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https://github.com/schrodingdong/data-driven-microservices
Using a data-driven approach within a microservice architecture
https://github.com/schrodingdong/data-driven-microservices
apache-jena data-driven java microservice ontology rabbitmq rdf
Last synced: about 2 months ago
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Using a data-driven approach within a microservice architecture
- Host: GitHub
- URL: https://github.com/schrodingdong/data-driven-microservices
- Owner: Schrodingdong
- Created: 2023-06-01T20:20:39.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-06-08T03:24:24.000Z (over 1 year ago)
- Last Synced: 2024-01-05T21:28:18.935Z (about 1 year ago)
- Topics: apache-jena, data-driven, java, microservice, ontology, rabbitmq, rdf
- Language: Java
- Homepage:
- Size: 238 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Ontological Discovery Service
## Possible Urls
- localhost:8080
- localhost:8080/?products (get all of them)
- localhost:8080/?customers
- localhost:8080/?orders
- localhost:8080/?productId=69 (get the product with the given id)
- localhost:8080/?customerId=45
- localhost:8080/?orderId=150
## Possible Methods
- GET
- POST
- PUT
- DELETE
## Possbile Bodies
### Product
For saving a product :
```json
{
"productName": "Product Name",
"productDescription": "Product Description",
"productPrice": 69.69
}
```
For updating a product (example) :
```json
{
"productId": 1,
"productName": "New product Name"
}
```
### Customer
For saving a customer :
```json
{
"customerFirstname": "Customer First Name",
"customerLastname": "Customer Last Name",
"customerEmail": "Customer Email"
}
```
For updating a customer (example) :
```json
{
"customerId": 1,
"customerFirstname": "New Customer First Name"
}
```
### Order
For saving an order :
```json
{
"customerId": 1,
"orderProducts": [
{
"productId": 1,
"quantity": 53
},
{
"productId": 2,
"quantity": 12
}
]
}
```
For updating an order :
```json
{
"orderId": 1,
"orderProducts": [
{
"productId": 1,
"quantity": 53
},
{
"productId": 2,
"quantity": 12
}
]
}
```
## Example combinations
NOTE that the following examples are not exhaustive, they are just here to give you an idea of how the service works.
The URLs shall be listed in the application.yaml file, following this structure for each service ontologically discovered
````
serviceName :
Method :
GET:
- uri1
...
POST:
- uri1
...
PUT:
- uri1
...
DELETE:
- uri1
...
````
### Example 1
Consider the following request :
````http request
POST http://localhost:8080/
Content-Type: application/json
{
"productName": "Product Name",
"productDescription": "Product Description",
"productPrice": 69.69
}
````
This SHOULD create a new product with the given information and will return the following response :
````http request
HTTP/1.1 200
Content-Type: application/json
{
"productId": 1,
"productName": "Product Name",
"productDescription": "Product Description",
"productPrice": 69.69
}
````
Workflow :
- The request is received by the server
- Get the path variable (here we have none) and the body (product)
- **Ontological analysis of the body**
- compare with each ontology
- find the best match
- return the service name (in this case, it's the product service)
- **Url generation**
- Analysis of the :
- Method (POST)
- Path variable (none)
- service name (product service)
- Generate the uri (/product/save)
### Example 2
Consider the following request :
````http request
PUT http://localhost:8080/
Content-Type: application/json
{
"productId": 1,
"productName": "New product Name"
}
````
This SHOULD update the product with the given information and will return the following response :
````http request
HTTP/1.1 200
Content-Type: application/json
{
"productId": 1,
"productName": "New product Name",
"productDescription": "Product Description",
"productPrice": 69.69
}
````
Workflow :
- The request is received by the server
- Get the path variable (here we have none) and the body (product)
- **Ontological analysis of the body**
- compare with each ontology
- find the best match
- return the service name (in this case, it's the product service)
- **Url generation**
- Analysis of the :
- Method (PUT)
- Path variable (none)
- service name (product service)
- generate the uri (/product/update)
### Example 3
Consider the following request :
````http request
GET http://localhost:8080/?productId=1
````
This SHOULD return the product with the given id and will return the following response :
````http request
HTTP/1.1 200
Content-Type: application/json
{
"productId": 1,
"productName": "product Name",
"productDescription": "Product Description",
"productPrice": 69.69
}
````
Workflow :
- The request is received by the server
- Get the path variable (productId) and the body (none)
- **Ontological analysis of the path variable**
- compare with each ontology
- find the best match
- return the service name (in this case, it's the product service)
- **Url generation**
- Analysis of the :
- Method (GET)
- Path variable (productId)
- service name (product service)
- Replace the path variables with their correct value
- generate the uri (/product/get/1)
## Messaging Service
We will be using RabbitMQ as our messaging service.
to run it, you can use the following command :
```shell script
docker run -it --rm --name rabbitmq -p 5672:5672 -p 15672:15672 rabbitmq:3.11-management
```
The management interface is available at http://localhost:15672/ with the default credentials (guest/guest).
The connection from the services is automatic (as long as the Rabbit MQ port is the same as the one in the cmd)
### Structure of the messaging system
Each Business Service has its own queue, that are linked to one exchange. The consumer (OntoogyDiscovery) listens to all the queues and update the .rdf files it has.
- Exchange : rdf.exchange
- Queues :
- product.rdf.queue
- customer.rdf.queue
- order.rdf.queue
- Routing keys :
- product.rdf.queue -> product.rdf.key
- customer.rdf.queue -> customer.rdf.key
- order.rdf.queue -> order.rdf.key