MongoDB MapReduce Example Tutorial

MongoDB MapReduce Example Tutorial

MongoDB MapReduce Example Tutorial. MapReduce is the data processing mechanism for condensing large volumes of data into useful aggregated results.

MongoDB MapReduce Example Tutorial is today’s leading topic. MapReduce is the data processing mechanism for condensing large volumes of data into useful aggregated results. MongoDB uses MapReduce command for map and reduce operations. MapReduce is used for processing large data sets. In straightforward terms, the MapReduce command takes two primary inputs, the mapper function, and the reducer function.

The Mapper will start by reading the collection of data and building the Map with the required fields that we need to process and group them into one array. And then this key-value pair is fed into the Reducer, which will transform the values. MapReduce is a framework which allows parallelizing the processing of large and extensive data sets across many physical or virtual servers. The typical Map/Reduce program consists of two phases:

  1. map phase: filter / transform / convert data
  2. reduce phase: perform aggregations over the data

mongodb mongodb mapreduce mapreduce

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