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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL
- The CAP theorem
- When to use NoSQL
- Columnar storage
- The NoSQL ecosystem
- Section 2: Cassandra Basics
- Design and architecture
- Nodes, clusters, and datacenters
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and tokens
- Quorum and consistency levels
- Labs: Interacting with Cassandra using CQLSH
- Section 3: Data Modeling – Part 1
- Introduction to CQL
- CQL data types
- Creating keyspaces and tables
- Selecting columns and types
- Defining primary keys
- Row and column data layout
- Time to live (TTL)
- Querying with CQL
- Updating data with CQL
- Collections (list, map, set)
- Labs: Data modeling exercises using CQL; experimenting with queries and supported data types
- Section 4: Data Modeling – Part 2
- Creating and using secondary indexes
- Composite keys (partition keys and clustering keys)
- Time series data
- Best practices for time series data
- Counters
- Lightweight transactions (LWT)
- Labs: Creating and using indexes; modeling time series data
- Section 5: Cassandra Internals
- Understanding Cassandra’s internal design
- SSTables, memtables, and commit log
- Section 6: Administration
- Hardware selection
- Cassandra distributions
- Node communication
- Reading and writing data to the storage engine
- Data directories
- Anti-entropy operations
- Cassandra compaction
- Selecting and implementing compaction strategies
- Best practices for compaction and garbage collection
- Setting up a test Cassandra instance with a low memory footprint
- Troubleshooting tools and tips
- Lab: Installing Cassandra and running benchmarks
Requirements
- Familiarity with the Linux environment (command-line navigation, file editing with vi or nano)
- For in-person training: A laptop or desktop equipped with 8 GB of RAM
- For online training: A pre-configured Cassandra lab environment will be provided; only a web browser is required on your end
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.
