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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL concepts
- The CAP theorem
- Identifying scenarios suitable for NoSQL
- Columnar storage structures
- 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 management
- Quorum and consistency levels
- Lab: Interacting with Cassandra using CQLSH
- Section 3: Data Modeling – part 1
- Introduction to CQL
- CQL data types
- Creating keyspaces and tables
- Selecting appropriate columns and data types
- Determining primary keys
- Data layout for rows and columns
- Time to live (TTL) configurations
- Executing queries with CQL
- Performing CQL updates
- Working with collections (list / map / set)
- Lab: 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 applications
- Using counters
- Lightweight transactions (LWT)
- Lab: Index creation and usage; modeling time series data
- Section 5: Cassandra Internals
- Understanding the underlying design of Cassandra
- sstables, memtables, and the commit log
- Section 6: Administration
- Hardware selection criteria
- Available Cassandra distributions
- Communication between Cassandra nodes
- Writing and reading data to/from the storage engine
- Managing data directories
- Anti-entropy operations
- Cassandra compaction processes
- Selecting and implementing compaction strategies
- Cassandra best practices (compaction, garbage collection)
- Setting up a test Cassandra instance with low memory usage
- Troubleshooting tools and practical tips
- Lab: Installing Cassandra and running performance benchmarks
Requirements
- Proficiency in Linux environments, including command-line navigation and file editing using vi / nano
- For on-site courses: a laptop or desktop equipped with at least 8 GB of RAM
- For remote courses: no special setup is required beyond a web browser, as a functional Cassandra lab environment will be provided
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.
