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Course Outline
- Section 1: Introduction to Big Data and NoSQL
- Overview of NoSQL
- The CAP theorem
- Identifying when NoSQL is the appropriate solution
- Columnar storage concepts
- The broader NoSQL ecosystem
- Section 2: Fundamentals of Cassandra
- System design and architecture
- Understanding Cassandra nodes, clusters, and datacenters
- Structuring data: keyspaces, tables, rows, and columns
- Mechanisms for partitioning, replication, and tokens
- Quorum protocols and consistency levels
- Hands-on 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 types
- Determining primary keys
- Data layout strategies for rows and columns
- Implementing Time to Live (TTL)
- Executing queries with CQL
- Performing CQL updates
- Working with collections (lists, maps, and sets)
- Hands-on labs: Data modeling exercises in CQL; experimenting with queries and data types
- Section 4: Data Modeling – Part 2
- Creating and leveraging secondary indexes
- Utilizing composite keys (partition and clustering keys)
- Managing time series data
- Best practices for time series implementation
- Using counters
- Lightweight Transactions (LWT)
- Hands-on labs: Index creation and usage; modeling time series data
- Section 5: Inside Cassandra
- Understanding the internal design and mechanics of Cassandra
- Key components: sstables, memtables, and the commit log
- Section 6: Administration
- Selecting appropriate hardware
- Reviewing Cassandra distributions
- Communication between Cassandra nodes
- Writing to and reading from the storage engine
- Managing data directories
- Anti-entropy processes
- Cassandra compaction mechanisms
- Selecting and implementing compaction strategies
- Best practices for compaction and garbage collection
- Setting up a low-memory test Cassandra instance
- Troubleshooting tools and tips
- Hands-on labs: Installing Cassandra and running benchmarks
Requirements
- Proficiency in Linux environments (navigating the command line and editing files using vi or nano)
- For on-site training: A laptop or desktop computer with at least 8 GB of RAM
- For remote training: A fully configured Cassandra lab environment will be provided, requiring only 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.
