https://github.com/nullhawk/book-analysis-lld
LLD assigment
https://github.com/nullhawk/book-analysis-lld
Last synced: 9 months ago
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LLD assigment
- Host: GitHub
- URL: https://github.com/nullhawk/book-analysis-lld
- Owner: nullHawk
- Created: 2025-08-19T17:39:22.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-08-19T18:21:52.000Z (10 months ago)
- Last Synced: 2025-08-19T20:25:44.971Z (10 months ago)
- Language: Java
- Size: 52.7 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Amazon Bestseller Book Analysis
A Java application that demonstrates **Low-Level Designs** and **optimal data structures** for efficient retrieval of book data from Amazon's Top 50 bestselling books dataset (2009-2019).
## Screenshots
## Project Architecture
The project follows a clean, layered architecture with proper separation of concerns:
```
src/com/nullhawk/books/
├── controllers/ # Application flow control
│ └── ApplicationController.java
├── model/ # Data entities
│ └── Book.java
├── services/ # Business logic and data access
│ ├── BookService.java
│ ├── InMemoryLoader.java
│ └── GUIDataService.java
├── views/ # User interface components
│ ├── BookAnalysisView.java
│ └── LauncherView.java
├── utils/ # Utility classes
│ └── ApplicationUtils.java
├── Main.java # Application entry point
├── BookAnalysisDemo.java # Console demonstration
└── DataStructureTest.java # Performance verification
```
## Features
- **O(1) Time Complexity** for author and rating lookups using HashMap indexing
- **Professional Java Swing GUI** with intuitive interface
- **Console Interface** for automation and scripting
- **Performance Testing** with real-time metrics
- **Clean Architecture** following SOLID principles
- **Robust CSV Parsing** with quoted field support
## Required Tasks Implementation
✅ **Get total number of books by a given author** - O(1) HashMap lookup
✅ **Print names of all unique authors** - O(1) HashSet retrieval
✅ **Get names of all books by author** - O(1) HashMap lookup + Stream mapping
✅ **Get books with specific rating** - O(1) HashMap lookup
✅ **Get book names and prices by author** - O(1) HashMap lookup + Stream collection
## Prerequisites
- **Java 8 or higher**
- **PowerShell** (Windows) or **Bash** (Linux/Mac)
## Quick Start
### Option 1: Run with Scripts (Recommended)
#### Windows (PowerShell)
```powershell
# Run the application
.\run.ps1
# Build distributable JAR
.\build-jar.ps1
```
#### Linux/Mac (Bash)
```bash
# Make scripts executable
chmod +x run.sh build-jar.sh
# Run the application
./run.sh
# Build distributable JAR
./build-jar.sh
```
### Option 2: Manual Compilation
```bash
# Compile the project
javac -d build -cp src src/com/nullhawk/books/*.java src/com/nullhawk/books/model/*.java src/com/nullhawk/books/services/*.java src/com/nullhawk/books/views/*.java src/com/nullhawk/books/controllers/*.java src/com/nullhawk/books/utils/*.java
# Copy resources
cp -r resources build/
# Run the application
cd build
java -cp . com.nullhawk.books.Main
```
## Usage
### Application Launcher
The application starts with a launcher that allows you to choose between:
1. **GUI Version** - Interactive Java Swing interface
2. **Console Version** - Command-line interface
### GUI Features
- **Query Operations**: Author lookups, rating filters, genre analysis
- **Advanced Queries**: Year ranges, price ranges, top-rated books
- **Performance Testing**: Real-time O(1) vs O(n) comparisons
- **Dataset Information**: Comprehensive data statistics
### Console Features
- **Interactive Demos**: All required tasks with examples
- **Performance Verification**: Data structure efficiency tests
- **Batch Operations**: Multiple queries in sequence
## Performance Characteristics
| Operation | Time Complexity | Data Structure |
|-----------|-----------------|----------------|
| Author lookup | **O(1)** | HashMap |
| Rating lookup | **O(1)** | HashMap |
| Unique authors | **O(1)** | HashSet |
| Genre filtering | **O(n)** | Stream + ArrayList |
| Year range filtering | **O(n)** | Stream + ArrayList |
| Top-rated books | **O(n log n)** | Stream + Sorting |
## Design Patterns
- **Service Layer Pattern**: Business logic separation
- **Repository Pattern**: Data access abstraction
- **Builder Pattern**: Immutable object creation
- **MVC Architecture**: Model-View-Controller separation
- **Observer Pattern**: Asynchronous data loading
## Project Structure
```
books/
├── resources/
│ └── data.csv # Amazon bestseller dataset
├── src/
│ └── com/nullhawk/books/
│ ├── controllers/ # Application flow control
│ ├── model/ # Data entities
│ ├── services/ # Business logic & data access
│ ├── views/ # User interface components
│ ├── utils/ # Utility classes
│ └── Main.java # Entry point
├── build/ # Compiled classes
├── dist/ # Distribution packages
├── run.sh # Bash run script
├── run.ps1 # PowerShell run script
├── build-jar.sh # Bash JAR build script
├── build-jar.ps1 # PowerShell JAR build script
└── README.md # This file
```
## Build Scripts
### Run Scripts
- **`run.sh`** / **`run.ps1`**: Compile and run the application
- **`build-jar.sh`** / **`build-jar.ps1`**: Create distributable JAR
### Script Features
- **Automatic compilation** with dependency management
- **Resource copying** to build directory
- **Error handling** with colored output
- **Cross-platform** support (Windows/Linux/Mac)
## Performance Results
The application demonstrates significant performance improvements:
- **Author lookups**: 277x faster than linear search
- **Rating lookups**: O(1) average case performance
- **Memory efficiency**: Optimal data structure usage
- **Scalability**: Linear indexing time, constant lookup time
## Testing
### Built-in Performance Tests
- **HashMap vs Linear Search** comparison
- **Real-time performance metrics**
- **Time complexity verification**
- **Memory usage analysis**
### Manual Testing
- **GUI Interface**: Interactive query testing
- **Console Interface**: Batch operation testing
- **Edge Cases**: Invalid inputs, boundary conditions
## Future Enhancements
1. **Database Integration**: Replace in-memory storage
2. **Caching Layer**: Redis implementation
3. **API Endpoints**: RESTful web services
4. **Real-time Updates**: Event-driven architecture
5. **Analytics Dashboard**: Data visualization
6. **Enhanced GUI**: Charts, graphs, advanced filtering