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LinkedIn Learning

Cassandra Data Modeling Essential Training (2017)

via LinkedIn Learning

Overview

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Learn about the architecture of Cassandra—a popular NoSQL database capable of handling large amounts of fast-changing data—and discover how to design Cassandra data models.

Syllabus

Introduction
  • Welcome
  • What you should know
  • Exercise files
1. Cassandra Architecture
  • Cassandra and relational databases
  • Keyspaces, tables, and columns
  • Primary keys, partitions, and secondary indexes
  • Cassandra clusters
  • Installing Java
  • Installing Cassandra
  • Creating a keyspace in tables
2. Cassandra Query Language Data Types
  • Numeric data types
  • String, date, and unique types
  • Collection data types
  • Tuple data types
3. Designing Cassandra Tables
  • Queries drive design
  • Denormalizing: Joining or sorting
  • Tuning tables to optimize queries
  • Data modeling for time series: Part 1
  • Data modeling for time series: Part 2
  • Time series exercise
  • When to use secondary indexes
  • When to use materialized views
  • UUID and delete exercise
4. Physical Data Modeling and Distributing Data
  • Estimating data size 1: The formulas
  • Estimating data size 2: An example
  • Replication in Cassandra
  • Understanding consistency levels
5. Cassandra Architecture and Its Impact on Data Modeling
  • Understanding the query process
  • Understanding commit writes
  • Bloom filters and query processing
  • Understand deletes and tombstones
  • Understand compaction
Conclusion
  • Five best practices for Cassandra data modeling
  • Next steps

Taught by

Dan Sullivan

Reviews

4.6 rating at LinkedIn Learning based on 113 ratings

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