Summary 

This chapter covered one component of GCP that allows you to build a data lake, called Dataproc. As we've learned in this chapter, learning about Dataproc means learning about Hadoop. We learned about and practiced the core and most popular Hadoop components, HDFS and Spark. 

By combining the nature of Hadoop with all the benefits of using the cloud, we also learned about new concepts. The Hadoop ephemeral cluster is relatively new and is only possible because of cloud technology. In a traditional on-premises Hadoop cluster, this highly efficient concept is never an option.  

From the perspective of a data engineer working on GCP, using Hadoop or Dataproc is optional. Similar functionality is doable using full serverless components on GCP; for example, use GCS and BigQuery as storage rather than HDFS and use Dataflow for processing unstructured data rather than Spark. But the popularity of Spark is one of the main reasons for people using Dataproc...