Hands-on Guide to Apache Spark 3 (eBook)
XIII, 403 Seiten
Apress (Verlag)
978-1-4842-9380-5 (ISBN)
- Master the concepts of Spark clusters and batch data processing
- Understand data ingestion, transformation, and data storage
- Gain insight into essential stream processing concepts and different streaming architectures
- Implement streaming jobs and applications with Spark Streaming
Alfonso Antolínez García 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.
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 on GitHub, this book will give you an understanding of large-scale data analysis concepts--and help you put them to use.Upon 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.What You Will LearnMaster the concepts of Spark clusters and batch data processingUnderstand data ingestion, transformation, and data storageGain insight into essential stream processing concepts and different streaming architecturesImplement streaming jobs and applications with Spark StreamingWho This Book Is ForData engineers, data analysts, machine learning engineers, Python and R programmers
Erscheint lt. Verlag | 5.6.2023 |
---|---|
Zusatzinfo | XIII, 403 p. 74 illus., 67 illus. in color. |
Sprache | englisch |
Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge | |
Informatik ► Theorie / Studium ► Algorithmen | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Schlagworte | Apache Mesos • Apache Spark • Data Science • Hadoop Yarn • MLib • PySpark • Python • Spark Streaming |
ISBN-10 | 1-4842-9380-0 / 1484293800 |
ISBN-13 | 978-1-4842-9380-5 / 9781484293805 |
Haben Sie eine Frage zum Produkt? |
Größe: 11,7 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich