Learn MongoDB In A Nutshell

The following topics will be covered in this article,

Insert Document
Update Data in collection
Delete Data in collection
Get All collections from Database
Use Equal, Less than, Greater Than, Less than or Equal and Greater than or Equal operators
And Clause, Or clause, Not clause, Between clause and Like clause
Sort, Limit, Projection, Sum, Count, Min, Max, Avg, Date time, Join, Group By and Having Clause

Databases originated in the 1960s in order to replace the existing file organization of data.

The first databases that appeared used hierarchical (tree-like) or network structures to store data.

Types of Databases

SQL

Structured Query Language is the standard language for dealing with Relational Databases. In this, data uses schemas and relations and will be scaled vertically.

Important characteristics of the Databases,

Structured data
Related data
Metadata
Data integrity & Data security
Data storage, retrieval, and update

NoSQL

Not only is SQL a schema-less database for no-relations (very few) data maintenance, it’s possible to do horizontal and vertical data scaling. It stores and processes huge volumes of data.

Important characteristics of the NoSQL Databases,

Need to store unstructured data
Need for scalability and flexibility
Need for real-time access.
Types of NoSQL Databases:

The following main types of NoSQL databases can be identified, depending on the data model used:

Key-value store
Document store
Column-oriented
Graph-oriented

The characteristics of the most popular products from each category are taken into account when performing the analysis. These are,

Redis for key-value stores;
MongoDB for document stores;
Apache Cassandra for column-oriented stores;
Neo4j for graph-oriented stores.

MongoDB is a No SQL database. It is an open-source, cross-platform, document-oriented database written in C++.

Why Use Mongo DB

Please look into the below snapshot for better understanding,

We can interact with MongoDB in different ways, as listed below.

Use mongo shell to insert data and perform query operations.
Use MongoDB Compass to connect to insert data and perform query operations.

Here is the link for more details.

Here is the list of most popular third party MongoDB tools

MongoBooster – RoboMongo – MongoVUE – RockMongo – MongoHub -UMongo-3T Mongo Chef

Configuration through Mongo Shell

If you use “mongo” in the command prompt without configuring it, then it would give an error. Hence, configure it first.

Step 1

Go to the local disk C and get into Program Files. There you'll find a folder named MongoDB.

C:\Program Files\MongoDB\Server\3.2\bin\

Open Command prompts and type “mongod” to start the service.

MongoDB requires a data directory to store all data. Mongo DB’s default data directory path is \data\db.

Create this folder,

Write command on the command prompt “mongo” to create the connection.

MongoDB – Create Database

Creation of a database is so easy. All you have to do is to put “use” before the name of the database and press Enter.

First Create Connection,

Mongo list collections with the command “Show dbs”

As we have created a database, now, let's create a mongo collection in it. For this purpose, a user must insert certain records which make up a mongo document in collection i.e. via Field Names & Field Values.

Connect to a MongoDB instance running on your local host with default port 27017.

Create a database with the name is MovieDatabase. This database has 2 collections: Movie collection and Product collection. Movie collection and Region collection have a One to Many. One movie can have many products and one region belongs to one and only one category.

/* Create MovieDatabase database */
use MovieDatabase

/* Create Movie collection */
db.createCollection('Movie');
/* Dumping data for ` movie ` collection */
db.getCollection('movie').insert({
name: 'Hollywood'
})
db.getCollection('movie').insert({
name: 'Bollywood'
})
db.getCollection('movie').insert({
name: 'Tollywood'
})
WriteResult({ "nInserted" : 1 })
> db.movie.find()
{ "_id" : ObjectId("5d6e06066f480eca73e15f22"), "name" : "Hollywood" }
{ "_id" : ObjectId("5d6e06106f480eca73e15f23"), "name" : "Bollywood" }
{ "_id" : ObjectId("5d6e061b6f480eca73e15f24"), "name" : "Tollywood" }
>

db.movie.find().pretty()

/* Create Region collection */
db.createCollection('region');
/* Dumping data for `` collection */
db.getCollection('region').insert({
FileName: 'Sahoo',
Budget: '350',
Language: 'Telugu',
date: ISODate('2019-08-30'),
movieId: ObjectId('5d6e061b6f480eca73e15f24'),
Industry: {
_id: new ObjectId(),
name: 'Tollywood'
}
});
db.getCollection('region').insert({
FileName: 'Bahuballi',
Budget: '200cr',
Language: 'Hindi',
date: ISODate('2015-08-30'),
movieId: ObjectId("5d6e06106f480eca73e15f23"),
Industry: {
_id: new ObjectId(),
name: 'Bollywood'
}
});
db.region.find().pretty()

Update Data in collection,

db.getCollection('region').update(
{_id: ObjectId('5d6e11aa6f480eca73e15f2a')},
{
$set:{Budget : '5000cr'}}
);

Check now if collection is updated or not

db.region.find().pretty()

Delete Data in Collection

db.getCollection('region').remove({_id: ObjectId('5d6e11aa6f480eca73e15f2a')});

Check now if particular id collection is deleted or not,

Get All collections from Database

Add some movies to the collections for better understanding.

db.getCollection('region').find({})

Use find() method to display documents in Region Collection

Use Equal Operator in Query Commands

db.getCollection('region').find({Language: 'Hindi'})

Use Less Than Operator in Query Commands

db.getCollection('region').find({ Budget: { $lte: 500 } })

Output

Use Less Than or Equal operator in Query Commands

db.getCollection('region').find({ Budget: { $lte: 500 } })

Output

Use Greater Than operator in Query Commands

db.getCollection('region').find({ Budget: { $gt: 300} })

Output

Use Greater Than or Equal Operator in Query Commands

db.getCollection('region').find({ Budget: { $gte: 300 } })

Output

And Clause in Query Commands

db.getCollection('region').find({ $and: [{Budget: {$lt: 200}}, {Language: "English"}] }).pretty()

Output

Or Clause in Query Commands

db.getCollection('region').find({ $or: [{Budget: {$gt: 2200}}, {Language: "Telugu"}] }).pretty()

Output

Not Clause in Query Commands

db.getCollection('region').find({ Language: { $ne: "Hindi" } }).pretty()

Output

Between Clause in Query Commands

db.getCollection('region').find({ $and: [{Budget: {$gte: 100}}, { Budget: {$lte: 300}}] }).pretty()

Output

Like Clause in Query Commands

Start with Mob string

db.getCollection('region').find({FileName: /^Ti/}).pretty()

Output

Ends with 2 string

db.getCollection('region').find({FileName: { $regex: /hi$/ } } ).pretty()

Output

Limit in Query Commands

If we want to fetch the first two documents from the collection "region", the following mongodb command can be used

db.region.find().limit(2).pretty();

If we want to fetch two documents after the first two documents from the collection 'region', the following mongodb command can be used :

db.region.find().skip(2).pretty();

If we want to fetch the two documents after the first document from the collection 'region', the following mongodb command can be used :

>db.region.find().skip(1).limit(2).pretty();

Output

Sort by Budget Ascending

db.getCollection('region').find().sort({Budget: 1})

Output

Sort by Budget Descending

db.region.find().sort({Budget:-1}).pretty()

Output

Sort and Condition

db.getCollection('region').find({Language: "Hindi"}).sort({price: -1})

Output

Sum in Query Commands

Sum Budget

db.getCollection('region').aggregate( [ { $group: { _id: '', total: { $sum: "$Budget" } } } ] ).pretty()

Output

Sum Budget With Conditions

db.getCollection('region').aggregate([
{
$match: {
$and: [{Budget: {$lt: 200}}, {Language: "English"}] }
},
{
$group: { _id: '', total: { $sum: "$Budget" } }
}
]).pretty()

Count Product in Query Command

db.getCollection('region').count()

Output

Sum Budget With Conditions

db.getCollection('region').find({Budget: {$lt: 200}}).count()

Output

Min and Max in Query Commands

The Biggest Price

db.getCollection('region').aggregate( [ { $group: { _id: '', total: { $max: "$Budget" } } } ] )

Output

The Smallest Budget

db.getCollection('region').aggregate( [ { $group: { _id: '', total: { $min: "$Budget" } } } ] )

Output

Use Date and Time with Conditions

db.getCollection('region').aggregate(
{
$project: { FileName: 1, Language: 1, month: {$month: '$date'}, year: {$year: '$date'}, day: {$dayOfMonth: '$date'} }
},
{
$match: {month: 8, year: 2019}
}
).pretty()

Output

Filter Data with Embed Document in Query Commands,

db.getCollection('region').find({'Industry.name': 'Tollywood'}).pretty()

Output

Join and Conditions in Query Commands

db.getCollection('region').aggregate(
{
"$match": { "Language": 'Hindi' }
},
{
"$sort": { "price": -1 }
},
{
"$limit": 3
},
{
$lookup: {
"localField": "_Id",
"from": "movie",
"foreignField": "_id",
"as": "IndustryInfo"
}
}, {
$project: {
'id': 1,
'FileName': 1,
'Budget': 1,
'industry._id': 1,
'industry.name': 1
}
}).pretty()

Output

Group By and Having in Query Commands

db.getCollection('region').aggregate([
{
"$group" : {_id: "$Language",
countProduct: {$sum: 1},
sumQuantity: {$sum: '$Budget'},
}
},
{
$match: { sumQuantity: { $gt: 200 } } // Having
},
{
$sort: { "sumQuantity": 1 }
}
]).pretty()

Output

MongoDB Compass GUI

MongoDB Compass to connect to insert data and perform query operations. Once we have downloaded and opened MongoDB Compass, we need to fill the below details for connecting mongo DB host. Here, at the top right corner, we have connection and disconnection options for connecting host.

You can create a database from this UI.

Here you can create collections (tables).

Here point to the environments pipeline,