{"product_id":"dataproc-cookbook-running-spark-and-hadoop-workloads-in-google-cloud-9781098157708","title":"Dataproc Cookbook: Running Spark and Hadoop Workloads in Google Cloud","description":"\u003cp\u003eWant 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. \u003c\/p\u003e\u003cp\u003eWritten 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. \u003c\/p\u003e\u003cul\u003e \u003cli\u003eCreate Dataproc clusters on Compute Engine and Kubernetes Engine \u003c\/li\u003e\n\u003cli\u003eRun data science workloads on Dataproc \u003c\/li\u003e\n\u003cli\u003eExecute Spark jobs on Dataproc Serverless \u003c\/li\u003e\n\u003cli\u003eOptimize Dataproc clusters to be cost effective and performant \u003c\/li\u003e\n\u003cli\u003eMonitor Spark jobs in various ways \u003c\/li\u003e\n\u003cli\u003eOrchestrate various workloads and activities \u003c\/li\u003e\n\u003cli\u003eUse different methods for migrating data and workloads from existing Hadoop clusters to Dataproc \u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003e\u003ci\u003eVenkataraman, Anuyogam:\u003c\/i\u003e\u003c\/b\u003e - 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.\u003cb\u003e\u003ci\u003eSadineni, Narasimha:\u003c\/i\u003e\u003c\/b\u003e - Narasimha Sadineni is a data engineer at Google who has 12 years of experience in Data \u0026amp; 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.","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":51424401260818,"sku":"9781098157708","price":57.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_cd215880-bd36-4507-bbb6-fbba6b5b7ac2.jpg?v=1751374649","url":"https:\/\/surprise-castle.myshopify.com\/products\/dataproc-cookbook-running-spark-and-hadoop-workloads-in-google-cloud-9781098157708","provider":"Surprise Castle","version":"1.0","type":"link"}