Start MongoDB journey

Start MongoDB journey

Luo Weifeng 2011-6-28

Environment: Ubuntu 11.04

Install MongoDB

$ Sudo apt-Get install MongoDB

Libpcrecpp0 libboost-system1.42.0 libboost-filesystem1.42.0 is automatically installed

Libboost-program-options1.42.0 libboost-thread1.42.0 xulrunner-2.0-mozjs

Dependent packages such as MongoDB-clients MongoDB-server MongoDB-dev MongoDB.

$ PS aux | grep primary d

Install the python driver

$ Sudo apt-Get install Python-setuptools

$ Sudo easy_install pymongo

Configure MongoDB

$ Sudo Vim/etc/MongoDB. conf

Dbpath = 'your datebase Path'

Logpath = 'Where to Log'

Logappend = true

Bind_id = 127.0.0.1

Port = 27017

Use Mongo to test the database

Mongo is the client, and mongod is the server. The following uses Mongo to test the service.

Root @ Ubuntu :~ # Mongo

MongoDB shell version: 1.6.3

Mon Jun 27 19:15:05 *** warning: Spider Monkey build without utf8 support. consider rebuilding with utf8 support

Connecting to: Test

>

> DB. serverstatus ()

There are several main types of output parameters in JSON format:

Uptime: server running time (seconds)

Localtime: local server time

Mem: Server Memory Information

Connections: current number of connections

Opcounters: Operation statistics

View All databases:

> Show DBS

Admin

Local

It can be seen that at the beginning, only the admin local test database was used, and test was not displayed here.

Switch Database

> Use Admin

Switched to DB Admin

> DB. Stats ()

Use Web testing database

Access 27017

Access 27017 + 1000 = 28017 again as required

You can see a complete management page, which is obviously not as beautiful as couchdb.

Complete Test to create a database

MongoDB does not have the command to create a database. You can use dbname to switch to a database that does not exist. when data is written, a database is created.

Root @ Ubuntu :~ # Mongo

> Use mytestdb

Create collection

The coolection database is created after you enter the database. Use

DB. createcollection ("mytestdb", {capped: True, size: 10000}) is measured in KB.

Or dB. runcommand ({createcollection: "mytestdb", capped: True, size: 100000 })

The capped parameter is used to create a database file of a fixed size. To ensure efficiency, Mongo occupies disk space during collection creation to prevent fragments.

> DB. createcollection ("mytestdb", {capped: True, size: 10000 })

> Show collections

Mytestdb

Document creation

> DB. mytestdb. insert ({Name: 'xiaowanzi', age: 8 })

Sample Query

Operator	SQL	Mongo
*	Select * From mytestdb	DB. mytestdb. Find ()
Column	Select name, age from mytestdb	DB. mytestdb. Find ({}, {Name: 1, age: 1 })
Where *	Select * From mytestdb where age = 24	DB. mytestdb. Find ({age: 24 })
Column where	Select name, age from mytestdb where age = 24	DB. mytestdb. Find ({age: 24}, {Name: 1, age: 1 })
> & Gt	Select * From mytestdb where age> 20	DB. mytestdb. Find ({'age': {& gt: 20 }})
Like	Select * From mytestdb where name like 'wang %'	DB. mytestdb. Find ({Name:/^ wangfan /})
	Select * From mytestdb where name like '% Wang %'	DB. mytestdb. Find ({Name:/wangfan /})
Order	Select * From mytestdb order by name DESC	DB. mytestdb. Find (). Sort ({Name:-1 })

> DB. mytestdb. Find ()

{"_ Id": objectid ("4e093ff90edf95f31cbc7c29"), "name": "xiaowanzi", "Age": 8}

Create an index

Use ensureindex to create an index

DB. mytestdb. ensureindex ({Name: 1 })

DB. runcommand ({dropindexes: 'foo', index :'*'})

Here, 1 is positive, and-1 is inverted.

Delete Index

DB. collection. dropindexes (); Delete All indexes

DB. mytestdb. dropindexes ({Name: 1 });

DB. runcommand ({dropindexes: 'wfcoll ', index: {Name: 1 }})

We create an index for the name field and a negative index for the age, as shown below:

> DB. mytestdb. ensureindex ({Name: 1 })

> DB. mytestdb. ensureindex ({age:-1 })

Test with Python

$ Python

>>> Import pymongo

>>> Conn = pymongo. Connection (host = "localhost", Port = 27017)

>>> DB = conn. mytestdb

>>> For user in db. wfcoll. Find ({}):

... Repr (User)