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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 Fundamentals
- Design and architecture
- Cassandra nodes, clusters, and data centers
- Keyspaces, tables, rows, and columns
- Partitioning, replication, and tokens
- Quorum and consistency levels
- Labs: interacting with Cassandra via CQLSH
- Section 3: Data Modeling – Part 1
- Introduction to CQL
- CQL Data Types
- Creating keyspaces and tables
- Selecting columns and data types
- Defining primary keys
- Data layout for rows and columns
- Time to Live (TTL)
- Querying with CQL
- Updating data with CQL
- Collections (list, map, set)
- Labs: various data modeling exercises using CQL; exploring 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 develop designs and models
- Discussion of various designs and analysis of design decisions
- Lab: implementation of one selected scenario
- Section 6: Cassandra Drivers
- Introduction to the Java driver
- CRUD (Create, Read, Update, Delete) operations using the Java client
- Asynchronous queries
- Labs: utilizing 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 (if time permits)
- Implement a music streaming service similar to Pandora or Spotify on Cassandra
Requirements
- Familiarity with the Java programming language
- Comfort in a Linux environment (navigating the command line, editing files with vi or nano)
Lab environment:
A fully operational Cassandra environment will be provided for all students. Participants will need an SSH client and a web browser to access the cluster.
Zero Install : No installation of Cassandra on personal machines is required.
21 Hours
Testimonials (1)
It was informative.
