Learn Big Data : Complete Hadoop Ecosystem with Practicals

Name: Learn Big Data : Complete Hadoop Ecosystem with Practicals
Rating: 3.7 (35 reviews)

Learn Complete Big Data Testing (Spark + MongoDB + Hadoop + Hive + Cassandra + HBase + Redis + Beeline) with Examples

Created byLead Big Data Engineer

Last updated 1/2026

English

What you'll learn

By the end of this course, students will have a strong understanding of Redis, Oozie, and HBase, including advanced queries and commands required for testers
At the end of this tutorial, students would be able to start their career in Development or Testing with this technology at different levels.
Learners will become familiar with core Hadoop concepts along with Hive for data warehousing, and multiple NoSQL databases such as HBase, Cassandra, Redis.
With hands-on knowledge and practical exposure, participants will be well prepared to begin working confidently in Big Data development or testing roles

Course content

12 sections • 103 lectures • 12h 41m total length

Agenda4:23
What is Hadoop Ecosystem?7:50
What is Big Data?4:40
Explore how big data processes huge, complex data from diverse formats to deliver insights near the end user, addressing storage, management, and scalability challenges with analytics-ready architectures.
Big Data Data Supports7:51
Difference - Hadoop 1 and Hadoop 26:04
Explore the differences between Hadoop 1 and Hadoop 2, highlighting changes in central resource management, backup capabilities, automatic failover, and overall cluster management improvements.
Big Data Overview4:40
Explains the challenges of processing and analyzing large, complex data sets, emphasizing storage, management systems, and real time analysis as central big data needs.
What is Hadoop?4:50
Why Hadoop?5:38
Hadoop Data Flow with Diagram5:39

What is Cassandra?4:08
Cassandra is an open source technology designed to manage huge amounts of data in real time. It can handle media in any format and is built for mass-market use.
Cassandra Architecture with Diagram11:07
Explore the Cassandra architecture through a diagram, highlighting a peer-to-peer cluster where every node can read and write data, with replication and gossip-based communication across the data center.
Cassandra SPOF Feature in Detail3:55
Cassandra Replication Factor6:28
Install Cassandra on UBuntu Machine16:27
Create Cassandra Table with Simple Strategy9:45
Create Cassandra Table with NetworkTopology Strategy5:35
Cassandra's Data Types in Detail2:50
How to Create Table and Insert Data in Cassandra Table?10:36
How to work with Cassandra's Table and Database Schema and Data?6:31
How to Update Table Data in Cassandra?11:03
Master updating Cassandra table data by defining a primary key, using update and delete operations with where clauses, and validating changes through read operations.
How to Delete Table Data in Cassandra?7:09
How to Insert Data from Files in Cassandra Table?11:58
Learn how to create a table and insert data from external files into a Cassandra table, including defining columns, loading a dataset, and verifying inserted records.

MongoDB Introduction with Practicals6:40
Learn MongoDB introduction with practicals, focusing on document store concepts, storing data in documents, and using indices to organize data across IDs and formats.
Different No-SQL Types Databases6:34
How to Install MongoDB on UBuntu Machine?12:01
MongoDB CRUD Operations5:10
No-SQL Features and How it differs from ACID Propeties5:15
Practicals - How to Create Database in MongoDB?9:23
Practicals - MongoDB Create Operations (CRUD Examples)10:09
Practicals - MongoDB READ Operations (CRUD Examples)6:34
Practicals - MongoDB Update Operations (CRUD Examples)7:23
Practicals - MongoDB Delete Operations (CRUD Examples)8:24

What is Redis and Its Features?5:09
Redis Overview5:07
Discover a Redis overview and its role in fast data processing within the big data ecosystem, highlighting performance benchmarks and practical implications.
What are the different Redis Data Types?0:48
Install Redis on UBuntu Machine16:47
How to Start Redis Server and Terminal?6:09
Start and manage the Redis server from the terminal to access your Hadoop lab environment, verify connections, and learn command line workflows in a cloud setup.
Practicals with Redis Data Type "String" - 14:48
Practicals with Redis Data Type "String" - 24:24
Practicals with Redis Data Type "String" - 33:59
Practicals with Redis Data Type "LIST" - 110:24
Practicals with Redis Data Type "LIST" - 26:16
Practicals with Redis Data Type "LIST" - 34:37
Learn how to work with Redis list data type by accessing elements by index, retrieving values, and using range queries to explore and manipulate list data.

What is HBase?4:53
Why HBase?2:49
HBase Architecture in Detail with Diagram8:53
Different HBase Features5:00
Explore how HBase uses tables with column families and columns, organizing data by time stamps and rules, and prepare for practical setup of HBase features.
Most Important HBASE Commands1:50
Learn the most important HBase commands and how to pull data from tables. Apply these concepts within the Hadoop ecosystem.
How to Start HBase Services and Terminal on Cloudera?7:27
Practicals - HBase Commands5:22
How to Integrate HBase and Hive Tables?22:22
ACID Vs CAP Theorem8:23

What is Spark and its Components?7:08
Explore spark, an open-source processing engine for fast cluster computing, and its components, including MLlib for machine learning, batch processing, and streaming, with Java and Scala support.
Spark Architecture with Diagram in Detail6:04
What is RDD and its Features?7:05
Different Variable in Spark3:25
Basic Scala Commands6:01
How to Load Data from File in Spark?10:10
How to work with LIST Object in Spark?9:53
How to create Functions in Spark?6:15
Variable Implementation in Spark - 18:01
Variable Implementation in Spark - 24:22
How to Create your First Program in Spark using Eclipse?11:07
Learn to create your first Spark program using Eclipse, leveraging Scala development in the Hadoop ecosystem and practical steps for setting up and running Spark applications.
Most Important Spark Keywords7:59
Discover the most important spark keywords and how they relate to cluster management, Yarn resource managers, and spot cluster management for efficient big data processing.
Working with List using Eclipse10:13
How to Read Data using Spark Context?14:33
Read data using Spark context by loading a text file, applying map and collect transformations, and building a Scala-based Spark application to process and print flight data.
How to Read JSON Data in Spark?9:10
How to Read Parquet Format Data in Spark?10:15
How to Read Data from Hive in Spark?12:06
How to work with Hive Filters/Conditions using Spark?5:55

Requirements

As such there is no prerequisite required for this course and it is useful for any level of Big Data profile candidate. Any Big Data profile candidate can start this tutorial.
Any Developer/QA can start this course who has basic knowledge of development or testing with any database knowledge. There is no specific prerequisite other than this.

Description

This course is specially designed for All profile students i.e. developers and testers who wanted to build their career into Big Data Arena in Real World. So I have designed this course so they can start working with All Big Data Related Tools and technologies i.e. Hadoop, Hive, Pig, HBASE, CASSANDRA, MONGODB, REDIS in complete Big Data. All the users who are working or looking their career in Big Data profile in Big Data and wanted to move into Testing domain should take this course and go through the complete tutorials which has beginner to advance knowledge.

I have included the material which is needed for big data testing profile and it has all the necessary contents which is required for learning All Big Data Related Tools and technologies like Hadoop and Hive with different big data databases i.e. HBase, Cassandra, MongoDB + Redis in complete Big Data environment.

It will give the detailed information for different Commands and Queries which are used in development and testing All Big Data Related Tools and technologies including different databases applications in complete queries/commands which is needed by the tester to move into bigger umbrella i.e. Big Data Ecosystems Environment.

This course is well structured with all elements of different All Big Data Related Tools and technologies databases i.e. Haoop , Hive , HBase + Cassandra + MongoDB + Redis in complete big data with advance commands in practical manner separated by different topics. Students should take this course who wanted to learn End to End Big Data Ecosystem Technologies including different databases in complete big data from scratch.

Who this course is for:

Any Level of Development/Testing Profile Candidate is the target audience for this course.
Any Developer or QA beginner use this technology to enhance their skills.

Learn Big Data : Complete Hadoop Ecosystem with Practicals

What you'll learn

Explore related topics

Course content

Course Introduction9 lectures • 52min

Cloudera Setup Process1 lecture • 20min

Important HDFS Commands for Hadoop Execution4 lectures • 34min

HIVE Introduction with Practicals5 lectures • 34min

Cassandra Introduction with Practicals13 lectures • 1hr 48min

MongoDB Introduction with Practicals10 lectures • 1hr 18min

Redis Introduction with Practicals11 lectures • 1hr 8min

HBase Introduction with Practicals9 lectures • 1hr 7min

Spark and Scala Introduction with Practicals18 lectures • 2hr 30min

PIG Scripting Introduction with Practicals7 lectures • 39min

Requirements

Description

Who this course is for: