Setup MongoDB on CentOS and Getting Started Guide

MongoDB is a cross-platform document-oriented database.

Classified as a NoSQL database, MongoDB's structure in are JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster

Setup MongoDB Repository:

Repository for CentOS 6:

$ cat >> /etc/yum.repos.d/mongodb-org-3.2.repo << EOF
[mongodb-org-3.2]
name=MongoDB Repository
baseurl=https://repo.mongodb.org/yum/redhat/6/mongodb-org/3.2/x86_64/
gpgcheck=0
enabled=1
EOF

Repository for CentOS 7:

$ cat >> /etc/yum.repos.d/mongodb-org-3.2.repo << EOF
[mongodb-org-3.2]
name=MongoDB Repository
baseurl=https://repo.mongodb.org/yum/redhat/7/mongodb-org/3.2/x86_64/
gpgcheck=0
enabled=1
EOF

Install and Start MongoDB:

$ yum install mongodb-org -y
$ /etc/init.d/mongod start
$ chkconfig mongod on

Usage of MongoDB:

Log onto MongoDB:

$ mongo
>

Lets use a specific DB called sysadmins:

> use sysadmins
switched to db sysadmins

To determine which db are we using:

> db
sysadmins

Inserting Records:

This is a simple record consisting of name and surname

> db.test.insert({name: "John", surname: "Dory"})
WriteResult({ "nInserted" : 1 })

In this example we will be adding users to our userdata collections:

db.userdata.insert({
    name: 'Ruan',
    surname: 'Bekker',
    username: 'ruanb',
    nationality: 'South Africa',
    occupation: 'Sysadmin',
    gender: 'male',
    age: '1987/01/01',
    os: 'linux'
})

db.userdata.insert({
    name: 'James',
    surname: 'Anderson',
    username: 'jamesa',
    nationality: 'New Zealand',
    occupation: 'Sysadmin',
    gender: 'male',
    age: '1987/04/02',
    os: 'linux'
})

db.userdata.insert({
    name: 'Marge',
    surname: 'Adam',
    username: 'margea',
    nationality: 'South Africa',
    occupation: 'Sysadmin',
    gender: 'female',
    age: '1989/04/05',
    os: 'mac'
})
  
db.userdata.insert({
    name: 'Kevin',
    surname: 'Dean',
    username: 'kevind',
    nationality: 'England',
    occupation: 'Developer',
    gender: 'male',
    age: '1992/04/05',
    os: 'linux'
})
  
db.userdata.insert({
    name: 'David',
    surname: 'Koggelberg',
    username: 'davidk',
    nationality: 'Australia',
    occupation: 'Management',
    gender: 'male',
    age: '1985/04/05',
    os: 'linux'
})

db.userdata.insert({
    name: 'Marge',
    surname: 'Adam',
    username: 'margea',
    nationality: 'South Africa',
    occupation: 'Sysadmin',
    gender: 'female',
    age: '1989/04/05',
    os: 'mac'
})

db.userdata.insert({
    name: 'Samantha',
    surname: 'Frost',
    username: 'samt',
    nationality: 'New Zealand',
    occupation: 'Developer',
    gender: 'female',
    age: '1992/04/09',
    os: 'windows'
})

db.userdata.insert({
    name: 'Mark', 
    surname: 'Beck', 
    username: 'markb', 
    nationality: 'South Africa', 
    occupation: 'Sysadmin',  
    gender: 'male', 
    age: '1989/04/05',  
    os: 'mac' 
})

Searching Records

Now that we have some sample data, we will do a scan to search for all records:

> db.userdata.find()

{ "_id" : ObjectId("56d0ae9cc806f4f7cfae1601"), "name" : "Ruan", "surname" : "Bekker", "username" : "ruanb", "nationality" : "South Africa", "occupation" : "Sysadmin", "gender" : "male", "age" : "1987/01/01", "os" : "linux" }
{ "_id" : ObjectId("56d0aecac806f4f7cfae1602"), "name" : "James", "surname" : "Anderson", "username" : "jamesa", "nationality" : "New Zealand", "occupation" : "Sysadmin", "gender" : "male", "age" : "1987/04/02", "os" : "linux" }
{ "_id" : ObjectId("56d0aecbc806f4f7cfae1603"), "name" : "Marge", "surname" : "Adam", "username" : "margea", "nationality" : "South Africa", "occupation" : "Sysadmin", "gender" : "female", "age" : "1989/04/05", "os" : "mac" }
{ "_id" : ObjectId("56d0aecbc806f4f7cfae1604"), "name" : "Kevin", "surname" : "Dean", "username" : "kevind", "nationality" : "England", "occupation" : "Developer", "gender" : "male", "age" : "1992/04/05", "os" : "linux" }
{ "_id" : ObjectId("56d0aecbc806f4f7cfae1605"), "name" : "David", "surname" : "Koggelberg", "username" : "davidk", "nationality" : "Australia", "occupation" : "Management", "gender" : "male", "age" : "1985/04/05", "os" : "linux" }
{ "_id" : ObjectId("56d0aecbc806f4f7cfae1606"), "name" : "Marge", "surname" : "Adam", "username" : "margea", "nationality" : "South Africa", "occupation" : "Sysadmin", "gender" : "female", "age" : "1989/04/05", "os" : "mac" }
{ "_id" : ObjectId("56d0aeccc806f4f7cfae1607"), "name" : "Samantha", "surname" : "Frost", "username" : "samt", "nationality" : "New Zealand", "occupation" : "Developer", "gender" : "female", "age" : "1992/04/09", "os" : "windows" }
{ "_id" : ObjectId("56d0b6f1c806f4f7cfae1608"), "name" : "Mark", "surname" : "Beck", "username" : "markb", "nationality" : "South Africa", "occupation" : "Sysadmin", "gender" : "male", "age" : "1989/04/05", "os" : "mac" }

Using Pretty Print:

> db.userdata.find().pretty()

...
{
        "_id" : ObjectId("56d0aeccc806f4f7cfae1607"),
        "name" : "Samantha",
        "surname" : "Frost",
        "username" : "samt",
        "nationality" : "New Zealand",
        "occupation" : "Developer",
        "gender" : "female",
        "age" : "1992/04/09",
        "os" : "windows"
}
...

Selectors:

Selectors are to Mongo what where clauses are to SQL

specify criteria that MUST match. i.e., an AND clause
specify criteria that CAN optionally match. i.e., an OR clause
specify criteria that MUST exist, etc.

We will use a basic selector that matches name = Ruan:

> db.userdata.find({name: "Ruan"}).pretty()

{
        "_id" : ObjectId("56d0ae9cc806f4f7cfae1601"),
        "name" : "Ruan",
        "surname" : "Bekker",
        "username" : "ruanb",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "male",
        "age" : "1987/01/01",
        "os" : "linux"
}

Find all users which uses Mac as OS:

> db.userdata.find({os: 'mac'}).pretty()

{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1603"),
        "name" : "Marge",
        "surname" : "Adam",
        "username" : "margea",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "female",
        "age" : "1989/04/05",
        "os" : "mac"
}
{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1606"),
        "name" : "Marge",
        "surname" : "Adam",
        "username" : "margea",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "female",
        "age" : "1989/04/05",
        "os" : "mac"
}

Multiple Criteria:

All users that use linux that's from Australia:

> db.userdata.find({os: 'linux', $or: [{nationality: 'Australia'}]}).pretty()

{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1605"),
        "name" : "David",
        "surname" : "Koggelberg",
        "username" : "davidk",
        "nationality" : "Australia",
        "occupation" : "Management",
        "gender" : "male",
        "age" : "1985/04/05",
        "os" : "linux"
}

And all users that uses linux thats from Australia and England:

> db.userdata.find({os: 'linux', $or: [{nationality: 'Australia'},{nationality: 'England'}]}).pretty()

{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1604"),
        "name" : "Kevin",
        "surname" : "Dean",
        "username" : "kevind",
        "nationality" : "England",
        "occupation" : "Developer",
        "gender" : "male",
        "age" : "1992/04/05",
        "os" : "linux"
}
{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1605"),
        "name" : "David",
        "surname" : "Koggelberg",
        "username" : "davidk",
        "nationality" : "Australia",
        "occupation" : "Management",
        "gender" : "male",
        "age" : "1985/04/05",
        "os" : "linux"
}

Sorting:

Here we will list all male users thats from South Africa and England, but the names are sorted by descending order

> db.userdata.find({gender: 'male', $or: [{nationality: 'South Africa'},{nationality: 'England'}]}).sort({name: -1}).pretty()

{
        "_id" : ObjectId("56d0ae9cc806f4f7cfae1601"),
        "name" : "Ruan",
        "surname" : "Bekker",
        "username" : "ruanb",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "male",
        "age" : "1987/01/01",
        "os" : "linux"
}
{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1604"),
        "name" : "Kevin",
        "surname" : "Dean",
        "username" : "kevind",
        "nationality" : "England",
        "occupation" : "Developer",
        "gender" : "male",
        "age" : "1992/04/05",
        "so" : "linux"
}

On Ascending order:

> db.userdata.find({gender: 'male', $or: [{nationality: 'South Africa'},{nationality: 'England'}]}).sort({name: 1}).pretty()

{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1604"),
        "name" : "Kevin",
        "surname" : "Dean",
        "username" : "kevind",
        "nationality" : "England",
        "occupation" : "Developer",
        "gender" : "male",
        "age" : "1992/04/05",
        "os" : "linux"
}
{
        "_id" : ObjectId("56d0ae9cc806f4f7cfae1601"),
        "name" : "Ruan",
        "surname" : "Bekker",
        "username" : "ruanb",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "male",
        "age" : "1987/01/01",
        "os" : "linux"
}

Sorting by nationality in Descending order and name in Ascending order:

> db.userdata.find({gender: 'male', $or: [{nationality: 'South Africa'},{nationality: 'England'}]}).sort({nationality: -1, name: 1}).pretty()

{
        "_id" : ObjectId("56d0b6f1c806f4f7cfae1608"),
        "name" : "Mark",
        "surname" : "Beck",
        "username" : "markb",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "male",
        "age" : "1989/04/05",
        "os" : "mac"
}
{
        "_id" : ObjectId("56d0ae9cc806f4f7cfae1601"),
        "name" : "Ruan",
        "surname" : "Bekker",
        "username" : "ruanb",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "male",
        "age" : "1987/01/01",
        "os" : "linux"
}
{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1604"),
        "name" : "Kevin",
        "surname" : "Dean",
        "username" : "kevind",
        "nationality" : "England",
        "occupation" : "Developer",
        "gender" : "male",
        "age" : "1992/04/05",
        "os" : "linux"
}

Limit Records:

Show only the first 2 records:

> db.userdata.find({nationality: 'South Africa'}).limit(2).pretty()

{
        "_id" : ObjectId("56d0ae9cc806f4f7cfae1601"),
        "name" : "Ruan",
        "surname" : "Bekker",
        "username" : "ruanb",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "male",
        "age" : "1987/01/01",
        "os" : "linux"
}
{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1603"),
        "name" : "Marge",
        "surname" : "Adam",
        "username" : "margea",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "female",
        "age" : "1989/04/05",
        "os" : "mac"
}

To see the 3rd and 4th record, meaning skipping the first 2 records:

> db.userdata.find({nationality: 'South Africa'}).limit(2).skip(2).pretty()

{
        "_id" : ObjectId("56d0aecbc806f4f7cfae1606"),
        "name" : "Marge",
        "surname" : "Adam",
        "username" : "margea",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "female",
        "age" : "1989/04/05",
        "os" : "mac"
}
{
        "_id" : ObjectId("56d0b6f1c806f4f7cfae1608"),
        "name" : "Mark",
        "surname" : "Beck",
        "username" : "markb",
        "nationality" : "South Africa",
        "occupation" : "Sysadmin",
        "gender" : "male",
        "age" : "1989/04/05",
        "os" : "mac"
}

Updating Records:

Mark Beck relocated to Seattle, lets update the record:

> db.userdata.update({username: 'markb'}, {$set: {nationality: 'Seattle'}})
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })

Deleting Records:

> db.userdata.remove({username: 'markb'})
WriteResult({ "nRemoved" : 1 })

> db.userdata.remove({name: 'Ruan'},{surname: 'Bekker'})
WriteResult({ "nRemoved" : 1 })

Resource:

Source

Setup MongoDB on CentOS and Getting Started Guide

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