Dataproc Cookbook: Running Spark and Hadoop Workloads in Google Cloud

Want to build big data solutions in Google Cloud? Dataproc Cookbook is your hands-on guide to mastering Dataproc and the essential GCP fundamentals--like networking, security, monitoring, and cost optimization--that apply across Google Cloud services. Learn practical skills that not only fast-track your Dataproc expertise, but also help you succeed with a wide range of GCP technologies.

Written by data experts Narasimha Sadineni and Anu Venkataraman, this cookbook tackles real-world use cases like serverless Spark jobs, Kubernetes-native deployments, and cost-optimized data lake workflows. You'll learn how to create ephemeral and persistent Dataproc clusters, run secure data science workloads, implement monitoring solutions, and plan effective migration and optimization strategies.

• Create Dataproc clusters on Compute Engine and Kubernetes Engine
• Run data science workloads on Dataproc
• Execute Spark jobs on Dataproc Serverless
• Optimize Dataproc clusters to be cost effective and performant
• Monitor Spark jobs in various ways
• Orchestrate various workloads and activities
• Use different methods for migrating data and workloads from existing Hadoop clusters to Dataproc