Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL databases
- The CAP theorem
- Scenarios where NoSQL is suitable
- Columnar storage concepts
- The NoSQL ecosystem
- Section 2 : Cassandra Basics
- Design and architectural overview
- Cassandra nodes, clusters, and datacenters
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and token management
- Quorum mechanisms 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 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
- Collections (list / map / set)
- Labs : various data modeling exercises using CQL ; experimenting with queries and supported data types
- Section 4: Data Modeling – part 2
- Creation and utilization of secondary indexes
- Composite keys (partition keys and clustering keys)
- Handling time series data
- Best practices for time series implementation
- Counters
- Lightweight transactions (LWT)
- Labs : creating and using indexes; modeling time series data
- Section 5 : Cassandra Internals
- Understanding Cassandra design under the hood
- sstables, memtables, and commit log
- Section 6: Administration
- Hardware selection considerations
- Cassandra distributions
- Communication between Cassandra Nodes
- Reading and writing data to/from the storage engine
- Managing 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 low memory footprint
- Troubleshooting tools and tips
- Lab : students install Cassandra, run benchmarks
Requirements
- Proficiency in navigating the Linux environment, including command-line usage and file editing via vi or nano
- For in-person sessions, a laptop or desktop computer equipped with 8 GB of RAM
- For remote sessions, a functional Cassandra lab environment is provided; a web browser is the only requirement
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.
