Getting Started with Hive for Relational Database Developers

Traditional databases focus on transactional processing, whereas Hive helps with analytical processing extracted from huge datasets. This course focuses on the similarities and differences between SQL and Hive.
Course info
Rating
(83)
Level
Beginner
Updated
Feb 24, 2017
Duration
2h 55m
Table of contents
Course Overview
Hive vs. RDBMS
Getting Started with Basic Queries in Hive
Creating Databases and Tables
Using Complex Data Types and Table Generating Functions
Understanding Constraints in Subqueries and Views
Designing Schema for Hive
Description
Course info
Rating
(83)
Level
Beginner
Updated
Feb 24, 2017
Duration
2h 55m
Description

Transactional processing focuses on accessing and updating individual records. Analytical processing works on data in bulk and deals more with summaries across the dataset, trends and insights. The difference in requirements and the kind of data they work on, lead to differences between Hive and traditional databases. This course, Getting Started with Hive for Relational Database Developers, teaches you about several gotchas involved while using familiar SQL constructs in Hive. You'll learn about loading and parsing data from files, views, subqueries, and some cool built-in functionality such as table generating functions. The course also demonstrates the constraints imposed by Hive architecture choices such as schema on read, denormalized storage in HDFS, and high latency of operations. This serves as a guide for user choices during storage and querying. By the end of this course, you'll feel confident in using Hive for your own relational database uses.

About the author
About the author

A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.

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