Transform Your Career: Big Data and Hadoop Class

Big Data and Hadoop

Managing Big data using Hadoop tools like MapReduce, Hive, Pig, hBase and m

Created by : Rated :4.1 34134 views

Last Updated: 2024-11-18 04:11:58 English Course Type: Self Learning

In late 1990s, Developers and Programmers were generating data through coding, in late 2000s everyone on Social media generating data on FB, Twitter, Insta etc and these days Machines are generating data which overall creating a Huge Volume of data which cannot be handled easily through traditional databases, so after completion of this course you'll be able to do that using HADOOP as your platform and also Able to crack Cloudera CCA 175 Certification

This is an interactive lecture of one of my Big data and Hadoop class where everything is covered from the scratch and also you will see students asking doubts so you can clear those concepts here as well.

Students will be Able to crack Cloudera CCA 175 Certification after successful completion and with little practice.

Tools covered :

1. Sqoop

2. Flume

3. MapReduce

4. Hive

5. Impala

6. Beeline

7. Apache Pig

8. HBase

9. OOZIE

10. Project on a real data set.

A Laptop, 6 GB RAM (at least), 100 GB FREE HDD

Students who want to step into Big Data, want to know how to Analyse, work on and manage it.

Section 1 : All about BIG DATA 26 Lectures 00:01:29
Lecture 1 :
Big Data and Hadoop Introduction Preview
Lecture 2 :
Hadoop framework
Lecture 3 :
Hadoop Ecosystem
Lecture 4 :
HDFS
Lecture 5 :
Magic Boxes, Sqoop and Flume
Lecture 6 :
NameNode, DataNode, JournalNode
Lecture 7 :
Input output operations, Ram and HDD, pros and cons
Lecture 8 :
Mapreduce Theory 1.1
Lecture 9 :
Mapreduce Theory 1.2
Lecture 10 :
Mapreduce Theory 1.3
Lecture 11 :
Combiner Approach in MapReduce
Lecture 12 :
Coding : Sqoop with SQL
Lecture 13 :
Visit to Cloudera Machine
Lecture 14 :
Sqoop commands with introduction to Linux commands as well
Lecture 15 :
Sqoop commands
Lecture 16 :
Basics of core Java, introduction to eclipse, MapReduce Coding
Lecture 17 :
Coding : MapReduce
Lecture 18 :
Hive Theory
Lecture 19 :
Hive: connecting, loading, defining delimiters
Lecture 20 :
Coding : Hive
Lecture 21 :
Hive to Impala and Beeline
Lecture 22 :
Hive : Partitioning
Lecture 23 :
Hive Bucketing
Lecture 24 :
YARN, HBASE, OOZIE
Lecture 25 :
FINAL PROJECT ON REAL DATA SET
Lecture 26 :
Assignment on DataNodes
Introduction Let's assume that, you have 100 TB of data to store and process with Hadoop. The configuration of each available DataNode is as follows: â€¢ 8 GB RAM â€¢ 10 TB HDD â€¢100 MB/s read-write speed ï€ You have a Hadoop Cluster with replication factor = 3 and block size = 64 MB. In this case, the number of DataNodes required to store would be: â€¢ Total amount of Data * Replication Factor / Disk Space available on each DataNode â€¢100 * 3 / 10 â€¢30 DataNodes ï€ Now, let's assume you need to process this 100 TB of data using MapReduce. And, reading 100 TB data at a speed of 100 MB/s using only 1 node would take: â€¢Total data / Read-write speed â€¢100 * 1024 * 1024 / 100 â€¢1048576 seconds â€¢291.27 hours ï€ So, with 30 DataNodes you would be able to finish this MapReduce job in: â€¢291.27 / 30 â€¢9.70 hours ï€ 1.Problem Statement How many such Data Nodes you would need to read 100TB data in 5 minutes in your Hadoop Cluster?

How do i access the course after purchase?
It's simple. When you sign up, you'll immediately have unlimited viewing of thousands of expert courses, paths to guide your learning, tools to measure your skills and hands-on resources like exercise files. There’s no limit on what you can learn and you can cancel at any time.
Are these video based online self-learning courses?
Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic.
Can i play & pause the course as per my convenience?
Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
How do i contact the instructor for any doubts or questions?
Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want.
Do i need a pc to access the course or can i do it on mobile & tablet as well?
Brilliant question? Isn't it? You can access the courses on any device like PC, Mobile, Tablet & even on a smart tv. For mobile & a tablet you can download the Learnfly android or an iOS app. If mobile app is not available in your country, you can access the course directly by visting our website, its fully mobile friendly.
Do i get any certificate for the courses?
Yes. Once you complete any course on our platform along with provided assessments by the instructor, you will be eligble to get certificate of course completion.
For how long can i access my course on the platform?
You require an active subscription to access courses on our platform. If your subscription is active, you can access any course on our platform with no restrictions.
Is there any free trial?
Currently, we do not offer any free trial.
Can i cancel anytime?
Yes, you can cancel your subscription at any time. Your subscription will auto-renew until you cancel, but why would you want to?

Saheb Singh chaddha,

262743 Course Views

6 Courses

Hello guys, How are you all doing? So a quick introduction of me, well I am a Big Data Expert and Data Scientist, I have 3 years of experience on these domain in companies as well as a trainer. My teaching method is completely different than others like I am not a slide reader, I use analogies and examples a lot to explain things and mostly try to be practical which you'll see in the course. Hope to see you all in the lectures, Good Luck!