MongoDB Part1

 

Course Objectives: This Course will enable students to

 

1.

Master the leading document-oriented NoSQL database, MongoDB Architecture, CRUD, Schema

2.

Design, Data Modelling and Indexing using real-life case studies

 

3.

Learn how to design Schema using Advanced Queries Course Outcomes

 

 

Course Outcomes: At the end of the course the student will be able to:

 

1.

Install, configure and setup the drivers to use MongoDB with your programming language of choice

 

K6

2.

Gain an in-depth understanding of main features of MongoDB and their use cases

 

K2

3.

Retrieve data in the database using advanced querying

 

K2

4.

choice to build new types of applications for mobile, cloud, e-commerce and and social technologies Perform Experiments related to the following concepts

 

K3

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1.     Introduction to MongoDB and its Architecture

 

MongoDB is a popular and widely used document-oriented NoSQL database. It was developed by MongoDB Inc. and was first released in 2009. MongoDB provides a flexible and scalable approach to storing and retrieving data, making it suitable for a wide range of applications.

 

Here are some key concepts and features of MongoDB:

 

Document-Oriented: MongoDB stores data in flexible, JSON-like documents called BSON (Binary JSON). A document can have a varying structure, allowing for a more dynamic and schema-less data model compared to traditional relational databases.

 

Collections and Documents: In MongoDB, documents are organized into collections, which are analogous to tables in a relational database. Collections can contain multiple documents, each with its own set of fields and values.

 

Schema Flexibility: MongoDB allows you to change the structure of documents within a collection without affecting other documents. This flexibility is beneficial in scenarios where data evolves over time or when dealing with semi-structured or unstructured data.

 

Query Language: MongoDB provides a rich query language that supports various operations, such as filtering, sorting, aggregation, and joining. The query language is expressive and allows for complex queries to retrieve and manipulate data.

 

Scalability and High Availability: MongoDB is designed to scale horizontally by distributing data across multiple servers or clusters. It offers built-in support for sharding, which allows for distributing data across multiple machines, and replica sets, which provide high availability and data redundancy.

 

Indexing: MongoDB supports indexing on fields within a collection, enabling efficient querying and retrieval of data. Indexes can be created on single fields or combinations of fields, improving query performance.

 

Rich Functionality: MongoDB offers a range of features, including support for geospatial queries to work with location-based data, text search capabilities, and the ability to execute server-side JavaScript through its query language.

 

Community and Ecosystem: MongoDB has a large and active community, which contributes to its ecosystem. It offers official drivers for various programming languages and frameworks, making it easy to integrate MongoDB into different application stacks.

 

MongoDB is widely used in various domains, such as web applications, content management systems, real-time analytics, Internet of Things (IoT), and more. Its flexibility, scalability, and ease of use have made it a popular choice for developers and organizations seeking a modern database solution.

 


 

Fig.1. MongoDB Basic Data Storage

 

ARCHITECTURE:

 

The architecture of MongoDB is designed to provide scalability, high availability, and flexibility in handling data. Let's explore the key components and their interactions within a MongoDB deployment:

 

MongoDB Server: At the core of MongoDB is the server process, which manages data storage, retrieval, and processing. The server interacts with clients, executes queries and commands, and performs data manipulations. It manages memory, storage, and concurrency control to ensure efficient operations.

 

Sharding: Sharding is the process of distributing data across multiple machines or clusters called shards. It allows MongoDB to horizontally scale by partitioning data and workload across shards based on a chosen shard key. Each shard is an independent replica set or cluster that stores a portion of the data.

 

Replica Sets: A replica set is a group of MongoDB servers that maintain the same data set, providing redundancy and high availability. Within a replica set, there is one primary node that handles all write operations and multiple secondary nodes that replicate data from the primary. If the primary node fails, one of the secondaries automatically becomes the new primary.

 

Documents and Collections: Data in MongoDB is organized into documents, which are JSON-like data structures. Documents are grouped into collections, which are analogous to tables in a relational database. Collections can have indexes defined on one or more fields to optimize query performance.

 

Indexes: MongoDB supports indexing on fields within collections. Indexes are used to improve query performance by allowing faster data retrieval based on specific fields. MongoDB offers various index types, including single-field indexes, compound indexes, text indexes for full-text search, and geospatial indexes for working with location-based data.

 

Query Router: In a sharded cluster, the query router, also known as the mongos process, acts as the interface between client applications and the underlying shards. The query router receives queries from clients, determines which shards contain the relevant data based on the shard key, and forwards the queries to the appropriate shards.

 

Config Servers: The config servers store metadata and configuration information about the sharded cluster, such as the location of data ranges and shard mappings. The query router uses this information to route queries efficiently to the appropriate shards. Config servers are typically deployed as a replica set for redundancy and high availability.

 

Client Applications and Drivers: Client applications interact with MongoDB using drivers or libraries specific to their programming language. MongoDB provides official drivers for various languages, allowing developers to connect, query, and manipulate data from their applications.

 

These components work together to provide a distributed, scalable, and fault-tolerant database system. MongoDB's architecture allows for horizontal scaling by adding more shards, provides high availability through replica sets, and supports flexible data modeling with its document-oriented approach.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2.     Installations of MongoDB Server, Compass and Shell

 

 

The general steps for installing MongoDB Server, Compass and MongoShell:

 

1. MongoDB Server Installation:

 

Step1: Visit the MongoDB Download Center (https://www.mongodb.com/try/download/community) in your web browser.

Step 2: Select the appropriate version of MongoDB Server for your operating system. Choose the Community Server edition, which is free.

Step 3: Choose the version and operating system that matches your requirements and click on the download button.

Step 4: Once the download is complete, open the installer file.

Step 5: Follow the installation wizard and accept the license agreement.

Step 6: Choose the components you want to install. Make sure to select the MongoDB Server option.

Step 7: Choose the installation directory or keep the default location.

Step 8: Select the options for MongoDB as per your preferences, such as enabling MongoDB as a service or adding MongoDB to the system's PATH.

Step 9: Click on the "Install" button to start the installation process.

Step 10: Once the installation is complete, you can proceed to configure and start MongoDB Server.

 

2. MongoDB Compass Installation:

 

Step 1: Visit the MongoDB Download Center (https://www.mongodb.com/try/download/compass) in your web browser.

Step 2: Select the appropriate version of MongoDB Compass for your operating system. Choose the Community edition, which is free.

Step 3: Choose the version and operating system that matches your requirements and click on the download button.

Step 4: Once the download is complete, open the installer file.

Step 5: Follow the installation wizard and accept the license agreement.

Step 6: Choose the components you want to install. Make sure to select MongoDB Compass.

Step 7: Choose the installation directory or keep the default location.

Step 8: Select the options for MongoDB Compass as per your preferences.

Step 9: Click on the "Install" button to start the installation process.

Step 10: Once the installation is complete, you can launch MongoDB Compass.

 

 

3. MongoShell:

 

To set up the MongoDB Shell, you can follow these steps:

Step 1: Visit the MongoDB Download Center (https://www.mongodb.com/try/download/shell) in your web browser.

Step 2: Select the appropriate version of MongoDB Shell for your operating system. Choose the Community edition, which is free.

Step 3: Choose the version and operating system that matches your requirements and click on the download button.

Step 4: Once the download is complete, extract the downloaded contents

Step5: Launch mongosh application, accept default connect string (press enter) and run commands

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3.     CRUD Operations in MONGODBExercise–I: Student Database

 

AIM: To perform CRUD operations in Student Database

 

THEORY:

 

CRUD in MongoDB refers to the basic operations that can be performed on data stored in a MongoDB database. CRUD stands for Create, Read, Update, and Delete, representing the four fundamental actions that can be applied to database records or documents.

 

Create (C): This operation is used to insert new documents into a MongoDB collection. To create a new document, you typically construct a JSON-like object with the desired data fields and values, and then insert it into the collection using the insertOne() or insertMany() method.

 

Read (R): The read operation is used to retrieve data from a MongoDB collection. MongoDB provides several methods to query documents, including find(), findOne(), and aggregate(). You can use query criteria to filter the results and specify the fields to be returned.

 

Update (U): The update operation allows you to modify existing documents in a collection. MongoDB provides methods like updateOne() and updateMany() to update documents. You specify a filter to identify the documents to be updated and the modifications to be applied. Here's an example:

 

Delete (D): The delete operation is used to remove documents from a collection. MongoDB provides methods such as deleteOne() and deleteMany() to delete documents that match a specified filter

 

 

PROGRAM:

 

Create database, Create collection, insert data, find, find one, sort, limit, skip, distinct, projection.

 

Create a student database with the fields: (SRN, Sname, Degree, Sem, CGPA)>

 

>use student1

 

Switched to db student1

 

>db.stud1col1.insert({srn:110,sname:"Rahul",degree:"BCA",sem:6,CGPA:7.9})

 

OR

 

> doc1=({srn:110,sname:"Rahul",degree:"BCA",sem:6,CGPA:7.9})

>db.studcol1.insert (doc1)

 

Note:insert 10 such documents.

 

Questions:1.display all the documents

 

>db.studcol1.find()

 

2.Display all the students in BCA

 

>db.studcol1.find({degree:"BCA"})

 

3.Display all the students in ascending order

 

>db. studcol1.find().sort({sname:1})

 

4.Display first 5 students

 

>db. studcol1.find().limit(5)

 

5.display students 5,6,7

 

>db. studcol1.find().skip(4).limit(3)

 

6.list the degree of student "Rahul"

 

>db. studcol1.find({sname : "Rahul"},{degree:1})

 

7.Display students details of 5,6,7 in descending order of percentage

 

>db. studcol1.find().sort({CGPA:-1}).skip(4).limit(3)

 

8.Display the number of students in BCA

 

>db. studcol1.find({degree:"BCA"}).count()

 

 

 

 

 

 

 

 

 

 

 

 

 

4.     CRUD Operations in MONGODBExercise–II: Employee Database

 

AIM: To perform CRUD Operations in Employee database

 

PROGRAM:

 

Update modifiers ($set, $unset, $inc, $push, $pushAll, $pull, $pullAll, $addToSet)

 

Create an employee database with the fields: {eid, ename, dept, desig, salary, yoj, address{dno,street, locality, city}}

 

> use empdb

 

switched to db empdb

 

> doc1 = {eid:001, ename:"Rahul", dept:"production", desig:"developer", salary:30000, yoj:2015,address:{dno:397, street:2, locality:"rmnagar", city:"bangalore"} }

 

>db.emp.insert(doc1)

 

WriteResult({ "nInserted" : 1 })

 

Note:insert 10 documents.

 

Questions:1.Display all the employees with salary in range (50000, 75000)

 

>db.emp09.find({salary:{$gt:50000, $lt:75000}})

 

2.Display all the employees with desig developer>db.emp09.find({desig:"developer"}

 

3.Display the Salary of “Rahul”

 

>db.emp09.find({ename:"Rahul"},{salary:1})

 

4.Display the city of employee

 

>db.emp09.find({ename:"Rahul"},{"address.city":1})

 

5.Update the salary of developers by 5000

 

>db.emp09.update({desig:"developer"},{$inc:{"salary":5000}})

 

6.Add field age to employee Rahul

 

>db.emp09.update({ename:"Rahul"},{$set:{age:"22"}})

 

7.Remove YOJ from “Rahul”

 

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