Lab - Data Modeling for Amazon DynamoDB

In this lab, you explore how to apply data modeling techniques to solve business use cases for efficiently storing and retrieving data in Amazon DynamoDB tables. You also explore the data access pattern of the application, then design and build DynamoDB tables and indexes to achieve efficient data access.

Objectives

• Determine table partition and sort keys based on data access patterns of the application.
• Determine optimal selection of local and global secondary indexes needed to support data access patterns.
• Create DynamoDB tables, local secondary indexes (LSI), and global secondary indexes (GSI).
• Explore how to query on many attributes using global secondary index key overloading.
• Explore how to run queries over a small subsection of a table using sparse indexes.

Prerequisites

• A basic knowledge of DynamoDB tables

Outline

• Task 1: Identify the partition key, sort key, and any secondary indexes for the orders table
• Task 2: Create the orders DynamoDB table and any secondary indexes
• Task 3: Validate orders table and indexes configuration
• Task 4: Querying data using global secondary index overloading
• Task 5: Querying data using sparse global secondary index