in Hadoop can be simplified using a number of abstractions and frameworks built on top of the Java APIs. In particular, we will learn about the following topics:
How the streaming API allows us to write MapReduce jobs using dynamic languages such as Python and Ruby
How frameworks such as Apache Crunch and Kite Morphlines allow us to express data transformation pipelines using higher-level abstractions
How Kite Data, a promising framework developed by Cloudera, provides us with the ability to apply design patterns and boilerplate to ease integration and interoperability of different components within the Hadoop ecosystem
