The Magic behind the Hadoop Technology and the Mapreduce design pattern

Posted by Sneha on September 30th, 2018

Do you have large sets of data that need processing? Do you work on a network where there are lots of computers to whom you need to distribute that processed data? The key is Hadoop MapReduce! It is a software infrastructure which is very simple. It can be used by the programmers to write collections of simple functions so that the huge amount expandable recyclerview of data can be processed easily and quickly. The experts have designed this software framework with the aim to create dependable and fault-tolerant outcomes.

In a set-up where there is a huge network of computers and large amount of data needs to be distributed in an efficient manner, Hadoop Distributed File System (HDFS) is definitely required. It is basically termed as a large-scale distributed batch processing infrastructure which is helpful for a set-up having numerous computers. While it can be used on a single machine but if you really want to experience the power of this system then you must use it on a network where hundreds or thousands of computers are available. In such a huge network data distribution is quite a task, but this Hadoop Mapreduce design pattern is so well-designed that it effectively distributes the entire data across the network. Lot of efforts are involved in the making of such efficient software systems and takes years in developing these magical instruments which ease out the work processes and bring more efficiency in the business outcomes.

Hadoop Distributed File System has the capacity to store vast quantities of information which can be processed irrespective of the operating system you are using. It has a unique feature of Hadoop ecosystem which provides some additive abilities to your distributed file system. Hadoop is a free Java software framework that supports data intensive distributed systems completely. Hadoop also offers a set of monitoring tools which can be really helpful in checking the health of your cluster.

Hadoop Distributed File System (HDFS)

MapReduce

In this, the HDFS facilitates quick data transfer between various types of computer nodes and also permits continued operation even in the event of any node failure. On the other hand, Hadoop commands map reduce distributes all the data processing over all such nodes, which reduces the complete workload on every individual computer and also permits for different computations and analysis beyond different capabilities of a particular computer or any kind of network.

If you think that Hadoop architecture and technology can help your enterprise and increase the overall productivity, more about it can be searched by browsing the web.