MongoDB - Map Reduce

According to MongoDB documentation, MapReduce is a data processing paradigm used to condense large data sets into useful aggregated results. MongoDB employs the mapReduce command for map-reduce operations, primarily for processing substantial data sets.

MapReduce Command Syntax

The basic syntax of the mapReduce command in MongoDB is as follows:

db.collection.mapReduce(
   function() {emit(key,value);},  // map function
   function(key,values) {return reduceFunction;},  // reduce function
   {   // options
      out: collection,  // specifies the location of the query result
      query: document,  // optional selection criteria for documents
      sort: document,   // optional sort criteria
      limit: number     // optional maximum number of documents to return
   }
)

In the above syntax:

• map is a JavaScript function that maps a value with a key and emits a key-value pair.
• reduce is a JavaScript function that reduces or groups documents with the same key.
• out specifies the location of the map-reduce query result.
• query specifies optional selection criteria for selecting documents.
• sort specifies optional sort criteria.
• limit specifies the optional maximum number of documents to return.

Using MapReduce

Consider a document structure storing user posts with fields like post_text, user_name, and status. We will perform a mapReduce function to select active posts, group them by user_name, and count the number of posts by each user.

db.posts.mapReduce( 
   function() { emit(this.user_name, 1); }, 
   function(key, values) { return Array.sum(values); }, 
   {  
      query: { status: "active" },  
      out: "post_total" 
   }
)

The above mapReduce query outputs the following result:

{
   "result" : "post_total",
   "timeMillis" : 9,
   "counts" : {
      "input" : 4,
      "emit" : 4,
      "reduce" : 2,
      "output" : 2
   },
   "ok" : 1
}

To see the result of this mapReduce query, you can use the find operator:

db.post_total.find()

This query will return results showing the count of active posts for each user:

{ "_id" : "tom", "value" : 2 }
{ "_id" : "mark", "value" : 2 }

MapReduce queries in MongoDB are powerful for constructing complex aggregation queries using custom JavaScript functions, providing flexibility in data processing and analysis.

Diagram: MapReduce Process

Performance Considerations

When using MapReduce in MongoDB:

• Consider the performance overhead, especially for large data sets.
• Optimize your map and reduce functions for efficiency.
• Utilize indexes to improve query performance.

Table: MapReduce Options

Option	Description
out	Specifies the location of the query result.
query	Optional selection criteria for documents.
sort	Optional sort criteria.
limit	Optional maximum number of documents to return