rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Fast Data Processing with Spark 2 - Third Edition
  name:
    name part: Sankar, Krishna
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xx
    date issued: 2016
    edition: 3rd edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (274 pages)
  abstract: Learn how to use Spark to process big data at speed and scale for sharper analytics. Put the principles into practice for faster, slicker big data projects. About This Book 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 Who This Book Is For This book is for developers with little to no knowledge of Spark, but with a background in Scala/Java programming. It's recommended that you have experience in dealing and working with big data and a strong interest in data science. 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 In Detail 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 …
  note: Sankar, Krishna.
  note: Electronic resource.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web.
  note: Mode of access: World Wide Web.
  identifier: 9781785889271
  identifier: 9781785882968
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 261016
    record change date: 20260129170004.1
    record identifier: in00004128316