Dataproc Cookbook: Running Spark and Hadoop Workloads in Google Cloud

by Narasimha Sadineni, Anuyogam Venkataraman

Overview

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

Product Details

ISBN-13:	9781098157661
Publisher:	O'Reilly Media, Incorporated
Publication date:	06/03/2025
Sold by:	Barnes & Noble
Format:	eBook
Pages:	438
File size:	19 MB
Note:	This product may take a few minutes to download.

About the Author

Narasimha Sadineni is a data engineer at Google who has 12 years of experience in Data & Analytics. While working as a professional services team member at Google and Cloudera, he helped 50+ organizations in solving BigData problems using tools like Hadoop and Google Cloud technologies. He has several years of teaching experience in Hadoop.

Anu Venkataraman is a Senior Program Manager. She previously served as a Data Lake Engineer at Google, accumulating extensive experience in data technologies. Anu assists customers in migrating large-scale distributed systems to the cloud. She finds joy in speaking at universities and contributing technical blogs and videos to the Data community, aiming to expedite customers' journeys to the cloud. Anu played a key role as one of the leads for the Professional Services Tech Talk playlist on the Google Cloud Tech YouTube channel. She holds a Master's degree in Electrical and Computer Engineering from Ryerson University, specializing in Medical Image Processing and Machine Learning.