Learn Cassandra with Edureka's comprehensive course

www.edureka.in/cassandra
Slide 1

Slide 2
Course Structure
 Module 1:
Getting Started With Cassandra
 Module 2:
Understanding Cassandra Data Model
 Module 3:
Understanding Cassandra Architecture
 Module 4:
Creating Sample Application
 Module 5:
Configuring, Monitoring, Maintenance and
Tuning Cassandra
 Module 6:
Integrating Cassandra With Hadoop
 Module 7:
CRUD operations in Cassandra
 Module 8:
Live Project

Slide 3
How it Works?
 Live Classes
 Class Recordings
 Module wise Quizzes, Coding Assignments
 24x7 on-demand Technical Support
 Sample Application and Live Project
 Online Certification Exam
 Lifetime access to the Learning Management System

Slide 4
Module 1
Getting Started With Cassandra
 New Problems which can’t be handled by traditional RDBMS
 Tradeoff between Consistency, Availability, Partition Tolerance (CAP theorem)
 What are the different solutions available?
 What is Cassandra?
 Use-Cases for Cassandra
 Cassandra Features – Tunable Consistency, P2P Architecture, Elastic Scalability, Col Orientation
 Demo Application using Cassandra
 Questions?

Slide 5
Module 2
 Understand what database model is.
 Understand the analogy between the RDBMS and Cassandra Data Model.
 Understand the following Cassandra database elements:
 Cluster
 Keyspaces
 Column Families
 Columns
 Super Columns
 Rows
 Indexes in Cassandra
 Primary and Composite Keys and their limitations
 Design Differences between RDBMS and Cassandra
 Materialized Views
 Valueless Columns
 Aggregate Keys

Slide 6
Module 3
Understanding Cassandra Architecture
 Learn about the System Keyspaces
 Learn about internode communication such as Peer to Peer structure as well as Gossip Protocols
 Learn how Cassandra detects the failures in the nodes and repairs it
 Learn about Anti Entropy and Read Repair
 Learn about the Memtables, Sstables, and Commit logs
 Hinted Handoffs
 Compaction
 Bloom Filters
 Tombstones
 SEDA
 Manager and Services

Slide 7
Module 4
Creating Sample Application
 Identify challenges faced by RDBMS
 Identify various possible available solutions
 Identify the rational behind choosing Cassandra
 Understand how data modelling differs in Cassandra from traditional relational databases
 Understand how queries are used to design Cassandra data model
 Apply Cassandra data modelling to various use cases
 Create the application which would involve creating various data elements you learned about in
Module 2
 Perform batch updates and search column families
 Overview of the whole project specifying how Cassandra solved the problem which was laid out
in the beginning

Slide 8
Module 5
Configuring, Monitoring, Maintenance and Tuning Cassandra
Learn about various options of configuring Keyspaces and Column Families
 Learn about various Cassandra Replacement Strategies
 Learn about Replication
 Learn about Partitioners
 Learn about Snitches
 Learn about configuring Cluster
 Learn about Security
 Learn about Monitoring Cassandra Cluster
 Learn about Cassandra Maintenance
 Getting Ring information
 Basic Maintenance
 Snapshots
 Load Balancing
 Decommissioning and Updating nodes
 Learn about Performance Tuning
 Data storage, Reply timeouts
 Commit Logs, MemTables, Caching and Buffer sizes

Slide 9
Integrating Cassandra with Hadoop
 Learn what Hadoop is
 Learn Hadoop Disribution File System
 Learn how to work with Map Reduce
 Learn Tools like PIG and HIVE
 Learn PIG and HIVE interaction with Cassandra
Module 6

Slide 10
CRUD Operations in Cassandra
 Learn about Reading and writing data in Cassandra
 Learn about Cassandra API (Thrift)
 Learn about Slice Predicates
 Learn Data Definition Language (DDL) in Cassandra
 Learn Data Manipulation Language (DML) statements within Cassandra
 Learn to execute CQL scripts from with in CQL and from Command prompt
 Learn to Create and Modify Users
 Learn about Batch Mutates and Batch Deletes
 Learn various Security configurations in Cassandra
 Learn to Capture CQL outputs to a file
 Learn to Import and Export data with CQL
Module 7

Slide 11
Live Project!
Module 8

Slide 12
What are we going to learn today?
 New Problems which can’t be handled by traditional RDBMS
 Tradeoff between Consistency, Availability, Partition Tolerance (CAP theorem)
 What are the different solutions available?
 What is Cassandra?
 Use-Cases for Cassandra
 Cassandra Features – Tunable Consistency, P2P Architecture, Elastic Scalability, Column Orientation
 Demo Application using Cassandra
 Questions

Slide 13
Twitter – Massive Scale, High Availability

Slide 14
Travel Booking – Scale and Availability

Slide 15
Movie Booking – Consistency and Scale

Slide 16
Facebook Graph Search – Fast, Complex Querying

Slide 17
Facebook Messenger – Consistency and Scale

Slide 18
So, What Is Common?
 Huge Data
 Fast Random access
 Variable Schema
 Need of Compression
 High Availability
 Need for Consistency
 Need of Distribution (Sharding)

Slide 19
NoSQL Database
 Non Relational
 Distributed
 Open Source
 Horizontally Scalable
 Features of NoSQL Database

Slide 20
NoSQL Database types

Slide 21
NoSQL Database types
CouchDB, MongoDB
Collection of key value
Connections
Incomplete Data
Tolerant
Query Performance, No
Standard Query Syntax
Hbase, Cassandra
Column Families
Fast Look-ups
Very Low Level API
Amazon Simple DB,
Redis
Collection of Key
Value pairs
Fast Look-ups
Stored Data
has no Schema
InfoGrid, Infinite Graph
“Property Graph” - Nodes
Graph Algorithms – Shortest
Path, Connected ness, Etc
Not easy to Cluster, traverse
whole graph to get answer
Data Model
Example
Weakness
Strength
Data Model
Example
Weakness
Strength
Data Model
Example
Weakness
Strength
Data Model
Example
Weakness
Strength
Document Data
Store Databases
Key Value
Databases
Columnar NoSQL
Databases
Graph NoSQL
Databases
No SQL
Database Types

Slide 22
Welcome To Cassandra!

Slide 23
Cassandra Name’s Story
Troy Destruction
King Priam Hecuba
Cassandra Greek God Apollo

Slide 24
Why Use Cassandra?
Why Use Cassandra…?
RDBMS
When there is RDBMS!

Slide 25
Drawbacks of RDBMS
 Scalability
 Joins Slow Down
 Non-Availability of Data
 Queuing

Slide 26
Solutions…
Vertical Scaling
 More Memory
 Faster Processor
 Upgrading Disks

Slide 27
Further Steps…
What can go wrong??
Replication
Or even add boxes in database cluster…
Leading to new problems…
Consistency
Failover
Scenario
DATA
DATA
DATA

Slide 28
More Steps…
Database Configuration
Caching Layer
Consistency problem between the updates in the Cache and
updates in the databases - Problem gets complex over clusters
Might mean manipulating the Write - Turning write logs off—
Not a desirable situation

Slide 29
Current Data Challenges
 Massive Data Growth and Scalability
 100% Availability
 Quick Real Time Analytics
 No Failures
!

Slide 30
Why to use Cassandra?
Why to Use Cassandra…?
For High Velocity Data
Writing Data Anywhere,
Everywhere
Scaling Writes and Reads
No Downtime
Scaling Out Strategy
Scaling for both READS
and WRITES
Voluminous Data
Data Originating from
Multiple Locations
Retaining Data for Long
Storing all types of Data
Delivering Fast Response
Time
Keeping Business Online and
Serving Customers

Slide 31
Cassandra Characteristics…
For More Details, visit our Blog post…http://www.edureka.in/blog/cassandra-advantages/

Slide 32
Column Oriented
Emp_no Dept_id Hire_date Emp_In Emp_fn
1 2 2010-08-05 Teresa Annie
2 4 2012-03-10 Ronald Susane
3 3 2012-11-06 Brown Donald
4 3 2011-07-03 Ruth David
5 1 2010-09-12 Stancy Elizabeth
6 2 2012-10-03 Catherine Amelia
1 2 2010-08-05 Teresa Annie
2 4 2012-03-10 Ronald Susane
3 3 2012-11-06 Brown Donald
1 2 3 4 5
2010-
08-05
2012-
03-10
2012-
11-06
2011-
07-03
2010-
09-12
2 4 3 3 1
Row-Oriented Database
Column-Oriented Database

Slide 33
Schema Free
Primary Key First Name Last Name E-mail ID
1 Avril D’Souza NULL
2 David Gomes davidgomes1@yahoo.com
3 Susane NULL NULL
First Name Last Name
Avril D’Souza
First Name Last Name E-mail ID
David Gomes davidgomes1@yahoo.com
First Name
Susane
Schema Based Table
Schema Free

Slide 34
Brewer’s CAP Theorem
http://www.w3resource.com/mongodb/nosql.php
Consistency
Partition
Tolerance
Availability
CA CP
AP
RDBMS MongoDB
HBase
Redis
CouchDB Cassandra DynamoDB Riak

Slide 35
NoSQL Landscape
Scalability
&
Speed
Query and Navigational Complexity
Performance
Key-Value
Stores
Dynamo (Amazon),
Voldemort
(LinkedIn), Citrusleaf,
Membase, Riak,
Tokyo Cabinet
Big Table
Clones
BigTable
(Google),
Cassandra,
HBase,
Hypertable Document
Database
CouchOne,
MongoDB,
Terrastore,
OrientDB
Graph
Databases
FlockDB (Twitter),
AllegroGraph,
DEX, InfoGrid,
Neo4J, Sones

Slide 36
Cassandra Usecase – Deep Drive
5000 TPS
Caching Layer
300 ~ 500 SQL
Transaction
100 ~ 200 SQL
Transaction
1000 TPS
WEB APPLICATION
RDBMS1
Applications Changing Data
RDBMS1
Elastic Scale

Slide 37
Using Cassandra
1000 TPS
Elastic Scale WEB APPLICATION
Applications Changing Data
Elastic Scale
CASSANDRA
300 ~ 500 SQL
Transaction
100 ~ 200 SQL
Transaction
5000 TPS

Slide 38
 E-Commerce (Travel Portal)
 Both B2B & B2C Consumers
 High volume of shopping transactions
(> 500 Million Visits / Day)
 High volume supply changes
(Manual & System) generated.
 Huge Inventory Database
(Millions of hotels)
 High Read/Write
(Thousands Reads & Writes/Second)
 Application has to 99.99% Available
 Fault Tolerant & Reliable.
 Fast & Quick Shopping Experience.
 Elastic Scale
 Innovative Recommendations & Algorithms.
 Should be fast for new changes
 Should be cost effective for maintenance.
 Development Approaches
 Legacy Way (Pure RDBMS)
 Augmented (RDBMS + Caching, Heavy
Database Hardware)
 Using Cassandra
Cassandra Usecase - Summary

Slide 39
Apache Cassandra is an open source, distributed, decentralized, elastically scalable, highly available,
fault-tolerant, Tuneably consistent, column-oriented database.
What is Apache Cassandra?
Cassandra Features
Open
Source
Distributed
Decentralized
Elastically
Scalable
Highly
Scalable
Fault
Tolerant
Tuneably
Consistent
Column
Oriented

Slide 40
Distributed and Decentralized
Post Office
Decentralised
Post Office
Centralised
CCY
Exchange stationary Letter/Couriers
Ccy Courier Stationary
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers

Slide 41
 Every Node Is Identical.
 Peer to Peer Protocol and uses Gossip Protocol to
maintain and keep the List of nodes in Sync.
 No Single Point of Failure.
 No Special Host to Coordinate Activities.
 Easier to Operate and Maintain because all nodes
are same.
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers
Distributed and Decentralized

Slide 42
Types of Scalability
 Vertical Scalability
 Horizontal Scalability
What is Elastic Scalability?
 This is special property of Horizontal Scalability.
 The cluster can seamlessly scale up and scale back down without major disruption.
Elastic Scalability

Slide 43
 Cluster must accept new nodes without major disruption or
reconfiguration.
ADD A NODE AND MOVE ON!!
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers
 Process should not be restarted
 Do not have to change application charges
 Don’t have to rebalance data
Elastic Scalability

Slide 44
 Highly Available
 No Downtime
High Availability and Fault Tolerance
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers
CCY, Stationary,
Letter/Couriers

Slide 45
Tunable Consistency
Strong Consistency
Eventual
Consistency
 Cassandra enables us to tune the Consistency based on the Application Requirement

Slide 46
 Cassandra was designed specifically from the ground up to take full advantage
of multiprocessor/ multicore machines, and to run across many dozens of
these machines housed in multiple data centres.
 It scales consistently and seamlessly to hundreds of terabytes.
 Shows exceptional performance under heavy loads.
 Consistently shows very fast throughput for writes per second on a basic
commodity workstation.
High Performance

Slide 47
Use if your application has:
 Big Data (Billions Of Records Rows & Columns)
 Very High Velocity Random Reads & Writes
 Flexible Sparse / Wide Column Requirements
 No Multiple Secondary Index Needs
 Low Latency
Use Cases:
 eCommerce Inventory Cache Use Cases
 Time Series / Events Use Cases
 Feed Based Activities / Use Cases
Where to Use Cassandra?

Slide 48
Where NOT to Use Cassandra?
Don’t Use if you application has:
 Secondary Indexes.
 Relational Data.
 Transactional (Rollback, Commit)
 Primary & Financial Records.
 Stringent Security & Authorization Needs On Data
 Dynamic Queries on Columns.
 Searching Column Data
 Low Latency

Slide 49
 Cassandra Installation & Configuration
 Conf/cassandra.yaml
 Tools
 Key Space Setup
 Column Family / Data Model Setup
 Key
 Columns & Data Types
 Indexes (Primary & Secondary)
 Programmatic Consistency
 Thrift Hector API
 CQL3 API
Application Demo

Slide 50
Application Demo

Slide 51
Application Demo

Slide 52
Application Demo

Slide 53
Application Demo

Slide 54
Application Demo

Slide 55
Application Demo

Slide 56
Application Demo

Slide 57
Module 2
 Understand what database model is.
 Understand the analogy between the RDBMS and Cassandra Data Model.
 Understand the following Cassandra database elements:
 Cluster
 Keyspaces
 Column Families
 Columns
 Super Columns
 Rows
 Indexes in Cassandra
 Primary and Composite Keys and their limitations
 Design Differences between RDBMS and Cassandra
 Materialized Views
 Valueless Columns
 Aggregate Keys

Slide 58
Hands On

Slide 59
Questions?

Thank You
See You in Class Next Module

Learn Cassandra with Edureka's comprehensive course

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