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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 suitable
- Columnar storage mechanisms
- The NoSQL ecosystem
- Section 2 : Cassandra Basics
- System design and architecture
- Cassandra nodes, clusters, and datacenters
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and token strategies
- 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
- Data layout for rows and columns
- Time to live (TTL) settings
- Executing queries with CQL
- Performing CQL updates
- Working with collections (list / map / set)
- Labs : Diverse data modeling exercises using CQL; testing queries and various 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
- Implementing counters
- Lightweight transactions (LWT)
- Labs : Creating and applying indexes; modeling time series data
- Section 5 : Cassandra Internals
- Understanding the underlying design of Cassandra
- SSTables, memtables, and commit logs
- Section 6: Administration
- Hardware selection considerations
- Cassandra distributions
- Communication between Cassandra nodes
- Writing and reading data within the storage engine
- Management of data directories
- Anti-entropy operations
- Cassandra compaction processes
- Selecting and implementing compaction strategies
- Cassandra best practices (compaction, garbage collection, etc.)
- Setting up a test Cassandra instance with a low memory footprint
- Troubleshooting tools and practical tips
- Lab : Installing Cassandra and executing benchmarks
Requirements
- Proficiency in a Linux environment, 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 remote sessions: A functional Cassandra lab environment will be provided; participants only require 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.
