sample questions
1.
- 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".
2.
- 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".
3. 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.
- Query the contacts collection and retrieve all documents sorted
by name in descending order.
4. Set 1
1. Create a new
database called blog and a collection
called posts.
2. Insert a new
document into the posts collection with
the fields title, content, author, and created_at.
3. Query the posts collection and retrieve all
documents.
4. Query the posts collection and retrieve only the title and created_at fields of all
documents.
5. Update the document
for a specific post by its title field to change its content.
Set 2
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.
Set 3
1. Create a new database
called music and a collection
called 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.
Set 4
1. Create a new
database called recipes and a collection
called dishes.
2. Insert 2 new
documents into the dishes collection, each
with the fields name, description, ingredients, and instructions.
3. Query the dishes collection and
retrieve all documents.
4. Query the dishes collection and
retrieve only the name and description fields of all
documents.
5. Update the document
for a specific dish by its name field to change its description.
Set 5
1. Create a new
database called movies and a collection
called actors.
2. Insert 4 new
documents into the actors collection, each
with the fields name, birthdate, nationality, and movies.
3. Query the actors collection and
retrieve all documents.
4. Query the actors collection and
retrieve only the name and nationality fields of all
documents.
5. Update the document
for a specific actor by its name field to change its birthdate.
Set 6
1. Create a new
database called store and a collection
called customers.
2. Insert 3 new
documents into the customers collection, each
with the fields name, email, phone, and address.
3. Query the customers collection and
retrieve all documents.
4. Query the customers collection and
retrieve only the name and email fields of all documents.
5. Update the document
for a specific customer by its email field to change its phone.
1. Create an index on
the name field of a
collection called students.
2. Query the students collection and
retrieve all documents sorted by the name field in ascending order.
3. Query the students collection and
retrieve only the documents where the name field contains the word
"John".
4. Create a compound
index on the name and age fields of the students collection.
5. Query the students collection and
retrieve only the documents where the name field contains the word
"John" and the age field is greater than or equal to
18.
Set 2
1. Create an index on
the title field of a
collection called books.
2. Query the books collection and retrieve all
documents sorted by the title field in descending order.
3. Query the books collection and retrieve only the
documents where the title field contains the
word "MongoDB".
4. Create a text index
on the description field of the books collection.
5. Query the books collection and retrieve only the
documents where the description field contains the
phrase "NoSQL database".
Set 3
1. Create an index on
the name field of a
collection called employees.
2. Query the employees collection and
retrieve all documents sorted by the name field in ascending order.
3. Query the employees collection and
retrieve only the documents where the name field contains the word
"Smith".
4. Create a hashed
index on the id field of the employees collection.
5. Query the employees collection and
retrieve only the documents where the id field equals a specific value.
Set 4
1. Create an index on
the date field of a
collection called orders.
2. Query the orders collection and
retrieve all documents sorted by the date field in descending order.
3. Query the orders collection and
retrieve only the documents where the date field is between two specific dates.
4. Create a compound
index on the customer_id and product_id fields of the orders collection.
5. Query the orders collection and
retrieve only the documents where the customer_id field equals a specific value and
the product_id field is not null.
Set 1
1. Use the $match stage to retrieve
only the documents where the age field is greater than or equal to
18.
2. Use the $group stage to group the
documents by the gender field and
calculate the average age for each group.
3. Use the $project stage to only
retrieve the name and age fields of the documents.
4. Use the $sort stage to sort the documents by the age field in descending order.
5. Use the $limit stage to retrieve
only the top 5 documents.
Set 2
1. Use the $match stage to retrieve
only the documents where the status field equals "active".
2. Use the $group stage to group the
documents by the category field and count
the number of documents in each group.
3. Use the $project stage to only
retrieve the category and price fields of the documents.
4. Use the $sort stage to sort the documents by the price field in ascending order.
5. Use the $limit stage to retrieve
only the top 10 documents.
Set 3
1. Use the $match stage to retrieve
only the documents where the type field equals "book".
2. Use the $group stage to group the
documents by the author field and
calculate the total price for each group.
3. Use the $project stage to only
retrieve the author and price fields of the documents.
4. Use the $sort stage to sort the documents by the price field in descending order.
5. Use the $limit stage to retrieve
only the top 3 documents.
Set 4
1. Use the $match stage to retrieve
only the documents where the date field is between two specific dates.
2. Use the $group stage to group the
documents by the product field and
calculate the total quantity for each group.
3. Use the $project stage to only
retrieve the product and quantity fields of the
documents.
4. Use the $sort stage to sort the documents by the quantity field in
descending order.
5. Use the $limit stage to retrieve
only the top 5 documents.
1. 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}
2. 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}
1. Write a Python program in Jupyter to
create following documents in MongoDB
DB: Sports
Collection: New
Documents:
{ name: cricket,
level:international, no:11}
{ name: hockey,
level:national, no:10}
DB: Countries
Collection: New1
Documents:
{ name: India,
capital:delhi, no_states:28 }
{ name: USA,
capital:Washington DC, no_states:50}
2. 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}
1. Write a Python program in Jupyter to
create following documents in MongoDB
DB: Sports
Collection: New
Documents:
{ name: cricket,
level:international, no:11}
{ name: hockey,
level:national, no:10}
DB: students
Collection: col1
Documents:
{ name: sudheer, degree:BTech,
sem:6, subjects:[s1,s2,s3] }
{ name: Rakesh, degree:BTech,
sem:5, subjects:[s1,s2] }
2. Write a Python program in Jupyter to
create following documents in MongoDB
DB: Sports
Collection: New
Documents:
{ name: cricket,
level:international, no:11, players:{batsmen:5,bowlers:3,Allrounders:2, WK:1}
{ name: hockey,
level:national, no:10, players:{GK:1,Offense:4,defense:5}
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