Apache Cassandra Certification Training

Goal: In this module, you will learn about Database Model and similarities between RDBMS and Cassandra Data Model. You will also understand the key Database Elements of Cassandra and learn about the concept of Primary Key.

Skills:

• Data Modelling in Cassandra
• Data Structure Design

Objectives:

At the end of this module, you will be able to

• Explain what is Database Modelling and it’s Features
• Describe the Different Types of Data Models
• List the Difference between RDBMS and Cassandra Data Model
• Define Cassandra Data Model
• Explain Cassandra Database Elements
• Implement Keyspace Creation, Updating and Deletion
• Implement Table Creation, Updating and Deletion

Topics:

• 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

Hands On:

• Creating Keyspace
• Creating Tables

Goal: Gain knowledge of architecting and creating Cassandra Database Systems. In addition, learn about the complex inner workings of Cassandra such as Gossip Protocol, Read Repairs and so on.

Skills:

• Cassandra Architecture

Objectives:

• Explain the Architecture of Cassandra
• Describe the Different Layers of Cassandra Architecture
• Learn about Gossip Protocol
• Describe Partitioning and Snitches
• Explain Vnodes and How Read and Write Path works
• Understand Compaction, Anti-Entropy and Tombstone
• Describe Repairs in Cassandra
• Explain Hinted Handoff

Topics:

• 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

Goal: In this module you will learn about Keyspace and its attributes in Cassandra. You will also create Keyspace, learn how to create a Table and perform operations like Inserting, Updating and Deleting data from a table while using CQLSH.

Skills:

• Database Operations
• Table Operations

Objectives: At the end of this module, you will be able to:

• Describe Different Data Types Used in Cassandra
• Explain Collection Types
• Describe What are CRUD Operations
• Implement Insert, Select, Update and Delete of various elements
• Implement Various Functions Used in Cassandra
• Describe Importance of Roles and Indexing
• Understand tombstones in Cassandra

Topics:

• 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

Hands-on/Demo:

• Create Keyspace in Cassandra
• Check Created Keyspace in System_Schema.Keyspaces
• Update Replication Factor of Previously Created Keyspace
• Drop Previously Created Keyspace
• Create A Table Using cqlsh
• Create A Table Using UUID & TIMEUUID
• Create A Table Using Collection & UDT Column
• Create Secondary Index On a Table
• Insert Data Into Table
• Insert Data into Table with UUID & TIMEUUID Columns
• Insert Data Using COPY Command
• Deleting Data from Table

Goal: Learn how to add nodes in Cassandra and configure Nodes using “cassandra.yaml” file. Use Nodetool to remove node and restore node back into the service. In addition, by using Nodetool repair command learn the importance of repair and how repair operation functions.

Skills:

• Node Operations

Objectives: At the end of this module, you will be able to:

• Explain Cassandra Nodes
• Understand Seed Nodes
• Configure Seed Nodes using cassandra.yaml file
• Add/bootstrap a node in a Cluster
• Use Nodetool utility to decommission a node from the cluster
• Remove a Dead Node from a Cluster
• Describe the need to repair Nodes
• Use Nodetool repair command

Topics:

• 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

Hands-on/Demo:

• Commissioning a Node
• Decommissioning a Node
• Nodetool Commands

Goal: The key aspects to monitoring Cassandra are resources used by each node, response latencies to requests, requests to offline nodes, and the compaction process. Learn to use various monitoring tools in Cassandra such as Nodetool and JConsole in this module.

Skills:

• Clustering

Objectives: At the end of this module, you will be able to:

• Describe the various monitoring tools available
• Implement nodetool utility to manage a cluster
• Use JConsole to monitor JMX statistics
• Understand OpsCenter tool

Topics:

• Cassandra monitoring tools
• Logging
• Tailing
• Using Nodetool Utility
• Using JConsole
• Learning about OpsCenter
• Runtime Analysis Tools

Hands-on/Demo:

• JMX and Jconsole
• OpsCenter

Goal: In this Module you will learn about the importance of Backup and Restore functions in Cassandra and Create Snapshots in Cassandra. You will learn about Hardware selection and Performance Tuning (Configuring Log Files) in Cassandra. You will also learn about Cassandra integration with various other frameworks.

Skills:

• Performance tuning
• Cassandra Design Principals
• Backup and Restoration

Objectives: At the end of this module, you will be able to:

• Learn backup and restore functionality and its importance
• Create a snapshot using Nodetool utility
• Restore a snapshot
• Understand how to choose the right balance of the following resources: memory, CPU, disks, number of nodes, and network.
• Understand all the logs created by Cassandra
• Explain the purpose of different log files
• Configure the log files
• Learn about Performance Tuning
• Integration with Spark and Kafka

Topics:

• 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

Hands-on/Demo:

• Creating Snapshots
• Integration with Kafka
• Integration with Spark

Goal: In this Module you will learn about Design, Implementation, and on-going support of Cassandra Operational Data. Finally, you will learn how to Host a Cassandra Database on Cloud.

Skills:

• Security
• Design Implementation
• On-going support of Cassandra Operational Data

Objectives: At the end of this module, you will be able to:

• Security
• Learn about DataStax
• Create an End-to-End Project using Cassandra
• Implement a Cassandra Database on Cloud

Topics:

• Security
• Ongoing Support of Cassandra Operational Data
• Hosting a Cassandra Database on Cloud

Hands-on/Demo:

• Hosting Cassandra Database on Amazon Web Services

This Apache Cassandra Training is designed by industry experts to help you master Apache Cassandra. The Cassandra Course offers:

• In-depth knowledge of NoSQL database, including features such as High Availablity, Fault Tolerance, Fast Processing, and Scalability
• Comprehensive knowledge of Cassandra Database and it's architecture.
• Capability to ingest data in Cassandra and perform various operations
• Experience with Single & Multi-Node Cluster setup and different Node Operations using nodetool
• Capability to Manage and Monitor the Cassandra Cluster
• Knowledge of various Security and Backup features provided by Cassandra
• Exposure to many real-life industry based Projects
• Case Studies which are diverse in nature covering banking, telecommunication, social media, and e-commerce domains

Apache Cassandra is one of the most widely used NoSQL database. It offers features such as Fault Tolerance, Scalability, Flexible Data Storage and it's efficient writes, which makes it the perfect database for various purposes. Apache Cassandra is the right choice of database if you are looking for scalability and high availability without compromising performance for your mission-critical applications.

To take benefits of these opportunities you need a structured training with an updated curriculum as per current industry requirements and best practices.

Besides strong theoretical understanding, you also need to work on real-life Cassandra projects as a part of solution strategy. It is open source and is used by many companies like Spotify, eBay, Comcast, Adobe, NASA, Netflix, and Twitter which led to increase in jobs in the Cassandra Domain.

Apache Cassandra Certification Training will help you to become a Cassandra expert. It will hone your skills by offering you comprehensive knowledge on Cassandra, it's internals and the required hands-on experience for solving real-time industry-based big data projects.

During the Cassandra Training, you will be guided and trained by our expert instructors to:

• Master the concepts of NoSQL database & understand where Cassandra is used
• Understand CAP theorem, to Cassandra's History
• Install Cassandra Single Node Cluster and manage them
• Describe Apache Cassandra Architecture
• Design and model applications for Cassandra
• Learn about Keyspaces, Tables
• Perform Cassandra Admin Operations for Managing a Cluster
• Learn concepts related to Cassandra Performance Tuning
• Implement Backup and Recovery Strategies for Cassandra
• Host Cassandra on Cloud

The market for Big Data analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Cassandra being Highly Available and extremely fast is one of the widely used NoSQL database. Our Apache Cassandra Training helps you to grab this opportunity and accelerate your career. It is best suited for:

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

As such there are no prerequisites for Apache Cassandra course. Knowledge of Linux command line is preferred. Exposure to Java, Database or Data-Warehouse concepts is a plus, but certainly not a mandate.

For this Cassandra training, we will help you to setup Brighter Connect's Virtual Machine in your System with local access. The detailed installation guides are provided in the LMS for setting up the environment. For any doubt, the 24*7 support team will promptly assist you. Brighter Connect Virtual Machine can be installed on Mac or Windows machine.

Case Study 1: Product Liking Functionality [Ecommerce]

Scenario: David is CEO of www.purhaseitnow.com. Currently, he is sDavid is CEO of www.purhaseitnow.com. Currently, he is selling 300k products per day across multiple categories. There are thousands of sellers having millions of products, registered on the portal. Soon David realizes that his sale is decreasing monthly due to the poor quality of products sold by some of the sellers. He then decided to categorize the products so that the site can recommend good products to his customers. He asked his CTO John, to develop the same functionality. John has suggested him that If they allow customers to give feedback about the product they purchased in the form of like & dislike, then they can recommend those products over other similar products.

John and Product Manager have gathered some requirements and decided to develop using Agile methodology.

Requirements:

• Get User Details by User Id
• Get Product Details by Product Id
• Get all products liked by User
• Get Product liked by Multiple Users

John is aware of RDBMS only and has suggested database schema as follows:

Tables:

• User
• User Id
• User Name
• Address

Product:

• Product Id
• Product Name
• Product Description

User Product Likes:

• User Id (FK user table)
• Product Id (FK product table)
• Timestamp

Soon after, huge data got accumulated in the last table, resulting in system imbalance. They tried to apply all optimization techniques but failed to overcome the issue.

After some digging, they realized that last 2 queries were not performing good due to.

• Tables will be huge due to large catalogue
• Retrieval products/users will take more time

To solve this, they hired you because you have some experience in NoSQL databases. You must come up with proper database selection and schema design.

Once you have finalized design you have to:

• Provide information about database type which you are opting RDBMS/NoSQL/GRAPH?
• Provide information about database why you selected?
• Provide schema details along with Primary/Partition/Composite/Clustering keys?

Extension to above problem:

• Get all products liked by a user should also return product names

Get all user names who have liked any products

Case Study 2: DOMAIN: BANK

Problem Statement:

Our consulting firm has been retained by a major bank to help improve the scalability of their current infrastructure. There are lots of transaction logs generated by various systems. Current database MySQL is not able to handle all the logs. The Firm also wants to run some aggregation jobs.

Key issues:

You must revamp existing code and migration of existing data.

Tasks:

You have given end points or log files path where data is being produced.

You have different pages on the website which can be search page, promotional page, deal of day page etc. You must use this log and design schema such that it can get daily request counts per day.

• Number of clicks on deal of the day page with Android device on 11 May 2017
• Number of clicks on deal of the page with IOS device on 11 May 2017
• Number of clicks on home page with Chrome browser on 11 May 2017
• Number of clicks on home page of Firefox browser on 11 May 2017

Case Study 3: Customer Help Desk Application

Problem Statement:

Model a Customer Help Desk application where customer complaints are logged and captured in a Cassandra column family. The Cassandra table HelpDesk shown in the following screenshot captures these details.

The columns CustomerId, TicketId, ActionTime constitute the Primary key. The column CustomerId becomes the Partition key. The records are stored in the descending order of TicketId, ActionTime. This is to make sure that the recent action details are accessible first.

Task:

• Create a table HelpDesk as per the above requirement
• Insert data into HelpDesk. For every record inserted, ActionTime should get the current timestamp.
• Use the CQL command to display all the data in the specified format.
• Write range query to retrieve data from to specific date and time. For example, between time-period 2017-11-12 19:14:00 and 2017-11-13 19:20:00

Case Study 4: Hotel Booking Application

Problem Statement:

Design a hotel room reservation application data model. Access available_rooms.csv file provided. The available_rooms.csv file contains a month’s worth of inventory for two small hotels with five rooms each.

Tasks:

• Create a table available_rooms_by_hotel_date as per the requirement with hotel_id as the partition key, while date and room_number are clustering columns.
• Bulk load to table available_rooms_by_hotel_data FROM available_rooms.csv
• Display all the records in available_rooms_by_hotel_date for a particular hotel_id (ex: AZ123) and room_number (ex: 101). Remember both hotel_id and room_number are part of composite primary key.
• Display all records for a particular hotel between two specific date range in descending order of date.
• Write an UDF is available which return 1 if a room is available else return 0 Make a call to the UDF to display the results for table available_rooms_by_hotel_date.
• Create UDF/UDFs to return the total available rooms.