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Duration 14 hours
Course Outline
- Module 1: Introduction to Big Data and NoSQL
- Overview of NoSQL technologies
- The CAP theorem
- Scenarios suitable for NoSQL implementations
- Columnar storage mechanisms
- The broader NoSQL ecosystem
- Module 2: Fundamentals of Cassandra
- System design and architecture
- Nodes, clusters, and data centers
- Keyspaces, tables, rows, and columns
- Partitioning strategies, replication, and token rings
- Quorum mechanisms and consistency levels
- Labs: Interacting with Cassandra via CQLSH
- Module 3: Data Modeling – Part 1
- Introduction to CQL
- CQL data types
- Creating keyspaces and tables
- Selecting appropriate columns and data types
- Defining primary keys
- Structuring row and column data layouts
- Time-to-Live (TTL) settings
- Executing queries with CQL
- Updating data via CQL
- Working with collections (lists, maps, and sets)
- Labs: Data modeling exercises in CQL; experimenting with queries and data types
- Module 4: Data Modeling – Part 2
- Creating and utilizing secondary indexes
- Composite keys (partition and clustering keys)
- Handling time-series data
- Best practices for time-series workloads
- Implementing counters
- Lightweight Transactions (LWT)
- Labs: Index creation and usage; modeling time-series data
- Module 5: Cassandra Internals
- Understanding Cassandra’s internal design
- SSTables, memtables, and the commit log
- Module 6: Administration
- Hardware selection criteria
- Comparing Cassandra distributions
- Inter-node communication protocols
- Data I/O operations with the storage engine
- Managing data directories
- Anti-entropy processes
- Cassandra compaction processes
- Selecting and applying compaction strategies
- Best practices (compaction tuning, garbage collection)
- Setting up low-memory Cassandra instances for testing
- Troubleshooting tools and diagnostic tips
- Labs: Installing Cassandra and executing performance benchmarks
Requirements
- Proficiency in Linux environments, including command-line navigation and file editing with vi or nano
- For in-person sessions: a laptop or desktop computer equipped with 8 GB of RAM
- For virtual sessions: a pre-configured Cassandra lab environment is provided; only a web browser is required
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.
