TOPICS

About The Course
The Apache Cassandra course at LearnChase starts with the fundamental concepts of using a highly-scalable, column-oriented database to implement appropriate use cases. It will cover topics like Cassandra Datamodels,Cassandra Architecture, Differences between RDBMS and Cassandra to name a few. There will be many challenging, practical and focused hands-on exercises for the learners during this course.

Course Objectives
After the completion of ‘Apache Cassandra’ course at LearnChase, you should be able to:

1. Understand Cassandra and NoSQL domain.
2. Create Cassandra cluster for different kinds of applications.
3. Understand Apache Cassandra Architecture.
4. Design and model Applications for Cassandra.
5. Port existing application from RDBMS to Cassandra.
6. Learn to use Cassandra with various programming languages.
Who should go for this course?
The following professionals can go for the course :

1. A developer working with large-scale, high-volume websites.

2. An application architect or data architect who needs to understand the available options for high-performance, decentralized, elastic data stores.
3. A database administrator or database developer currently working with standard relational database systems who needs to understand how to implement a fault-tolerant, eventually consistent data store.
4. A manager who wants to understand the advantages (and disadvantages) of Cassandra and related columnar databases to help make decisions about technology strategy.
5. A student, analyst, or researcher who is designing a project related to Cassandra or other non-relational data store options.
Pre-requisites
This course assumes no prior knowledge of Apache Cassandra or any other NoSQL database. Though some familiarity with Linux command line is essential, minimal exposure to Java,database or data-warehouse concepts is required.

Why Learn Cassandra?
Apache Cassandra™ , an Apache Software Foundation project, is an open-source NoSQL distributed database management system. Apache Cassandra was originally developed at Facebook, and is used by many companies today. While many developers have embraced simpler NoSQL variants (like MongoDB and CouchDB), Cassandra is possibly at the forefront of the NoSQL innovation, providing a level of reliability and fine tuning not found in many of the competitors’ offerings. When it comes to scaling, nothing scales like it, the biggest example being the Facebook which uses Cassandra for storing petabytes of Data.

1. Cassandra is designed to handle Cassandra workloads across multiple data centers with no single point of failure, providing enterprises with extremely high database performance and availability.
2. World’s largest Website (i.e Cassandra) is running over Cassandra.
3. Daily 100s of start-ups and large product companies are choosing Cassandra for their next generation computing and data platforms. Some companies using Cassandra are Facebook, Twitter, IBM, Cisco, Rackspace, NetFlix, eBay, Reddit, @WalmartLabs, Zoho, Digg and so on.
4. Apache Cassandra is open-source. It means you can deep dive into its source code and change it according to your own requirements.
5. The job market for Apache Cassandra is at peak and is growing at rate of 300%!

1. Getting Started with Cassandra
Learning Objectives – After this module students will be able to:
Explain the differences between NoSQL and RDBMS databases, Explain what the various NoSQL databases are, Explain the various Cassandra features, Explain why Cassandra scores over other NoSQL databases, Distinguish between use cases when Cassandra is a strong choice and when it is not, Understand the use cases where Cassandra is implemented.

Topics – Quick Review of RDBMS: Transactions, ACIDity, Schema, Two Phase Commit, Sharding and Share Nothing Architecture, Feature Based, Key Based, Lookup Table Based, NoSQL Databases, Brewers CAP Theorem, Cassandra Definition and Features, Distributed and Decentralised, Elastic Scalability, High Availability and Fault Tolerance, Tuneable Consistency, Strict Consistency, Casual Consistency, Weak (Eventual Consistency), Column Orientation, Schema Free, High Performance, USE Cases for Cassandra, Cassandra Installation.

2. Understanding Cassandra Data Model
Learning Objectives – After this module students will be able to:

Run basic Cassandra commands, Understand Design differences between RDBMS and Cassandra data model, Describe What a Cassandra cluster is,Describe what a Keyspace is, how it relates to Cluster and what is stored in the Keyspace, Explain what a Column Family is, Explain the primary key and its uses, Explain the parts of the compound primary Key, Explain what a partition key is, Explain how data is stored in a partition, Explain how clustering columns ensure that the stored data will be clustered in a partition, Explain secondary indexes and there implications, Explain how Cassandra locate data in the data cluster, Explain expiring column and Time to Live (TTL).

Topics – Installing Cassandra, Running the Command-Line Client Interface, Basic CLI Commands, Help, Connecting to a Server, Describing the Environment, Creating and Keyspace and Column Family, Writing and Reading Data, The Relational Data Model, Simple Introduction, Cluster, Keyspaces, Column Families, Column Family Options, Columns, Wide Rows, Skinny Rows, Column Sorting, Super Columns, Composite Keys, Design Differences between RDBMS and CASSANDRA, Query Language, Referential Integrity, Secondary Indexes, Sorting, DeNormalisation, Design Patterns, Materialized Views.

3. Understanding Cassandra Architecture
Learning Objectives – After this module students will be able to:

Explain what happens during the read and write operations, Explain how Cassandra accomplishes some of its basic notable aspects, such as durability and high availability. Understand more complex inner workings, such as the gossip protocol, hinted handoffs, read repairs, Merkle trees etc, Understand Staged Event-Driven Architecture (SEDA).

Topics – System Keyspace, Peer-To-Peer, Gossip and Failure Detection, Anti-Entropy and Read Repair, Memtables, SSTables, and Commit Logs, Hinted Handoff, Compaction, Bloom Filters, Tombstones, Staged Event-Driven Architecture (SEDA), Read, Mutation, Gossip, Response, Anti-Entropy, Load Balance, Migration, Streaming, Managers and Services, Casssandra Daemon, Storage Service, Messaging Service, Hinted Handoff Manager.

4. Creating Sample Application
Learning Objectives – After this module students will be able to:

Analyze the requirements for a Cassandra use case and apply data modeling techniques, Identify the challenges faced by RDBMS, Identify the design consideration for designing Cassandra data model, Understand how data modeling differs in Cassandra from traditional relational databases, Understand how to De-Normalize RDBMS data, Demonstrate how the queries are used to design Cassandra data model, Demonstrate ability to apply data modeling concepts to various exercises that are given during the class, Understand the implications of the client side joins when writing application that access data in Cassandra, Able to insert data, perform batch updates and search column families.

Topics – Database Design, Sample Application RDBMS Design, Sample Application Cassandra Design, Application Code, Creating Database, Loading Schema, Data Structures, Setting Connections, Population of database, Application Features.

5. Configuring, Reading and Writing Data in Cassandra
Learning Objectives – After this students will be able to:

Understand what Replicas are, Understand various replica Placement Strategies, Understand Partitions, Understand Snitches, Create Clusters, Understand Dynamic Ring Participation, Understanding Security with in Cassandra, Understand Miscellaneous Settings and various additional tools in Cassandra, Understand Basic read and Write Properties, Understand what Slice Predicates are.

Topics – Keyspaces, Replicas, Replica Placement Strategy, Replication Factor, Partitioner, Snitches, Creating Clusters, Dynamic Ring Participation, Security, Miscellaneous Settings, Additional Tools, Query differences between RDBMS and Cassandra, Basic Write Properties, Consistency Level, Basic Read Properties, API’s, Set Up and Inserting Data, Slice Predicate, Get Range Slices, Multiget Slice, Deleting, Programmatically Defining Keyspaces and Column Families.

6. Integrating Cassandra with Hadoop
Learning Objectives – After this module students will be able to:

Understand what Hadoop is and how it is used, Describe Cassandra File System, Start working with Map Reduce, Understand tools above Map Reduce like Pig and Hive and how they work with Cassandra, Understand Cluster Configuration, Understand live use cases.

Topics – Hadoop, MapReduce, Cassandra Hadoop Source Package, Outputting Data to Cassandra, PIG, HIVE, Use Cases.

7. CQL
Learning Objectives – After this module the will be able to:

Perform Data Definition Language (DDL) Statements within Cassandra, Perform Data Manipulation Language (DML) Statements within Cassandra, Create and modify Users and User permission within Cassandra, Capture CQL output to a file, Import and export data with CQL, Execute CQL scripts from within CQL and from the command prompt.

Topics – Data Definition language(DDL) Statements, Data Manipulation Language (DML), Create and modify Users, User permission, Capture CQL output to a file, Import and export data, CQL scripts from within CQL, CQL Scripts from the command prompt.

8. Clients and Live Project
Learning Objectives – After this module students will be able to:

Understand what Thrift is, Understand Cassandra web console, Demonstrate ability to implement the concepts learned during the course on a real life problem.

Topics – Basic Client API, Thrift, Thrift Support for Java, Exceptions, Thrift Summary, Cassandra Web Console, Hector (Java), Features, Hector API, Live Project.