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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL databases
- Understanding the CAP theorem
- Scenarios where NoSQL is appropriate
- Concepts in columnar storage
- The broader NoSQL ecosystem
- Section 2: Cassandra Basics
- System design and architecture
- Cassandra nodes, clusters, and data centres
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and token rings
- Quorum mechanisms and consistency levels
- Labs: Interacting with Cassandra using CQLSH
- Section 3: Data Modelling – Part 1
- Introduction to CQL
- CQL data types
- Creating keyspaces and tables
- Selecting appropriate columns and types
- Defining primary keys
- Data layout considerations for rows and columns
- Time-to-live (TTL) settings
- Executing queries with CQL
- Performing CQL updates
- Working with collections (list, map, set)
- Labs: Various data modelling exercises using CQL; experimenting with queries and supported data types
- Section 4: Data Modelling – Part 2
- Creating and utilising secondary indexes
- Composite keys (partition keys and clustering keys)
- Handling time-series data
- Best practices for time-series storage
- Counters
- Lightweight Transactions (LWT)
- Labs: Creating and using indexes; modelling time-series data
- Section 5: Cassandra Internals
- Understanding the internal design of Cassandra
- SSTables, memtables, and commit logs
- Section 6: Administration
- Hardware selection considerations
- Available Cassandra distributions
- Cassandra node communication protocols
- Writing and reading data to/from the storage engine
- Managing data directories
- Anti-entropy operations
- Cassandra compaction processes
- Choosing and implementing compaction strategies
- Cassandra best practices (including compaction and garbage collection)
- Creating a test Cassandra instance with a low memory footprint
- Troubleshooting tools and practical tips
- Lab: Installing Cassandra and running performance benchmarks
Requirements
- Confidence in using the Linux environment, including command-line navigation and file editing with vi or nano
- For on-site training, a laptop or desktop computer equipped with at least 8 GB of RAM
- For remote courses, a fully configured Cassandra lab environment will be provided; participants only need a web browser to access it
14 Hours
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.
