Hadoop Ecosystem Explained | Hadoop tools for handling Big Data | Hadoop Full Course | Lecture 2

This lecture is all about Hadoop ecosystem and their different components in details and how they work together to crunch Big Data!
Here we have seen the basic introductory part for following Hadoop tools:
MapReduce, YARN, Hive, Apache Pig, Apache HBase and HBase components, Apache mahout, Sqoop, Apache Spark, Apache Flume, Ambari, Zookeeper and Apache Oozie.
Want to know more about Big Data? then checkout the full course dedicated to Big Data fundamentals: • Big Data Full Course
In the previous lecture we have seen Hadoop Introduction where we have discussed what is Hadoop?, why it is different from Big Data?, Why it is used?, and Hadoop architecture.
We have also covered Hadoop core components in details which are:
1. Hadoop Distributed File System (HDFS)
2. MapReduce
3. YARN
Also check out similar informative videos in the field of cloud computing:
What is Big Data: • What is Big Data? | Bi...
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What is Cloud? • What is Cloud Computing?
Top 10 facts about Cloud Computing that will blow your mind! • Top 10 facts about Clo...
Audience
This tutorial is made for professionals who are willing to learn the basics of Big Data Analytics using Hadoop Ecosystem and become a Hadoop Developer. Software Professionals, Analytics Professionals, and ETL developers are the key beneficiaries of this course.
Prerequisites
Before you start proceeding with this course, I am assuming that you have some basic knowledge to Core Java, database concepts, and any of the Linux operating system flavors.
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[@ankuryadav2891]

Sir plz share ur notes it will of great help.

[@bharathns1361]

thank you sir

[@ampcode]

Thank you! 😊

[@srikant-kumar]

Hi I am working in company and working on 30 gb size of data which has 25 crore rows and 256 coulmns . We are facing issue to get faster result with sql queries we are using postgreSQL so we need help to setup technology that can handle our problem while getting results
If you are intrested then we can pay you as well

[@ampcode]

Sorry for late reply. I hope your issue is resolved. If not we can have a connect and discuss further on it!