An open source platform that is used to manage large data set within an organization, Hadoop MapReduce spreads large set of data into various small sets so that it can be easily managed. It is known to help large enterprises with large datasets to get quick results by using innovative, scalable and consistent architecture. In Hadoop architecture, both data and its processing are distributed across various servers. Below are 7 key points every user must remember about Hadoop, its process and technology.

1. Every existing server in Hadoop applications provide local storage and multiplication, which means, if somebody runs some query contrary to huge sets of data; every server in this circulated architecture will be executing the query on its local machine contrary to the data sets present locally. In conclusion, the final set from all these local servers is incorporated. 2. In laymen’s terms, instead of running a query on an individual server and creating issues among all the teams present in the organization, it is fragmented across numerous servers, and the results are collective. The whole process makes it less complicated; as a result, the query is solved faster. 3. While using Hadoop, you do not necessarily require a powerful server. You can also use some less expensive commodity servers as individual notes and perform the task. This will diminish the chances of any further confusion and also helps organization to manage better and faster, without a powerful server. 4. The major feature that makes Hadoop MapReduce favorite of large enterprises is its high fault tolerance power, which means if any of the nodes fail in the environment, the enterprise data management system won’t face any halt and it will run as smoothly as it was running before. This is because the architecture takes care of allocating and reproducing the data efficiently through numerous nodes. 5. Easy implementation can use only two servers to perform the tasks but the single one may scale up to hundreds of servers without putting much of an effort.

Further to the aforesaid, there are several other benefits of Hadoop such as it is used for data mining, for sorting, for machine learning, for web search and also for numerous other systems. Although, it is an open source system, Hadoop training is important to excel in the field. If you feel that Hadoop can help leverage your business, more information can be searched about the framework online.