Hadoop 3 With Hive 3

Explain the capabilities of Hive, HQL dialects, and best practices.

Get Course Info

Audience: Business analysts, Software developers, Managers

Duration: Two to three days

Overview

Hive is de-facto standard the SQL interface into Big Data. Hive has moved on to Hive 3. Today, it offers ACID tables, storage requirements reduction by the factor of 2 with erasure coding, HBase integration with Phoenix, and much more. However, in order to achieve efficiency, one must be familiar with the best practices of the HQL language, compare different tools for looking at your data, whether it be Hive, Phoenix HBase, or plain Excel. This course will explain the capabilities of Hive, HQL dialects, and best practices.

Objective

Explain the capabilities of Hive, HQL dialects, and best practices.

What You Will Learn

Hive 3 new features
HBase with Phoenix

Course Details

Audience: Business analysts, Software developers, Managers

Duration: Two to three days

Prerequisites:

Exposure to SQL • Be able to navigate Linux command line

Setup: Working environment provided in the browser • Zero Install: There is no need to install software on students’ machines

Detailed Outline

The motivation for Hadoop
Use cases and case studies about Hadoop

MapReduce, HDFS, YARN
New in Hadoop 3
Erasure Coding vs 3× replication

Defining Hive Tables
SQL Queries over Structured Data
Filtering / SearchService Level Objectives
Aggregations / Ordering
Partitions
Joins

ACID tables
Hive Query Language (HQL)
How to run a good query?
How to troubleshoot queries?

Basics
HBase tables – design and use
Phoenix driver for HBase tables

Tool
Architecture
Use

Overview
Spark SQL

How Hadoop fits into your architecture
Hive vs HBase with Phoenix vs Excel