"Interview and abuse of vegetables"--MONGODB knowledge finishing

Why should we use MongoDB?

Characteristics:

• High performance, easy to deploy, easy to use, easy to store data. The main features are:
• For collection storage, easy to store data for object types.
• Mode of freedom.
• Supports dynamic queries.
• Supports full indexes, including internal objects.
• Support Queries.
• Supports replication and recovery.
• Use efficient binary data storage, including large objects such as video.
• Automatically process fragmentation to support scalability at the cloud level
• Drivers for Python,php,ruby,java,c,c#,javascript,perl and C + + languages are supported, and drivers for Erlang and. NET platforms are also available in the community.
• The file storage format is Bson (an extension of JSON).
• can be accessed over the network.

Function:

• Collection-oriented storage: suitable for storing objects and data in JSON form.
• Dynamic Query: The MONGO supports rich query expressions. Query directives use a JSON-style tag to easily query objects and arrays embedded in the document.
• Full index support: includes embedded objects and arrays in the document. The query optimizer of MONGO parses the query expression and generates an efficient query plan.
• Query monitoring: MONGO contains a monitoring tool for analyzing the performance of database operations.
• replication and automatic failover: The MONGO database supports data replication between servers and supports replication between master-slave mode and server. The primary goal of replication is to provide redundancy and automatic failover.
• Efficient Traditional storage: supports binary data and large objects (such as photos or pictures)
• Auto-sharding to support cloud-scale scalability: automatic sharding supports a level of database clustering, adding additional machines dynamically.

Applicable occasions:

• Website data: MONGO is ideal for real-time inserts, updates and queries, as well as the replication and high scalability required for real-time data storage on the site.
• Caching: Because of its high performance, MONGO is also suitable as a caching layer for the information infrastructure. After the system restarts, the persistent cache layer built by MONGO can avoid overloading the underlying data sources.
• Large, low-value data: Storing some data in a traditional relational database can be expensive, and many times programmers often choose traditional files for storage.
• Highly scalable scenario: The MONGO is ideal for databases made up of dozens of or hundreds of servers. Built-in support for the MapReduce engine is already included in the roadmap for MONGO.
• Storage for objects and JSON data: The MONGO Bson data format is ideal for storing and querying in a document format.

MongoDB to pay attention to the problem

1 because MongoDB is fully indexed, it directly puts the index in memory, so it supports up to 2.5G of data. If the 64-bit will be more.

2 because there is no recovery mechanism, so do a good job of data backup

3 because the default listener address is 127.0.0.1, it is not safe to authenticate, or it is recommended to configure it as localhost hostname

4 ensure change through GetLastError. ( this does not understand, actually did not use )

MongoDB Structure Introduction

The objects stored in MongoDB are Bson, a JSON-like binary file that consists of a number of key-value pairs. As shown below

{  "name": "Huangz",  "age": +, "  sex": "Male"  }  {    "name": "Jack",  "Class": 3,   "Grade ": 3  

The overall structure of the database is composed of the following:

Key-value pairs--"document--" collection--"database

MongoDB file size not more than 4M, but the new version can be increased to 16M

The key naming rules in MongoDB are as follows:

• "\" cannot be used
• With "." Number, "_" and "$" prefix are reserved
• There are differences in case, age is different from age
• The same document cannot have the same key
• All other UTF-8 characters can be used except for the above rules

Common commands

1 #进入数据库

Use admin

2 #增加或修改密码

Db.adduser (' Xingoo ', ' 123 ')

db.adduser ("Xingoo", "123", true) parameters are user name, password, read-only

3 #查看用户列表

Db.system.users.find ()

4 #用户认证

Db.auth (' Xingoo ', ' 123 ')

5 #删除用户

Db.removeuser (' Xingoo ')

6 #查看所有用户

Show Users

7 #查看所有数据库

Show DBS

8 #查看所有的collection集合

Show collections

9 #查看各个collection的状态

Db.printcollectionstats ()

Ten #查看主从复制状态

Db.printreplicationinfo ()

#修复数据库

Db.repairdatabase ()

#设置profiling, 0:off 1:slow 2 All

Db.setprofilinglevel (1)

#查看profiling

Show profiling

#拷贝数据库

Db.copydatabase (' xingootest ', ' xingootest1 ')

Db.copydatabase ("Xingootest", "temp", "127.0.0.1")

#删除集合collection

Db.xingootest.drop ()

#删除当前数据库

Db.dropdatabase ()

MongoDB additions and Deletions change command

1 #存储嵌套的对象

Db.foo.save ({' name ': Xingoo, ' age ': +, ' address ': {' city ': ' Changchun ', ' Province ': ' Jilin '}})

2 #存储数组对象

Db.foo.save ({' name ': Xingoo, ' age ': +, ' address ': [' Jilin Province ', ' Liaoning Province ']})

3 #根据query条件修改, insert if not present, allow multiple records to be modified

Db.foo.update ({' Age ': '},{' $set ': {' name ': ' Xingoo '}},upsert=true,multi=true)

4 #删除yy Records of =5

Db.foo.remove ({' name ': ' Xingoo '})

5 #删除所有的记录

Db.foo.remove ()

Index

1 #增加索引: 1 asc-1 desc

Db.foo.ensureIndex ({firstname:1,lastname:-1},{unieap:true})

2 #索引子对象 (not understood)

Db.foo.ensureIndex ({' Al.em ':!})

3 #查看索引信息

Db.foo.getIndexes ()

Db.foo.getIndexKeys ()

4 #根据索引名删除索引 (not understood)

Db.foo.dropIndex (' al.em_1 ')

Inquire

Conditional operator

1 $GT---->2$LT----<3 $gte---- >=4$lte----<=5 $ne---- !=, <>6 $in---- in7 $nin---- not in8 $all---- All9 $or----orTen $not----Anti-match

1 #查询所有记录

Db.foo.find ()----SELECT * from foo

2 #查询某列非重复的记录

Db.foo.distinct ("Xingoo")----SELECT distinct name from foo

3 #查询age = 22 of records

Db.foo.find ({"Age": $})----SELECT * from foo where age = 22

Records for 4 #查询age > 22

Db.foo.find ({age:{$gt:)----SELECT * from foo where age > 22

Records for 5 #查询age < 22

Db.foo.find ({age:{$lt:)----SELECT * from Foo where age < 22

6 #查询age Records of <= 25

Db.foo.find ({age:{$lte: 25}})

7 #查询age >= 23 and age <=26 records

Db.foo.find ({age:{$gte:%, $lte: 26}})

8 #查询name中包含xingoo的数据

Db.foo.find ({name:/xingoo/})----SELECT * from foo where name like '%xingoo% '

9 #查询name中以xingoo开头的数据

Db.foo.find ({name:/^xingoo/})----SELECT * from foo where name like ' xingoo% '

Data for #查询指定列name, age

Db.foo.find ({},{name:1,age:1})----Select Name,age from foo

One #查询制定列name, age data, and age > 22

Db.foo.find ({age:{$gt: 22}},{name:1,age:1})----Select Name,age from foo where age >22

#按照年龄排序

Ascending:db.foo.find (). Sort ({age:1}) descending:db.foo.find (). Sort ({age:-1})

Data #查询name =xingoo.age=25

Db.foo.find ({name: ' Xingoo ', age:22})----SELECT * from foo where name= ' Xingoo ' and age = ' 25 '

14# Query the first 5 data

Db.foo.find (). Limit (5)----SELECT Top 5 * from Foo

#查询10条以后的数据

Db.foo.find (). Skip (Ten)----select * from foo where ID not in (select top of * from Foo);

Data between #查询在5-10

Db.foo.find (). Limit (Ten). Skip (5)

#or与查询

Db.foo.find ({$or: [{age:22},{age:25}]})----SELECT * from foo where age=22 or an age =25

#查询第一条数据

Db.foo.findOne (), Db.foo.find (). Limit (1)----SELECT top 1 * from Foo

#查询某个结果集的记录条数

Db.foo.find ({age:{$gte:). COUNT ()----SELECT COUNT (*) from Foo where age >= 20

#按照某列进行排序 (not understand)

Db.foo.find ({sex:{$exists: true}}). COUNT ()----select count (Sex) from Foo

#查询age取模10等于0的数据

Db.foo.find (' this.age% 10 = = 0 '), Db.foo.find ({age:{$mod: [10,0]}})

#匹配所有

Db.foo.find ({age:{$all: [22,25]}})

Record #查询不匹配name =x* lead

Db.foo.find ({name:{$not:/^x.*/}})

#排除返回age字段

Db.foo.find ({name: ' Xingoo '},{age:0})

#判断字段是否存在

Db.foo.find ({name:{$exists: true}})

Management

1 #查看collection数据大小

Db.xingootest.dataSize ()

2 #查看collection状态

Db.xingootest.stats ()

3 #查询所有索引的大小

Db.xingootest.totalIndexSize ()

Resources:

"MongoDB Introduction and Installation" Http://database.51cto.com/art/201103/247882.htm

"Getting Started with MongoDB" http://www.linuxidc.com/Linux/2013-01/78251.htm

"Interview and abuse of vegetables"--MONGODB knowledge finishing