Setup

1. Install Node.js and MongoDB on your machine.
2. Clone the repository for the service and navigate to the project directory.
3. Install the project dependencies by running npm install.
4. Start the MongoDB server by running mongod.
5. Create a .env file in the project directory and set the following environment variables:
6. MONGODB_URI: The URI of the MongoDB instance to connect to (e.g. "mongodb://localhost:27017/my_database"). PORT: The port on which the service should run (e.g. "3000").
7. Start the service by running npm start.
8. To run tests, use the npm test command.
9. To generate OpenAPI documentation, use the npm run docs command. This will create a docs directory with the generated documentation.

Tech Stack

• For this service, I would recommend using the following tech stack:

1. Node.js - This is a JavaScript runtime that allows for fast and efficient server-side development. It also has a vast ecosystem of libraries and frameworks that can be used for building the service.

2. Express.js - This is a popular web framework for Node.js that provides a simple and intuitive way to build HTTP APIs.

3. MongoDB - This is a NoSQL database that is well-suited for storing large amounts of data and handling high traffic loads. It is also flexible and easy to scale, making it a good choice for this service.

4. Mongoose - This is an Object Document Mapper (ODM) for MongoDB that makes it easy to map database objects to JavaScript objects and vice versa. It also provides a simple and intuitive API for interacting with the database.

5. Jest - This is a testing framework that is well-suited for testing Node.js applications. It is easy to use, has a large number of features, and is well-supported by the community.

6. OpenAPI 3.0 - This is a specification for building APIs that allows for easy documentation and testing of API endpoints. It can be used to define the API endpoints and request/response schemas for this service.

HTTP APIs

• List top users by internet usage

  Endpoint: /api/users/top
  

Method: GET

Parameters:

time_period (optional, one of "1d", "7d", "30d"): The time period for which to retrieve the top users. Defaults to "1d".
page (optional, integer): The page number for the results. Defaults to 1.
limit (optional, integer): The number of results per page. Defaults to 10.

Response:

200: Success. Returns a list of users sorted by internet usage in descending order. Each user has the following fields:
id (string): The unique identifier for the user.
name (string): The name of the user.
usage (integer): The total internet usage for the specified time period (in bytes).
created_at (string): The date and time when the user was created (in ISO 8601 format).

• Search users by name

  Endpoint: /api/users/search
  

Method: GET

Parameters:

name (required, string): The name of the user to search for.

Response:

200: Success. Returns a list of users matching the specified name. Each user has the following fields:
id (string): The unique identifier for the user.
name (string): The name of the user.
usage (integer): The total internet usage for the specified time period (in bytes).
created_at (string): The date and time when the user was created (in ISO 8601 format).

Database Model

The database model for this service will consist of a single collection called "users", which will store the following fields for each user:
id (string): The unique identifier for the user.
name (string): The name of the user.
usage (integer): The total internet usage for the specified time period (in bytes).
created_at (string): The date and time when the user was created (in ISO 8601 format).
This model will allow for fast and efficient retrieval of user data, as well as easy query. 

+++ To ingest the provided dataset into the service's database, we can create a script that reads the data from the file and inserts it into the "users" collection in the database.

Here is an example of how this script might work:

1. Connect to the database using Mongoose.
2. Read the data from the file and parse it into a JavaScript object.
3. Iterate through the object and create a new "User" model for each record.
4. Save the model to the database.

Here is a code to demonstrates how this script might work:

const mongoose = require('mongoose');
const User = require('./models/user');

// Connect to the database
mongoose.connect('mongodb://localhost:27017/internet_usage', { useNewUrlParser: true, useUnifiedTopology: true });

// Read the data from the file and parse it into a JavaScript object
const data = require('./data.json');

// Iterate through the data and create a new User model for each record
data.forEach(record => {
  const user = new User({
    id: record.id,
    name: record.name,
    usage: record.usage,
    created_at: record.created_at
  });

  // Save the model to the database
  user.save();
});

// Close the database connection
mongoose.connection.close();

This script can be run from the command line using the following command:

  node ingestion_script.js

To implement the paginated HTTP API to list top users by their internet usage, we can create an endpoint that accepts the following parameters:

time_period (optional, one of "1d", "7d", "30d"): The time period for which to retrieve the top users. Defaults to "1d". page (optional, integer): The page number for the results. Defaults to 1. limit (optional, integer): The number of results per page. Defaults to 10. The endpoint should return a list of users sorted by internet usage in descending order, with the specified number of results per page.

Here is an example of how this endpoint might work:

const express = require('express');
const router = express.Router();
const User = require('../models/user');

// List top users by internet usage
router.get('/top', async (req, res) => {
  try {
    // Parse the query parameters
    const timePeriod = req.query.time_period || '1d';
    const page = parseInt(req.query.page) || 1;
    const limit = parseInt(req.query.limit) || 10;

    // Set the date range based on the time period
    let startDate, endDate;
    if (timePeriod === '1d') {
      startDate = new Date();
      startDate.setDate(startDate.getDate() - 1);
      endDate = new Date();
    } else if (timePeriod === '7d') {
      startDate = new Date();
      startDate.setDate(startDate.getDate() - 7);
      endDate = new Date();
    } else if (timePeriod === '30d') {
      startDate = new Date();
      startDate.setDate(startDate.getDate() - 30);
      endDate = new Date();
    }

    // Retrieve the top users from the database
    const users = await User.find({
      created_at: {
        $gte: startDate,
        $lte: endDate
      }
    })
      .sort({ usage: -1 })
      .skip((page - 1) * limit)
      .limit(limit);

    // Send the results back to the client
    res.send(users);
  } catch (error) {
    res.status(500).send(error);
  }
});

module.exports = router;

This endpoint can be accessed by sending a GET request to the following URL:

/api/users/top?time_period=7d&page=2&limit=20

This will return the top 20 users for the past 7 days, starting from page 2.

To implement the user details HTTP API to search users by their exact name, we can create an endpoint that accepts a name parameter and returns the matching user's internet usage consumption.

Here is an example of how this endpoint might work:

const express = require('express');
const router = express.Router();
const User = require('../models/user');

// Search users by name
router.get('/search', async (req, res) => {
  try {
    // Retrieve the user from the database
    const user = await User.findOne({ name: req.query.name });

    // Send the results back to the client
    res.send(user);
  } catch (error) {
    res.status(500).send(error);
  }
});

module.exports = router;