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: Hadoop Fundamentals for Data Scientists
  name:
    name part: Kim, Jenny
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Bengfort, Benjamin
    role:
      role term: author.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: moving image
  genre: videorecording
  genre: Electronic videos.
  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 (1 video file, approximately 6 hr., 6 min.)
  abstract: Get a practical introduction to Hadoop, the framework that made big data and large-scale analytics possible by combining distributed computing techniques with distributed storage. In this video tutorial, hosts Benjamin Bengfort and Jenny Kim discuss the core concepts behind distributed computing and big data, and then show you how to work with a Hadoop cluster and program analytical jobs. You'll also learn how to use higher-level tools such as Hive and Spark. Hadoop is a cluster computing technology that has many moving parts, including distributed systems administration, data engineering and warehousing methodologies, software engineering for distributed computing, and large-scale analytics. With this video, you'll learn how to operationalize analytics over large datasets and rapidly deploy analytical jobs with a variety of toolsets. Once you've completed this video, you'll understand how different parts of Hadoop combine to form an entire data pipeline managed by teams of data engineers, data programmers, data researchers, and data business people. Understand the Hadoop architecture and set up a pseudo-distributed development environment Learn how to develop distributed computations with MapReduce and the Hadoop Distributed File System (HDFS) Work with Hadoop via the command-line interface Use the Hadoop Streaming utility to execute MapReduce jobs in Python Explore data warehousing, higher-order data flows, and other projects in the Hadoop ecosystem Learn how to use Hive to query and analyze relational data using Hadoop Use summarization, filtering, and aggregation to move Big Data towards last mile computation Understand how analytical workflows including iterative machine learning, feature analysis, and data modeling work in a Big Data context Benjamin Bengfort is a data scientist and programmer in Washington DC who prefers technology to politics but sees the value of data in every domain. Alongside his work teaching, writing, and developing large-scale analytic…
  note: Kim, Jenny.
  note: Videorecording.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web.
  note: Mode of access: World Wide Web.
  identifier: 9781491913161
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 140115
    record change date: 20260130165303.1
    record identifier: in00004136882