MapReduce is a programming model and software framework developed by Google for processing large amounts of data in a distributed computing environment. It is mainly used for parallel processing of huge datasets in a cluster of computers. The model consists of two main functions - Map and Reduce - that are responsible for processing and transforming the data. MapReduce is built on top of the Hadoop Distributed File System (HDFS) and provides fault tolerance and scalability for handling large datasets.
In the Map function, data is divided into subgroups and operations are performed on each subgroup in parallel. The output of each Map operation is a key-value pair. In the Reduce function, data is aggregated by the key and the results are combined to produce the final result.
MapReduce is widely used in big data analytics, machine learning, and data processing applications. It is an efficient and scalable framework for distributed computing and has become a standard in the big data industry.
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