1.

Record Nr.

UNINA9910300752003321

Autore

Luu Hien

Titolo

Beginning Apache Spark 2 : With Resilient Distributed Datasets, Spark SQL, Structured Streaming and Spark Machine Learning library / / by Hien Luu

Pubbl/distr/stampa

Berkeley, CA : , : Apress : , : Imprint : Apress, , 2018

ISBN

9781484235799

1484235797

Edizione

[1st ed. 2018.]

Descrizione fisica

1 online resource (XI, 393 p. 86 illus.)

Disciplina

005.7

Soggetti

Big data

Java (Computer program language)

Data mining

Open source software

Computer programming

Big Data

Java

Data Mining and Knowledge Discovery

Open Source

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di contenuto

1. Introduction to Apache Spark -- 2. Working with Apache Spark -- 3. Resilient Distributed Dataset -- 4. Spark SQL - Foundation -- 5. Spark SQL - Advanced -- 6. Spark Streaming -- 7. Spark Streaming Advanced -- 8. Machine Learning with Spark.

Sommario/riassunto

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. You will: Understand Spark unified data processing platform Use and manipulate RDDs Deal with structured data using Spark SQL Build real-time applications using Spark Structured Streaming Develop intelligent applications with the Spark Machine Learning library.