To aggregate second element from input element, use mapReduce(). Map-reduce is a data processing paradigm for condensing large volumes of data into useful aggregated results. Let us create a collection with documents −
> db.demo621.insert({ _id: 101, Name1: "John", Name2: "John" }); WriteResult({ "nInserted" : 1 }) > db.demo621.insert({ _id: 102, Name1: "Bob", Name2: "John" }); WriteResult({ "nInserted" : 1 }) > db.demo621.insert({ _id: 103, Name1: "Chris", Name2: "John" }); WriteResult({ "nInserted" : 1 }) > db.demo621.insert({ _id: 104, Name1: "Sam", Name2: "John" }); WriteResult({ "nInserted" : 1 })
Display all documents from a collection with the help of find() method −
> db.demo621.find();
This will produce the following output −
{ "_id" : 101, "Name1" : "John", "Name2" : "John" } { "_id" : 102, "Name1" : "Bob", "Name2" : "John" } { "_id" : 103, "Name1" : "Chris", "Name2" : "John" } { "_id" : 104, "Name1" : "Sam", "Name2" : "John" }
Following is the query to aggregate second element from input element −
> db.demo621.mapReduce( ... function () { ... track++; ... var actualId= this._id; ... delete this._id; ... if ( track % div == 0 ) ... emit(actualId, this ); ... }, ... function() {}, ... { ... "scope": { "track": 0, "div": 2 }, ... "out": { "inline": 1 } ... } ... )
This will produce the following output −
{ "results" : [ { "_id" : 102, "value" : { "Name1" : "Bob", "Name2" : "John" } }, { "_id" : 104, "value" : { "Name1" : "Sam", "Name2" : "John" } } ], "timeMillis" : 48, "counts" : { "input" : 4, "emit" : 2, "reduce" : 0, "output" : 2 }, "ok" : 1 }