Get in Touch

Course Outline

  • Section 1: Introduction to Big Data / NoSQL
    • Overview of NoSQL
    • CAP theorem
    • Identifying when NoSQL is appropriate
    • Columnar storage
    • The NoSQL ecosystem
  • Section 2 : Cassandra Basics
    • Design and architecture
    • Cassandra nodes, clusters, and datacentres
    • 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
    • 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 modelling 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; modelling time series data
  • Section 5 : Cassandra Internals
    • Understanding Cassandra design under the hood
    • sstables, memtables, and commit log
  • Section 6: Administration
    • Hardware selection
    • Cassandra distributions
    • Communication between Cassandra nodes
    • Writing and reading data to and from the storage engine
    • Data directories
    • Anti-entropy operations
    • Cassandra Compaction
    • Choosing and implementing compaction strategies
    • Cassandra best practices (compaction, garbage collection, etc.)
    • Creating a test Cassandra instance with a low memory footprint
    • Troubleshooting tools and tips
    • Lab: Installing Cassandra and running benchmarks

Requirements

  • Confidence working within a Linux environment, including navigating the command line and editing files using vi or nano
  • For on-site delivery: a laptop or desktop computer equipped with at least 8 GB of RAM
  • For remote delivery: no local setup is required, as a functional Cassandra lab will be provided; only a web browser is needed
 14 Hours

Number of participants


Price per participant

Testimonials (2)

Provisional Upcoming Courses (Require 5+ participants)

Related Categories