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Working with Apache Hive

Course Summary

The Working with Apache Hive training course is designed to demonstrate how to use Apache Hive to efficiently run analytical queries on big data.

The course begins with the basics of Hive including architecture, Yarn, HDFS, and running Hive with different execution engines. Next, it explores the Hive basic operations, data formats, compressions, and Hive Functions. The course concludes by analyzing Hive's advanced features and various optimization techniques to run queries faster.

Prerequisites: A basic knowledge of SQL is assumed.

Purpose
Promote an in-depth understanding of how to use Apache Hive in the most efficient way to run analytical queries on big data.
Audience
Business analysts, big data developers and testers who want to run analytics queries on big data systems.
Role
Business Analyst - Software Developer
Skill Level
Introduction
Style
Workshops
Duration
2 Days
Related Technologies
Hadoop | System Administration Training | Apache

 

Productivity Objectives
  • Run analytics queries using Apache Hive
  • Tune and optimize Hive system to run queries faster

What You'll Learn:

In the Working with Apache Hive training course, you'll learn:
  • Hive Overview
    • Understand Hadoop File System
    • Yarn Overview
    • Hive Overview and Architecture
    • Hive Execution Engines overview - Apache Spark, Tej and MapReduce
  • Hive Basic Operations
    • Hive Databases
    • Hive Managed/External Tables
    • Hive DDL and DML
  • Working with different File formats
    • Work with Parquet Files
    • Parquet versus Orc Files
    • Understand Avro
    • Schema Evolution with Avro
  • Hive Functions
    • Conditional Functions
    • String Functions
    • Date Functions
  • Hive Joins
    • Sort Merge Joins
    • Broadcast Joins
    • Bucket Joins
    • Multi Joins
  • Hive Analytics
    • Aggregations
    • Grouping
    • Subquery
    • Conditional statements
  • Hive Advance
    • Views/Lateral Explode
    • Windowing
    • Materialized view
  • Hive Optimization
    • File Partitioning
    • Bucketing
    • Dynamic Partition Pruning
“I appreciated the instructor's technique of writing live code examples rather than using fixed slide decks to present the material.”

VMware

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