Dataproc is a paid Google Cloud service built on top of open source software Apache Hadoop, Apache Spark, and other big data technologies, such as Apache Kafka, JupyterHub, and Apache Solr. As a managed service, Dataproc abstracts creating, updating, managing, and deleting all the required cloud services and resources.
Dataproc offers three different environments for running it:
Dataproc on Google Compute Engine (GCE)
Dataproc on Google Kubernetes Engine (GKE)
Dataproc Serverless
In this chapter, we focus on the first option: running Dataproc on GCE (see Figure 1-1).
Before you start using this product, you should understand the billing and charges. This service has two types of charges: a charge for the software and a charge for the underlying components (compute engine, disks, cloud storage, network, etc.). Dataproc’s pay-as-you-go model allows you to pay for only the services you use. For more information on pricing, refer to the Dataproc pricing documentation. Dataproc Serverless has a different pricing model that we will discuss in Chapter 4.
Figure 1-1. Dataproc on GCE high-level architecture diagram
The first step in the process of creating a Dataproc cluster is to secure a Google Cloud account. If you don’t have one already, sign up for a new Google Cloud account at cloud.google.com.
Tip
Google encourages new users to try ...
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