# Design Location Based App

* **Yelp** or Nearby Friends
* Proximity server

## Requirements and Goals of the System

**Functional Requirements:**

1. Users should be able to add/delete/update **Places**.
2. **Given** their **location** (longitude/latitude), users should be able to **find** **all** **nearby** **places** **within** a **given** **radius**.
3. Users should be able to add feedback/review about a place. The feedback can have pictures, text, and a rating.

**Non-functional Requirements:**

1. Users should have a real-time search experience with minimum latency.
2. Our service should support a heavy search load. There will be a lot of search requests compared to adding a new place.

## Scale Estimation

500M daily user \* 2 times per day \* 5 queries per time / 86400 seconds \~ 50k QPS

Peak hour: \* 2 \~ 100k QPS

Assuming 500M places

## Database Schema

### Each location:

1. **LocationID** (8 bytes): Uniquely identifies a location.
2. **Name** (256 bytes)
3. **Latitude** (8 bytes)
4. **Longitude** (8 bytes)
5. **Description** (512 bytes)
6. **Category** (1 byte): E.g., coffee shop, restaurant, theater, etc.

Total size: 8 + 256 + 8 + 8 + 512 + 1 => 793 bytes

### reviews, photos, and ratings of a Place

1. **LocationID** (8 bytes)
2. **ReviewID** (4 bytes): Uniquely identifies a review, assuming any location will not have more than 2^32 reviews.
3. **ReviewText** (512 bytes)
4. **Rating** (1 byte): how many stars a place gets out of ten.

## System APIs

API for searching

```
search(api_dev_key, search_terms, user_location, radius_filter, maximum_results_to_return, 
    category_filter, sort, page_token)
```

## Basic System Design and Algorithm

### Two different use case:

* Location of a place doesn’t change that often, we don’t need to worry about frequent updates of the data.
* Objects do change their location frequently, e.g., people or taxis


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