Differences between Hadoop 1 x & 2 x

difference between Hadoop 1.X and 2.X. So, let us discuss what are the different features

have got added with the new version of Hadoop, that is, Hadoop 2.X

Hadoop 1.X was having a basic features are there. So, we had the Hadoop, that is the HDFS, we had the map reduce, we're having the respective

hype, but in case of Hadoop 2.X, we have got so many different components and features

have got added. So, let us go for some more detailing about them

So, this is our Hadoop 1.0. We are having here the PIG, the HIB and the others are there

And here we are having this MAPReduce which is required for cluster resource management

and data processing. We are having the SDFS which is redundant reliable storage, that is Hadoop distributed file system

But if you consider this Hadoop 2.0, it is having so many different other components are there

We are having this MAP produce, we are having PIG, HIP, so they were having HIP, so they were

already there in the version 1.0. Now we are having the other features like your RT stream

We are having Graffstrom Zruff we having the services from H having this stage for this execution engine yearn that is yet another resource negotiator cluster resource management

SDFS2, the version has become HDFS2, redundant and further reliable storage. So the main difference between Hadoop 1.X and Hadoop 2.X is in their architecture and

Hadoop 1.X was designed with some basic features. like our HDFS, PIG, MapReduce, Hib, etc

So, these are the basic features we had in our Hadoop 1.X

And also Hadoop 1.X was having so many different drawbacks, and that's why Hadoop 2.X has come in the market

So, in case of Hadoop 2.X, there are many additional frameworks have got added

As we have discussed, here we're having this year on. SDFS2 is that second version I'm getting T.A. T.H

We're having the respective H-base. We are having the storm and so on

So, let us go for one comparison table for the better understanding what was not there

and what has come. So here we are having one comparison table for you So it supports only MapReduce tool in case of Haddub 1 It supports more than the basic map reduced tool like our Spark HBS etc Next one is that Hadoop 1 was having

maximum limit was 4,000 nodes per cluster. But here the limit has got too much increased

So it is scalable up to 10,000 nodes per cluster. So now it is capable to deal with huge amount

of data. It was the 4,000 number of nodes per cluster. Now it has become 10,000 number of

nodes per cluster. Works on slots, each slot can run either map or reduce task. So here

works on containers and the containers they can do generic tasks depending upon the business

logic needed. We can do the tax implementation accordingly. So single name note is used and multiple

NAMNodes may be used for the load sharing if we require, Hadoop 2.AX supports multiple

name nodes. So, supports only Linux system and it supports Microsoft Windows system also

So it supports only Linux and it supports also the Microsoft Windows system There is another some points are there No additional files are needed to execute a map reduce program but in case of Hadoop 2

X to run the program on Hadoop 1.X in 2.X we need some additional files there

So here if you write a program in Hadoop 1.X and if you want to run that program, that is

a running of the program of Hadoop 1.X in the 2.X environment we require some X

files so MapReduce does both the processing and the cluster resource management

but here we are having the yearn which will be doing the job for us so the cluster

resource management is done by yearn and processing is been done by another

processing models next one is that failure of name node affects the stack and

here hype pig edge base all are responsible for handling the name note failure so

So, when the name note will have the failure, in that case, this high pig and edge base

so they will take care of that situation and the system will be restored and revived

So these are the differences between Hadoop 1. X and 2.X. We have made one comparison table for your better understanding

Thanks for watching this video