What is MapReduce?
MapReduce is a programming technique, and we can write MapReduce programmes in any language we want. MapReduce is a programming paradigm that enables large-scale scalability across a Hadoop cluster’s thousands of servers. MapReduce, as the processing component, is at the heart of Apache Hadoop. The term “MapReduce” refers to two distinct tasks performed by Hadoop programmes. The first is map work, which transforms a set of data into another set of data by dividing certain components into tuples (key-value pairs).
Benefits of MapReduce:
1. Scalability: The Hadoop Distributed File System allows businesses to interact with and analyse petabytes of data.
2. Flexibility: Hadoop enables easier access to a larger number of data sources and diverse sorts of data.
3. Speed: Hadoop uses parallel computing and little data transport to process data quicker.
4. Simple: The Mapreduce programme can be written in a variety of languages, including Java, C++, and Python.