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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 using CQLSH
- Section 3: Data Modeling – Part 1
- Introduction to CQL
- CQL Data Types
- Creating keyspaces and tables
- Selecting columns and data types
- Choosing primary keys
- Row and column data layout
- Time to live (TTL)
- Querying with CQL
- Updating data with CQL
- Collections (list, map, and 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 : Data Modeling Labs : Group Design Session
- Multiple use cases from various domains are presented
- Students work in groups to develop designs and models
- Discussion of various designs and analysis of design decisions
- Lab : implementation of one of the scenarios
- Section 6: Cassandra Drivers
- Introduction to the Java driver
- CRUD (Create, Read, Update, Delete) operations using the Java client
- Asynchronous queries
- Labs : using the Java API for Cassandra
- Section 7 : Cassandra Internals
- Understanding Cassandra's underlying design
- SSTables, Memtables, and Commit Log
- Read and write paths
- Caching mechanisms
- VNodes
- Section 8: Administration
- Hardware selection
- Cassandra distributions
- Installing Cassandra
- Running benchmarks
- Tools for monitoring performance and node activities
- DataStax OpsCenter
- Diagnosing Cassandra performance issues
- Investigating node crashes
- Understanding data repair, deletion, and replication
- Additional troubleshooting tools and tips
- Cassandra best practices (compaction, garbage collection)
- Section 9: Bonus Lab (time permitting)
- Implement a music service similar to Pandora or Spotify on Cassandra
Requirements
- Proficiency in the Java programming language
- Familiarity with the Linux environment (command-line navigation, file editing with vi or nano)
Lab environment:
A fully functional Cassandra environment will be provided for students. Access to the cluster requires an SSH client and a web browser.
Zero Install : No need to install Cassandra on your own machines!
21 Hours
Testimonials (1)
It was informative.
