big data analytics spark (18 Ergebnisse)

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Hardcover. Zustand: Très bon. Ancien livre de bibliothèque. Jaquette abîmée. Edition 2014. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Damaged dust jacket. Edition 2014. Ammareal gives back up to 15% of this item's net price to charity organizations.

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Sprache: Englisch XVI, 216 Seiten. Pappband mit OU. Guter frischer Zustand!

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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 328 | Sprache: Englisch | Produktart: Bücher | Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, yoüll set up the Scala environment ready for examining your first Scala programs. This is followed by sections on Scala fundamentals including mutable/immutable variables, the type hierarchy system, control flow expressions and code blocks. The author discusses functions at length and highlights a number of associated concepts such as functional programming and anonymous functions. The book then delves deeper into Scaläs powerful collections system because many of Apache Spark¿s APIs bear a strong resemblance to Scala collections. Along the way yoüll see thedevelopment life cycle of a Scala program. This involves compiling and building programs using the industry-standard Scala Build Tool (SBT). Yoüll cover guidelines related to dependency management using SBT as this is critical for building large Apache Spark applications. Scala Programming for Big Data Analytics concludes by demonstrating how you can make use of the concepts to write programs that run on the Apache Spark framework. These programs will provide distributed and parallel computing, which is critical for big data analytics. What You Will LearnSee the fundamentals of Scala as a general-purpose programming language Understand functional programming and object-oriented programming constructs in Scala Use Scala collections and functions Develop, package and run Apache Spark applications for big data analytics Who ThisBook Is For Data scientists, data analysts and data engineers who intend to use Apache Spark for large-scale analytics.

Taschenbuch. Zustand: Neu. Neuware -Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. In addition, this book will help you become a much sought-after Spark expert.Spark is one of the hottest Big Data technologies. The amount of data generated today by devices, applications and users is exploding. Therefore, there is a critical need for tools that can analyze large-scale data and unlock value from it. Spark is a powerful technology that meets that need. You can, for example, use Spark to perform low latency computations through the use of efficient caching and iterative algorithms; leverage the features of its shell for easy and interactive Data analysis; employ its fast batch processing and low latency features to process your real time data streams and so on. As a result, adoption of Spark is rapidly growing and is replacing Hadoop MapReduce as the technology of choice for big data analytics.This book provides an introduction to Spark and related big-data technologies. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, and MLlib. Big Data Analytics with Spark is therefore written for busy professionals who prefer learning a new technology from a consolidated source instead of spending countless hours on the Internet trying to pick bits and pieces from different sources. The book also provides a chapter on Scala, the hottest functional programming language, and the program that underlies Spark. Yoüll learn the basics of functional programming in Scala, so that you can write Spark applications in it.What's more, Big Data Analytics with Spark provides an introduction to other big data technologies thatare commonly used along with Spark, like Hive, Avro, Kafka and so on. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. The only thing that you are expected to know is programming in any language.There is a critical shortage of people with big data expertise, so companies are willing to pay top dollar for people with skills in areas like Spark and Scala. So reading this book and absorbing its principles will provide a boost¿possibly a big boost¿to your career.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 304 pp. Englisch.

Zustand: New. &Uumlber den AutorMd. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data.