Question

First, introduce user collection.

user {'username':, 'age':, 'account':}

The following are normal group_by and count implementations

//SQL implementation

select username,count(sku) from user group by username

//MapReduce Implementation

map=function (){
 emit(this.username,{count:1})
 }
 
 reduce=function (key,values){
 var cnt=0;
 values.forEach(function(val){ cnt+=val.count;  });
 return {"count":cnt}
 }

//Execute mapreduce

db.test.mapReduce(map,reduce,{out:”mr1″})

db.mr1.find()

{ "_id" : "Joe", "value" : { "count" : 416 } }
 { "_id" : "Josh", "value" : { "count" : 287 } }
 { "_id" : "Ken", "value" : { "count" : 297 } }

Then

//SQL implementation

select sum(age * account) from user

//MapReduce implementation, or other methods can also be used
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?

Answer 1

In general, we would suggest avoiding using map/reduce in MongoDB, and the performance is not very good. The aggregation framework can be used most of the time, especially when only one table is involved.

db.user.aggregate([
 {$group: {_id: '$username', count: {$sum: 1}}}
 ]);

Please refer to the grammar of aggregation for specific grammar.a*bIt will be more complicated. What you really need is the value of a*b (pipline1) for each record, and then sum (pipline2):

db.user.aggregate([
 {$group: {_id: "$username", temp_result: {$multiply: ["$age", "$account"]}}},
 {$group: {_id: null, result: {$sum: "$temp_result"}}}
 ]);