Dataproc Cookbook : Running Spark and Hadoop Workloads in Google Cloud
Language: English
Published by O'reilly Media Jul 2025, 2025
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Neuware - 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.…
Seller Inventory # 9781098157708
- Title
- Dataproc Cookbook : Running Spark and Hadoop Workloads in Google Cloud
- Author
- Narasimha Sadineni
- Publisher
- O'reilly Media Jul 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1098157702
- ISBN 13
- 9781098157708
- Item weight
- 744 grams
- Dimensions
- 229x176x24 mm
Get up to speed with Dataproc, the fully managed and highly scalable service for running open source big data tools and frameworks, including Hadoop, Spark, Flink, and Presto. This cookbook shows data engineers, data scientists, data analysts, and cloud architects how to use Dataproc, integrated with Google Cloud, for data lake modernization, ETL, and secure data science at a fraction of the cost.
Narasimha Sadineni from Google and former Googler Anu Venkataraman show you how to set up and run Hadoop and Spark jobs on Dataproc. You'll learn how to create Dataproc clusters and run data engineering and data science workloads in long-running, ephemeral, and serverless ways. In the process, you'll gain an understanding of Dataproc, orchestration, logging and monitoring, Spark History Server, and migration patterns.
This cookbook includes hands-on examples for configuring, logging, securing clusters, and migrating from on-prem to Dataproc. You'll learn how to:
- 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
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
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