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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL
- 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 types
- Selecting 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: Data Modeling Labs: Group Design Session
- Multiple use cases from various domains are presented
- Students collaborate in groups to design models
- Discussion of different designs and analysis of decisions
- Lab: Implement 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 path and write path
- Caching
- Vnodes
- Section 8: Administration
- Hardware selection
- Cassandra distributions
- Installing Cassandra
- Running benchmarks
- Tooling for monitoring performance and node activities
- DataStax OpsCenter
- Diagnosing Cassandra performance issues
- Investigating node crashes
- Understanding data repair, deletion, and replication
- Other troubleshooting tools and tips
- Cassandra best practices (compaction, garbage collection)
- Section 9: Bonus Lab (time permitting)
- Implement a music service like Pandora or Spotify on Cassandra
Requirements
- Comfortable with the Java programming language
- Familiar with the Linux environment (navigating the command line, editing files with vi or nano)
Lab environment:
A ready-to-use Cassandra environment will be provided for students. Access requires only an SSH client and a web browser to connect to the cluster.
Zero Install: No need to install Cassandra on your personal machine!
21 Hours
Testimonials (1)
It was informative.
