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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL databases
- The CAP theorem
- Scenarios suitable for NoSQL solutions
- Columnar storage concepts
- The broader NoSQL ecosystem
- Section 2 : Cassandra Basics
- System design and architecture
- Understanding Cassandra nodes, clusters, and datacenters
- Key components: keyspaces, tables, rows, and columns
- Partitioning, replication, and token distribution
- Quorum mechanisms and consistency levels
- Labs: Interacting with Cassandra via CQLSH
- Section 3: Data Modeling – part 1
- Introduction to CQL
- Supported CQL data types
- Creating keyspaces and tables
- Selecting appropriate columns and data types
- Defining primary keys effectively
- Data layout considerations for rows and columns
- Managing Time to Live (TTL)
- Executing queries with CQL
- Performing updates in CQL
- Working with collections (list / map / set)
- Labs: Various data modeling exercises using CQL; experimenting with queries and supported data types
- Section 4: Data Modeling – part 2
- Creating and utilising 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 underlying design of Cassandra
- Key components: sstables, memtables, and the commit log
- Section 6: Administration
- Selecting appropriate hardware
- Available Cassandra distributions
- Communication between Cassandra nodes
- Data writing and reading to/from 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 practical tips
- Lab: Students install Cassandra and run performance benchmarks
Requirements
- Proficiency with Linux environments (including command-line navigation and file editing using vi or nano)
- For on-site training, a laptop or desktop equipped with 8 GB of RAM
- For remote sessions, a fully functional Cassandra lab environment will be provided; you only need a web browser to participate
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.
