Duration: Hours

Apache Cassandra is an open-source second-generation distributed database released by Facebook. The write-optimized and shared-nothing architecture results in excellent performance and scalability. The master class ring design of Apache makes it elegant, easy setup and maintenance and used to provide a simple solution for complex problems like Metrics and Logging. It is the small footprint of Major or Primary Database so easy to learn

Training Mode: Online

Description

Cassandra

Objectives of the Course

a). Creating Sample Application

b). Configuring, Reading and Writing Data

c). Integrating Cassandra with Hadoop

d). Data Model

e). Cassandra Environment

f). Understanding Architecture

Who should do the course?

a). Professionals looking for a career

b). Project Managers

c). IT Developers

d). Testing professionals

e). Graduates looking to upgrade their skills to Databases

f). Analyst/Researcher

 

                                                               Course Content :

a).What is Big Data

1. Technology Landscape

2. Big Data Relevance

3. Distributed Systems and Challenges

b).Why NoSQL Databases

1. Relational DB vs. NoSQL

2. Type of NoSQL Databases

3. NoSQL Landscape

4. CAP Theorem and Eventual Consistency

5. Key Characteristics of NoSQL Database systems

6. ACID vs BASE

c). Fundamentals

1. Distributed and Decentralized

2. Elastic Scalability

3. High Availability and Fault Tolerance

4. Tuneable Consistency

5. Row-Oriented

6. Schema-Free

7. High Performance

d). Data Model

1. The Relational Data Model

2. A Simple Introduction

3. Clusters

4. Keyspaces

5. Hands-on Session

e). Installation and Setup

1. Single Node Setup

2. Multi-Node Cluster Setup

3. Key Configurations for Cassandra

4. CLI and Hands-On with Cassandra

f). Modeling

1. Cassandra (Column Family NoSQL DB)

2. Key Concepts – Key Space – Column Family – Column Family Options – Wide Rows, Skinny Row – Column Sorting – Super Columns – Counter Column Family – Composite Keys and Columns – Time To Live –

3. Secondary Indexes in Cassandra

4. Difference between Custom Indexes and Secondary Indexes

5. Difference between Relational Modeling and Cassandra Modeling

6. Key Points to note while modeling a Cassandra Database

7. Patterns and Anit-Patterns in Cassandra Modeling

g). Architecture & Intro to CQL

1. Anatomy of Reading operation

2. Anatomy of the Write operation

3. How is Deletes handled

4. System Keyspace

5. Peer to Peer Model Logical Data Model: Keyspace, Column Family/Table, Rows, Columns

6. Traditional Ring design vs. VNodes

7. Partitioners: Murmer3, Random (md5) and ByteOrdered

8. Gossip and Failure Detection

9. Anti-Entropy and Read Repair

10. Memtables, SSTables and Commit Log

11. Compaction fundamentals to reduce SSTable data files

12. Hinted Handoff

13. Compaction

14. Bloom Filters, Tombstones

15. Managers and Services

16. VNodes

17. Indexes and Caches

18. Coordinator node

19. Seed nodes

20. Write/Read consistency levels: Any, One, Two, Three, Quorum

21. Snitches: Dynamic snitching, Simple Snitch, Rack Inferring Snitch, Property File Snitch, Gossiping Property File Snitch

22. Routing Client requests

23. Nodetool commands: gossipinfo, cfstats, describing

24. YAML file fundamentals

25. Operations management web GUI

26. Stress testing Cassandra

27. CQL command fundamentals

h). API

1. Key concepts for Reading and Write

2. Tunable Consistency

3. Simple Get, Multi-get Slice

4. Range and Slice

5. Slice Predicate

6. Delete

7. Hands-on CLI commands

i). CQSHL

1. Composite Keys

2. Hands-on examples on CQL 3.0

j). Clients

1. How to establish Client Connections

2. Thrift Client

3. Connection Pooling

4. Auto-discovery and Failover in Hector

5. Client with CQL

k). Monitoring and Administration

1. Backup and Recovery methods

2. Balancing

3. Bootstrapping

4. Node Tools Commands

5. Upgrades

6. Monitoring critical metrics

7. Bulk Loading Data

8. Bulk Export of Data

9. Hands-on Examples for each of them

l). Analytics Cluster

1. Hadoop Integration

m). Search Cluster

1. Integration of Solr

2. Search Query

For more inputs on Cassandra you can connect here.
Contact the L&D Specialist at Locus IT

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