Description
Apache Cassandra is an open source second generation distributed database released by Facebook and used to provide a simple solution for complex problem.
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
Â
                                                              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 Search Cluster
2. Search Query
For more inputs on Cassandra you can connect here.
Contact the L&D Specialist at Locus IT
Locus Academy has more than a decade experience in delivering the training/staffing on Cassandra for corporates across the globe. The participants for the training/staffing on Cassandra are extremely satisfied and are able to implement the learnings in their on going projects.
Reviews
There are no reviews yet.