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Titlebook: Hands-on Guide to Apache Spark 3; Build Scalable Compu Alfonso Antolínez‘García Book 2023 Alfonso Antol�nez Garc�a 2023 Data Science.Apach

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发表于 2025-3-21 17:13:37 | 显示全部楼层 |阅读模式
书目名称Hands-on Guide to Apache Spark 3
副标题Build Scalable Compu
编辑Alfonso Antolínez‘García
视频video
概述Covers Apache Spark application development using PySpark and SQL APIs.Explains building Apache Spark data analytics workflow and analyzing real-time data.Discusses Apache Spark with other stream proc
图书封面Titlebook: Hands-on Guide to Apache Spark 3; Build Scalable Compu Alfonso Antolínez‘García Book 2023 Alfonso Antol�nez Garc�a  2023 Data Science.Apach
描述This 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 o
出版日期Book 2023
关键词Data Science; Apache Spark; Python; Spark Streaming; Hadoop Yarn; Apache Mesos; PySpark; Mlib
版次1
doihttps://doi.org/10.1007/978-1-4842-9380-5
isbn_softcover978-1-4842-9379-9
isbn_ebook978-1-4842-9380-5
copyrightAlfonso Antol�nez Garc�a 2023
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发表于 2025-3-21 23:14:57 | 显示全部楼层
Spark Dataset API and Adaptive Query Executionatasets because these data structures are the ones more efficiently using Spark storage and query optimizers, hence achieving the best data processing performance. Therefore, DataFrames and datasets are the best Spark tools in getting the best performance to handle structured data. Spark DataFrames
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Spark Structured Streamingrmation at scale. Real-time data analysis is commonly associated with processes that require decisions to be taken quickly and without delay. Therefore, infrastructures capable of providing instant analytics, management of continuously flowing data, and fault tolerance and handling stragglers or slo
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Alfonso Antolínez Garcíat complete collection of the invited andcontributed papers delivered at the Seventh European TurbulenceConference, sponsored by EUROMECH and ERCOFTAC and organized by theObservatoire de la Côte d‘Azur. New high-Reynolds numberexperiments combined with new techniques of imaging, non-intrusiveprobing,
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