{"product_id":"hands-on-guide-to-apache-spark-3-build-scalable-computing-engines-for-batch-and-stream-data-processing-paperback-1","title":"Hands-On Guide to Apache Spark 3: Build Scalable Computing Engines for Batch and Stream Data Processing - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eAlfonso Antol?ez Garc?\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eThis book explains how to scale Apache Spark 3 to handle massive amounts of data, either via batch or streaming processing. It covers how to use Spark's structured APIs to perform complex data transformations and analyses you can use to implement end-to-end analytics workflows. This book covers Spark 3's new features, theoretical foundations, and application architecture. The first section introduces the Apache Spark ecosystem as a unified engine for large scale data analytics, and shows you how to run and fine-tune your first application in Spark. The second section centers on batch processing suited to end-of-cycle processing, and data ingestion through files and databases. It explains Spark DataFrame API as well as structured and unstructured data with Apache Spark. The last section deals with scalable, high-throughput, fault-tolerant streaming processing workloads to process real-time data. Here you'll learn about Apache Spark Streaming's execution model, the architecture of Spark Streaming, monitoring, reporting, and recovering Spark streaming. A full chapter is devoted to future directions for Spark Streaming. With real-world use cases, code snippets, and notebooks hosted on GitHub, this book will give you an understanding of large-scale data analysis concepts--and help you put them to use.\u003cbr\u003eUpon completing this book, you will have the knowledge and skills to seamlessly implement large-scale batch and streaming workloads to analyze real-time data streams with Apache Spark.\u003cbr\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eMaster the concepts of Spark clusters and batch data processing\u003c\/li\u003e\n\u003cli\u003eUnderstand data ingestion, transformation, and data storage\u003c\/li\u003e\n\u003cli\u003eGain insight into essential stream processing concepts and different streaming architectures\u003c\/li\u003e\n\u003cli\u003eImplement streaming jobs and applications with Spark Streaming\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003eData engineers, data analysts, machine learning engineers, Python and R programmers\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eThis book explains how to scale Apache Spark 3 to handle massive amounts of data, either via batch or streaming processing. It covers how to use Spark's structured APIs to perform complex data transformations and analyses you can use to implement end-to-end analytics workflows. This book covers Spark 3's new features, theoretical foundations, and application architecture. The first section introduces the Apache Spark ecosystem as a unified engine for large scale data analytics, and shows you how to run and fine-tune your first application in Spark. The second section centers on batch processing suited to end-of-cycle processing, and data ingestion through files and databases. It explains Spark DataFrame API as well as structured and unstructured data with Apache Spark. The last section deals with scalable, high-throughput, fault-tolerant streaming processing workloads to process real-time data. Here you'll learn about Apache Spark Streaming's execution model, the architecture of Spark Streaming, monitoring, reporting, and recovering Spark streaming. A full chapter is devoted to future directions for Spark Streaming. With real-world use cases, code snippets, and notebooks hosted on GitHub, this book will give you an understanding of large-scale data analysis concepts--and help you put them to use.\u003cbr\u003eUpon completing this book, you will have the knowledge and skills to seamlessly implement large-scale batch and streaming workloads to analyze real-time data streams with Apache Spark.\u003cbr\u003eYou will: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eMaster the concepts of Spark clusters and batch data processing\u003c\/li\u003e\n\u003cli\u003eUnderstand data ingestion, transformation, and data storage\u003c\/li\u003e\n\u003cli\u003eGain insight into essential stream processing concepts and different streaming architectures\u003c\/li\u003e\n\u003cli\u003eImplement streaming jobs and applications with Spark Streaming\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003cb\u003eAlfonso Antol?ez Garc?\u003c\/b\u003e is a senior IT manager with a long professional career serving in several multinational companies such as Bertelsmann SE, Lafarge, and TUI AG. He has been working in the media industry, the building materials industry, and the leisure industry. Alfonso also works as a university professor, teaching artificial intelligence, machine learning, and data science. In his spare time, he writes research papers on artificial intelligence, mathematics, physics, and the applications of information theory to other sciences.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 403\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.86 x 10 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e June 06, 2023\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47213276692729,"sku":"9781484293799","price":75.58,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/VdfZfH-dOb9781484293799_02ea0db6-47d5-4a0a-8674-c6bba5e7688e.webp?v=1768104467","url":"https:\/\/bookscloud.io\/products\/hands-on-guide-to-apache-spark-3-build-scalable-computing-engines-for-batch-and-stream-data-processing-paperback-1","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}