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Course Outline
- Section 1: Introduction to Big Data / NoSQL
- Overview of NoSQL
- The CAP theorem
- When to choose NoSQL
- Columnar storage structures
- The NoSQL ecosystem
- Section 2 : Cassandra Basics
- Design philosophy and architecture
- Nodes, clusters, and datacenters in Cassandra
- 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 Datatypes
- Creating keyspaces and tables
- Selecting columns and appropriate types
- Defining primary keys
- Organizing row and column data layout
- Time to live (TTL)
- Executing queries with CQL
- Performing CQL updates
- Working with collections (lists, maps, sets)
- Labs : Completing various data modeling exercises using CQL; experimenting with queries and supported data types
- Section 4: Data Modeling – part 2
- Creating and utilizing secondary indexes
- Composite keys (partition keys and clustering keys)
- Handling time series data
- Best practices for time series data
- Using counters
- Lightweight transactions (LWT)
- Labs : Creating and using indexes; modeling time series data
- Section 5 : Data Modeling Labs : Group design session
- Presentation of multiple use cases across various domains
- Collaborative group work to design and model solutions
- Discussion of different designs and analysis of design decisions
- Lab : Implementing one of the presented scenarios
- Section 6: Cassandra drivers
- Introduction to the Java driver
- Performing CRUD (Create, Read, Update, Delete) operations via the Java client
- Executing asynchronous queries
- Labs : Using the Java API for Cassandra
- Section 7 : Cassandra Internals
- Understanding the underlying Cassandra design
- SSTables, memtables, and the commit log
- The read and write paths
- Caching mechanisms
- Virtual nodes (vnodes)
- Section 8: Administration
- Selecting appropriate hardware
- Overview of Cassandra distributions
- Installing Cassandra
- Conducting benchmark tests
- Tools for monitoring performance and node activity
- DataStax OpsCenter
- Diagnosing performance issues in Cassandra
- Investigating node crashes
- Understanding data repair, deletion, and replication
- Additional troubleshooting tools and tips
- Cassandra best practices (compaction, garbage collection, etc.)
- Section 9: Bonus Lab (time permitting)
- Implementing a music streaming service similar to Pandora or Spotify using Cassandra
Requirements
- Familiarity with the Java programming language
- Comfortable working in a Linux environment (navigating the command line, editing files using vi or nano)
Lab environment:
A pre-configured Cassandra environment will be made available to all students. Access requires only an SSH client and a web browser.
Zero Install : There is no need to install Cassandra on your personal machine.
21 Hours
Testimonials (1)
It was informative.
