Features Included:

1. User Authentication: Secure login and registration.

2. Room Listings: Hosts can list their rooms with details such as location, amenities, and pricing.

3. Bookings: Users can book rooms for specific dates.

4. Reviews and Ratings: Users can review and rate rooms and hosts.

5. Messaging: Communication between hosts and guests.

6. Search Functionality: Users can search for available rooms based on location, dates, and amenities.

7. Transaction Processing: Handling room reservations and payments.

8. Dynamic Pricing of Rooms: Room prices can change based on demand, season, etc.

9. Multi-Currency Support: Room pricing can be in different currencies.

10. Inventory Management: Manage the availability of rooms based on bookings.

Entity/Table with Detailed Info about Every Value

1. Users Table:

   • user_id (Primary Key): Unique identifier for each user.

   • username: Username chosen by the user.

   • email: User's email address.

   • password_hash: Encrypted password.

   • created_at: Timestamp of user account creation.

2. Rooms Table:

   • room_id (Primary Key): Unique identifier for each room.

   • host_id (Foreign Key): User ID of the host.

   • location: Location of the room.

   • amenities: Amenities offered by the room.

   • base_price_per_night: Base price per night for the room in the default currency.

   • currency: Currency of the base price.

   • created_at: Timestamp of when the room was listed.

3. DynamicPricing Table:

   • pricing_id (Primary Key): Unique identifier for each pricing entry.

   • room_id (Foreign Key): Room ID.

   • start_date: Start date for the dynamic pricing.

   • end_date: End date for the dynamic pricing.

   • price_per_night: Dynamic price per night for the specified date range.

   • currency: Currency of the dynamic price.

4. Bookings Table:

   • booking_id (Primary Key): Unique identifier for each booking.

   • room_id (Foreign Key): Room ID of the booked room.

   • guest_id (Foreign Key): User ID of the guest.

   • check_in_date: Check-in date for the booking.

   • check_out_date: Check-out date for the booking.

   • total_price: Total price for the booking in the currency of the room.

   • currency: Currency of the total price.

   • created_at: Timestamp of when the booking was made.

5. Reviews Table:

   • review_id (Primary Key): Unique identifier for each review.

   • room_id (Foreign Key): Room ID being reviewed.

   • user_id (Foreign Key): User ID of the reviewer.

   • rating: Rating given by the user.

   • comment: Review comment.

   • created_at: Timestamp of when the review was created.

6. Messages Table:

   • message_id (Primary Key): Unique identifier for each message.

   • sender_id (Foreign Key): User ID of the sender.

   • receiver_id (Foreign Key): User ID of the receiver.

   • content: Message content.

   • created_at: Timestamp of when the message was sent.

7. Currencies Table:

   • currency_code (Primary Key): Currency code (e.g., USD, EUR).

   • exchange_rate_to_base: Exchange rate to convert to the base currency.

Details about 1-NF, 2-NF, etc., of Each Table in Tabular Format with Explanation Details

All Queries Required for Applications

1. Retrieve available rooms for a given location and date range:

    SELECT r.*
    FROM Rooms r
    LEFT JOIN Bookings b ON r.room_id = b.room_id
       AND :check_in_date < b.check_out_date
       AND :check_out_date > b.check_in_date
    WHERE r.location = :location
    AND b.booking_id IS NULL;
   

2. Retrieve dynamic pricing for a room and date range:

    SELECT dp.*
    FROM DynamicPricing dp
    WHERE dp.room_id = :room_id
    AND dp.start_date <= :check_in_date
    AND dp.end_date >= :check_out_date;
   

3. Retrieve bookings for a specific user:

    SELECT * FROM Bookings
    WHERE guest_id = :user_id;
   

4. Retrieve reviews for a specific room:

    SELECT * FROM Reviews
    WHERE room_id = :room_id;
   

5. Retrieve messages between two users:

    SELECT * FROM Messages
    WHERE (sender_id = :user_id1 AND receiver_id = :user_id2)
       OR (sender_id = :user_id2 AND receiver_id = :user_id1);
   

6. Convert room pricing to a different currency:

    SELECT r.*, r.price_per_night * c.exchange_rate_to_base AS price_in_target_currency
    FROM Rooms r
    JOIN Currencies c ON r.currency = c.currency_code
    WHERE r.room_id = :room_id
    AND c.currency_code = :target_currency;
   

All Required Indexing or Background Jobs

1. Indexing:

   • Index on location in the Rooms table for efficient location-based searches:

       CREATE INDEX idx_location ON Rooms (location);
     

   • Index on room_id in the Bookings table for optimizing room availability queries:

       CREATE INDEX idx_room_id ON Bookings (room_id);
     

   • Index on check_in_date and check_out_date in the Bookings table for optimizing date range queries:

       CREATE INDEX idx_booking_dates ON Bookings (check_in_date, check_out_date);
     

   • Index on user_id in the Reviews table for fast review retrieval:

       CREATE INDEX idx_user_id ON Reviews (user_id);
     

   • Index on sender_id and receiver_id in the Messages table for efficient message retrieval:

       CREATE INDEX idx_sender_receiver ON Messages (sender_id, receiver_id);
     

   • Index on room_id, start_date, and end_date in the DynamicPricing table for efficient dynamic pricing queries:

       CREATE INDEX idx_dynamic_pricing ON DynamicPricing (room_id, start_date, end_date);
     

2. Background Jobs:

   • Regularly update room availability based on bookings and check-out dates.

   • Periodic maintenance tasks to analyze and optimize query performance.

   • Background tasks for handling transactions and updating user-related statistics.

   • Regularly update currency exchange rates in the Currencies table.

Query Plan Optimization

1. Regularly Review and Optimize:

   • Periodically review and optimize the execution plans of the search queries using tools like EXPLAIN in MySQL.

2. Database Profiling:

   • Use a database profiler to identify slow-performing queries and optimize accordingly.

3. Caching:

   • Implement caching for frequently accessed data to reduce database load.

4. Denormalization:

   • Consider denormalizing data for frequently accessed information, such as precomputed availability for popular locations.

5. Partitioning:

   • Partition large tables based on criteria such as location or date to improve query performance.

6. Load Balancing:

   • Distribute the database load using load balancing techniques to handle high traffic efficiently.

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