Hotel Finder Web App

Hotel finder website created in Vue.js with a backend written in Go using the Gin web framework and MongoDB as database for Geospatial Queries

About The Project

This is an example of a Nearby search REST API for searching nearby hotels, in this case all routes are accessible by anyone but in a real life scenario the search API is going to be used by users and only the hotels API or at least the writing parts of it will be accessible to the hotel owners.

API Endpoints

Here are the available endpoints for now:

API for search

GET /v1/search/nearby This endpoint returns hotels based on certain search criteria. In real-life applications, search results are also paginated so we need to add parameters for that.

Request Parameters:

Field Description Type
latitude Latitude of a given location float
longitude Longitude of a given location float
radius Optional. Default is 5000 meters float
offset Optional. Defaul is 0 int
limit Optional. Default is 20 int

The hotel object returned contains everything needed to render the search result page. But we may still need additional attributes such as pictures, reviews, star rating, etc., to render each hotel detail page when we visit them.

In the future we can also add more complex searches like let a user define an area which will be formatted as GeoJSON and then send that to the backend and return only hotels in that area. Or even add search filters like star rating, price, etc.

API for hotels

The APIs related to an hotel object are shown in the table below:

API Detail
GET /v1/hotels/:id Return detailed information about an hotel
POST /v1/hotels Add an hotel
PUT /v1/hotels/:id Update details of an hotel
DELETE /v1/hotels/:id Delete an hotel

Read/Write Ratio

Since most of the time we’re going to use the search for nearby hotels API and also the view information about an hotel, most likely we’re going to have an high read volume. The write on the other hand is low since it happens only when we’re adding, removing or updating an hotel page.

Most of the time for a read-heavy system, a relational database such as MySQL is a better fit than other solutions. But for ease of development we’re going to use MongoDB with its built-in support for Geospatial Queries which are easy to use than MySQL Geo Queries.

Data Model

Hotel Object

Variable Type Description
name String Name of the hotel
starRating Int Rating of the hotel
address String Address of the hotel
state String State where the hotel is located
location Point Coordinates of the hotel in GeoJSON point format

Point Object

Variable Type Description
type String In this case the type will always be Point
coordinates []Int An array of two values with the first being the longitude and the last being the latitude

An example of the Point format is the following:

    type: "Point", 
    coordinates: [ 40, 5 ] 

Of course we will use a GeoSpatial Index for efficient processing of spatial operations.

High-level Design

The high-level design diagram is the following. The system is divided into two parts the location search service API and the hotels related API.

Alt text

So normally the website should act upon a database cluster but for semplicity we’re going to use only one database. The database cluster is setup using the primary-secondary architecture, where the primary database handles all write operations and replicas of that primary database which are secondary are used for read operations.

Built With

This project was built with the following technologies:

  • HTML
  • CSS
  • JavaScript
  • Vue.js
  • Golang
  • MongoDB

Getting Started – Setup

By default you’ll need to provide a .env file or set up the environment variables for your operating system, these are required variables that you need to setup:

Variable Description
PORT The HTTP/HTTPS server port
MONGODB_URI The URI for connecting to your MongoDB server
DB_NAME The name of the database (inside MongoDB) where you want to store the users and posts
GO_ENV Tells go if the build is for production or not, set it to “production” to enable it

Also be aware that for the API to work you need to set up a Geo Index inside MongoDB using the following commands inside MongoShell:

db.collName.createIndex({fieldName: "2dsphere"})


License: GPL v3

Distributed under the GPL v3 License. See LICENSE for more information.


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