Yelp-alitics Customer Profiler

Generates customer profile/restaurant preferences based on user check-ins, and reviews. This is a microservice intended to integrate with the entire Yelp-alitics system.

Contributing

See CONTRIBUTING.md for contribution guidelines.

Table of Contents

1. Usage
2. Requirements
3. Development
   1. Installing Dependencies
   2. Architecture Information
   3. Roadmap

Usage

Setup

Create a MongoDB database to hold customer profiler data with the following collections: users; restaurants; reviews; check-ins; clicks; queries.

Data Generation

To run this in isolation from other microservices, simulated data needs to be generated. Create a set of simulated historical data using the following steps:

1. Generate simulated restaurants, users, and user clicks, reviews, check-ins, and queries by running the scripts that end in Generator.js in the dataGeneration folder. This will add a JSON file for each collection in a MongoDB-friendly format to the data folder.

2. Import each generated file into MongoDB using the following command:

mongoimport --db YOUR_DB_NAME --collection YOUR_COLLECTION --drop --file YOUR_FILE_PATH/data/FILENAME --jsonArray

Streaming Simulated Data

To simulate the flow of data into the system, run dataGeneration/streamData.js

Streaming Data

This service accepts data via Amazon Web Services SQS. The sqs folder contains the scripts that need to be running in order to receive messages from other services.

Requirements

• Node 6.11.1
• MongoDB 3.4

Installing Dependencies

Install dependencies with npm install

Architecture Information

Architecture diagram

Schema

Roadmap

View the project roadmap here