Apache Cassandra Certification Training

Learn to host a Cassandra database on cloud, integrate with various Apache frameworks

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Key Highlights

  • 24 Hours of Live Instructor-led Classes
  • 8 sessions of 3 hours each on Weekends
  • Live Project on Real-life Case Studies
  • Practical Assignments
  • Lifetime Access to Learning Management System
  • 24x7 Expert Support
  • Course Completion Certificate
  • Online Forum for Discussions

Course Price

$349.00 $700.00

Contact Us

1866-216-7898

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Available Courses Delivery

This course is available in the following formats:

Course Overview

Cassandra is an extensively scalable database that can manage and support a large amount of unorganized data. The Apache Cassandra Certification Training educates about database operations, node operations, table operations, cluster management, performance tuning, and more. With training, you?ll be able to host a Cassandra Database on cloud and integrate it with other Apache frameworks like Kafka, Spark, Hadoop.

Course Objectives

  • Extensive knowledge of NoSQL database, including fault tolerance, fast processing, scalability, and high availability features
  • In-depth knowledge of Cassandra database architecture
  • Gain experience in Single & Multi-Node Cluster setup using Nodetool
  • Get acquainted with industry-based projects and several case studies from various niches

Career Benefits

  • Learn an extremely fast NoSQL database system
  • Grab better database administration opportunities in the market
  • Manage clusters better with Cassandra Admin operations
  • Better remunerations

Prerequisites

  • None, but knowledge of Linux command line helps, along with RDBMS education

Who should take up?

  • Big Data Developer/Administrator/Architect/Analyst/Engineer
  • Software Architect Engineer/Developer
  • Solution Delivery Consultant
  • Senior BI/ETL Developer
  • NoSQL Big Data Developer

Course Content

  • Introduction to Big Data and Problems caused by it
  • 5V ? Volume, Variety, Velocity, Veracity and Value
  • Traditional Database Management System
  • Limitations of RDMS
  • NOSQL databases
  • Common characteristics of NoSQL databases
  • CAP theorem
  • How Cassandra solves the Limitations?
  • History of Cassandra
  • Features of Cassandra
  • Introduction to Database Model
  • Understand the analogy between RDBMS and Cassandra Data Model
  • Understand following Database Elements: Cluster, Keyspace, Column Family/Table, Column
  • Column Family Options
  • Columns
  • Wide Rows, Skinny Rows
  • Static and dynamic tables
  • Cassandra as a Distributed Database
  • Key Cassandra Elements
  • a. Memtable
  • b. Commit log
  • c. SSTables
  • Replication Factor
  • Data Replication in Cassandra
  • Gossip protocol ? Detecting failures
  • Gossip: Uses
  • Snitch: Uses
  • Data Distribution
  • Staged Event-Driven Architecture (SEDA)
  • Managers and Services
  • Virtual Nodes: Write path and Read path
  • Consistency level
  • Repair
  • Incremental repair
  • Replication Factor
  • Replication Strategy
  • Defining columns and data types
  • Defining a partition key
  • Recognizing a partition key
  • Specifying a descending clustering order
  • Updating data
  • Tombstones
  • Deleting data
  • Using TTL
  • Updating a TTL
  • Cassandra nodes
  • Specifying seed nodes
  • Bootstrapping a node
  • Adding a node (Commissioning) in Cluster
  • Removing (Decommissioning) a node
  • Removing a dead node
  • Repair
  • Read Repair
  • What?s new in incremental repair
  • Run a Repair Operation
  • Cassandra and Spark Implementation
  • Cassandra monitoring tools
  • Logging
  • Tailing
  • Using Nodetool Utility
  • Using JConsole
  • Learning about OpsCenter
  • Runtime Analysis Tools
  • Creating a Snapshot
  • Restoring from a Snapshot
  • RAM and CPU recommendations
  • Hardware choices
  • Selecting storage
  • Types of Storage to Avoid
  • Cluster connectivity, security and the factors that affect distributed system performance
  • End-to-end performance tuning of Cassandra clusters against very large data sets
  • Load balance and streams
  • Security
  • Ongoing Support of Cassandra Operational Data
  • Hosting a Cassandra Database on Cloud

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