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Getting Started with Hive for Relational Database Developers

by Janani Ravi

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.

What you'll learn

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.

Table of contents

Course Overview

About the author

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. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing ... more

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