Summary
In this chapter, we used the same dataset to present two completely different use cases. For each use case, we explored the data and then designed and implemented data-processing applications in Scalding. We also looked at how an abstract pipelining language (Scalding) is translated in MapReduce phases.
We also introduced techniques such as bucketing and windowed calculations through a solution to a problem. The expressiveness of the language allows us to implement even complex use cases with ease.
In the following chapter, we will present some design patterns that will enable us to develop more modular and testable code.
