MongoDB Group Package (most specific, most popular, most understandable explanation)

As with databases, group is often used for statistics. MongoDB Group also has a lot of restrictions, such as: The return result set can not exceed 16M, the group operation will not process more than 10,000 unique keys. It seems that the index cannot be used [not very sure].

The group needs some number of references.

1.key: The field used to group the document.

And Keyf both must have a
2.KEYF: Able to accept a JavaScript function. The field used to dynamically determine the grouped document. And key both must have a
Initialization of variables used in 3.initial:reduce
4.reduce: Run the reduce function. The function needs to return a value.
5.cond: Conditions for running the filter.

6.finallize: After the reduce is run, the result set returns the function that was last run on the result set. Optional.

An example is described below:

Insert test data first:

1. General Group Query

Db.test.group ({                       key:{age:true},                       initial:{num:0},                       $reduce: function (doc,prev) {                              prev.num++                       }                      

2. Filter and then group

Db.test.group ({key:{age:true},initial:{num:0}, $reduce: function (doc,prev) {prev.num++},condition:{age:{$gt: 2}}) ; Db.runcommand ({group:{ns: "Test", key:{age:true},initial:{num:0}, $reduce: function (Doc,prev) {prev.num++}, condition:{age:{$GT: 2}}});

3, the ordinary $where query:

Db.test.find ({$where: function () {return this.age>2;}});

Group Federated $where Query

Db.test.group ({key:{age:true},initial:{num:0}, $reduce: function (doc,prev) {prev.num++},condition:{$where: function () {return this.age>2;}});

4. Grouping using function return values//Note that $KEYF the specified function must return an object

5. Using finalizers

Db.test.group ({$keyf: function (DOC) {return {age:doc.age};},initial:{num:0}, $reduce: function (doc,prev) {prev.num++ },finalize:function (DOC) {Doc.count=doc.num;delete doc.num;}}); Db.runcommand ({group:{ns: "Test", $keyf: function (DOC) {return {age:doc.age};},initial:{num:0}, $reduce: function (doc , prev) {prev.num++},finalize:function (doc) {Doc.count=doc.num;delete doc.num;}});

About MapReduce

First insert test data

for (Var i=1;i<21;i++) {Db.test.insert ({_id:i,name: ' mm ' +i});} Mapreducedb.runcommand ({mapreduce: ' Test ', map:function () {Emit (This.name.substr (0,3), this);},reduce:function (key,vals) {return vals[0];},//Note: Vals is an object instead of an array out: ' Wq '});

Note:
1.mapreduce is grouped according to the first parameter of the emit function called in the map function.
2. Key and document collections are processed by the reduce function only if a key matches multiple documents after grouping by grouping key. Like what:

Db.runcommand ({mapreduce: ' Test ', map:function () {Emit (This.name.substr (0,3), this);},reduce:function (key,vals) { Return ' Wq ';},out: ' Wq '});

after running the MapReduce command, review the WQ table data:

Db.wq.find () {"_id": "MM1", "Value": "Wq"} {"_id": "mm2", "Value": "Wq"} {"_id": "Mm3", "value": {"_id": 3, "Nam E ":" Mm3 "}} {" _id ":" MM4 "," value ": {" _id ": 4," name ":" Mm4 "}} {" _id ":" MM5 "," value ": {" _id ": 5," name ":"  MM5 "}} {" _id ":" MM6 "," value ": {" _id ": 6," name ":" MM6 "}} {" _id ":" MM7 "," value ": {" _id ": 7," name ":" MM7 "} } {"_id": "MM8", "value": {"_id": 8, "name": "MM8"}} {"_id": "Mm9", "value": {"_id": 9, "name": "Mm9"}}

MongoDB Group Package (most specific, most popular, most understandable explanation)