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Beginning Apache Spark 2
With Resilient Distributed Datasets, Spark Sql, Structured Streaming and Spark Machine Learning Library
Hien Luu
Livre broché | Anglais
46,45 €
+ 92 points
Description
Develop applications for the big data landscape with Spark and Hadoop. This book also explains the role of Spark in developing scalable machine learning and analytics applications with Cloud technologies. Beginning Apache Spark 2 gives you an introduction to Apache Spark and shows you how to work with it.
Along the way, you'll discover resilient distributed datasets (RDDs); use Spark SQL for structured data; and learn stream processing and build real-time applications with Spark Structured Streaming. Furthermore, you'll learn the fundamentals of Spark ML for machine learning and much more. After you read this book, you will have the fundamentals to become proficient in using Apache Spark and know when and how to apply it to your big data applications. What You Will Learn
Who This Book Is For
Programmers and developers active in big data, Hadoop, and Java but who are new to the Apache Spark platform.
Along the way, you'll discover resilient distributed datasets (RDDs); use Spark SQL for structured data; and learn stream processing and build real-time applications with Spark Structured Streaming. Furthermore, you'll learn the fundamentals of Spark ML for machine learning and much more. After you read this book, you will have the fundamentals to become proficient in using Apache Spark and know when and how to apply it to your big data applications. What You Will Learn
- Understand Spark unified data processing platform
- How to run Spark in Spark Shell or Databricks
- Use and manipulate RDDs
- Deal with structured data using Spark SQL through its operations and advanced functions
- Build real-time applications using Spark Structured Streaming
- Develop intelligent applications with the Spark Machine Learning library
Who This Book Is For
Programmers and developers active in big data, Hadoop, and Java but who are new to the Apache Spark platform.
