We set the context of building data-intensive apps by describing the overall architecture structured around the infrastructure, persistence, integration, analytics, and engagement layers. We also discussed Spark and Anaconda with their respective building blocks. We set up an environment in a VirtualBox with Anaconda and Spark and demonstrated a word count app using the text content of the first chapter as input.

In the next chapter, we will delve more deeply into the architecture blueprint for data-intensive apps and tap into the Twitter, GitHub, and Meetup APIs to get a feel of the data we will be mining with Spark.