Aggregation of MongoDB Tutorials (count, distinct, and group) _mongodb

1. Count:

code as follows:

--In an empty collection, Count returns a number of 0.
> Db.test.count ()
0
--Test the return value of count after inserting a document.
> Db.test.insert ({"Test": 1})
> Db.test.count ()
1
> Db.test.insert ({"Test": 2})
> Db.test.count ()
2
--count, like find, also accepts conditions. As you can see from the results, only eligible documents are involved in the calculation.
> Db.test.count ({"Test": 1})
1

2. Distinct:

Distinct is used to find all the different values for a given key. You must also specify collections and keys when you use them.

code as follows:

--to facilitate subsequent testing, empty the test collection.
> Db.test.remove ()
> Db.test.count ()
0
--Insert 4 test data. Please note the age field.
> Db.test.insert ({"Name": "Ada", "Age": 20})
> Db.test.insert ({"Name": "Fred", "Age": 35})
> Db.test.insert ({"Name": "Andy", "Age": 35})
> Db.test.insert ({"Name": "Susan", "Age": 60})
The--distinct command must specify the collection name, such as test, and the fields you want to differentiate, such as age.
-The following command executes the distinct command based on the age field in the Test collection.
> Db.runcommand ({"distinct": "Test", "Key": "Age"})
{
"Values": [
20,
35,
60
],
"Stats": {
"N": 4,
"Nscanned": 4,
"Nscannedobjects": 4,
"Timems": 0,
"Cursor": "Basiccursor"
},
"OK": 1
}

3. Group:
The aggregation made by group is somewhat complex. Select the key on which the group is based, and then mongodb the collection according to the selected key values to several groups. You can then produce a result document by aggregating the documents within each group.

code as follows:

--Here is the test data that is prepared
> Db.test.remove ()
> Db.test.insert ({"Day": "2012-08-20", "Time": "2012-08-20 03:20:40", "Price": 4.23})
> Db.test.insert ({"Day": "2012-08-21", "Time": "2012-08-21 11:28:00", "Price": 4.27})
> Db.test.insert ({"Day": "2012-08-20", "Time": "2012-08-20 05:00:00", "Price": 4.10})
> Db.test.insert ({"Day": "2012-08-22", "Time": "2012-08-22 05:26:00", "Price": 4.30})
> Db.test.insert ({"Day": "2012-08-21", "Time": "2012-08-21 08:34:00", "Price": 4.01})
--This will use day as the grouping key for group, and then remove the document with the time key value as the latest timestamp, and also remove the price key value for the document.
> Db.test.group ({
... "Key": {"Day": true},--if it is more than one field, can be {"F1": True, "F2": true}
... ' initial ': {' time ': ' 0 '},--initial represents the initial value of the $reduce function parameter prev. Each group has a copy of the initial value.
... "$reduce": function (Doc,prev) {--reduce functions accept two parameters, doc represents the current document being iterated, Prev represents an accumulator document.
... if (Doc.time > Prev.time) {
... prev.day = Doc.day
... prev.price = Doc.price;
... prev.time = doc.time;
...     }
... } } )
[
{
"Day": "2012-08-20",
"Time": "2012-08-20 05:00:00",
"Price": 4.1
},
{
"Day": "2012-08-21",
"Time": "2012-08-21 11:28:00",
"Price": 4.27
},
{
"Day": "2012-08-22",
"Time": "2012-08-22 05:26:00",
"Price": 4.3
}
]
--The following example is to count the number of documents within each packet.
> Db.test.group ({
... key: {day:true},
... initial: {count:0},
... reduce:function (obj,prev) {prev.count++;},
... } )
[
{
"Day": "2012-08-20",
"Count": 2
},
{
"Day": "2012-08-21",
"Count": 2
},
{
"Day": "2012-08-22",
"Count": 1
}
]
--The last one is an example of how reduce results are modified through the completion device.
> Db.test.group ({
... key: {day:true},
... initial: {count:0},
... reduce:function (obj,prev) {prev.count++;},
. Finalize:function (out) {out.scaledcount = Out.count * 10}-Adds a key to the resulting document.
... } )
[
{
"Day": "2012-08-20",
"Count": 2,
"Scaledcount": 20
},
{
"Day": "2012-08-21",
"Count": 2,
"Scaledcount": 20
},
{
"Day": "2012-08-22",
"Count": 1,
"Scaledcount": 10
}
]