Introduction to MongoDB (3)--? The index of MongoDB

"MongoDB Entry" Reading notes download:
Index view index of http://download.csdn.net/detail/ch717828/9833847 MongoDB
Db.test_table.getIndexes () create INDEX (1 for ascending, 1 for descending)
Db.test_table.ensureIndex ({x:1})

Types of indexes

_ID Index

_id indexes are indexes that are established by default for most collections, and a unique _id field is automatically generated for each inserted data MongoDB

Single-Touch indexing

One-touch is the most common index

Db.test_table.ensureIndex ({x:1})

Multi-Key indexing

The value of a multi-key index has multiple records, such as an array, based on a single-button index

Db.test_table.insert ({x:[1,2,3,4,5]})

For this insert record, MongoDB creates a multi-key index for X

Composite Index

Use multiple keys as indexes

Db.test_table.ensureIndex ({x:1,y:1})

Expired Index

An index that expires after a certain period of time and the corresponding data is deleted after the index expires. This is ideal for storing data that will expire after a certain period of time, such as user login information, stored logs

Db.test_table.ensureIndex ({y:1},{expireafterseconds:30})
Db.test_table.insert ({y:new Date ()})
Db.test_ Table.insert ({y:1})

After observing a period of time, you will find that the value of Y is automatically deleted, and the value of Y is 1 is not deleted. So
The value stored in the Expired index field must be the specified time type (isodate or isodate array, cannot use timestamp). If a isodate array is established, it is deleted by the minimum time in the array. In addition, an expired index cannot be a composite index. Deletion time is not accurate (the removal process is timed by the daemon, and the deletion process takes time, so there is an error)

Full-Text Indexing

Create full-text indexes (only one full-text index is allowed per data collection)

Db.test_table.ensureIndex ({key: "text"}) 
Db.test_table.ensureIndex ({key_1: "text", Key_2: "Text"}) 
Db.test _table.ensureindex ({"$**": "Text"})  #$** represents the creation of a full-text index on all string fields.

Using Full-Text indexing

Db.test_table.insert ({"article": "ABCD abcd ABCD"}) 
Db.test_table.insert ({"article": "One by One"}) 
Db.test_ Table.ensureindex ({"article": "Text"})
Db.test_table.find ({$test: {$search: "ABCD"}})
Db.test_table.find ( {$test: {$search: "ABCD One"}}) 
Db.test_table.find ({$test: {search: "abcd-11"}}) # contains ABCD but does not contain one
Db.test_table.find ({$test: {$serach: "\" abcd\ "\" 11\ ""}) # includes ABCD and contains one
db.test_table.find ({$test: {$search: "ABCD 1234"}},{score:{$meta: "Textscore"}}) # Full-text index similarity

Location Index

Planar geo-Location index

Db.test_location.ensureIndex ({"W": "2d"}) # Creates a 2D planar geo-location index
db.test_location.insert ({w:[100,150]})   #插入记录
Db.test_location.find ({w:{$near: [First]}})  #查找距离 The nearest point (default 100)
Db.test_location.find ({w:{$ near:[1,1], $maxDistance: ten})  #查找距离 [10]
db.test_location.find ({w:{$geoWithin: {$box: [0,0],[ 3,3]]}}) #查找矩形 the point db.test_location.find in [[0,0],[3,3]]
({w:{$geoWithin: {$center: [[0,0],5]}}})  #查找圆心 [0,0] The point db.test_location.find within a circle with a radius of 5
({w:{$geoWithin: {$polygon: [[[0,0],[0,1],[2,2],[3,3]}}})  #查找多边形 [[0,0],[ 0,1],[2,2],[3,3]]
, point Db.runcommand ({geonear: "Test_location", near:[1,2], $maxDistance: 10,num:2}) #查找test_ In location, the maximum distance from [Max] is less than 10 of 2 records

Spherical geo-Location index

The name of the index
Db.test_table.ensureIndex ({x:1,y:1,z:1},{name: "normal}")

Uniqueness of the Index

Db.test_table.ensureIndex ({m:1,n:1},{unique:true})
Db.test_table.insert ({m:1,n:2})  #插入成功
Db.test_table.insert ({m:1,n:2})  #插入失败, Key violation

The sparsity of the index (a sparsity of TRUE indicates that no index is created for fields that do not exist)
Db.test_table.ensureIndex ({x:1},{sparse:true})

You cannot find records that do not exist on a sparse index, for example:

"'
Db.test_table.insert ({m:1})
Db.test_table.insert ({N:1})
Db.test_table.find ({m:{exists:true}}) #查找m存在的记录
Db.test_table.ensureIndex ({m:1},{sparse:true}) #创建稀疏索引
Db.test_table.find ({m:{exists:true}}) #查找m存在的记录 Db.test_table.ensureIndex ({m:1},{sparse:true}) #创建稀疏索引 Db.test_ Table.find ({M:{exists:false}}) #查找m不存在的记录, still finds M, which is a sparse index problem
Db.test_table.find ({m:{$exists: false}}). Hind ("m_1") #可以实现查找m不存在的记录

"' index build condition Analysis

Mongostat: Viewing the MongoDB running status program

./bin/mongostat--hlep   #查看mongostat帮助
./bin/mongostat-h 127.0.0.1:12345  #查看当前系统的运行情况 (see how many writes per second)

Explain: Displays the details of the query once

Db.test_table.find ({x:1}). Explain ();

MongoDB Security

Turn on MongoDB authentication
Vim conf/mongod.conf

Port = 12345
dbpath = data
LogPath = log/mongod.log
fork = true
Author = True
 "
Create a user using CreateUser

Db.createuser ({User: "TestUser", pwd: "TestUser", Roles:[{role: "Useradmin", DB: "admin"},{role: "read", DB: "Test"}]}) # Create TestUser user, have useradmin permission to admin, read permission to test
"' the role of multi-key indexing

Multi-key index and one-touch index in the use of a very different way, on the basis of a single-button index, if the inserted value is an array, MongoDB creates a multi-key index for it. When you query, you can find the record by using any of the values in the multi-key array.