MongoDB: a detailed explanation of mongodb's advanced operations, aggregation, and cursors

A few days ago, I summarized the mongodb installation entry and explained in detail the basic operations for adding, deleting, modifying, and querying. Today I will summarize more advanced operations, aggregation, and cursors for mongodb.

I. Aggregation: mongodb's aggregation operations are generally divided into four scenarios: count, distinct, group, and mapReduce

1. count

Count is the simplest, easiest, and most commonly used aggregate tool. It is usually used by everyone, so it is not a problem for everyone, so it is the simplest ~~

countdb.person.find()db.person.count()db.person.count({"age":40})

2. distinct <喎?http: www.bkjia.com kf ware vc " target="_blank" class="keylink"> VcD4KPHA + ucvD + fingerprint + hozwvcD4KPHA + PHByZSBjbGFzcz0 = "brush: SQL;"> db. person. distinct ("age ")

3. group

Group operations are a little complicated, but the more complicated the operation, the more flexible the application is. group operations are essentially equivalent to a "key-value" model.

In the following example, the group operation is performed according to age, and the value is the name of the corresponding age. The following describes these parameters:

Key: this is the group key. Here we are grouping ages.
Initial: each group shares an "initialization function". Note: Each group shares an initial function, for example, the list of values of age = 10, age = 40 also shares an initial function.
$ Reduce: the first parameter of this function is the current document object. The second parameter is the cumulative object of the last function operation. The first parameter is {"perosn": []} in initial. How many documents will be called by $ reduce.

groupdb.person.group({"key":{"age":true},"initial":{"person":[]},"$reduce":function(cur,prev){  prev.person.push(cur.name);}})

The above results may sometimes have other requirements, such:

1. filter out age <26 years old members.

2. Sometimes people have too many Members and I cannot view them one by one. So I want to count them. This looks more convenient.

This is very easy to do in group, because mongodb has two optional parameters: condition and finalize.

Condition is a filtering condition.

Finalize is a method that is triggered after each article is executed. You can add count to this method.

Condition and finalizedb. person. group ({"key": {"age": true}, "initial": {"person": []}, "$ reduce": function (cur, prev) {prev. person. push (cur. name) ;}, "finalize": function (count) {out. count = out. person. length ;}, "condition": {"age": {$ gte: 10 }}})

4. mapReduce

MapReduce is actually a programming model used in distributed computing. It has a "map" function and a "reduce" function.
1. map:
This is called a ing function, which calls emit (key, value). The set will be mapped to the group according to the specified key.
2. reduce:
This is called a simplification function, which simplifies grouping of data after map grouping. Note: The key in reduce (key, value) is
In emit, the key and vlaue are the set of emit (value) after the emit group. Here there are many {"count": 1} arrays.
3. mapReduce:
This is the final execution function. The parameters are map, reduce, and some optional parameters. The specific figure shows:

mapReducemapfunction(){emit(this.name,{count:1});}reducefunction(key,value){var result={count:0};for(var i=0;i<value.length;i++){result.count += value[i].count;}return result;}db.person.mapReduce(map,reduce,{"out":"collection"}){"result":"collection","timeMillis":15,"counts":{"input":7,"emit":7,"reduce":3,"output":4},"ok":1,}

Seo8L3A + CjxwPiBtb25nb2RiwO/release + MrHyerD99K7uPahsLLp0a + release/release + release "brush: SQL;"> cursor var list = db. person. find (); list. forEach (function (x) {print (x. name );})

At the same time, we can also query by PAGE and sort!

This reduces unnecessary overhead.

var single=db.person.find().sort({"name":1}).skip(2).limit(2);

Well, aggregation and cursors are basically the same. If there is something wrong, please correct it.

Original article, reproduced please indicate the source: http://blog.csdn.net/jessonlv

In the next phase, I will write operations such as mongodb index creation.