sample questions 1

 

Set1.

      Create a new database in MongoDB using the use command. Insert a document with your name, email address, and phone number into a new collection called contacts.

      Query the contacts collection and retrieve all documents using the find method.

      Query the contacts collection and retrieve only the name field of all documents using the find method and projection.

      Insert two new documents into the contacts collection. One should have the name "John Smith" and the other should have the name "Jane Doe".

Answer:



use myDatabase

o/p: switched to db myDatabase


db.contacts.insertOne({

  name: "John Doe",

  email: "johndoe@example.com",

  phone: "123-456-7890"

}) 

o/p:

{ "acknowledged" : true, "insertedId" : ObjectId("...") }

db.contacts.find()

op:

{ "_id" : ObjectId("..."), "name" : "John Doe", "email" : "johndoe@example.com", "phone" : "123-456-7890" }


 

db.contacts.find({}, {name: 1})

op:

{ "_id" : ObjectId("..."), "name" : "John Doe" }

 

db.contacts.insertMany([

  {

    name: "John Smith",

    email: "johnsmith@example.com",

    phone: "987-654-3210"

  },

  {

    name: "Jane Doe",

    email: "janedoe@example.com",

    phone: "555-555-5555"

  }

])

 o/p:

{ "acknowledged" : true, "insertedIds" : [ ObjectId("..."), ObjectId("...") ] }




Set2.

 

• Create a new database in MongoDB using the use command. Insert a document with your name, email address, and phone number into a new collection called contacts.

• Insert two new documents into the contacts collection. One should have the name "John Smith" and the other should have the name "Jane Doe".

• Update the document for "John Smith" to include an additional field called address with the value "123 Main St".

• Update the document for "John Doe" to include an additional field called address with the value "125 Second St".

 

Solution

use myDatabase

db.contacts.insertOne({

  name: "John Doe",

  email: "johndoe@example.com",

  phone: "123-456-7890"

})

 O/p;

switched to db myNewDatabase

{

  "acknowledged" : true,

  "insertedId" : ObjectId("...")

}


db.contacts.insertMany([

  {

    name: "John Smith",

    email: "johnsmith@example.com",

    phone: "987-654-3210"

  },

  {

    name: "Jane Doe",

    email: "janedoe@example.com",

    phone: "555-555-5555"

  }

])

o/p:

{

  "acknowledged" : true,

  "insertedIds" : [

    ObjectId("..."),

    ObjectId("...")

  ]

}


 

db.contacts.updateOne(

  {name: "John Smith"},

  {$set: {address: "123 Main St"}}

)

o/p: 

{

  "acknowledged" : true,

  "matchedCount" : 1,

  "modifiedCount" : 1

}


db.contacts.updateOne(

  {name: "John Doe"},

  {$set: {address: "125 Second St"}}

)

 o/p:

{

  "acknowledged" : true,

  "matchedCount" : 1,

  "modifiedCount" : 1

}


Set3.

 

.  insert 5 documents in contacts collection

 

{

  "name": "John Smith",

  "email": "john.smith@example.com",

  "phone": "+1 (555) 123-4567",

  "address": {

    "street": "123 Main St",

    "city": "Anytown",

    "state": "CA",

    "zip": "12345",

    "country": "USA"

  }

},

{

  "name": "Jane Doe",

  "email": "jane.doe@example.com",

  "phone": "+1 (555) 987-6543",

  "address": {

    "street": "456 Oak St",

    "city": "Sometown",

    "state": "NY",

    "zip": "54321",

    "country": "USA"

  }

},

{

  "name": "Bob Johnson",

  "email": "bob.johnson@example.com",

  "phone": "+1 (555) 555-5555",

  "address": {

    "street": "789 Elm St",

    "city": "Anyville",

    "state": "TX",

    "zip": "67890",

    "country": "USA"

  }

},

{

  "name": "Emma Williams",

  "email": "emma.williams@example.com",

  "phone": "+44 123 456 7890",

  "address": {

    "street": "10 Downing St",

    "city": "London",

    "state": "",

    "zip": "SW1A 2AA",

    "country": "UK"

  }

},

{

  "name": "Hiroshi Nakamura",

  "email": "hiroshi.nakamura@example.com",

  "phone": "+81 3-1234-5678",

  "address": {

    "street": "2-1-2 Otemachi",

    "city": "Chiyoda-ku",

    "state": "Tokyo",

    "zip": "100-0004",

    "country": "Japan"

  }

}

Query the contacts collection and retrieve all documents sorted by name in ascending order.

 

db.contacts.find({}).sort({name:1})

 o/p;

{ "_id" : ObjectId("609db534e5d5a5c5d5b5bf5c"), "name" : "Bob Johnson", "email" : "bob.johnson@example.com", "phone" : "+1 (555) 555-5555", "address" : { "street" : "789 Elm St", "city" : "Anyville", "state" : "TX", "zip" : "67890", "country" : "USA" } }

{ "_id" : ObjectId("609db534e5d5a5c5d5b5bf5b"), "name" : "Emma Williams", "email" : "emma.williams@example.com", "phone" : "+44 123 456 7890", "address" : { "street" : "10 Downing St", "city" : "London", "state" : "", "zip" : "SW1A 2AA", "country" : "UK" } }

{ "_id" : ObjectId("609db534e5d5a5c5d5b5bf5d"), "name" : "Hiroshi Nakamura", "email" : "hiroshi.nakamura@example.com", "phone" : "+81 3-1234-5678", "address" : { "street" : "2-1-2 Otemachi", "city" : "Chiyoda-ku", "state" : "Tokyo", "zip" : "100-0004", "country" : "Japan" } }

{ "_id" : ObjectId("609db534e5d5a5c5d5b5bf5a"), "name" : "Jane Doe", "email" : "jane.doe@example.com", "phone" : "+1 (555) 987-6543", "address" : { "street" : "456 Oak St", "city" : "Sometown", "state" : "NY", "zip" : "54321", "country" : "USA" } }

{ "_id" : ObjectId("609db534e5d5a5c5d5b5bf59"), "name" : "John Doe", "email" : "johndoe@example.com", "phone" : "123-456-7890", "address" : "125 Second St" }

{ "_id" : ObjectId("609db534e5d5a5c5d5b5bf58"), "name" : "John Smith", "email" : "john.smith@example.com", "phone" : "+1 (555) 123-4567", "address" : { "street" : "123 Main St", "city" : "Anytown", "state" : "CA", "zip" : "12345", "country" : "USA" } }


 

Query the contacts collection and retrieve all documents sorted by name in descending order.

 

db.contacts.find({}).sort({name:-1})

o/p:


{ "_id" : ObjectId("614c791784e6ea9b89c90b8a"), "name" : "John Smith", "email" : "john.smith@example.com", "phone" : "+1 (555) 123-4567", "address" : { "street" : "123 Main St", "city" : "Anytown", "state" : "CA", "zip" : "12345", "country" : "USA" } } { "_id" : ObjectId("614c791784e6ea9b89c90b8b"), "name" : "Jane Doe", "email" : "jane.doe@example.com", "phone" : "+1 (555) 987-6543", "address" : { "street" : "456 Oak St", "city" : "Sometown", "state" : "NY", "zip" : "54321", "country" : "USA" } } { "_id" : ObjectId("614c791784e6ea9b89c90b8d"), "name" : "Hiroshi Nakamura", "email" : "hiroshi.nakamura@example.com", "phone" : "+81 3-1234-5678", "address" : { "street" : "2-1-2 Otemachi", "city" : "Chiyoda-ku", "state" : "Tokyo", "zip" : "100-0004", "country" : "Japan" } } { "_id" : ObjectId("614c791784e6ea9b89c90b8c"), "name" : "Emma Williams", "email" : "emma.williams@example.com", "phone" : "+44 123 456 7890", "address" : { "street" : "10 Downing St", "city" : "London", "state" : "", "zip" : "SW1A 2AA", "country" : "UK" } } 

{ "_id" : ObjectId("614c791784e6ea9b89c90b89"), "name" : "Bob Johnson", "email" : "bob.johnson@example.com", "phone" : "+1 (555) 555-5555", "address" : { "street" : "789 Elm St", "city" : "Anyville", "state" : "TX", "zip" : "67890", "country" : "USA" } } 

 

4.

 

Create a new database called blog and a collection called posts.

Insert a new document into the posts collection with the fields title, content, author, and created_at.

Query the posts collection and retrieve all documents.

Query the posts collection and retrieve only the title and created_at fields of all documents.

Update the document for a specific post by its title field to change its content.

 

Solution.

 

> use blog

switched to db blog

> db.createCollection("posts")

{ "ok" : 1 }

> db.posts.insertOne({

...   title: "My First Blog Post",

...   content: "Hello, world! This is my first blog post.",

...   author: "Jane Doe",

...   created_at: new Date()

... })

{

  "acknowledged" : true,

  "insertedId" : ObjectId("...") // ObjectId will be a unique ID generated by MongoDB

}

> db.posts.find()

{ "_id" : ObjectId("..."), "title" : "My First Blog Post", "content" : "Hello, world! This is my first blog post.", "author" : "Jane Doe", "created_at" : ISODate("2023-04-17T20:52:18.854Z") }

> db.posts.find({}, {title: 1, created_at: 1})

{ "_id" : ObjectId("..."), "title" : "My First Blog Post", "created_at" : ISODate("2023-04-17T20:52:18.854Z") }

> db.posts.updateOne(

...   {title: "My First Blog Post"},

...   {$set: {content: "Updated content for my first blog post."}}

... )

{ "acknowledged" : true, "matchedCount" : 1, "modifiedCount" : 1 }


 

5.

 

1. Create a new database called ecommerce and a collection called products.

2. Insert 5 new documents into the products collection, each with the fields name, description, price, quantity, and created_at.

3. Query the products collection and retrieve all documents.

4. Query the products collection and retrieve only the name and price fields of all documents.

5. Update the document for a specific product by its name field to change its quantity

 

Solution

 > use ecommerce

switched to db ecommerce

> db.createCollection("products")

{ "ok" : 1 }

> db.products.insertMany([

...   {

...     name: "Product A",

...     description: "This is product A",

...     price: 10.99,

...     quantity: 50,

...     created_at: new Date()

...   },

...   {

...     name: "Product B",

...     description: "This is product B",

...     price: 19.99,

...     quantity: 20,

...     created_at: new Date()

...   },

...   {

...     name: "Product C",

...     description: "This is product C",

...     price: 15.99,

...     quantity: 30,

...     created_at: new Date()

...   },

...   {

...     name: "Product D",

...     description: "This is product D",

...     price: 29.99,

...     quantity: 10,

...     created_at: new Date()

...   },

...   {

...     name: "Product E",

...     description: "This is product E",

...     price: 9.99,

...     quantity: 100,

...     created_at: new Date()

...   }

... ])

{

        "acknowledged" : true,

        "insertedIds" : [

                ObjectId("61717a6f20b6c1c7d50b0e01"),

                ObjectId("61717a6f20b6c1c7d50b0e02"),

                ObjectId("61717a6f20b6c1c7d50b0e03"),

                ObjectId("61717a6f20b6c1c7d50b0e04"),

                ObjectId("61717a6f20b6c1c7d50b0e05")

        ]

}

> db.products.find()

{ "_id" : ObjectId("61717a6f20b6c1c7d50b0e01"), "name" : "Product A", "description" : "This is product A", "price" : 10.99, "quantity" : 50, "created_at" : ISODate("2023-04-17T10:25:19.973Z") }

{ "_id" : ObjectId("61717a6f20b6c1c7d50b0e02"), "name" : "Product B", "description" : "This is product B", "price" : 19.99, "quantity" : 20, "created_at" : ISODate("2023-04-17T10:25:19.973Z") }

{ "_id" : ObjectId("61717a6f20b6c1c7d50b0e03"), "name" : "Product C", "description" : "This is product C", "price" : 15.99, "quantity" : 30, "created_at" : ISODate("2023-04-17T10:25:19.973Z") }

{ "_id" : ObjectId("61717a6f20b6c1c7d50b0e04"), "name" : "Product D", "description" : "This is product D", "price" : 29.99, "quantity" : 10, "created_at" : ISODate("2023-04-17T10:25:19.973Z") }

db.products.find({}, {name: 1, price: 1})

o/p;


{ "_id" : ObjectId("..."), "name" : "Product A", "price" : 10.99 }
{ "_id" : ObjectId("..."), "name" : "Product B", "price" : 19.99 }
{ "_id" : ObjectId("..."), "name" : "Product C", "price" : 15.99 }
{ "_id" : ObjectId("..."), "name" : "Product D", "price" : 29.99 }
{ "_id" : ObjectId("..."), "name" : "Product E", "price" : 9.99 }


db.products.updateOne( {name: "Product A"}, {$set: {quantity: 100}}

o/p:

{ "acknowledged": true, "matchedCount": 1, "modifiedCount": 1 }

6.

 

1. Create a new database called music and a collection called indian_artists.

2. Insert 3 new documents into the artists collection, each with the fields name, genre, albums, and members.

3. Query the artists collection and retrieve all documents.

4. Query the artists collection and retrieve only the name and genre fields of all documents. 5. Update the document for a specific artist by its name field to change its genre.

 

 use music


db.createCollection("indian_artists")


db.indian_artists.insertMany([
  {
    name: "A. R. Rahman",
    genre: "Film Score",
    albums: ["Roja", "Slumdog Millionaire", "Dil Se"],
    members: ["A. R. Rahman"]
  },
  {
    name: "Lata Mangeshkar",
    genre: "Classical",
    albums: ["Lata Mangeshkar: The Golden Collection", "Melodies Of Lata", "Lata Geetmala"],
    members: ["Lata Mangeshkar"]
  },
  {
    name: "Pandit Ravi Shankar",
    genre: "Indian Classical",
    albums: ["The Living Room Sessions Part 1", "West Meets East"],
    members: ["Pandit Ravi Shankar"]
  }
])
db.indian_artists.find()
o/p:
{ "_id" : ObjectId("..."), "name" : "A. R. Rahman", "genre" : "Film Score", "albums" : [ "Roja", "Slumdog Millionaire", "Dil Se" ], "members" : [ "A. R. Rahman" ] }
{ "_id" : ObjectId("..."), "name" : "Lata Mangeshkar", "genre" : "Classical", "albums" : [ "Lata Mangeshkar: The Golden Collection", "Melodies Of Lata", "Lata Geetmala" ], "members" : [ "Lata Mangeshkar" ] }
{ "_id" : ObjectId("..."), "name" : "Pandit Ravi Shankar", "genre" : "Indian Classical", "albums" : [ "The Living Room Sessions Part 1", "West Meets East" ], "members" : [ "Pandit Ravi Shankar" ] }

db.indian_artists.updateOne(
  {name: "A. R. Rahman"},
  {$set: {genre: "World Music"}}
)

o/p:
{ "acknowledged" : true, "matchedCount" : 1, "modifiedCount" : 1 }


7.

 

Write a Python program in Jupyter to create following documents in MongoDB

 

DB: Fruits

Collection: New

Documents:

                { name: banana, color:yellow, no:5, price:10}

                { name: grape, color:dark blue, no:100, price:2}

 

DB: Countries

Collection: New1

Documents:

                { name: India, capital:delhi, no_states:28 }

                { name: USA, capital:Washington DC, no_states:50}

 

 

Solution:

 

pip install pymongo

 

import pymongo

 

# Connect to MongoDB server

client = pymongo.MongoClient("mongodb://localhost:27017/")

 

# Create the Fruits database and New collection

db = client["Fruits"]

collection = db["New"]

 

# Define the documents to insert

document1 = {

    "name": "banana",

    "color": "yellow",

    "no": 5,

    "price": 10

}

 

document2 = {

    "name": "grape",

    "color": "dark blue",

    "no": 100,

    "price": 2

}

 

# Insert the documents into the collection

collection.insert_many([document1, document2])

 

 

 

# Create the Countries database and New1 collection

db = client["Countries"]

collection = db["New1"]

 

# Define the documents to insert

document1 = {

    "name": "India",

    "capital": "delhi",

    "no_states": 28

}

 

document2 = {

    "name": "USA",

    "capital": "Washington DC",

    "no_states": 50

}

 

# Insert the documents into the collection

collection.insert_many([document1, document2])

  to test open Mongodb compass and check data

8. Write a Python program in Jupyter to create following documents in MongoDB

 

DB: Sports

Collection: New1

Documents:

                { name: cricket, level:international, no:11, players:{batsmen:[ram,lokesh,veeru,bodhan,rajesh],bowlers:[venkat,kapil,gowtham],Allrounders:[jaiswal,raju] WK:[kethan]}}

 

                { name: hockey, level:national, no:10, players:{GK:1,Offense:4,defense:5}

 

 

Solution:

 

pip install pymongo

import pymongo

 

# Connect to MongoDB server

client = pymongo.MongoClient("mongodb://localhost:27017/")

 

# Create the Sports database and New1 collection

db = client["Sports"]

collection = db["New1"]

 

# Define the documents to insert

document1 = {

    "name": "cricket",

    "level": "international",

    "no": 11,

    "players": {

        "batsmen": ["ram", "lokesh", "veeru", "bodhan", "rajesh"],

        "bowlers": ["venkat", "kapil", "gowtham"],

        "Allrounders": ["jaiswal", "raju"],

        "WK": ["kethan"]

    }

}

 

document2 = {

    "name": "hockey",

    "level": "national",

    "no": 10,

    "players": {

        "GK": 1,

        "Offense": 4,

        "defense": 5

    }

}

 

# Insert the documents into the collection

collection.insert_many([document1, document2])

 to test open Mongodb compass and check data

 

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