Fast Data Processing with Spark 2 - Third Edition

Krishna Sankar

Fast Data Processing with Spark 2 - Third Edition
  • 出版商: Packt Publishing
  • 出版日期: 2016-10-21
  • 定價: $1,330
  • 售價: 9.0 折 $1,197
  • 語言: 英文
  • 頁數: 274
  • 裝訂: Paperback
  • ISBN: 1785889273
  • ISBN-13: 9781785889271
  • 相關分類: Spark

    • 立即出貨 (庫存=1)

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商品描述

Key Features

  • A quick way to get started with Spark – and reap the rewards
  • From analytics to engineering your big data architecture, we’ve got it covered
  • Bring your Scala and Java knowledge – and put it to work on new and exciting problems

Book Description

When people want a way to process big data at speed, Spark is invariably the solution. With its ease of development (in comparison to the relative complexity of Hadoop), it’s unsurprising that it’s becoming popular with data analysts and engineers everywhere.

Beginning with the fundamentals, we’ll show you how to get set up with Spark with minimum fuss. You’ll then get to grips with some simple APIs before investigating machine learning and graph processing – throughout we’ll make sure you know exactly how to apply your knowledge.

You will also learn how to use the Spark shell, how to load data before finding out how to build and run your own Spark applications. Discover how to manipulate your RDD and get stuck into a range of DataFrame APIs. As if that’s not enough, you’ll also learn some useful Machine Learning algorithms with the help of Spark MLlib and integrating Spark with R. We’ll also make sure you’re confident and prepared for graph processing, as you learn more about the GraphX API.

What you will learn

  • Install and set up Spark in your cluster
  • Prototype distributed applications with Spark's interactive shell
  • Perform data wrangling using the new DataFrame APIs
  • Get to know the different ways to interact with Spark's distributed representation of data (RDDs)
  • Query Spark with a SQL-like query syntax
  • See how Spark works with big data
  • Implement machine learning systems with highly scalable algorithms
  • Use R, the popular statistical language, to work with Spark
  • Apply interesting graph algorithms and graph processing with GraphX

About the Author

Krishna Sankar is a Senior Specialist—AI Data Scientist with Volvo Cars focusing on Autonomous Vehicles. His earlier stints include Chief Data Scientist at http://cadenttech.tv/, Principal Architect/Data Scientist at Tata America Intl. Corp., Director of Data Science at a bioinformatics startup, and as a Distinguished Engineer at Cisco. He has been speaking at various conferences including ML tutorials at Strata SJC and London 2016, Spark Summit [goo.gl/ab30lD], Strata-Spark Camp, OSCON, PyCon, and PyData, writes about Robots Rules of Order [goo.gl/5yyRv6], Big Data Analytics—Best of the Worst [goo.gl/ImWCaz], predicting NFL, Spark [http://goo.gl/E4kqMD], Data Science [http://goo.gl/9pyJMH], Machine Learning [http://goo.gl/SXF53n], Social Media Analysis [http://goo.gl/D9YpVQ] as well as has been a guest lecturer at the Naval Postgraduate School. His occasional blogs can be found at https://doubleclix.wordpress.com/. His other passion is flying drones (working towards Drone Pilot License (FAA UAS Pilot) and Lego Robotics—you will find him at the St.Louis FLL World Competition as Robots Design Judge.

Table of Contents

  1. Installing Spark and Setting Up Your Cluster
  2. Using the Spark Shell
  3. Building and Running a Spark Application
  4. Creating a SparkSession Object
  5. Loading and Saving Data in Spark
  6. Manipulating Your RDD
  7. Spark 2.0 Concepts
  8. Spark SQL
  9. Foundations of Datasets/DataFrames – The Proverbial Workhorse for DataScientists
  10. Spark with Big Data
  11. Machine Learning with Spark ML Pipelines
  12. GraphX

商品描述(中文翻譯)

主要特點


  • 快速入門Spark，並獲得回報

  • 從分析到設計大數據架構，我們都有涵蓋

  • 運用你的Scala和Java知識，解決新穎有趣的問題

書籍描述

當人們需要以高速處理大數據時，Spark往往是解決方案。相較於Hadoop的相對複雜性，Spark的開發容易性使其在數據分析師和工程師中越來越受歡迎。

從基礎知識開始，我們將向您展示如何輕鬆設置Spark。然後，您將熟悉一些簡單的API，並探索機器學習和圖形處理 - 我們將確保您知道如何應用您的知識。

您還將學習如何使用Spark shell，在載入數據之前，了解如何構建和運行自己的Spark應用程序。發現如何操作您的RDD並深入研究一系列DataFrame API。如果這還不夠，您還將通過Spark MLlib學習一些有用的機器學習算法，並將Spark與R集成。同時，我們還將確保您對圖形處理感到自信和準備就緒，因為您將更多地了解GraphX API。

你將學到什麼


  • 在集群中安裝和設置Spark

  • 使用Spark的交互式shell原型分佈式應用程序

  • 使用新的DataFrame API進行數據整理

  • 了解與Spark的分佈式數據表示（RDD）進行交互的不同方式

  • 使用類似SQL的查詢語法查詢Spark

  • 了解Spark如何處理大數據

  • 使用高度可擴展的算法實現機器學習系統

  • 使用流行的統計語言R與Spark一起工作

  • 應用有趣的圖形算法和圖形處理與GraphX

關於作者

Krishna Sankar是Volvo Cars的高級專家 - AI數據科學家，專注於自動駕駛車輛。他之前的職位包括http://cadenttech.tv/的首席數據科學家，Tata America Intl. Corp.的首席架構師/數據科學家，一家生物信息學初創公司的數據科學總監，以及Cisco的杰出工程師。他曾在各種會議上發表演講，包括Strata SJC和倫敦2016年的ML教程，Spark Summit [goo.gl/ab30lD]，Strata-Spark Camp，OSCON，PyCon和PyData，撰寫有關機器人規則的博客[goo.gl/5yyRv6]，大數據分析 - 最好的最壞[goo.gl/ImWCaz]，預測NFL，Spark [http://goo.gl/E4kqMD]，數據科學[http://goo.gl/9pyJMH]，機器學習[http://goo.gl/SXF53n]，社交媒體分析[http://goo.gl/D9YpVQ]，並在海軍研究生院擔任客座講師。他的偶爾博客可以在https://doubleclix.wordpress.com/找到。他的另一個熱情是飛行無人機（正在努力獲得無人機飛行員許可證（FAA UAS Pilot）和樂高機器人 - 您將在聖路易斯FLL世界競賽中找到他作為機器人設計評委）。

目錄


  1. 安裝Spark並設置您的集群

  2. 使用Spark Shell

  3. 構建和運行Spark應用程序

  4. 創建SparkSession對象

  5. 在Spark中加載和保存數據

  6. 操作您的RDD

  7. Spark 2.0概念

  8. Spark SQL

  9. 數據科學家的數據集/數據框基礎知識

  10. Spark與大數據

  11. 使用Spark ML Pipelines進行機器學習

  12. GraphX

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