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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- NoSQL overview
- CAP theorem
- When is NoSQL appropriate
- Columnar storage
- NoSQL ecosystem
- Section 2 : Cassandra Basics
- Design and architecture
- Cassandra nodes, clusters, datacenters
- Keyspaces, tables, rows and columns
- Partitioning, replication, tokens
- Quorum and consistency levels
- Labs : interacting with Cassandra using CQLSH
- Section 3: Data Modeling – part 1
- Introduction to CQL
- CQL Datatypes
- Creating keyspaces & tables
- Choosing columns and types
- Choosing 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 design under the hood
- SStables, memtables, commit log
- Section 6: Administration
- Hardware selection
- Cassandra distributions
- Cassandra Nodes 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)
- Creating a test Cassandra instance with a low memory footprint
- Troubleshooting tools and tips
- Lab : students install Cassandra, run benchmarks
Requirements
- Familiarity with the Linux environment, including navigating the command line and editing files using vi or nano
- For on-site courses: A laptop or desktop with 8 GB of RAM
- For remote courses: A functional Cassandra lab environment will be provided; all that is required 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.
