MongoDB query, index, and aggregation

Organize from

Https://www.shiyanlou.com/courses/running/77

Initializing the MongoDB database

>Use chenshiswitched to DB chenshi> db.createcollection ("Shiyanlou")#无参数 {"OK":1}> Show CollectionsshiyanlouSystem.indexes> userdoc1= ({"USER_ID":1,"Name":"Cloud","State":"Active","Actor":"User","E-mail":The test@qq. com ","Vm_num":2,"Time": [{"Date":"2014-08-12","Hour":"10:53 PM"}]}) > userdoc2= ({"USER_ID":2,"Name":"Testadmin","State":"Active","Actor":"Admin", "e-mail":  "Test @qq. com",  "Vm_num": 2, "time": [{ "Date":  "2014-08-11",  "hour": " name ": " Peter ",  "position":  "Teacher"}) > Db.shiyanlou.insert (USERDOC1) Writeresult ({ "ninserted": 1}) > Db.shiyanlou.insert ( USERDOC2) Writeresult ({ "ninserted": 1}) > Db.shiyanlou.insert (Doc1) writeresult ({ "ninserted": 1}) 
 
                 /span>   

Query statements

Db. Collection_name.find (Parameter) Example:

> db.shiyanlou.find()

Document information, this directive is equivalent to the SELECT * FROM table_name in SQLite

Conditional operator 1

The conditional operators in MongoDB are:

• (>) greater than-\ $GT #greate
• (<) less than-\ $lt #low
• (>=) greater than or equal to-\ $gte #equal
• (<=) less than or equal to-\ $lte

Example:

db.shiyanlou.find({user_id:{$gt:1}})> db.shiyanlou.find({user_id:{$lte:2,$gt:1}})

Conditional operator 2

Grammar:

$type

The value of type:

• Double Type-1
• String-2
• Objects-3
• Array-4
• Binary Data-5
• Object ID-7
• Boolean Type-8
• Data-9
• Null-10
• Regular Expressions-11
• JS Code-13
• Symbol-14
• Scoped JS Code-15
• 32-bit integer number-16
• Timestamp-17
• 64-bit integer number-18
• Min key-255
• Max key-127

Example:

> db.shiyanlou.find({"name":{$type:2}})

Find name is a string of document records

Limit and Skip

Reads a specified number of data records-limit

Example:

> db.shiyanlou.find().limit(1)

Reads a record, the default is the first line is read

Skips a specified number of data records while reading-skip

Example:

> db.shiyanlou.find().limit(1).skip(1)

Of course, you can also add parameters for find criteria to find more accurate

MongoDB sort-sort ()

As with the sort in sqlite there are ascending and descending, where ascending is indicated by 1, and descending with-1 means syntax:

db.COLLECTION_NAME.find().sort({KEY:1|-1})

Example:

> db.shiyanlou.find().sort({"time":1})

Index-Ensureindex ()

Indexes can often greatly improve the efficiency of queries, and if there is no index, MongoDB must scan every file in the collection and select those records that meet the query criteria when reading the data. This scan full set of query efficiency is very low, especially in the processing of large amounts of data, the query can take dozens of seconds or even a few minutes, no doubt the performance of the site is very deadly.

Indexes are special data structures that are stored in an easy-to-traverse collection of data that is a structure that sorts the values of a document or multiple documents in a database collection.

Grammar:

db.COLLECTION_NAME.ensureIndex({KEY:1|-1})

The same 1 stands for ascending, 1 for descending

Example:

> db.shiyanlou.ensureIndex({"name":1})

Optional parameters for Ensureindex ():

if not specified

parameter	type	description
background	Boolean	Build index to not block other database operations, default to False
unique	Boolean	If the index is unique, the default is
name	string	index, and the system automatically generates
dropdups	Boolean	whether duplicate records are deleted when a unique index is established, default Flase
sparse	Boolean	does not enable indexing for field data that does not exist for a document, default false
expireafterseconds	integer	Set the lifetime of the collection in seconds
v	Index version	revision number
weights	Document	index weight value, ranging from 1 to 99999
default-language	string	default to English
language_override	string	default value is language

Example:

> db.shiyanlou.ensureIndex({"user_id":1,"name":1},{background:1})

Iv. polymerization-aggregate ()

Grammar:

db.COLLECTION_NAME.aggregate({$match:{x:1},{limit:NUM},$group:{_id:$age}})

These parameters are optional

• $match: Query, same as find;
• $limit: Limit the number of results displayed;
• $skip: Ignore the number of results;
• $sort: Sort;
• $group: Combines the results by a given expression.

Example:

> db.shiyanlou.aggregate([{$group:{_id:"$name", user:{$sum:"$user_id"}}}])

$name means to get the value of name

Aggregation expressions

name	Description
$sum	Calculate sum
$avg	Calculate average
\ $min and $max	Calculate minimum and maximum values
$push	Inserting values into an array in the resulting document
$addToSet	Inserts a value into an array in the resulting document, but does not create a copy
$first	Get the first document data based on the ordering of the resource documents
$last	Get the last document data based on the ordering of the resource documents

Pipeline

MongoDB's aggregation pipeline passes the MongoDB document to the next pipeline processing after a pipeline has finished processing. Pipeline operations can be repeated.

Expression: Processes the input document and outputs it. The expression is stateless and can only be used to calculate the document for the current aggregated pipeline and cannot process other documents. Several common operations in the aggregation framework:

• $project: Modifies the structure of the input document. You can use it to rename, add, or delete fields, or to create calculations and nested documents.
• \ $match: Used to filter data and only output documents that match the criteria. $match a standard query operation using MONGODB.
• $limit: Used to limit the number of documents returned by the MongoDB aggregation pipeline.
• $skip: Skips the specified number of documents in the aggregation pipeline and returns the remaining documents.
• $unwind: Splits one of the array type fields in the document into multiple bars, each containing a value in the array.
• $group: Groups The documents in the collection to be used for statistical results.
• $sort: Sorts the input documents after the output.
• $geoNear: Outputs an ordered document that is close to a geographic location.

Example:

 > db.shiyanlou.aggregate ([{ $match: {User_id:{ $gt: 0, $lte: 2}}},{ $group: {_id: "user", Count : { $sum: 1}}]) { "_id":  "user",  "Count": 2}    

                

      

MongoDB query, index, and aggregation