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Duration 14 hours
Course Outline
- Section 1: Introduction to Big Data and NoSQL
- Overview of NoSQL databases
- The CAP theorem
- Determining when NoSQL is the appropriate choice
- Columnar storage mechanisms
- The broader NoSQL ecosystem
- Section 2: Cassandra Fundamentals
- System design and architecture
- Understanding Cassandra nodes, clusters, and datacenters
- Key concepts: Keyspaces, tables, rows, and columns
- Partitioning, replication, and token distribution
- Quorum and consistency levels
- Practical lab: 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
- Data layout for rows and columns
- Time to Live (TTL) settings
- Executing queries with CQL
- Performing CQL updates
- Working with collections (lists, maps, and sets)
- Practical lab: Various data modeling exercises using CQL, including experimentation 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 managing time series data
- Counters
- Lightweight transactions (LWT)
- Practical lab: Creating and using indexes, and modeling time series data
- Section 5: Cassandra Internals
- Understanding the underlying Cassandra design
- SSTables, memtables, and the commit log
- Section 6: Administration
- Hardware selection criteria
- Cassandra distributions
- Inter-node communication in Cassandra
- Data writing and reading via the storage engine
- Managing data directories
- Anti-entropy operations
- Cassandra compaction processes
- Selecting and implementing compaction strategies
- Cassandra best practices (including compaction and garbage collection)
- Setting up a low-memory footprint test instance
- Troubleshooting tools and tips
- Practical lab: Installing Cassandra and running benchmarks
Requirements
- Proficiency in Linux environments (including command-line navigation and file editing with vi or nano)
- For on-site courses: a laptop or desktop equipped with 8 GB of RAM
- For remote courses: A working Cassandra lab environment will be provided, requiring only a web browser
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.
