Cassandra Data Modeling Essential Training

Introduction

• Designing data models in Cassandra
• What you should know
• Exercise files

1. Cassandra Architecture

• Cassandra and relational databases
• Keyspaces, tables, rows, and columns
• Primary keys and secondary indexes
• Cassandra clusters
• Challenge: Design a table for a mobile app
• Solution: Design a table for a mobile app

2. Installing Cassandra

• Install Cassandra
• Creating a keyspace and table

3. Cassandra Query Language Data Types

• Numeric data types
• String, date, and unique types
• Collection data types
• Tuple data types
• Working with JSON
• Challenge: Choose the correct data types
• Solution: Choose the correct data types

4. Designing Cassandra Tables

• Queries drive design
• Denormalizing: Joining or sorting
• Tuning tables to optimize queries
• Data modeling for time series
• Challenge: Define a time series table
• Solution: Define a time series table

5. Additional Table Features

• Secondary indexes
• Materialized views
• Virtual tables
• Challenge: Create materialized view
• Solution: Create materialized view

6. Physical Data Modeling and Distributing Data

• Estimating data size formulas
• Example of estimating data size
• Replication in Cassandra
• Understanding consistency levels
• Challenge: Size a table
• Solution: Size a table

7. Cassandra Architecture and Its Impact on Data Modeling

• Understand the query process
• Understand commit writes
• Bloom filters and query processing
• Understand deletes and tombstones
• Understand compaction
• Challenge: Diagnose performance problem
• Solution: Diagnose performance problem

Conclusion

• Five best practices for Cassandra data modeling