🔥 Enroll for FREE Big Data Hadoop Spark Course & Get your Completion Certificate: https://www.simplilearn.com/learn-hadoop-spark-basics-skillup?utm_campaign=Hadoop&utm_medium=DescriptionFirstFold&utm_source=youtube
This Hadoop tutorial will help you understand what is Big Data, what is Hadoop, how Hadoop came into existence, what are the various components of Hadoop and an explanation on Hadoop use case. Below topics are explained in this Hadoop tutorial:
Below topics are explained in this Hadoop tutorial:
(02:30)The rise of Big Data
(06:31)What is Big Data?
(09:40)Big Data and its challenges
(11:17)Hadoop as a solution
(11:31)What is Hadoop?
(11:51)Components of Hadoop
(25:16)Use case of Hadoop
To learn more about Hadoop, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1
To access the slides, click here: https://www.slideshare.net/Simplilearn/what-is-hadoop-what-is-big-data-hadoop-introduction-to-hadoop-hadoop-tutorial-simplilearn/Simplilearn/what-is-hadoop-what-is-big-data-hadoop-introduction-to-hadoop-hadoop-tutorial-simplilearn
Watch more videos on HadoopTraining: https://www.youtube.com/watch?v=CKLzDWMsQGM&list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ
#Hadoop #WhatIsHadoop #BigData #Hadooptutorial #HadoopTutorialForBeginners #LearnHadoop #HadoopTraining #HadoopCertification #SimplilearnHadoop #Simplilearn
Simplilearn’s Big Data Hadoop training course lets you master the concepts of the Hadoop framework and prepares you for Cloudera’s CCA175 Big data certification. With our online Hadoop training, you’ll learn how the components of the Hadoop ecosystem, such as Hadoop 3.4, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real life projects in banking, telecommunication, social media, insurance, and e-commerce on CloudLab.
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
Who should take up this Big Data and Hadoop Certification Training Course?
Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals:
1. Software Developers and Architects
2. Analytics Professionals
3. Senior IT professionals
4. Testing and Mainframe professionals
5. Data Management Professionals
6. Business Intelligence Professionals
7. Project Managers
8. Aspiring Data Scientists
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training?utm_campaign=What-is-Hadoop-iANBytZ26MI&utm_medium=Tutorials&utm_source=youtube
For more information about Simplilearn courses, visit:
– Facebook: https://www.facebook.com/Simplilearn
– Twitter: https://twitter.com/simplilearn
– LinkedIn: https://www.linkedin.com/company/simplilearn/
– Website: https://www.simplilearn.com
Get the Android app: http://bit.ly/1WlVo4u
Get the iOS app: http://apple.co/1HIO5J0
🔥Explore Our FREE Courses With Completion Certificate: https://www.youtube.com/watch?v=-caxhMlw_04
thank you! very well structured!
$10 thousand times 100 of em = lotta mone
you guys are amazing at explaining complex stuff
Simple and Straight forward .. the sound is just not easy to listen to
We are a Family heart
Best Hadoop explanation I've watched so far. Thank you very much for making this video!
people who teach using visual parables that are relatable and easy to understand and ingest are SO UNDER APPRECIATED. Thanking you.
Great lecture, thanks!
I love the teaching and useful knowledge you provide for us. Although my ears hurt either cuz the mic is too close to the mouth or something else, so I can’t even finish watching these amazing videos, unfortunately
This is so well explained – simply amazing. Superb job, very well done…
Very well explained. Thank you very much!
This is very good presentation on Basics of Hadoop , thanks
Thala un english puriyala 😂😂
This is a detailed introductory class to Hadoop. I hope to get more of this in the nearest future.
It's an amazing tutorial. Very very nice. Thanks sir
Nice. Liked it. Short and Simple.
wow, it was an awesome introduction of hadoop. I am looking into what's next and how to I become hadoop developer and where to start as a first step?
The audio quality is awful to listen to. Why would you spend that much time and effort on producing content this good, but then use the worst possible microphone??
There are gaps in architecture of Hadoop as explained in this tutorial, otherwise overall it is good start
Thanks and u let me know the stuff clear
At 16:08 I believe you meant "first column" not "first row".
This was the perfect introductory video to hadoop…thank you.
Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you. Thanks for watching the video. Cheers!