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MongoDB - basic

简介:

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

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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()

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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 itAND 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
                }
        ]
}




本文转自Ryan.Miao博客园博客,原文链接:http://www.cnblogs.com/woshimrf/p/5651017.html,如需转载请自行联系原作者

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