mongoDB basic

from:http://www.tutorialspoint.com/mongodb

prject:https://github.com/chenxing12/l4mongodb

  1. overview
  2. getting-start
  3. collection
  4. dataType
  5. insert
  6. find

Overview

MongoDB is a cross-platform, document oriented database that provides, high

performance, high availability, and easy scalability. MongoDB works on concept

of collection and document.

Database

Database is a physical container for collections. Each database gets its own set

of files on the file system. A single MongoDB server typically has multiple

databases.

Collection

Collection is a group of MongoDB documents. It is the equivalent of an RDBMS

table. A collection exists within a single database. Collections do not enforce

a schema. Documents with a collection can have different fields. Typically, all

documents in a collection are of similar or related purpose.

Document

A document is a set of key-value pairs. Documents have dynamic schema. Dynamic

schema means that documents in the same collection do not need to have the same

set of fields or structure, and common fields in a collection's documents may

hold different types of data.

Below given table shows the relationship of RDBMS terminology with MongoDB

RDBMS MongoDB
Database Database
Table Collection
Tuple/Row Document
column Field
Table Join Embedded Documents
Table Join Primary Key(Default key _id provided by mongodb itself)

Sample document

Below given example shows the document structure of a blog site which is simply

a comma separated key value pair.

{
_id: ObjectId(7df78ad8902c)
title: 'MongoDB Overview',
description: 'MongoDB is no sql database',
by: 'tutorials point',
url: 'http://www.tutorialspoint.com',
tags: ['mongodb', 'database', 'NoSQL'],
likes: 100,
comments: [
{
user:'user1',
message: 'My first comment',
dateCreated: new Date(2011,1,20,2,15),
like: 0
},
{
user:'user2',
message: 'My second comments',
dateCreated: new Date(2011,1,25,7,45),
like: 5
}
]
}

Getting-Start

top

Database

check all the databases:

> show dbs
local 0.000GB
mrf 0.000GB
test 0.005GB

create database: for example create mydb

> use mydb
switched to db mydb
> show dbs
local 0.000GB
mrf 0.000GB
test 0.005GB

The database mydb has not been created, because the db is empty,

You must create at lest one collection next.For example:

>
> use mydb
switched to db mydb
> show dbs
local 0.000GB
mrf 0.000GB
test 0.005GB
>
> show collections
> db.user.insert({name:"Ryan"})
WriteResult({ "nInserted" : 1 })
> show dbs
local 0.000GB
mrf 0.000GB
mydb 0.000GB
test 0.005GB

check current database:

> db
mydb

switch db:

> db
mydb
> use test
switched to db test
> db
test

drop database:

> show dbs
local 0.000GB
mrf 0.000GB
mydb 0.000GB
test 0.005GB
> use mydb
switched to db mydb
> db.dropDatabase()
{ "dropped" : "mydb", "ok" : 1 }
> show dbs;
local 0.000GB
mrf 0.000GB
test 0.005GB

collection

top

create collection

when you insert data, if the collection not exists, it will be created automatically:

> show collections
restaurants
test
> db.mycollection.insert({name:"test"})
WriteResult({ "nInserted" : 1 })
> show collections
mycollection
restaurants
test

Of course, there is other way to create a specify collection:

Syntax

Basic syntax of createCollection() command is as follows:

db.createCollection(name, options)

In the command, name is the name of collection created, Options is a document

and used to specify configuration of collection.

Options parameter is optional, so you need to specify only name of the collection.

Following is the list of options you can use:

Filed Type Description
capped Boolean (Optional) If true, enables a capped collection. Capped collection is a collection fixed size collection that automatically overwrites its oldest entries when it reaches its maximum size. If you sepecify true, you need specify size parameter too
autoIndexID Boolean (Optional) If true, automatically create index on _id filed. Default value is false
size number (Optional) Specify a maximum size in bytes for a capped collection. If capped is true, then you need specify this filed also
max number (Optional) Specifies the maximum number of documents allowed in the capped collection.

while inserting the document , MongoDB first checks size filed of capped collection, then it checks max filed.

Example

> db.mycollection.drop()
true
> show collections
restaurants
test
>
>
> db.createCollection("mycollection")
{ "ok" : 1 }
> show collections
mycollection
restaurants
test
>
> db.createCollection("mycol",{capped:true,autoIndexID:true,size:6142800, max:10000})
{ "ok" : 1 }
> show collections
mycol
mycollection
restaurants
test
>

drop()

> use test
switched to db test
> show collections
mycol
mycollection
restaurants
test
> db.mycol.drop()
true
> show collections
mycollection
restaurants
test

DataType

  1. top

MongoDB supports many datatypes whose list is given below:

String : This is most commonly used datatype to store the data. String in mongodb must be UTF-8 valid.

Integer : This type is used to store a numerical value. Integer can be 32 bit or 64 bit depending upon your server.

Boolean : This type is used to store a boolean (true/ false) value.

Double : This type is used to store floating point values.

Min/ Max keys : This type is used to compare a value against the lowest and highest BSON elements.

Arrays : This type is used to store arrays or list or multiple values into one key.

Timestamp : ctimestamp. This can be handy for recording when a document has been modified or added.

Object : This datatype is used for embedded documents.

Null : This type is used to store a Null value.

Symbol : This datatype is used identically to a string however, it's generally reserved for languages that use a specific symbol type.

Date : This datatype is used to store the current date or time in UNIX time format. You can specify your own date time by creating object of Date and passing day, month, year into it.

Object ID: This datatype is used to store the document’s ID.

Binary data : This datatype is used to store binay data.

Code : This datatype is used to store javascript code into document.

Regular expression : This datatype is used to store regular expression

Insert

  1. top

MongoDB insert option:

> show dbs;
local 0.000GB
mrf 0.000GB
test 0.005GB
> use test
switched to db test
> show collections;
mycollection
restaurants
test
>
>
> db.mycollection.insert({
title:"MongoDB Overview",
description:'MongoDB is no sql database',
by:'tutorials point',
url:'http://www.tutorialspoint.com',
tags:['mongodb','database','NoSQL'],
likes:100
})
WriteResult({ "nInserted" : 1 })
>
> db.mycollection.find()
{ "_id" : ObjectId("577e0dce99da0904659393c0"), "title" : "MongoDB Overview", "description" : "MongoDB is no sql databas
e", "by" : "tutorials point", "url" : "http://www.tutorialspoint.com", "tags" : [ "mongodb", "database", "NoSQL" ], "lik
es" : 100 }
> db.mycollection.find().pretty()
{
"_id" : ObjectId("577e0dce99da0904659393c0"),
"title" : "MongoDB Overview",
"description" : "MongoDB is no sql database",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 100
}
>

Here mycollections is our collection name, as created in previous tutorial. If the

collection doesn't exist in the database, then MongoDB will create this collection

adn then insert document into it.

In the inserted document if we don't specify the _id parameter, then MongoDB

assigns an unique ObjectId for this document.

_id is 12 bytes hexadecimal number unique for every document in a collection.

12 Bytes are dived as follows :

_id: ObjectId(4 bytes timestamp, 3 bytes machine id, 2 bytes process id, 3 bytes incrementer)

To insert multiple documents in single query, you can pass an array of documents

in insert() command.

Example

db.post.insert([
{
title: 'MongoDB Overview',
description: 'MongoDB is no sql database',
by: 'tutorials point',
url: 'http://www.tutorialspoint.com',
tags: ['mongodb', 'database', 'NoSQL'],
likes: 100
},
{
title: 'NoSQL Database',
description: 'NoSQL database doesn\'t have tables',
by: 'tutorials point',
url: 'http://www.tutorialspoint.com',
tags: ['mongodb', 'database', 'NoSQL'],
likes: 20,
comments: [
{
user:'user1',
message: 'My first comment',
dateCreated: new Date(2013,11,10,2,35),
like: 0
}
]
}
])

find()

top

The find() Method

To query data from MongoDB collection, you need to user MongoDB's find() method.

Syntax

Basic syntax of find() method id as follows:

db.collection_name.find()

find()method will display all the documents in a non structured way.

The pretty() Method

To display the results in a formatted way, you can use pretty() method.

db.collection_name.find().pretty()

Example

> show collections
mycollection
post
restaurants
test
> db.post.find().pretty()
{
"_id" : ObjectId("577e11fd502847799b05f062"),
"title" : "MongoDB Overview",
"description" : "MongoDB is no sql database",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 100
}
{
"_id" : ObjectId("577e11fd502847799b05f063"),
"title" : "NoSQL Database",
"description" : "NoSQL database doesn't have tables",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 20,
"comments" : [
{
"user" : "user1",
"message" : "My first comment",
"dateCreated" : ISODate("2013-12-10T10:35:00Z"),
"like" : 0
}
]
}
>

RDBMS Where Clause Equivalents in MongoDB

To query the document on the basis of some codition, you can use following

options:

Options Syntax Example RDBMS Equivalent
Equal {<key>:<value>} db.mycol.find({'by':'abc'}).pretty() where by='abc'
Less Than {<key>:{$lt:<value>}} db.mycol.find({'likes':{$lt:50}}).pretty() where likes < 50
Less Than Equals {<key>:{$lte:<value>}} db.mycol.find({'likes':{$lte:50}}).pretty() where likes <= 50
Greater Than {<key>:{$gt:<value>}} db.mycol.find({'likes':{$gt:50}}).pretty() where likes > 50
Greater Than Equals {<key>:{$gte:<value>}} db.mycol.find({'likes':{$gte:50}}).pretty() where likes >= 50
Not Equals {<key>:{$ne:<value>}} db.mycol.find({'likes':{$ne:50}}).pretty() where likes != 50

Example

> db.mycol.find().pretty()
{
"_id" : ObjectId("577e19c5502847799b05f064"),
"title" : "MongoDB Overview",
"description" : "MongoDB is no sql database",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 100
}
{
"_id" : ObjectId("577e19c5502847799b05f065"),
"title" : "NoSQL Database",
"description" : "NoSQL database doesn't have tables",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 20,
"comments" : [
{
"user" : "user1",
"message" : "My first comment",
"dateCreated" : ISODate("2013-12-10T10:35:00Z"),
"like" : 0
}
]
}
>
> db.mycol.find({'likes':{$gt:50}}).pretty()
{
"_id" : ObjectId("577e19c5502847799b05f064"),
"title" : "MongoDB Overview",
"description" : "MongoDB is no sql database",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 100
}
> db.mycol.find({'likes':{$lt:50}}).pretty()
{
"_id" : ObjectId("577e19c5502847799b05f065"),
"title" : "NoSQL Database",
"description" : "NoSQL database doesn't have tables",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 20,
"comments" : [
{
"user" : "user1",
"message" : "My first comment",
"dateCreated" : ISODate("2013-12-10T10:35:00Z"),
"like" : 0
}
]
}

AND in MongoDB

Syntax

In the find() method if you pass multiple keys by separating them by ',' then

MongoDB treats it AND condition. Basic syntax of AND is shown below:

db.mycol.find({ keys:value, key2:value2 }).pretty()

Example:

Below given example will show all the tutorials written by and

whose title is 'MongoDB OVerview':

> db.mycol.find({"by":"tutorials point","title":"MongoDB Overview"}).pretty()
{
"_id" : ObjectId("577e19c5502847799b05f064"),
"title" : "MongoDB Overview",
"description" : "MongoDB is no sql database",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 100
}

For the above given example equivalent where clause will be

where by='tutorials point' AND title = 'MongoDB Overview'.

You can pass any number of key, value pairs in find clause.

OR in MongoDB

Syntax

To query documents based on the OR condition, you need to use $or keyword.

Basic syntax of OR is shown below −

>db.mycol.find(
{
$or: [
{key1: value1}, {key2:value2}
]
}
).pretty()

Example

> db.mycol.find(
{
$or:[
{"title":"MongoDB Overview"},{"likes":20}
]
}).pretty() {
"_id" : ObjectId("577e19c5502847799b05f064"),
"title" : "MongoDB Overview",
"description" : "MongoDB is no sql database",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 100
}
{
"_id" : ObjectId("577e19c5502847799b05f065"),
"title" : "NoSQL Database",
"description" : "NoSQL database doesn't have tables",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 20,
"comments" : [
{
"user" : "user1",
"message" : "My first comment",
"dateCreated" : ISODate("2013-12-10T10:35:00Z"),
"like" : 0
}
]
}

Using AND and OR together

Example

Below given example will show the documents that have likes greater than 10

and whose title is either 'MongoDB Overview' or by is 'tutorials point':

Equals:where likes>10 AND (by = 'tutorials point' OR title = 'MongoDB Overview')

> db.mycol.find({
"likes": {$gt:10},
$or: [
{"by": "tutorials point"}, {"title": "MongoDB Overview"}
]
}).pretty()
{
"_id" : ObjectId("577e19c5502847799b05f064"),
"title" : "MongoDB Overview",
"description" : "MongoDB is no sql database",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 100
}
{
"_id" : ObjectId("577e19c5502847799b05f065"),
"title" : "NoSQL Database",
"description" : "NoSQL database doesn't have tables",
"by" : "tutorials point",
"url" : "http://www.tutorialspoint.com",
"tags" : [
"mongodb",
"database",
"NoSQL"
],
"likes" : 20,
"comments" : [
{
"user" : "user1",
"message" : "My first comment",
"dateCreated" : ISODate("2013-12-10T10:35:00Z"),
"like" : 0
}
]
}

MongoDB - basic的更多相关文章

  1. DB Intro - MongoDB Basic

    mongoDB basic from:http://www.tutorialspoint.com/mongodb prject:https://github.com/chenxing12/l4mong ...

  2. [AWS] Deploy react project on EC2

    如何在aws部署项目 申请到亚马逊AWS免费账户后,我们可以拥有很多的免费云服务产品项目,其中包括: EC2云服务器. Amazon S3存储. Amazon RDS数据库. Amazon Cloud ...

  3. MongoDB-2.6.0 (OpenLogic CentOS7.2)

    平台: CentOS 类型: 虚拟机镜像 软件包: mongodb basic software database linux open source 服务优惠价: 按服务商许可协议 云服务器费用:查 ...

  4. basic mongodb

    basic mongodb */--> pre { background-color: #2f4f4f;line-height: 1.6; FONT: 10.5pt Consola," ...

  5. lbs basic mongodb

    MongoDB地理位置索引常用的有两种. db.places.ensureIndex({'coordinate':'2d'}) db.places.ensureIndex({'coordinate': ...

  6. 【MongoDB】The basic operation of Index in MongoDB

    In the past four blogs, we attached importance to the index, including description and comparison wi ...

  7. MySQL、MongoDB、Redis数据库Docker镜像制作

    MySQL.MongoDB.Redis数据库Docker镜像制作 在多台主机上进行数据库部署时,如果使用传统的MySQL的交互式的安装方式将会重复很多遍.如果做成镜像,那么我们只需要make once ...

  8. 搭建高可用mongodb集群(三)—— 深入副本集内部机制

    在上一篇文章<搭建高可用mongodb集群(二)—— 副本集> 介绍了副本集的配置,这篇文章深入研究一下副本集的内部机制.还是带着副本集的问题来看吧! 副本集故障转移,主节点是如何选举的? ...

  9. Mongodb源代码阅读笔记:Journal机制

    Mongodb源代码阅读笔记:Journal机制 Mongodb源代码阅读笔记:Journal机制 涉及的文件 一些说明 PREPLOGBUFFER WRITETOJOURNAL WRITETODAT ...

随机推荐

  1. windows多线程编程星球(一)

    以前在学校的时候,多线程这一部分是属于那种充满好奇但是又感觉很难掌握的部分.原因嘛我觉得是这玩意儿和编程语言无关,主要和操作系统的有关,所以这部分内容主要出现在讲原理的操作系统书的某一章,看完原理是懂 ...

  2. PHP基础知识之对象复制

    对象的复制默认为浅复制 进行深复制的方法为:在类中定义魔法方法__clone(),类的对象复制时,会自动调用 __clone方法,在 __clone方法中可以进行各种复制对象的个性化 class My ...

  3. java读写Properties属性文件公用方法

    Java中有个比较重要的类Properties(Java.util.Properties),主要用于读取Java的配置文件. 它提供了几个主要的方法: 1. getProperty ( String ...

  4. Unity学习疑问记录之协程

    http://blog.csdn.net/huang9012/article/details/38492937 总结:1.协程相当于多线程但不是,(尽管它们看上去是这样的),它们运行在同一线程中,跟普 ...

  5. SQL Server 变更数据捕获(CDC)监控表数据

    一.本文所涉及的内容(Contents) 本文所涉及的内容(Contents) 背景(Contexts) 实现过程(Realization) 补充说明(Addon) 参考文献(References) ...

  6. Python Django Apache配置

    项目结构目录: Apache 安装配置目录: C:\Apache2.2\conf\httpd.conf LoadModule wsgi_module modules/mod_wsgi.soWSGISc ...

  7. 自己动手模拟开发一个简单的Web服务器

    开篇:每当我们将开发好的ASP.NET网站部署到IIS服务器中,在浏览器正常浏览页面时,可曾想过Web服务器是怎么工作的,其原理是什么?“纸上得来终觉浅,绝知此事要躬行”,于是我们自己模拟一个简单的W ...

  8. 借助 Lucene.Net 构建站内搜索引擎(下)

    前言:上一篇我们学习了Lucene.Net的基本概念.分词以及实现了一个最简单的搜索引擎,这一篇我们开始开发一个初具规模的站内搜索项目,通过开发站内搜索模块,我们可以方便地在项目中集成站内搜索功能.本 ...

  9. ASP.NET MVC 5 Web编程2 -- URL映射(路由原理)

    本章将讲述ASP.NET MVC5 的路由原理,即URL映射机制. 简单点就是解释:为什么MVC在浏览器输入地址就能访问到类(或类中的方法)?这是怎么做到的?我自己可以通过.NET写出一个自己的MVC ...

  10. ASP.NET MVC学前篇之扩展方法、链式编程

    ASP.NET MVC学前篇之扩展方法.链式编程 前言 目的没有别的,就是介绍几点在ASP.NETMVC 用到C#语言特性,还有一些其他琐碎的知识点,强行的划分一个范围的话,只能说都跟MVC有关,有的 ...