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Duration 14 hours
Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL databases
- The CAP theorem
- Identifying appropriate use cases for NoSQL
- Columnar storage mechanisms
- The broader NoSQL ecosystem
- Section 2 : Cassandra Basics
- Design principles and architecture
- Components: nodes, clusters, and datacenters
- Logical structure: keyspaces, tables, rows, and columns
- Core concepts: partitioning, replication, and tokens
- Quorum mechanisms and consistency levels
- Labs: Interacting with Cassandra using CQLSH
- Section 3: Data Modeling – part 1
- Introduction to CQL
- Supported CQL data types
- Creating keyspaces and tables
- Selecting appropriate columns and types
- Defining primary keys
- Understanding data layout for rows and columns
- Implementing Time to Live (TTL)
- Executing queries with CQL
- Performing CQL updates
- Working with collections (lists, maps, and sets)
- Labs: Various data modeling exercises using CQL; experimenting with queries and supported data types
- Section 4: Data Modeling – part 2
- Creating and leveraging secondary indexes
- Composite keys (partition keys and clustering keys)
- Handling time series data
- Best practices for time series implementation
- Using counters
- Lightweight transactions (LWT)
- Labs: Creating and using indexes; modeling time series data
- Section 5 : Cassandra Internals
- Understanding the internal design of Cassandra
- Key components: sstables, memtables, and commit logs
- Section 6: Administration
- Hardware selection criteria
- Overview of Cassandra distributions
- Communication between Cassandra nodes
- Data writing and reading mechanisms in the storage engine
- Management of data directories
- Anti-entropy operations
- Cassandra compaction processes
- Selecting and implementing compaction strategies
- Cassandra best practices (including compaction and garbage collection)
- Setting up a test Cassandra instance with a low memory footprint
- Troubleshooting tools and practical tips
- Lab: Installing Cassandra and running benchmarks
Requirements
- Familiarity with the Linux environment, including command-line navigation and file editing via vi or nano
- For on-site training, a laptop or desktop equipped with 8 GB of RAM
- For remote training, a functional 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.
