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Movie Sales Analysis Application

This application is designed for a movie research company to analyze movie sales data. It provides functionalities to:

• Seed the database with large datasets (e.g., 1 million sales records).
• Identify the theater with the highest sales on a specific date via a console command.
• Display sales data and charts through a web UI.
• Run feature tests to ensure application correctness.

Database Schema and Data Explanation

Database Schema Overview

The application uses a MySQL database with the following main tables:

1. theaters columns:

• id (Primary Key)
• name (String)
• rating (Unsigned tiny integer)
• location (String)
• Timestamps (created_at, updated_at)

2. movies Columns:

• id (Primary Key)
• title (String)
• genre (String)
• rating (Unsigned tiny integer)
• release_date (Date)
• Timestamps (created_at, updated_at)

3. sales Columns:

• id (Primary Key)
• theater_id (Foreign Key to theaters.id)
• movie_id (Foreign Key to movies.id)
• sale_date (Date)
• tickets_sold (Integer)
• Timestamps (created_at, updated_at)

Relationships

• Each sale belongs to a theater and a movie.
• A theater can have many sales.
• A movie can have many sales.

Indexes

Indexes are added to optimize query performance:

• sales table:
• Index on sale_date
• Index on theater_id
• Index on movie_id

Database Dump Files

Sample database dump files are provided in the database/schema directory:

• Structure Dump: Contains the SQL statements to create the tables and indexes.
• Sample Data Dump: Contains a small set of data to illustrate the schema (not the full dataset due to size constraints).

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Prerequisites

Before setting up the project, ensure you have the following installed:

• Docker
• Docker Compose

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Installation

Clone the Repository

git clone https://github.com/elite133713/ata-laravel
cd ata-laravel

Environment Setup

The project is containerized using Docker and Docker Compose. Follow the steps below to set up the environment.

Copy .env File

Copy the example .env file and set your environment variables:

cp .env.example .env

Build and Start the Docker Containers

Run the following command to build and start the containers:

docker-compose up -d --build

This command will: • Build the Docker images for the application and database. • Start the containers in detached mode.

Install Composer Dependencies

Execute the following command inside the app container:

docker-compose exec app composer install

Generate Application Key

Inside the app container, run:

docker-compose exec app php artisan key:generate

Run Migrations

docker-compose exec app php artisan migrate

Seed the Database

Note: Seeding large datasets (e.g., 1 million records) can take significant time and resources. Ensure your system has sufficient memory and disk space.

Option 1: Seed Full Dataset

docker-compose exec app php artisan db:seed

Option 2: Seed Smaller Dataset for Testing • Adjust the $totalSales variable in SaleSeeder.php to a smaller number (e.g., 1000). • Run the seeder:

docker-compose exec app php artisan db:seed

Running the Application

Access the Application

The application should be accessible at http://localhost:8000.

Using the Console Command

The application includes an Artisan command to find the theater with the highest sales on a specific date.

Run the Command

docker-compose exec app php artisan highest-sales:theater

Follow the Prompt

• You will be asked to enter a date in the format YYYY-MM-DD.

• Example: Enter a date (YYYY-MM-DD):

• After entering the date, the command will output the theater with the highest sales on that date.

Sample Output

Theater with highest sales on 2024-05-15: Theater: Sample Theater, Tickets Sold: 1500

Using the Web UI

The application provides a web interface to find the theater with the highest sales and view monthly sales charts.

Access the Highest Sales Page

Navigate to:

http://localhost:8000/highest-sales

Select a Date

• Use the date picker to select a date within the range of your sales data (e.g., 2024-05-15). • Click the Submit button.

*** View Results***

• The page will display: • The theater with the highest sales on the selected date. • The number of tickets sold. • A bar chart showing the total tickets sold for each day of the month.

Chart Interactivity

• Hover over the bars in the chart to view tooltips with sales data. • The selected date will be highlighted in the chart.

Running Tests

Feature tests are included to ensure the application functions as expected.

Run Tests

docker-compose exec app php artisan test

Sample Output

PASS  Tests\Feature\SalesControllerTest
✓ index page loads successfully
✓ show page displays correct data for valid date
✓ show page displays validation error for invalid date
✓ show page displays message when no sales data found
✓ show page returns highest sales among multiple theaters

Tests:  5 passed

Troubleshooting

Containers Not Starting

• Issue: Containers fail to start or exit immediately. • Solution: Check the Docker Compose logs:

docker-compose logs

Look for error messages and resolve any issues (e.g., port conflicts, permission issues).

Database Connection Errors

Issue: The application cannot connect to the database.

Solution: Ensure the database container is running:

docker-compose ps

Verify database credentials in the .env file match those in docker-compose.yml. Wait a few seconds after starting the containers to allow the database to initialize.

Seeding Process Hangs or Crashes

Issue: Seeding large datasets causes the container to hang or crash.

Solution: Allocate more resources to Docker (memory and CPU) via Docker settings. Seed a smaller dataset for testing purposes.

Artisan Commands Not Found

Issue: php artisan commands are not recognized inside the container.

Solution: Ensure Composer dependencies are installed:

docker-compose exec app composer install

Contact

Thank you for using the Movie Sales Analysis Application!