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Course Outline
- Section 1: Introduction to Big Data and NoSQL
- Overview of NoSQL concepts
- The CAP theorem
- Scenarios suitable for NoSQL implementation
- Columnar storage structures
- The NoSQL ecosystem
- Section 2: Cassandra Fundamentals
- System design and architecture
- Components: Cassandra nodes, clusters, and datacenters
- Data organization: Keyspaces, tables, rows, and columns
- Mechanisms: Partitioning, replication, and token distribution
- Quorum logic and consistency levels
- Laboratories: Interacting with Cassandra via CQLSH
- Section 3: Data Modeling – Part 1
- Introduction to CQL
- CQL data types
- Defining keyspaces and tables
- Selection of columns and data types
- Determining primary keys
- Structuring data for rows and columns
- Time-to-live (TTL) management
- Executing queries with CQL
- Performing CQL updates
- Working with collections (lists, maps, sets)
- Laboratories: Data modeling exercises in CQL; experimenting with queries and supported data types
- Section 4: Data Modeling – Part 2
- Implementing and utilizing secondary indexes
- Composite keys (partition and clustering keys)
- Handling time-series data
- Best practices for time-series modeling
- Counter implementations
- Lightweight Transactions (LWT)
- Laboratories: Creating and utilizing indexes; modeling time-series data
- Section 5: Cassandra Internals
- Understanding the internal design of Cassandra
- Core components: SSTables, memtables, and commit logs
- Section 6: Administration
- Hardware selection criteria
- Cassandra distribution options
- Inter-node communication protocols
- Data read and write operations with the storage engine
- Managing data directories
- Anti-entropy processes
- Cassandra compaction mechanisms
- Selection and implementation of compaction strategies
- Best practices for compaction and garbage collection
- Setting up a low-memory test Cassandra instance
- Troubleshooting tools and diagnostic tips
- Laboratory: Installing Cassandra and executing performance benchmarks
Requirements
- Familiarity with Linux environments, including command-line navigation and file editing using 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 will be provided, requiring only a web browser
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.
