Cassandra Certification

Curriculum

1 Introduction to Cassandra
Learning Objective:
Get introduced to Apache Cassandra and some of its design considerations and components and learn about various use cases of Cassandra.

• Differences between NoSQL and RDBMS
• Replication in RDBMS
• Key Challenges with RDBMS
• Schema
• Advantage & Limitation
• Key Characteristics of No SQL Data Base
• Advantages of Cassandra
• Where and when to use it?
• Brewers CAP Theorem
• Cassandra Key Features
• Distributed and Decentralised
• Elastic Scalability
• High Availability and Fault Tolerance
• Tuneable Consistency
• Strict Consistency
• Casual Consistency
• Weak (Eventual Consistency)
• Column Orientation
• Column Orientation
• Introduction to Cassandra
• USE Cases for Cassandra

2 Getting Started with Cassandra
Learning Objective:
Install and configure Cassandra. Build your own local, single-node cluster. Learn about CCM with some basic commands with Cassandra's nodetool.

• Installation
• Configuration
• Starting Cassandra
• Cassandra Cluster Manager
• Introduction to the data model
• Shutting down Cassandra

Hands-on:

• Installation and configuration
• Starting up and shutting down Cassandra

3 Cassandra Data Model
Learning Objective:
Learn to run Command-Line Client Interface, connect to a server. Also, learn about the relational data model, design differences between RDBMS and Cassandra.

• Installation
• Running the Command-Line Client Interface
• Basic CLI Commands, Help
• Connecting to a Server, Describing the Environment
• Creating and Keyspace and Column Family
• Writing and Reading Data
• The Relational Data Model
• Cluster
• Keyspaces
• What is Column oriented database
• Column Families
• Column Family Options
• Columns
• Wide Rows
• Skinny Rows
• Column Sorting
• Super Columns
• Composite Keys
• Design Differences between RDBMS and CASSANDRA
• Query Language
• Referential Integrity
• Secondary Indexes
• Sorting, DeNormalisation
• Design Patterns
• Materialized Views

Hands-on:

• Run Command- Line Client Interface. Read and write data.

4 Steps in Configuration
Learning Objective:
Learn to configure a data model.

• Token calculation
• Configuration overview
• Node tool
• Validators
• Comparators
• Expiring column

Hands-on:

• Configure a data model using Token calculation, node tool, validators, comparators.

5 Cassandra Architecture
Learning Objective:
Learn about the concepts that influenced Cassandra's design and use. Understand Brewer's CAP theorem data-distribution and partitioning; Cassandra's read and write paths; how data is stored on-disk; inner workings of components such as the snitch, tombstones, and failure-detection; and the delivered security features.

• Cassandra's ring architecture
• Cassandra's write path
• Cassandra's read path
• On-disk storage
• Additional components of Cassandra

Hands-on:

• Problems that Cassandra was designed to solve
  Cassandra's read and write paths
  The role that horizontal scaling plays
  How data is stored on-disk
  How Cassandra handles failure scenarios

6 Cassandra Query Language (CQL)
Learning Objective:
Learn about CQL, its syntax and usage and evolution as a language and comparing some of its capabilities to the well-known SQL of the relational database world.

• Overview of Cassandra Data Modeling
• cqlsh
• Getting started with CQL

Hands-on:

• Build primary keys that facilitate high-performing data models at scale
  Use CQL syntax and solve different types of problems using it

7 Configuring a Cluster
Learning Objective:
Learn to start the cluster, examine its performance, make an adjustment, and test.

• Evaluating instance requirement
• Operating systems optimization
• Configuring the JVM
• Configuring Cassandra

Hands-on:

• Sizing hardware and computer resources for Cassandra deployments
  Operating system optimizations
  Configuring the JVM
  Configuring Cassandra

8 Performance Tuning
Learning Objective:
Learn about Cassandra-Stress and how to establish a performance baseline for a specific data model. Evaluate factors that can influence write performance. Understand read performance, and the different configuration properties that can help Apache Cassandra perform well during read-heavy and mixed workloads.

• Cassandra Stress
• Write performance
• Read performance
• Other performance considerations

Hands-on: 

• Using the Cassandra-Stress tool discover opportunities for improvement
  Looking into situations to apply different table-compaction strategies
  Examining Apache Cassandra's cache and compression options
  Improving upon the efficiency of the JVM
  Optimizing network settings and configuration to avoid performance bottlenecks.

9 Managing a Cluster
Learning Objective:
Learn to scale your cluster horizontally, as well as to remove and replace failed nodes.

• Add/Remove Nodes
• Scaling Up
• Scaling Down
• Backing up and restoring data
• Maintenance

Hands-on:

• Adding and removing nodes
  Working with logical data centers
  Backups
  Techniques for ensuring data consistency.

10 Monitoring
Learning Objective:
Learn about the wide variety of options available for monitoring and logging for Apache Cassandra, which will help in identifying issues proactively.

• JMX interface
• Node tool utility
• Metric stack
• Log stack
• Troubleshooting

Hands-on:

Understand different monitoring and logging tools, and how they provide more insight for problem solving on your cluster.
Make decisions using reliable out-of-the-box applications from the open source community, including installing, configuring, analyzing, and setting up alerting.

11 Application Development
Learning Objective:
Learn the correct use cases and database selection. Discover the DataStax Java driver, its behaviors and configurations, and how it interacts with Apache Cassandra.

• Common mistakes made at the application and data model levels
• Driver selection
• Appropriate connection properties
• Handling simple and complex result sets in Java
• Loading data without overwhelming your nodes

Hands-on:

• Select Driver
• Appropriate connection properties
• Handling simple and complex result sets in Java
• Loading data without overwhelming your nodes.

12 Integrating Cassandra with Apache Spark
Learning Objective:
Learn about Spark architecture, which stands on top among other sets of available tools; it offers ease of installation and a huge community, as well as backing up on Hadoop for data warehousing. Get to know the different ways of installation, along with a custom all-in-one Docker image, which has Apache Cassandra, a monitoring stack, and Spark including PySpark, SparkR, and Jupyter with their dependencies.

• Spark (architecture, installation, and configuration)
• PySpark
• SparkR
• Read, transform, and write
• The Jupyter web interface

Hands-on:

• Read, transform, and write
• Work with Jupyter web interface.