Big Data Analytics with Spark: A Practitioner's Guide to Using Spark for Large Scale Data Analysis (Paperback)

Mohammed Guller

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商品描述

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. You’ll 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 that are 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.

商品描述(中文翻譯)

《使用Spark進行大數據分析》是一本逐步指南,教你學習Spark。Spark是一個開源的快速通用的集群計算框架,用於大規模數據分析。你將學習如何在不同類型的大數據分析項目中使用Spark,包括批處理、交互式、圖形和流數據分析,以及機器學習。此外,這本書還將幫助你成為一位備受追捧的Spark專家。

Spark是最熱門的大數據技術之一。今天設備、應用程序和用戶生成的數據量正在爆炸性增長。因此,需要能夠分析大規模數據並從中獲得價值的工具至關重要。Spark是滿足這一需求的強大技術。例如,你可以使用Spark通過高效的緩存和迭代算法執行低延遲計算;利用其Shell的功能進行輕鬆和交互式數據分析;利用其快速批處理和低延遲功能處理實時數據流等。因此,Spark的使用正在迅速增長,並且正在取代Hadoop MapReduce成為大數據分析的首選技術。

本書介紹了Spark及其相關的大數據技術。它涵蓋了Spark核心及其附加庫,包括Spark SQL、Spark Streaming、GraphX和MLlib。《使用Spark進行大數據分析》是為那些希望從一個整合的來源學習新技術的忙碌專業人士而寫的,而不是花費無數時間在互聯網上從不同來源中選取片段。

本書還提供了一章關於Scala,這是最熱門的函數式編程語言,也是Spark的基礎程序語言。你將學習Scala的函數式編程基礎,以便能夠使用Scala編寫Spark應用程序。

此外,《使用Spark進行大數據分析》還介紹了與Spark常用的其他大數據技術,如Hive、Avro、Kafka等。因此,這本書是自給自足的;涵蓋了你需要了解的所有使用Spark的技術。唯一需要你知道的是任何一種編程語言。

由於缺乏大數據專業知識的人才,企業願意為具有Spark和Scala等技能的人付出高薪。因此,閱讀本書並吸收其中的原則將對你的職業生涯提供一個可能是巨大的推動。