Advances of Hadoop 3.0 over 2.0
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In this IT world, data is generated enormously. Today roughly 2.5 Quintilian bytes of data generated every day.  So processing this huge amount of data and updating it has become a complex job. Processing this bulk amount of data has become a typical task. Because processing this amount of data usually takes more than a day .have you ever think how to process this data?do you think that RDBMS solve this problem of handling the data? If so you are wrong. The alternative to handle this bulk amount of data is using of the framework. For complete answer read Advances of Hadoop 3.0 over 2.0.

This framework needs to processes the data in a short span of time.  Among those many frameworks, why do companies prefer Hadoop? the reason is Hadoop is a distributed File processing system. It means the data that they get divided into small chunks and processed parallelly rather than sequentially. So this method saves time. This is the secreted  Hadoop is one of the most commonly used frameworks for file distribution. This framework is being used by many companies today. Because of its high usage, it has advancements from day to day. Today in this article, I would like to  explain to you the advances of Hadoop 3.0 over 2.0

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Since its release, the Hadoop has been releasing various version sequentially. Now its latest version is Hadoop 3.0.  this version has many exciting features when compared to the previous versions.  So read the complete article to know the  advances of Hadoop 3.0 over 2.0

Advances of Hadoop 3.0 over 2.0 :

Along with updated version, there are some essential requirements  of using Hadoop 3.0


In order to run the cluster, one has to use either JAVA (or) python. Most of the old and efficient programmers usually use JAVA. Even this java has several versions. Its latest version is 10. But in order to run the Hadoop 3.0 minimum, JAVA 8 is mandatory. This version of Java supports all the necessary plugins in order to set up the cluster.

Erasure coding :

As we know that replication factor of HDFS is 3.  It means that other than original copy two more xerox copies will be stored in the cluster. This is made for purpose of retrieving the original copy when it fails. But one of the drawbacks of this feature is it consumes more space. It means for 2 xerox copies it consumes the 200 % of storage. But through  Erasure coding, we can reduce the space consumption to 50 % with same fault tolerance.

Rewriting of Shell scripts :

For the purpose of running the cluster, we usually take the help of scripting language. Bugs were common while running the cluster.  So when the cluster does not run, we usually find the bugs in a shell script and make some changes in the environment in order to run the cluster. Some of the points to remember while writing shell scripts are as follows :

1)All the Hadoop shell script subsystem now allows, which allows all the environment variable to be in one location.

2)Operations which trigger ssh connections can now use pdsh if installed.

3)Scripts now test and report various error messages for various states of logs and pids.

Unlimited NameNodes :

In the previous versions of Hadoop, we have one primary name node and one standby name-node. But in this fast growing   IT environment, developers require more standby name-nodes.  So to satisfy that requirement, Hadoop 3.0 allows an unlimited number of standby name nodes.

Change of Port numbers :

We usually point to a specific port using port numbers.  But some startup were confusing with the default port numbers.So in Hadoop 3.0  some of the port numbers were changed. 

Along with that, there are some more additional benefits of Hadoop 3.0.  So get those benefits from the real-time experts of  OnlineITGuru  through Big Data Hadoop online Course.

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