{"id":111776,"date":"2021-03-08T10:36:22","date_gmt":"2021-03-08T05:06:22","guid":{"rendered":"https:\/\/www.vskills.in\/certification\/tutorial\/?page_id=111776"},"modified":"2024-04-12T14:31:35","modified_gmt":"2024-04-12T09:01:35","slug":"map-reduce","status":"publish","type":"page","link":"https:\/\/www.vskills.in\/certification\/tutorial\/map-reduce\/","title":{"rendered":"Map-Reduce"},"content":{"rendered":"\n

Map-Reduce<\/strong><\/h4>\n\n\n\n

Map-reduce is a data processing paradigm for condensing large volumes of data into useful aggregated results. For map-reduce operations, MongoDB provides the mapReduce database command. Consider the following map-reduce operation.<\/p>\n\n\n

\n
\"Image<\/figure>\n<\/div>\n\n\n
Diagram of the annotated map-reduce operation.<\/h5>\n\n\n\n

In this map-reduce operation, MongoDB applies the map phase to each input document (i.e. the documents in the collection that match the query condition). The map function emits key-value pairs. For those keys that have multiple values, MongoDB applies the reduce phase, which collects and condenses the aggregated data. MongoDB then stores the results in a collection. Optionally, the output of the reduce function may pass through a finalize function to further condense or process the results of the aggregation.<\/p>\n\n\n\n

All map-reduce functions in MongoDB are JavaScript and run within the mongod process. Map-reduce operations take the documents of a single collection as the input and can perform any arbitrary sorting and limiting before beginning the map stage. mapReduce can return the results of a map-reduce operation as a document, or may write the results to collections. The input and the output collections may be sharded.<\/p>\n\n\n\n

For most aggregation operations, the Aggregation Pipeline provides better performance and more coherent interface. However, map-reduce operations provide some flexibility that is not presently available in the aggregation pipeline.<\/p>\n\n\n\n

Map-Reduce JavaScript Functions<\/strong> – In MongoDB, map-reduce operations use custom JavaScript functions to map, or associate, values to a key. If a key has multiple values mapped to it, the operation reduces the values for the key to a single object. The use of custom JavaScript functions provide flexibility to map-reduce operations. For instance, when processing a document, the map function can create more than one key and value mapping or no mapping. Map-reduce operations can also use a custom JavaScript function to make final modifications to the results at the end of the map and reduce operation, such as perform additional calculations.<\/p>\n\n\n\n

Map-Reduce Behavior<\/strong> – In MongoDB, the map-reduce operation can write results to a collection or return the results inline. If you write map-reduce output to a collection, you can perform subsequent map-reduce operations on the same input collection that merge replace, merge, or reduce new results with previous results.<\/p>\n\n\n\n

When returning the results of a map reduce operation inline, the result documents must be within the BSON Document Size limit, which is currently 16 megabytes. MongoDB supports map-reduce operations on sharded collections. Map-reduce operations can also output the results to a sharded collection.<\/p>\n\n\n\n

Apply for MongoDB Certification Now!!<\/h3>\n\n\n\n

https:\/\/www.vskills.in\/certification\/databases\/mongodb-server-administrator<\/a><\/p>\n\n\n\n

Back to Tutorial<\/strong><\/a><\/h4>\n","protected":false},"excerpt":{"rendered":"

Map-Reduce Map-reduce is a data processing paradigm for condensing large volumes of data into useful aggregated results. For map-reduce operations, MongoDB provides the mapReduce database command. Consider the following map-reduce operation. Diagram of the annotated map-reduce operation. 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