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LinkedIn Learning

Cassandra Data Modeling Essential Training

via LinkedIn Learning

Overview

Learn about the basics of designing data models in the latest release of Cassandra, the popular NoSQL database capable of handling large amounts of fast-changing data.

Syllabus

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

Taught by

Dan Sullivan

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