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Duration 14 hours
Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL technologies
- The CAP theorem
- Scenarios where NoSQL is the appropriate choice
- Columnar storage concepts
- The NoSQL ecosystem
- Section 2 : Cassandra Basics
- Design and architectural overview
- Cassandra nodes, clusters, and datacenters
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and token mechanisms
- 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 appropriate columns and types
- Defining primary keys
- Structuring data for rows and columns
- Time to Live (TTL) settings
- Executing queries with CQL
- Updating data via CQL
- Working with collections (list / map / set)
- Labs: Data modeling exercises using CQL; experimenting with various queries and 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 management
- Using counters
- Lightweight transactions (LWT)
- Labs: Creating and utilizing indexes; modeling time series data
- Section 5 : Cassandra Internals
- Understanding Cassandra's internal design
- SSTables, memtables, and the commit log
- Section 6: Administration
- Hardware selection criteria
- Cassandra distributions
- Communication between Cassandra nodes
- Data writing and reading from the storage engine
- Managing data directories
- Anti-entropy operations
- Cassandra compaction processes
- Selecting and implementing compaction strategies
- Cassandra best practices (compaction, garbage collection)
- Setting up a low-memory footprint test instance
- Troubleshooting tools and strategies
- Lab: Installing Cassandra and running performance benchmarks
Requirements
- Proficiency in Linux environments, including command-line navigation and file editing using vi or nano
- For in-person sessions: a laptop or desktop computer with 8 GB of RAM
- For remote sessions: no specific setup is required other than a web browser, as a working Cassandra lab environment will be provided
Testimonials (2)
Extensive knowledge of NoSQL environments, not only Cassandra (ex: HADOOP)
Stefan Marcoci - Videotron ltee
Course - Cassandra Administration
The 1:1 style meant the training was tailored to my individual needs.
