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: Learning Hadoop 2
  name:
    name part: Turkington, Garry
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Modena, Gabriele
    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: 2015
    edition: 1st edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (382 pages)
  abstract: Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2 In Detail This book introduces you to the world of building data-processing applications with the wide variety of tools supported by Hadoop 2. Starting with the core components of the framework?HDFS and YARN?this book will guide you through how to build applications using a variety of approaches. You will learn how YARN completely changes the relationship between MapReduce and Hadoop and allows the latter to support more varied processing approaches and a broader array of applications. These include real-time processing with Apache Samza and iterative computation with Apache Spark. Next up, we discuss Apache Pig and the dataflow data model it provides. You will discover how to use Pig to analyze a Twitter dataset. With this book, you will be able to make your life easier by using tools such as Apache Hive, Apache Oozie, Hadoop Streaming, Apache Crunch, and Kite SDK. The last part of this book discusses the likely future direction of major Hadoop components and how to get involved with the Hadoop community. What You Will Learn Write distributed applications using the MapReduce framework Go beyond MapReduce and process data in real time with Samza and iteratively with Spark Familiarize yourself with data mining approaches that work with very large datasets Prototype applications on a VM and deploy them to a local cluster or to a cloud infrastructure (Amazon Web Services) Conduct batch and real time data analysis using SQL-like tools Build data processing flows using Apache Pig and see how it enables the easy incorporation of custom functionality Define and orchestrate complex workflows and pipelines with Apache Oozie Manage your data lifecycle and changes over time
  note: Turkington, Garry.
  note: Electronic resource.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web.
  note: Mode of access: World Wide Web.
  identifier: 9781783285518
  identifier: 9781783285525
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 160215
    record change date: 20260128184507.2
    record identifier: in00004250709