Hands-On Big Data Analytics with PySpark

Idioma: inglés

Editorial: Packt Publishing Limited, GB, 2019

183864413X / 9781838644130

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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK

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Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobsKey FeaturesWork with large amounts of agile data using distributed datasets and in-memory cachingSource data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3Employ the easy-to-use PySpark API to deploy big data Analytics for productionBook DescriptionApache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs.You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark.By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively.What you will learnGet practical big data experience while working on messy datasetsAnalyze patterns with Spark SQL to improve your business intelligenceUse PySpark s interactive shell to speed up development timeCreate highly concurrent Spark programs by leveraging immutabilityDiscover ways to avoid the most expensive operation in the Spark API: the shuffle operationRe-design your jobs to use reduceByKey instead of groupByCreate robust processing pipelines by testing Apache Spark jobsWho this book is forThis book is for developers, data scientists, business analysts, or anyone who needs to reliably analyze large amounts of large-scale, real-world data. Whether you're tasked with creating your company's business intelligence function or creating great data platforms for your machine learning models, or are looking to use code to magnify the impact of your business, this book is for you.…

N° de ref. del artículo LU-9781838644130

Título
Hands-On Big Data Analytics with PySpark
Autor
Rudy Lai, Bartlomiej Potaczek
Editorial
Packt Publishing Limited, GB
Año de publicación
2019
Estado
New
Encuadernación
Paperback
Idioma
inglés
ISBN 10
183864413X
ISBN 13
9781838644130

Rarewaves.com UK

London, Reino Unido

Vendedor de 5 estrellas

Vendedor de AbeBooks desde el 11 de junio de 2025

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ArtículoDe 60 a 60 días hábilesDe 60 a 60 días hábiles
Primer artículoEUR 76,48EUR 117,67
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