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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL concepts
- The CAP theorem
- Appropriate use cases for NoSQL
- Columnar storage mechanisms
- The NoSQL ecosystem
- Section 2 : Cassandra Basics
- Design and architectural overview
- Understanding Cassandra nodes, clusters, and datacenters
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and token distribution
- Quorum and consistency levels
- Practical labs: Interacting with Cassandra using CQLSH
- Section 3: Data Modeling – part 1
- Introduction to CQL
- CQL datatypes
- Creating keyspaces and tables
- Selecting appropriate columns and data types
- Defining primary keys
- Data layout for rows and columns
- Time to Live (TTL) settings
- Executing queries with CQL
- Performing updates in CQL
- Managing collections (list / map / set)
- Practical labs: Various data modeling exercises using CQL; experimenting 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 time series data management
- Working with counters
- Lightweight Transactions (LWT)
- Practical labs: Creating and using 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 criteria
- Cassandra distributions
- Communication between Cassandra nodes
- Writing and reading data to/from the storage engine
- Configuring data directories
- Anti-entropy operations
- Cassandra Compaction mechanisms
- 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 diagnostic tips
- Practical lab: Installing Cassandra and executing benchmarks
Requirements
- Familiarity with the Linux environment, including command-line navigation and file editing using vi or nano
- For on-site sessions, a laptop or desktop equipped with at least 8 GB of RAM
- For remote sessions, a functional Cassandra lab environment will be provided; participants only need 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.
