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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- NoSQL overview
- CAP theorem
- When to use NoSQL
- Columnar storage
- NoSQL ecosystem
- Section 2: Cassandra Basics
- Design and architecture
- Cassandra nodes, clusters, and datacenters
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and tokens
- Quorum and consistency levels
- Labs: interacting with Cassandra via CQLSH
- Section 3: Data Modeling – Part 1
- Introduction to CQL
- CQL data types
- Creating keyspaces and tables
- Choosing columns and data types
- Selecting primary keys
- Data layout for rows and columns
- Time to live (TTL)
- Querying with CQL
- CQL updates
- 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 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 underlying design
- SSTables, memtables, and commit log
- Section 6: Administration
- Hardware selection
- Cassandra distributions
- Cassandra node communication
- Writing and reading data to/from the storage engine
- Data directories
- Anti-entropy operations
- Cassandra compaction
- Choosing and implementing compaction strategies
- Cassandra best practices (compaction, garbage collection)
- Setting up a test Cassandra instance with a low memory footprint
- Troubleshooting tools and tips
- Lab: students install Cassandra and run benchmarks
Requirements
- Proficiency in a Linux environment (command line navigation, editing files with vi/nano)
- For in-person classes: a laptop or desktop with at least 8 GB of RAM
- For online classes: a pre-configured Cassandra lab environment is provided; all you need is 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.
