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Learning and Development notes of mongdb
2022-06-13 00:36:00 【A small snail in a big city】
1.《MongoDB course Novice tutorial 》
（1）https://www.runoob.com/mongodb/mongodb-tutorial.html
（2）https://www.mongodb.org.cn/drivers/
This is the foundation , stay mongoshell Next pair mongoDB Direct manipulation , For the following node.jsAPI Lay a foundation for operation
in addition mongoDB Different drivers are required in the application to operate mongoDB, link (2) You can select different language drivers in
C,C++,Perl,Jave,Node.js,C#,.NET,PHP
note: Personally, I think it is better than the official website
2.《Node.js course 》
（1）https://www.runoob.com/nodejs/nodejs-mongodb.html《 Novice tutorial 》
（2）http://nodejs.cn/learn《 Official website tutorial 》
note： I suggest you learn from the novice first , There are enough foundations , Detailed enough
Then watch the official website tutorial , To supplement
Node.js Installation in different environments is a difficult problem , Especially for embedded platforms , Good luck
3.《mongoose.js course 》
Then use it , First you have to install node.js and mongodb
Mongoose Is in node.js In asynchronous environment mongodb Object model tools for easy operation
（1）http://cw.hubwiz.com/card/c/543b2e7788dba02718b5a4bd/1/1/2/《 Huizhi online tutorial 》
（2）https://mongoosejs.com/docs/index.html《 Official website tutorial 》
note： These two tutorials have their own merits ,
Personally, I suggest （1）, There are enough foundations , Detailed enough
Then watch the official website tutorial , To supplement
4 mongodb $unwind Polymerization pipe
$unwind： Split an array type field in the document into multiple fields , Each contains a value in the array .
demand ：
{
"_id" : ObjectId("5951c5de567ebff0d5011fba"),
"name" : " Chen Xiaochan ",
"address" : " Chaoyang District of Beijing ",
"weekday" : [
1,
2,
3,
4,
5
]
}
Yes weekday To break up :
db.getCollection('chenxiaochantest').aggregate(
[
{
$unwind:"$weekday"
}
]
)
Break up the results : Use **$unwind Can be weekday** Each data in is decomposed into a document , And in addition to weekday The value of is different , The other values are the same .
/* 1 */
{
"_id" : ObjectId("5951c5de567ebff0d5011fba"),
"name" : " Chen Xiaochan ",
"address" : " Chaoyang District of Beijing ",
"weekday" : 1
}
/* 2 */
{
"_id" : ObjectId("5951c5de567ebff0d5011fba"),
"name" : " Chen Xiaochan ",
"address" : " Chaoyang District of Beijing ",
"weekday" : 2
}
/* 3 */
{
"_id" : ObjectId("5951c5de567ebff0d5011fba"),
"name" : " Chen Xiaochan ",
"address" : " Chaoyang District of Beijing ",
"weekday" : 3
}
/* 4 */
{
"_id" : ObjectId("5951c5de567ebff0d5011fba"),
"name" : " Chen Xiaochan ",
"address" : " Chaoyang District of Beijing ",
"weekday" : 4
}
/* 5 */
{
"_id" : ObjectId("5951c5de567ebff0d5011fba"),
"name" : " Chen Xiaochan ",
"address" : " Chaoyang District of Beijing ",
"weekday" : 5
}
5 MongoDB Aggregation operation $group Use
grammar
{
$group: {
_id: <expression>, <field1>: {
<accumulator1> : <expression1> }, ... } }
Parameter description ：
_id ： Mandatory must exist . It can be for null.
The remaining calculation fields are optional , And use the operator to calculate . Specific use , This is illustrated by the following code ：
First, prepare some data ：
// insert data
db.getCollection('sales').insertMany([
{
"_id" : 1, "item" : "abc", "price" : 10, "quantity" : 2, "date" : ISODate("2014-03-01T08:00:00Z") },
{
"_id" : 2, "item" : "jkl", "price" : 20, "quantity" : 1, "date" : ISODate("2014-03-01T09:00:00Z") },
{
"_id" : 3, "item" : "xyz", "price" : 5, "quantity" : 10, "date" : ISODate("2014-03-15T09:00:00Z") },
{
"_id" : 4, "item" : "xyz", "price" : 5, "quantity" : 20, "date" : ISODate("2014-04-04T11:21:39.736Z") },
{
"_id" : 5, "item" : "abc", "price" : 10, "quantity" : 10, "date" : ISODate("2014-04-04T21:23:13.331Z") }
]);
Example ： according to item Fields are grouped , Count each one item The number of documents below
db.sales.aggregate([
{
$group : {
_id : "$item",
count: {
$sum : 1}
}
}
]);
// Return results
{
"_id" : "xyz", "count" : 2 }
{
"_id" : "jkl", "count" : 1 }
{
"_id" : "abc", "count" : 2 }
Example ： according to item Fields are grouped , Count each one item below price Total of ,quantity The average of
db.sales.aggregate([
{
$group : {
_id : "$item",
totalPrice: {
$sum : "$price"},
avgQuantity: {
$avg: "$quantity" }
}
}
]);
// Return results
{
"_id" : "xyz", "totalPrice" : 10, "avgQuantity" : 15 }
{
"_id" : "jkl", "totalPrice" : 20, "avgQuantity" : 1 }
{
"_id" : "abc", "totalPrice" : 20, "avgQuantity" : 6 }
Example ： according to item Fields are grouped , Count each one item below quantity Maximum and minimum values of
db.sales.aggregate([
{
$group : {
_id : "$item",
maxQuantity: {
$max : "$quantity"},
minQuantity: {
$min: "$quantity" }
}
}
]);
// Return results
{
"_id" : "xyz", "maxQuantity" : 20, "minQuantity" : 10 }
{
"_id" : "jkl", "maxQuantity" : 1, "minQuantity" : 1 }
{
"_id" : "abc", "maxQuantity" : 10, "minQuantity" : 2 }
* Example ： Keep the first and the last
db.sales.aggregate([
{
$group : {
_id : "$item",
first: {
$first : "$quantity"},
}
}
]);
// Return results
{
"_id" : "xyz", "first" : 10 }
{
"_id" : "jkl", "first" : 1 }
{
"_id" : "abc", "first" : 2 }
db.sales.aggregate([
{
$group : {
_id : "$item",
last: {
$last : "$quantity"},
}
}
]);
// Return results
{
"_id" : "xyz", "last" : 20 }
{
"_id" : "jkl", "last" : 1 }
{
"_id" : "abc", "last" : 10 }
Example ： monthly , Group documents by day and year , And calculate the total price and average quantity , And calculate the number of documents in each group
db.sales.aggregate([
{
$group : {
// _id : { filed : value } This structure is custom , Used to define what groups are grouped by
// "$date" This field indicates the operation , $month、$dayOfMonth and $year It means from $date Get the corresponding date data
_id : {
month: {
$month: "$date" }, day: {
$dayOfMonth: "$date" }, year: {
$year: "$date" } },
// [ "$price", "$quantity" ] It refers to the operation of these two data ,$multiply Sum multiple fields
totalPrice: {
$sum: {
$multiply: [ "$price", "$quantity" ] } },
// "$quantity" Value is to manipulate this data ,$avg To find the average
averageQuantity: {
$avg: "$quantity" },
// There are several sets of statistics
count: {
$sum: 1 }
}
}
]);
// Return results ：
{
"_id" : {
"month" : 4, "day" : 4, "year" : 2014 }, "totalPrice" : 200, "averageQuantity" : 15, "count" : 2 }
{
"_id" : {
"month" : 3, "day" : 15, "year" : 2014 }, "totalPrice" : 50, "averageQuantity" : 10, "count" : 1 }
{
"_id" : {
"month" : 3, "day" : 1, "year" : 2014 }, "totalPrice" : 40, "averageQuantity" : 1.5, "count" : 2 }
5.1 Special operation mode
In addition to the above operation , Officials also introduced another method of operation
// The data are as follows
{
"_id" : 8751, "title" : "The Banquet", "author" : "Dante", "copies" : 2 }
{
"_id" : 8752, "title" : "Divine Comedy", "author" : "Dante", "copies" : 1 }
{
"_id" : 8645, "title" : "Eclogues", "author" : "Dante", "copies" : 2 }
{
"_id" : 7000, "title" : "The Odyssey", "author" : "Homer", "copies" : 10 }
{
"_id" : 7020, "title" : "Iliad", "author" : "Homer", "copies" : 10 }
Example 1 ： Use $push operation , Concatenate data into an array
// according to author grouping , Will be the same author Of title Spliced into an array
db.books.aggregate(
[
{
$group : {
_id : "$author", books: {
$push: "$title" } } }
]
);
// Return results
{
"_id" : "Homer", "books" : [ "The Odyssey", "Iliad" ] }
{
"_id" : "Dante", "books" : [ "The Banquet", "Divine Comedy", "Eclogues" ] }
There is a problem in the above operation , If there is duplicate data , Duplicate data will also be put into the returned results , In this case, use the following operation ：
// Use $addToSet operation
db.books.aggregate(
[
{
$group : {
_id : "$author", books: {
$addToSet: "$title" } } }
]
);
Example 2 ： Use $$ROOT （ System variables ） operation
The returned generated document must not exceed BSON Document size limit .
// Query operation
db.books.aggregate(
[
{
$group : {
_id : "$author", books: {
$push: "$$ROOT" } } }
]
)
// Return results
{
"_id" : "Homer",
"books" :
[
{
"_id" : 7000, "title" : "The Odyssey", "author" : "Homer", "copies" : 10 },
{
"_id" : 7020, "title" : "Iliad", "author" : "Homer", "copies" : 10 }
]
}
{
"_id" : "Dante",
"books" :
[
{
"_id" : 8751, "title" : "The Banquet", "author" : "Dante", "copies" : 2 },
{
"_id" : 8752, "title" : "Divine Comedy", "author" : "Dante", "copies" : 1 },
{
"_id" : 8645, "title" : "Eclogues", "author" : "Dante", "copies" : 2 }
]
}
6 mongodb Embedded array The operator $slice usage
Suppose an embedded array of documents arr The length is 10, The data Namely 1-10 ：
{
_id:1000,
arr : {
1,2,3,4,5,6,7,8,9,10
}
}
Now let's explain $slice usage ：
Normal usage and limit Paging query Not much difference Such as
db.col.find( {
_id:1000},
{
"arr":{
$slice : [0,5]
}
}
)
The result is 1,2,3,4,5
Let's see below. Values in reverse order
db.col.find( {
_id:1000},
{
"arr":{
$slice : [-1,5]
}
}
)
The result is 10
db.col.find( {
_id:1000},
{
"arr":{
$slice : [-5,5]
}
}
)
The result is 6 7 8 9 10
6 mongodb The query returns the specified array object in the array
MongoDB Provides : $elemMatch, $slice, and $. Operator to return the specified array data .
The following example passes $slice Operator returns the last data in the array .
db.inventory.find( { status: “A” }, { name: 1, status: 1, instock: { $slice: -1 } } )
$elemMatch, $slice, and $ These three operators are the only way to specify that the data in the returned array , You cannot specify an array index to return data from an array . for example { “instock.0”: 1 } The first element in the array is not returned .
7 Specify array position ：
Yes num：12 Conduct +2, How to operate ？
$ ： Will remember the location of the query results .
db.ArrayTest.updateOne({“address.street”: “JingKe”},{ KaTeX parse error: Expected '}', got 'EOF' at end of input: inc: {"address..num": 2}})
8 MongoDB Addition, deletion and modification of array elements
1、 Place holder $
Place holder $ Is mainly used to return the value of the first matched array element in the array ( A subset of ), The point is the first
When the element position in the specified array is not displayed at the time of update , Place holder $ Used to identify the position of elements
The document of the first matching element value found by the array filter condition will be updated
Examples of use
> db.students.insertMany([
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 90 ] },
{
"_id" : 2, "semester" : 1, "grades" : [ 90, 90, 92 ] },
{
"_id" : 3, "semester" : 1, "grades" : [ 85, 100, 90 ] },
{
"_id" : 4, "semester" : 2, "grades" : [ 79, 85, 80 ] },
{
"_id" : 5, "semester" : 2, "grades" : [ 88, 88, 92 ] },
{
"_id" : 6, "semester" : 2, "grades" : [ 95, 90, 96 ] }])
Use styles ：
db.collection.find( {
<array>: <value> ... },
{
"<array>.$": 1 } )
db.collection.find( {
<array.field>: <value> ...},
{
"<array>.$": 1 } )
Update element value style :
db.collection.update(
{
<array>: value ... },
{
<update operator>: {
"<array>.$" : value } }
)
Update the document style embedded in the array ( Use .$. Member mode )
db.collection.update(
{
<query selector> },
{
<update operator>: {
"array.$.field" : value } }
)
Placeholder for update operation $ Match the first element of the query document
The array field must be the filter condition of the query
Update array element values
// The following query semester The value is 1,grades by 90 Documents
// The results are as follows , All contain 90 All documents are returned
> db.students.find( {
semester: 1, grades: {
$eq: 90 } })// Equivalent ：db.students.find({semester:1,grades:90})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 90 ] }
{
"_id" : 2, "semester" : 1, "grades" : [ 90, 90, 92 ] }
{
"_id" : 3, "semester" : 1, "grades" : [ 85, 100, 90 ] }
// Here is a placeholder $ To filter the results of the array , That is, only the first one is 90 Will be displayed , The rest of the element values are not displayed
> db.students.find( {
semester: 1, grades: {
$eq: 90 } },{
"grades.$": 1 } )
{
"_id" : 1, "grades" : [ 90 ] }
{
"_id" : 2, "grades" : [ 90 ] } // Note that this is the first one in the document 90
{
"_id" : 3, "grades" : [ 90 ] }
// Now use placeholders to update
> db.students.update({
semester: 1, grades:90},{
$set:{
"grades.$":95}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 }) // Tips 1 Documents were updated
// Here's the document _id by 1 The array value of is updated to 95
> db.students.find( {
semester: 1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ] }
{
"_id" : 2, "semester" : 1, "grades" : [ 90, 90, 92 ] }
{
"_id" : 3, "semester" : 1, "grades" : [ 85, 100, 90 ] }
// Use multi:true Options , We can see as follows ,2 Matching documents were updated
// But only the first element value is updated ( file _id by 2 The value is 90 The second element of is not updated )
> db.students.update({
semester: 1, grades:90},{
$set:{
"grades.$":95}},{
multi:true})
WriteResult({
"nMatched" : 2, "nUpserted" : 0, "nModified" : 2 })
> db.students.find( {
semester: 1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ] }
{
"_id" : 2, "semester" : 1, "grades" : [ 95, 90, 92 ] }
{
"_id" : 3, "semester" : 1, "grades" : [ 85, 100, 95 ] }
Update the document embedded in the array
// Add a document to the collection
> db.students.insert(
... {
... _id:7,
... grades: [
... {
grade: 80, mean: 75, std: 8 },
... {
grade: 85, mean: 90, std: 5 },
... {
grade: 90, mean: 85, std: 3 }
... ]
... })
WriteResult({
"nInserted" : 1 })
// As shown below , Use array names .$. Member name
//
> db.students.update(
... {
_id: 7, "grades.grade": 85 },
... {
$set: {
"grades.$.std" : 6 } })
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.find({
"grades.grade":85},{
"grades.$": 1 })
{
"_id" : 7, "grades" : [ {
"grade" : 85, "mean" : 90, "std" : 6 } ] }
Update the document embedded in the array ( Multiple condition matching )
// For multi condition matching , Use $elemMatch
> db.students.update({
"_id":7,grades:{
$elemMatch:{
grade:{
$lte:90},mean:{
$gt:80}}}},
... {
$set: {
"grades.$.std" : 6 } })
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 }) // A prompt is updated
// The verification results , Although there are 2 Embedded documents meet the query conditions , But only the first one was updated
> db.students.find({
"grades.std":6}).pretty()
{
"_id" : 7, // Author: Leshami
"grades" : [ // Blog : http://blog.csdn.net/leshami
{
"grade" : 80,
"mean" : 75,
"std" : 8
},
{
"grade" : 85,
"mean" : 90,
"std" : 6
},
{
"grade" : 90,
"mean" : 85,
"std" : 3
}
]
}
2、 The operator $addToSet
When the array element value does not exist , Add the value to the array . otherwise , Do nothing .
style ：
{
$addToSet: {
<field1>: <value1>, ... } }
$addToSet Make sure no duplicate items are added to the array collection , The existing repeating elements are not affected .
$addToSet There is no guarantee of the order of the elements when they are added
If <field1> It's empty , operation failed , If the added value is an array , Then the entire value will be appended as a single element
> db.students.update({
"_id":6},{
$addToSet:{
grades:99}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.find({
"_id":6})
{
"_id" : 6, "semester" : 2, "grades" : [ 95, 90, 96, 99 ] }
// Try adding again 99, The following prompts are matched , But no updates
> db.students.update({
"_id":6},{
$addToSet:{
grades:99}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 0 })
// The following will grades:[100,101] Add as a whole element to the array
> db.students.update({
"_id":6},{
$addToSet:{
grades:[100,101]}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
// verification ,100,101 As a whole , Not a single element
> db.students.find({
"_id":6})
{
"_id" : 6, "semester" : 2, "grades" : [ 95, 90, 96, 99, [ 100, 101 ] ] }
// combination $each Operator usage $addToSet
//$addToSet combination $each, allow $addToSet Add multiple values to the array at once
// as follows , We need to [96,99,100,101] These values are added to the array
>db.students.update({
"_id":6},{
$addToSet:{
grades:{
$each:[96,99,100,101]}}})
// Such as the following query results ,96,99 The element value already exists before , Therefore not added , and 100,101 Is added
> db.students.update({
"_id":6},{
$addToSet:{
grades:{
$each:[96,99,100,101]}}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.find({
"_id":6})
{
"_id" : 6, "semester" : 2, "grades" : [ 95, 90, 96, 99, [ 100, 101 ], 100, 101 ] }
3、 The operator $push
$push Add a specified value to the array , If it is a nested document , Use . Member mode
style ：
{
$push: {
<field1>: <value1>, ... } }
Behavior ：
If the updated document does not exist in the array , that $push Array fields and values will be added
If the field is not an array , operation failed
If the value is an array , Then the entire array is added to the array as a single element
$push Modification order of ( Refer to the comprehensive example later in this dot )
Update the added element to the array
If sorting is specified , Then apply sorting
If you specify slice, So cut the array
Storage array
Example ：
// When the field does not exist
> db.students.update({
"_id":1},{
$push:{
score:80}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
// View the added results ,score Add as an array field to the document
> db.students.find({
"_id":1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ], "score" : [ 80 ] }
// Again score The fields go $push
> db.students.update({
"_id":1},{
$push:{
score:90}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
// View the added results , because score Array field exists , So append an array element to it 90
> db.students.find({
"_id":1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ], "score" : [ 80, 90 ] }
> //$push combination $each, Once to the array push Multiple element values , The same element value is not ignored
> // Here is $push And $addToSet The biggest difference , A filter weight , An unfiltered weight
> db.students.update({
"_id":1},{
$push:{
score:{
$each:[80,100,120]}}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.find({
"_id":1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ], "score" : [ 80, 90, 80, 100, 120 ] }
//$push combination $each,$slice,$sort Comprehensive example of
// First add the document to the collection
> db.students.insert({
"_id" : 8,
"quizzes" : [
{
"wk": 1, "score" : 10 },
{
"wk": 2, "score" : 8 },
{
"wk": 3, "score" : 5 },
{
"wk": 4, "score" : 6 }
]
})
// Use the following update operation
> db.students.update(
{
_id: 8 },
{
$push: {
quizzes: {
// Use $each Add to array 3 Elements
$each: [ {
wk: 5, score: 8 }, {
wk: 6, score: 7 }, {
wk: 7, score: 6 } ],
$sort: {
score: -1 }, // be based on socre Flashback to arrange
$slice: 3 // Keep only 3 Elements
}
}
}
)
// The updated results are as follows ,score,10,8,8 Reserved , The rest are deleted
> db.students.find({
"_id":8}).pretty()
{
"_id" : 8,
"quizzes" : [
{
"wk" : 1,
"score" : 10
},
{
"wk" : 2,
"score" : 8
},
{
"wk" : 5,
"score" : 8
}
]
}
4、 The operator $pop
$pop Operator removes the first or last element in the array (1 For the last element ,-1 For the first element )
If the array is a nested document , Use . Member mode
style :
{
$pop: {
<field>: <-1 | 1>, ... } }
// see "_id" The value is 1 Documents
> db.students.find({
"_id":1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ], "score" : [ 80, 90, 80, 100, 120, 80, 100, 120 ] }
// remove score The last element
> db.students.update({
"_id":1},{
$pop:{
score:1}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.find({
"_id":1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ], "score" : [ 80, 90, 80, 100, 120, 80, 100 ] }
// remove score First element
> db.students.update({
"_id":1},{
$pop:{
score:-1}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.find({
"_id":1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ], "score" : [ 90, 80, 100, 120, 80, 100 ] }
// Remove the last element of the nested array
> db.students.update({
"_id":8},{
$pop:{
quizzes:1}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.find({
"_id":8})
{
"_id" : 8, "quizzes" : [ {
"wk" : 1, "score" : 10 }, {
"wk" : 2, "score" : 8 } ] }
5、 The operator $pull
$pull Operator removes all instances of values or values that match the specified criteria from the existing array
style ：
{
$pull: {
<field1>: <value|condition>, <field2>: <value|condition>, ... } }
explain ：
If specified <condition> When the array element is an embedded document ,$pull Operator application <condition>, Just like every array element is a document in a collection
If specified <value> To remove the array ,$pull Only remove the array elements that meet the specified conditions ( Exactly match , Including the order )
If specified <value> To remove a document ,$pull Only remove elements of the array that exactly match fields and values ( The order can be different )
Example ：
Remove all specific element values
> db.students.find({
"_id":6})
{
"_id" : 6, "semester" : 2, "grades" : [ 95, 90, 96, 99, [ 100, 101 ], 100, 101 ] }
// Remove single array element values
> db.students.update({
"_id":6},{
$pull:{
grades:99}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
// Remove nested array element values
> db.students.update({
"_id":6},{
$pull:{
grades:[100,101]}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
// The verification results
> db.students.find({
"_id":6})
{
"_id" : 6, "semester" : 2, "grades" : [ 95, 90, 96, 100, 101 ] }
// Use $in To remove all matching elements
> db.students.update({
"_id":6},{
$pull:{
grades:{
$in:[95,96]}}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
// The verification results
> db.students.find({
"_id":6})
{
"_id" : 6, "semester" : 2, "grades" : [ 90, 100, 101 ] }
Remove all numeric elements that match a specific condition
// Remove array grades Medium greater than or equal to 100 The elements of
> db.students.update({
"_id":6},{
$pull:{
grades:{
$gte:100}}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
// The following query 100,101 The element value no longer exists
> db.students.find({
"_id":6})
{
"_id" : 6, "semester" : 2, "grades" : [ 90 ] }
Remove document type array items
> db.survey.insert([
{
_id: 1,
results: [
{
item: "A", score: 5 },
{
item: "B", score: 8, comment: "Strongly agree" }
]
},
{
_id: 2,
results: [
{
item: "C", score: 8, comment: "Strongly agree" },
{
item: "B", score: 4 }
]
}])
// Below update operation , remove results Nested documents in an array score The value of is 8,item The value is B The numeric element of
> db.survey.update(
{
},
{
$pull: {
results: {
score: 8 , item: "B" } } },
{
multi: true }
)
WriteResult({
"nMatched" : 2, "nUpserted" : 0, "nModified" : 1 }) //2 A match ,1 Updates
> db.survey.find().pretty()
{
"_id" : 1, "results" : [ {
"item" : "A", "score" : 5 } ] }
{
"_id" : 2,
"results" : [
{
"item" : "C",
"score" : 8,
"comment" : "Strongly agree"
},
{
"item" : "B",
"score" : 4
}
]
}
6、 The operator $pullAll
This operator removes all instances of the specified value from an existing array ( That is, delete multiple values at once ).
$pull The operator is to remove an element of a specified query ,$pullAll Remove matching list all elements worth
style ：
{
$pullAll: {
<field1>: [ <value1>, <value2> ... ], ... } }
explain ：
When the specified <field> Is an embedded document or array , Use . Member mode
If <value> Is a document or array ,$pullAll Only exactly remove matching assignments <value> Elements of array ( Sequence requires matching )
Example
> db.students.find({
"_id":{
$in:[1,5]}})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ], "score" : [ 90, 80, 100, 120, 80, 100 ] }
> db.students.find({
"_id":1})
{
"_id" : 1, "semester" : 1, "grades" : [ 70, 87, 95 ], "score" : [ 90, 80, 80 ] }
> db.students.find({
"_id":5}).pretty()
{
"_id" : 5,
"semester" : 2,
"grades" : [
88,
88,
92
],
"quizzes" : [
{
"wk" : 5,
"score" : 8
},
{
"wk" : 6,
"score" : 7
},
{
"wk" : 7,
"score" : 6
}
]
}
> db.students.update({
"_id":5},{
$pullAll:{
"quizzes":[{
"wk" : 5,"score" : 8}]}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.update({
"_id":5},{
$pullAll:{
"quizzes":[{
"wk" : 7,"score" : 6}]}})
WriteResult({
"nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.students.find({
"_id":5}).pretty()
{
"_id" : 5,
"semester" : 2,
"grades" : [
88,
88,
92
],
"quizzes" : [
{
"wk" : 6,
"score" : 7
}
]
}
9 MongoDB——》 Aggregate query （project、match、limit、skip、unwind、group、sort）
db： Current database name
test： Current collection name
test The data in the set is shown in the following figure ：
1 polymerization
1、 polymerization
2、 Aggregate operator 
Two 、 Aggregate operator
1、$project
Modify the structure of the input document rename 、 Add or remove fields Create calculation results and nested documents
1) example ： obtain test A collection of weight Fields and name Field （_id Show ）
db.test.aggregate(
{
$project : {
weight: 1 ,
name : 1
}}
);
2) example ： obtain test A collection of weight Fields and name Field （_id No display ）
db.test.aggregate(
{
$project : {
_id : 0 ,
weight: 1 ,
name : 1
}}
);
3) example ： Use ＄add to weight Add... To the value of the field 10, Then assign the result to a new field :newWeight
db.test.aggregate(
{
$project : {
_id : 0 ,
name : 1 ,
weight : 1 ,
newWeight : {
$add:["$weight", 10] }
}}
);
4) example ： hold weight Rename it to newWeight
db.test.aggregate(
{
$project : {
_id : 0 ,
name : 1 ,
weight : 1 ,
newWeight : "$weight"
}}
);
2、$match
For filtering data , Output only documents that meet the criteria stay ＄match Cannot be used in ＄geoNear Geospatial operators and ＄where Expression operators
1) example ： obtain test A collection of weight>=0.5 And weight<=1
db.test.aggregate( {
$match :
{
weight :
{
$gte : 0.5, $lte : 1 }
}
});
perhaps
db.test.aggregate([
{
$match :
{
weight :
{
$gte : 0.5, $lte : 1 }
}
}
]);
2) example ： obtain test A collection of weight>=0.5 And weight<=1, Then send the eligible records to the next stage $group The pipeline operator handles
db.test.aggregate([
{
$match :
{
weight :
{
$gte : 0.5, $lte : 1 }
}
},
{
$group:
{
_id: null,
count: {
$sum: 1 }
}
}
]);
3、$group
Group documents in a collection , Can be used for statistical results stay ＄match Cannot be used in ＄geoNear Geospatial operators and ＄where Expression operators
1) example ： obtain test A collection of weight>=0.5 And weight<=1, Then send the eligible records to the next stage $group The pipeline operator handles 
4、$limit
＄limit Will accept a number n, Returns the first... In the result set n A document
1) example ： Inquire about 5 Document records
db.test.aggregate({
$limit : 5 });
5、$skip
＄skip Accept a number n, Before discarding the result set n A document Limit the number of documents that can be passed to the next pipeline of the aggregation operation
1) example ： obtain test In the set 5 Data after a piece of data 
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