Apache Cassandra Online Course

Cassandra is a NoSQL database with decentralized, fault-tolerant, scalable, and low-cost features, making it a core component of cloud computing systems. The more recent versions have greatly improved the security features, making it suitable for use in enterprise systems. In this tutorial, you’ll see how Cassandra overcomes the challenges that relational databases face during high scalability demand. You will become familiar with the Cassandra terminologies, components, and their roles.

Then you will learn how to create a multi-node Cassandra structure, understand the roles and responsibilities of Cassandra components, and see the data flow during database operations that demand speed, accuracy, and durability.

Course Table of Contents

Introduction to Cassandra

• The Course Overview
• What Is Apache Cassandra?
• Key Space, Table Schema, Partition Key, and Clustering Key
• Start a Single Node Cassandra Database
• Introduction to Cqlsh Command Line Client
• Loading and Reading Data

Cassandra Distributed Architecture

• Node and Ring Structure
• Replication and Consistency Model
• Racks and Datacenters
• CAP Theorem
• Gossip
• Read Repair, Hinted Handoff

Diagnostics

• Understanding Files in the Data Directory
• Use Nodetool to Examine Performance Statistics
• System and Output Logs
• JMX to Monitor Metrics
• Choosing the Appropriate Compaction Strategy

Data Modelling Principles

• Primary Key and Cluster Ordering
• Denormalization and Design for the Read Performance
• Optimizing for BlindWrites

Data Modelling in Cassandra

• Collection Types
• Static Columns
• Indexes, Materialized Views
• Data Aggregation
• compareAndSet
• Counter Type

Optimization of Data

• The Impact of Frequent Updates and Delete
• Wide Rows and Primary Key Considerations
• Load Testing with CQL Stress
• Logged and Unlogged Batching

Integrating Cassandra Database with Your Application

• A Maven Project Using the Java Driver
• Connection Information for the Driver
• Basic Statements
• Using Prepared Statements
• Understanding Errors

Overview of Apache Spark

• A What Is Apache Spark and Spark Architecture
• Get Started with Spark
• Working with Spark’s Data Structures – RDD, Data Frame, and Dataset
• Setting Up the Spark Connector

Connecting Spark with Cassandra

• Writing Data to Cassandra from Spark
• Reading Data from Cassandra Using Spark RDD
• Join, Aggregate Data Using Spark Data Frame API and Spark SQL
• Cassandra Aware Partitioning in Spark

Integrate Cassandra with Spark Streaming

• Use Cases for Near Real Time Stream Processing Using Spark Streaming
• Advanced Stream Receiver Using Kafka Connectors
• Stateless and Stateful Transformations
• Persistence of Live Stream on to Cassandra