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WHAT	 	IS	 	HADOOP	 	AND	 	ITS		 	 	 	 	
COMPONENTS?			
WHAT IS HADOOP?
Hadoop is owned by the Apache. Hadoop is a framework which is majorly
used for storing and processing the big data. Hadoop is an open-source
software which means that anyone can change its features. The code of the
Hadoop software is openly available. The Hadoop software works in the
distributed computing environment. This environment of Hadoop is known as
Hadoop Distributed File System. The software is written in the Java
programming language.
FEATURES OF HADOOP
Here are some features of the Hadoop software which makes it more
user-friendly. They are listed below-->
● Perfect for the analysis of big data
Hadoop is one of those frameworks which are capable of processing and
storing the big data. If the data is processed in the Hadoop software,
then it will require low bandwidth because the logic of the processing
is transferred to the computing nodes instead of the actual data.
Here, low bandwidth means we can work on the low internet
connection also. This activity increases the efficiency of the
applications built in Hadoop. This concept of Hadoop is known as
the data locality concept.
● Scalability
The scalability means the Hadoop clusters can be extended to any
number of computer nodes. There would not be any problem. For the
extension, we do not need to modify the logic of the applications.
● Fault tolerance
The best feature of the Hadoop framework is its backup system. The Hadoop
software automatically makes the copies of the input data. The data can be
recovered easily in case of system failure.
MODULES OF THE HADOOP FRAMEWORK
Here are the modules of the Hadoop framework. Modules mean the small and
important parts of the Hadoop software. They are listed below-->
● HDFS
HDFS is an important component of the Hadoop framework. What it does is,
it breaks the input data into small pieces and distributes them over the
computer nodes. The Hadoop works on the principle of parallel computing.
● YARN
YARN stands for Yet Another Resource Negotiator. The task of the YARN is
job scheduling and the management of the clusters.
● MapReduce
The MapReduce is a framework which does parallel computing in the Hadoop
with the help of key-value pair. What it does is, it receives the input data
and converts the input data into a data set which can be computed into the
key-value pairs. The output of such input is taken with the help of the
reduce task method.
● Hadoop Common
These are nothing but the Java libraries. These libraries are used for initiating
the Hadoop software. These libraries are also used by the other modules of
the Hadoop software.
ADVANTAGES OF THE HADOOP
Here are some advantages of the Hadoop software. They are listed below-->
● It can prevent system failure.
● It is scalable.
● It is cost-effective.
● The framework is fast.
● It is flexible.
CONCLUSION
As said above, Hadoop is used for the management of big data. We know that
at present every sector is working on the big data. The big data has a bright
future and so does the Hadoop. Big data is not possible without frameworks
like Hadoop. Students should learn Hadoop. Many courses are available which
provide a complete course on Hadoop as well as Hadoop certification.

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WHAT IS HADOOP AND ITS COMPONENTS?

  • 1. WHAT IS HADOOP AND ITS COMPONENTS? WHAT IS HADOOP? Hadoop is owned by the Apache. Hadoop is a framework which is majorly used for storing and processing the big data. Hadoop is an open-source software which means that anyone can change its features. The code of the Hadoop software is openly available. The Hadoop software works in the distributed computing environment. This environment of Hadoop is known as Hadoop Distributed File System. The software is written in the Java programming language. FEATURES OF HADOOP Here are some features of the Hadoop software which makes it more user-friendly. They are listed below--> ● Perfect for the analysis of big data Hadoop is one of those frameworks which are capable of processing and storing the big data. If the data is processed in the Hadoop software, then it will require low bandwidth because the logic of the processing is transferred to the computing nodes instead of the actual data. Here, low bandwidth means we can work on the low internet connection also. This activity increases the efficiency of the applications built in Hadoop. This concept of Hadoop is known as the data locality concept. ● Scalability The scalability means the Hadoop clusters can be extended to any number of computer nodes. There would not be any problem. For the extension, we do not need to modify the logic of the applications.
  • 2. ● Fault tolerance The best feature of the Hadoop framework is its backup system. The Hadoop software automatically makes the copies of the input data. The data can be recovered easily in case of system failure. MODULES OF THE HADOOP FRAMEWORK Here are the modules of the Hadoop framework. Modules mean the small and important parts of the Hadoop software. They are listed below--> ● HDFS HDFS is an important component of the Hadoop framework. What it does is, it breaks the input data into small pieces and distributes them over the computer nodes. The Hadoop works on the principle of parallel computing. ● YARN YARN stands for Yet Another Resource Negotiator. The task of the YARN is job scheduling and the management of the clusters. ● MapReduce The MapReduce is a framework which does parallel computing in the Hadoop with the help of key-value pair. What it does is, it receives the input data and converts the input data into a data set which can be computed into the key-value pairs. The output of such input is taken with the help of the reduce task method. ● Hadoop Common These are nothing but the Java libraries. These libraries are used for initiating the Hadoop software. These libraries are also used by the other modules of the Hadoop software. ADVANTAGES OF THE HADOOP Here are some advantages of the Hadoop software. They are listed below--> ● It can prevent system failure. ● It is scalable. ● It is cost-effective. ● The framework is fast. ● It is flexible.
  • 3. CONCLUSION As said above, Hadoop is used for the management of big data. We know that at present every sector is working on the big data. The big data has a bright future and so does the Hadoop. Big data is not possible without frameworks like Hadoop. Students should learn Hadoop. Many courses are available which provide a complete course on Hadoop as well as Hadoop certification.