Working with Apache Hive

Hive is the de-facto standard for data warehousing Hadoop. This course starts with a Hive setup and operations and continues into advanced Hive uses. It also discusses performance and execution engines while ending with a practical workshop.

    Nov 12 2020

    November 12 - 13, 2020 | 10:00 AM - 6:00 PM (EST) | Virtual Classroom Live

    Date: 11/12/2020 - 11/13/2020 (Thursday - Friday) | 10:00 AM - 6:00 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    Working with Apache Hive

    November 12 - 13, 2020 | 10:00 AM - 6:00 PM (EST) | Virtual Classroom Live


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    Join Our Email List?

    Dec 17 2020

    December 17 - 18, 2020 | 10:00 AM - 6:00 PM (EST) | Virtual Classroom Live

    Date: 12/17/2020 - 12/18/2020 (Thursday - Friday) | 10:00 AM - 6:00 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    Working with Apache Hive

    December 17 - 18, 2020 | 10:00 AM - 6:00 PM (EST) | Virtual Classroom Live


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    Join Our Email List?

Hive Basics

  • Defining Hive Tables
  • SQL Queries over Structured Data
  • Filtering / Search
  • Aggregations / Ordering
  • Partitions
  • Joins
  • Text Analytics (Semi-Structured Data)

Hive Advanced

  • Transformation, Aggregation
  • Working with Dates, Timestamps, and Arrays
  • Converting Strings to Date, Time, and Numbers
  • Create new Attributes, Mathematical Calculations, Windowing Functions
  • Use Character and String Functions
  • Binning and Smoothing
  • Processing JSON Data
  • Execution Engines (Tez, MR, and Spark)

Impala (for Cloudera track)

  • Architecture
  • Impala joins and other SQL specifics

Bonus Project

  • Students will work in teams to do this end-to-end workshop
  • Setup a data warehouse with Hive
  • Query and analyze data with Hive and Spark

Join an engaging hands-on learning environment, where you’ll learn:

  • Hive basics and features
  • How to process, transform, and manage data
  • Processing and performance management
  • How to setup a date warehouse with Hive
  • Data query and analysis

This course has a 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work.

 

Before attending this course, you should:

  • Be familiar with SQL
  • Be able to navigate the Linux command line
  • Have basic knowledge of command line Linux editors (VI/nano)

 

 

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