https://github.com/agkloop/products-compare

https://github.com/agkloop/products-compare

Last synced: 10 months ago
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• Host: GitHub
• URL: https://github.com/agkloop/products-compare
• Owner: agkloop
• Archived: true
• Created: 2021-01-04T23:14:29.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2021-01-07T12:21:48.000Z (over 5 years ago)
• Last Synced: 2025-04-15T09:45:09.510Z (about 1 year ago)
• Language: Java
• Size: 317 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# products-comparison

##### This project is composed of 2 microservices

   * REST API (Reading ) + projection consumer that updates the db in a realtime fashion.

   * Sources scraping and mapping 

   

## REST API (Reading ) + projection consumer ##

   built using reactor reactive stream on jvm  and high performance batch db writing using jdbc template api

## Sources scraping and mapping ##

 is built using reactive kafka that integrate reactive streams with kafka API 

 it's also use protobuf serialization protocol in the published messages

 and communication between the producer and consumer. 

   

   

## Following the reactive architecture the high level structure ##   

![Image of Yaktocat](digram.png)

## How it works ##

1. in the Sources/dataProvider microservice we have a scheduled task that run every day or week for each source [here](com.product.all/sources/src/main/java/com/task/sources/AppStartupRunner.java)

2. the Sources/dataProvider fetch and map the data to a common structure then push it to kafka

3. in the Projection there is a reactive consumer running to consume and update the DB in a real time with backpressure applied.

4. finally, the REST API part [here](#Try)

### what is missing ###

1. Separating the projection consumer to be a separate service using kafka-connect

2. Using elastic search cluster as a primary source of data

3. Using kubernetes  

4. More test coverage 

	   

## Requirement ##

* jave 15 

* maven 

* Docker

 

## Build ## 

 1. run `mvn clean package` to create the jar file

 2. run ` docker-compose up --build`

## Try 

 

 1. call  `${localhost/docker-machine-ip}:8080/category ` to list all the available categories

 2. call  `${localhost/docker-machine-ip}:8080/category/{Category_id}/product/{Product_name} ` to list all the available products that have similar name with prices

 eg: call  `http://192.168.99.100/:8080/category/1/product/iphone `