Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL
- Understanding the CAP theorem
- When to apply NoSQL solutions
- Columnar storage mechanisms
- The NoSQL ecosystem
- Section 2: Cassandra Basics
- Design and architecture overview
- Cassandra nodes, clusters, and datacenters
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and tokens
- Quorum and consistency levels
- Labs: Interacting with Cassandra via CQLSH
- Section 3: Data Modeling – Part 1
- Introduction to CQL
- CQL data types
- Creating keyspaces and tables
- Selecting columns and data types
- Defining primary keys
- Data layout for rows and columns
- Time to live (TTL) settings
- Executing queries with CQL
- Updating data with CQL
- Working with collections (list, map, set)
- Labs: Conducting various data modeling exercises using CQL; experimenting with queries and supported data types
- Section 4: Data Modeling – Part 2
- Creating and utilizing secondary indexes
- Composite keys (partition keys and clustering keys)
- Handling time series data
- Best practices for time series data
- Using counters
- Lightweight transactions (LWT)
- Labs: Creating and using indexes; modeling time series data
- Section 5: Data Modeling Labs – Group Design Session
- Presentation of multiple use cases across various domains
- Group collaboration to develop designs and data models
- Discussion and analysis of different design decisions
- Lab: Implementing one of the proposed scenarios
- Section 6: Cassandra Drivers
- Introduction to the Java driver
- Performing CRUD (Create, Read, Update, Delete) operations using the Java client
- Executing asynchronous queries
- Labs: Utilizing the Java API for Cassandra
- Section 7: Cassandra Internals
- Understanding Cassandra’s underlying design
- SSTables, memtables, and commit logs
- The read and write paths
- Caching mechanisms
- Virtual nodes (vnodes)
- Section 8: Administration
- Selecting appropriate hardware
- Overview of Cassandra distributions
- Cassandra best practices (including compaction and garbage collection)
- Troubleshooting tools and tips
- Lab: Installing Cassandra and running performance benchmarks
- Section 9: Bonus Lab (if time permits)
- Implementing a music streaming service similar to Pandora or Spotify on Cassandra
Requirements
- Familiarity with the Java programming language
- Proficiency in the Linux environment (including command-line navigation and file editing with vi or nano)
Testimonials (7)
The practical exercises and examples of implementing examples of real models and contexts.
Leandro Gomes
Course - Cassandra for Developers
I enjoyed the very good explanations with in depth examples.
Rui Magalhaes
Course - Cassandra for Developers
I liked all technical explanation and theoretical introduction.
Andre Santos
Course - Cassandra for Developers
I liked the amount of exercises. We could immediately apply the knowledge shared and ensure the information was on point.
Joana Pereira
Course - Cassandra for Developers
There was a lot of knowledge and material shared that will help me to do my current tasks.
Miguel Fernandes
Course - Cassandra for Developers
I already using and have an application in production with Cassandra so mostly of the topics i already know but the data modeling and advanced topics are a lot interesting.
Tiago Costa
Course - Cassandra for Developers
The last exercise was very good.
