LearnMongoDB

NoSQL

• NoSQL databases (aka "not only SQL") are non-tabular databases and store data differently than relational tables.
• NoSQL databases come in a variety of types based on their data model.
• The main types are document, key-value, wide-column, and graph.
• They provide flexible schemas and scale easily with large amounts of data and high user loads.

MongoDB

• MongoDB is a source-available cross-platform document-oriented database program.
• Classified as a NoSQL database program, MongoDB uses JSON-like documents with optional schemas.

Features

• MongoDB uses Mozilla's SpiderMonkey JavaScript Engine
• MongoDB is a document based database which is different from relational database.
• Database has Collections (i.e Tables)
• Collections contains Documents (i.e Records)
• Documents in Database are stored in BSON format
• Binary JSON (BSON) data type is the binary representation of a JSON data type format for serializing JSON documents
• Extended JSON is used to represent/read BSON data types

Types of Databases

1. Relational:
   • SQL DB
   • Data is stored in relational tables comprising of Rows & Columns
   • It is mandatory to have fixed schema
2. Document
   • NoSQL DB
   • Data is stored in documents.
   • Its not mandatyory to have same schema for all documents

JSON data Type

https://chistadata.com/wp-content/uploads/2022/06/image_2022-06-07_202609039-1536x725.png

BSON data Type

https://f4n3x6c5.stackpathcdn.com/article/datatypes-in-mongodb/Images/image1.png

MacOS

Launch Terminal

• Intall MongoDB CLI using --> brew install mongodb-atlas
• Run --> atlas auth login
• Provide the auth-key for Atlas User authentication using the Atalas Cloud account
• Run --> atlas. (The response includes available commands and options for the Atlas CLI)

To view list of Atlas Cluster

• atlas cluster list

To view the connection String

• atlas clusters connectionStrings describe Cluster0

Installed Mongosh

1. Open .zshrc file nano $HOME/.zshrc
2. You will see the commented $PATH variable here
3. export PATH=$HOME/bin:/usr/local/bin:/Users/ebin/Documents/Softwares/mongoDB/bin:$PATH
4. Activate the change source $HOME/.zshrc

Use Mongosh to create Database & Collections

• show databases
• use forum
• db.createCollection('posts')
• show collections

Insert Documents

• create a JSON object for a document, say doc1={postId: NumberInt(3511),shared: false};, doc2={postId: NumberInt(3511),shared: false};
• db.posts.insertOne(doc1)
• db.posts.insertMany([doc1, doc2])

Find Documents

• db.getCollection('posts').find({})
• db.getCollection('posts').findOne({postId: 3015})
• db.getCollection('posts').find({"author.name": "Emily Watson"})
• db.getCollection('posts').find({tags: "programming"})

Query Operators

• $or

• $and

• $eq

• $ne

• $lt

• $gt

• $in

• $nin

• $regex

• db.getCollection('posts').find({comments: {$gt: 0}})

• db.getCollection('posts').find({$and: [{comments: {$lt: 5}}, {comments: {$gt: 0}}]})

• db.getCollection('posts').find({ tags: {$in: ["programming", "coding"]}})

Helper Methods

• sort() --> db.getCollection('posts').find({}).sort({comments: 1}). #here 1 means ascending sort & -1 means decending sort
• limit() --> db.getCollection('posts').find({}).limit(2)
• skip() --> db.getCollection('posts').find({}).skip(3)

Update Operators

• $set
• $unset
• $inc
• $rename
• $currentDate
• $addToSet

Update documents

• updateOne()

• updateMany()

• Args: , ,

• db.posts.updateOne({postId: 2618}, {$set: {shared: true}}) --> # here we are querying postId who's value is 2618 and setting shared=True

• db.posts.updateMany({tags: []}, {$unset: {tags: 1}})

• db.posts.updateMany({postId: 8451}, {$inc: {comments: 1}})

Delete Documents

• deleteOne({query})

• deleteMany({query})

• db.getCollection('posts').deleteOne({postId: 1111}

• db.getCollection('posts').deleteMany({title: {$exists: false}})

Aggregation Framework

Aggregation in MongoDB allows for the transforming of data and results in a more powerful fashion than from using the find() command. Through the use of multiple stages and expressions, you are able to build a "pipeline" of operations on your data to perform analytic operations.

Aggregating

• db.posts.aggregate([{$group: {_id: "$author.name"}}])

Indexes

• db.posts.getIndexes()