Map Reduce Features :
Features of MapReduce are as follows :
Scalability: Apache Hadoop is a highly scalable framework. This is because of its ability to store and distribute huge data across plenty of servers.
Flexibility : MapReduce programming enables companies to access new sources of data. It enables companies to operate on different types of data.
Security and Authentication: The MapReduce programming model uses HBase and HDFS security platform that allows access only to the authenticated users to operate on the data.
Cost-effective solution: Hadoop’s scalable architecture with the MapReduce programming framework allows the storage and processing of large data sets in a very affordable manner.
Fast: Even if we are dealing with large volumes of unstructured data, Hadoop MapReduce just takes minutes to process terabytes of data. It can process petabytes of data in just an hour.
A simple model of programming: One of the most important features is that it is based on a simple programming model.
Parallel Programming: It divides the tasks in a manner that allows their execution in parallel. Parallel processing allows multiple processors to execute these divided tasks.
Availability: If any particular node suffers from a failure, then there are always other copies present on other nodes that can still be accessed whenever needed.
Resilient nature: One of the major features offered by Apache Hadoop is its fault tolerance. The Hadoop MapReduce framework has the ability to quickly recognizing faults that occur.
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