Description

On-Premise Course during September -2025
Venue: London/Birmingham/Manchester
Note: Actual venue and schedule will be shared after registeration
Prerequisite: Anyone willing to learn and Adopt Cassandra
1. Introduction to Cassandra Enterprise
a. Comparision of RDBMS and NOSQL
b. What is Cassandra
c. Why Cassandra

2. Cassandra Enterprise Operations & Tuning
a. Introduction to Environment Setup
b. Virtual nodes (Vnodes) and Single-Token Nodes
c. Managing Cassandra Pre checks and Increasing Nodes
d. How to Add Nodes
e. Maintaining Cassandra
f. Monitor Performance
g. Environment Tuning
h. Cassendra Tunning
i. Disk Tuning
3. Combining Cassandra with Apache Solr enables full-text search capabilities
a. Introduction
b. Use cases
c. Search large volumes of textual data efficiently
d. Use Solr query syntax to perform complex search
e. Solr Schema & Core
4. Cassandra Core Concepts
a. Operating System Readiness: Ensure the OS is optimized for running Cassandra
b. Install a Cassandra Distribution
c. Configure & Manage
d. Starting & Stopping
e. Using Node tool
f. Interacting Cassandra using CQLSH
g. Cluster Configuration Manager Overview
h. Internal Architecture
i. Replication & Consistency
j. Ensuring data consistency across nodes “Anti Entropy Operation”
k. Nodes communication and share state information
l. System Key-Space
5. Introduction to Data Model and CQL
a. Analogue to table in RDBMS “Column Families”
b. Column Families to CQL
c. CQL to DDL
d. Clustering Order
e. Indexing Non Primary Key columns “Secondary Index”
f. Special Data Types: UUID , Timestamp , Counter
g. Complex Data Type for Advance Modelling: Collections , UDT , Tuple
h. DevCenter
i. CRUD Operation: Insert, Update , DELETE , TTL ,LWT
j. Data Modelling functions in Cassandra
6. Data Modeling with Cassandra Enterprise
a. Introduction to KillrVideo
b. Quick Wins & Conceptual Data Modelling
c. Relationship Keys & Hierarchy
d. Modelling Methodologies
e. Visual representation of Cassandra data models “Chebotko Diagrams”
f. Mapping Rules & Patterns
g. Data Duplication
h. Balancing consistency and availability
i. Techniques for aggregating data
7. Cassandra Enterprise Analytics with Apache Spark
a. Spark Architecture & components
i. Spark Shell & Web UI
b. Resilient Distributed Datasets Transformation and Actions
c. Reading, Processing & Converting Data from Cassandra
d. Caching and persisting RDD
e. Introduction to Pair RDDs
f. Aggregation & Grouping and Sorting – Application on Key / Value Pairs
g. Partitioning & Data Shuffling
h. Spark/Cassandra Connector
i. Spark SQL
j. Transactions