https://github.com/ananyo141/propulsionai-interview-assignment

https://github.com/ananyo141/propulsionai-interview-assignment

Last synced: 6 days ago
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• Host: GitHub
• URL: https://github.com/ananyo141/propulsionai-interview-assignment
• Owner: ananyo141
• Created: 2024-06-07T20:00:08.000Z (5 months ago)
• Default Branch: master
• Last Pushed: 2024-06-07T20:53:29.000Z (5 months ago)
• Last Synced: 2024-10-10T20:43:57.195Z (28 days ago)
• Language: TypeScript
• Size: 61.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
#### Objective:

Extend the existing functionality of the CRUD operations and regex-based search by integrating MongoDB to log search queries and user interactions, while PostgreSQL handles the main CRUD operations on item data.

#### Requirements:

1. **Backend (NodeJS + Express):**

   - Use PostgreSQL to handle CRUD operations on the items.

   - Integrate MongoDB to log each search query along with metadata like the timestamp and user ID (if authentication is implemented).

   - Enhance the search functionality in the Express server to interact with both databases appropriately.

2. **Database Setup:**

   - **PostgreSQL:** Continue using PostgreSQL for managing the `items` table with CRUD operations.

   - **MongoDB:** Set up a MongoDB collection to store search logs. Each log entry should include the search term, the date/time of the search, and optionally the user ID.

3. **Frontend (ReactJS):**

   - Maintain the existing UI components for displaying and managing items.

   - Update the search functionality to log each search action to the MongoDB database through the Express API.

#### Steps to Follow:

1. **Backend Setup:**

   - Modify the `GET /api/items` route to log search details to MongoDB whenever a search is performed. This involves inserting a document into a MongoDB collection each time the search API is hit.

   - Ensure proper configuration and connection handling for both PostgreSQL and MongoDB in the Express app.

2. **Database Configuration:**

   - Ensure PostgreSQL is configured for item data management with optimized queries for regex searches.

   - Set up MongoDB with appropriate indexing on the search logs collection to optimize query performance for logs retrieval or analysis.

3. **Frontend Setup:**

   - Adjust the `ItemList` component to handle search logging. Make sure that every search, whether successful or not, triggers a log entry to MongoDB via the backend.

#### Additional Challenges:

- Implement real-time feedback on the frequency of searches for certain items, potentially using MongoDB's aggregation capabilities to summarize recent search activity.

- Provide a dashboard component in React to visualize search trends or log data fetched from MongoDB.

#### Deliverables:

- Source code for the backend with dual database handling.

- Updated React components for item management and search logging.

This task will effectively test a developer's skills in managing multiple databases, handling complex backend logic, and integrating frontend interactions with backend services. It also provides a practical scenario where SQL and NoSQL databases are used together, reflecting a real-world application structure.