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1.The Purpose of Cassandra?

Understanding What Cassandra is Language?
Exercise: Access the Apache Cassandra websiteand
Learning What Cassandra is Being Used For
Exercise: Learn what Cassandra is being used for
Lab: Open the main course virtual machine

2. Getting Started with the Architecture

Understanding that Cassandra is a Distributed Database
Exercise: View Cassandra documentation
Learning What Snitch is For
Learning What Gossip is For
Exercise: Check your understanding
Learning How Data Gets Distributed and Replicated
Exercise: Access related documentation
Lab: View the course projects

3. Installing Cassandra

Downloading Cassandra
Exercise: Locate the tarball
Ensuring Oracle Java 7 is Installed
Exercise: Check that Oracle Java 7 is installed
Installing Cassandra
Exercise: Install Cassandra
Viewing the Main Configuration File
Exercise: View the cassandra.yaml file
Providing Cassandra with Permission to Directories
Exercise: Provide Cassandra with permission to directories
Starting Cassandra
Exercise: Start Cassandra
Checking Status
Exercise: Check status
Accessing the Cassandra system.log File

Exercise: Access the Cassandra system.log file
4. Communicating with Cassandra

Understanding Ways to Communicate with Cassandra
Exercise: View CQL commands
Using cqlsh
Exercise: Access cqlsh
Lab: Use cqlsh

5. Creating a Database

Understanding a Cassandra Database
Exercise: View the existing keyspaces
Defining a Keyspace
Exercise: Define a keyspace
Lab: Create a second database

6. Creating a Table

Exercise: Enter a keyspace
Defining Columns and Data Types
Exercise: Define columns and data types
Defining a Primary Key
Exercise: Define a primary key
Recognizing a Partition Key
Exercise: Recognize a partition key
Specifying a Descending Clustering Order
Exercise: Specify a descending clustering order
Lab: Create a second table

7. Inserting Data

Understanding Ways to Write Data

Using the INSERT INTO command
Exercise: Use the INSERT INTO command
Using the COPY command
Exercise: Use the COPY command
Seeing How Data is Stored in Cassandra
Exercise: See how data is stored in Cassandra
Lab: Insert data

8. Modeling Data

Understanding Data Modeling in Cassandra

Understanding Secondary Indexes
Exercise: Use a WHERE clause
Creating a Secondary Index
Exercise: Create a secondary index
Defining a Composite Partition Key
Exercise: Define a composite partition key

9. Creating an Application

Understanding Cassandra Drivers
Exercise: View the Cassandra drivers
Exploring the DataStax Java Driver
Exercise: Explore the DataStax Java driver
Setting Up a Development Environment
Exercise: Access a development environment
Creating an Application Page
Exercise: Create an application page
Getting the DataStax Java Driver Classes
Exercise: Get the DataStax Java driver classes
Connecting to a Cassandra Cluster
Exercise: Connect to a Cassandra cluster
Executing a Query
Exercise: Execute a query
Displaying Query Results
Exercise: Display query results
Using an MVC Pattern
Exercise: View an MVC pattern
Lab: Create a second application

10. Updating and Deleting Data

Updating Data

Exercise: Update data Understanding How Updating Works
Exercise: Get an inside view into how updating works
Deleting Data
Exercise: Delete data
Understanding Tombstones
Exercise: View a tombstone
Using TTLs
Exercise: Create a TTL
Lab: Update and delete data

11. Selecting Hardware

Understanding Hardware Choices

Understanding RAM and CPU Recommendations
Exercise: Check for RAM
Selecting Storage
Exercise: View available storage on your computer
Deploying in the Cloud
Exercise: View cloud recommendations < /p>

12. Adding Nodes to a Cluster

Understanding Cassandra Nodes

Exercise: Set up a second a node
Having a Network Connection
Exercise: Have a network connection
Specifying the IP Address for a Node
Exercise: Specify the IP address for a node
Specifying Seed Nodes
Exercise: Specify seed nodes
Bootstrapping a Node
Exercise: Bootstrap a node
Cleaning Up a Node
Exercise: Clean up a node
Using cassandra-stress
Exercise: Use cassandra-stress
Lab: Add a third node

13. Monitoring a Cluster

Understanding Cassandra Monitoring Tools

Using nodetool
Exercise: Use nodetool
Using JConsole
Exercise: Use JConsole
Learning About OpsCenter
Exercise: Learn about OpsCenter

14. Repairing Nodes

Understanding Repair

Exercise: Modify the replication factor of a keyspace
Repairing Nodes
Exercise: Repair nodes
Understanding Consistency
Exercise: Specify consistency
Understanding Hinted Handoff
Understanding Read Repair
Exercise: View read repair and hinted handoff settings
Lab: Repair nodes for a keyspace

15. Removing a Node

Understanding Removing a Node

Decommissioning a Node
Putting a Node Back into Service
Exercise: Put a node back into service
Removing a Dead Node
Exercise: Remove a dead node
Lab: Put a node back into service

16. Redefining a Cluster for Multiple Data Centers

Redefining for Multiple Data Centers

Changing Snitch Type
Exercise: Change snitch type
Exercise: Modify
Changing Replication Strategy
Exercise: Change replication strategy
Lab: Insert data

1. Why Spark?

Problems with Traditional Large-Scale Systems
Introducing Spark & Spark Basics
Apache MapReduce vs Apache Spark
Using the Spark Shell
Resilient Distributed Datasets (RDDs)
Functional Programming with Spark
Working with RDDs


Key-Value Pair RDDs
Types of RDDs

  • ParallelCollectionRDD
  • SequenceFileRDD
  • DoubleRDD
  • PairRDD
  • PipedRDD

MapReduce and Pair RDD Operations
Read data from text file
Using HDFS with Spark



  • Reduce, Collect
  • Count, First
  • Take, TakeSample
  • TakeOrdered
  • SaveAsTextFile


  • Map, Filter
  • FlatMap, Map-partitions
  • Sample, Unionle
  • Intersection
  • Distinct, Cartesian

Working With Partitions
Executing Parallel Operations
Caching Overview
Caching and Persistence
Distributed Persistence
Writing Spark Applications

5.Data Frame

Spark 2.0 data frames
Introduction of Data Frame
Create Data Frame
Data input & output
Gathering data frame information
Using SQL on data frame
Apply filter on data frame

6.Spark DataFrame Dates And Timestamps

Introduction to Date & timestamps
Working with Dates & timestamps
Spark DataFrame Aggregate Operations
Aggregate and GroupBy concepts
Sorting & Ordering

7.Spark DataFrame Working With Missing Data

Introduction to Missing Data
Dropping Data
Filling missing data


A Spark Cluster
The Spark Web UI<
Parallel Programming with Spark
Creating the SparkContext
Configuring Spark Properties
Building and Running a Spark Application Logging
Spark, Hadoop, and the Enterprise Data Center

9.Spark SQL

Introduction to Spark SQL
Inferring a schema
Applying a schema
Loading and Writing schema
SQL caching and UDF
Spark SQL queries to perform computations

Fees: 22,000 Rs/-
Duration: 2.5 Months


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