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https://github.com/zbhavyai/test-openhouseai
Assessment for OpenHouse.ai
https://github.com/zbhavyai/test-openhouseai
hibernate panache-entity postgres quarkus rest-api
Last synced: 24 days ago
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Assessment for OpenHouse.ai
- Host: GitHub
- URL: https://github.com/zbhavyai/test-openhouseai
- Owner: zbhavyai
- Created: 2022-06-26T01:26:37.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-07-15T17:54:36.000Z (over 2 years ago)
- Last Synced: 2023-03-05T07:25:35.115Z (almost 2 years ago)
- Topics: hibernate, panache-entity, postgres, quarkus, rest-api
- Language: Java
- Homepage:
- Size: 175 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# OpenHouse.ai Assessment
Backend Assessment - retrieving logs
## How to build and run
1. The following are required to build and run this project:
- JDK version 11.0.11 or above
- Maven version 3.6.3 or above (if not using maven wrapper)
- PostgreSQL version 14.4 or above
2. Start your postgres database server. Set the property `quarkus.datasource.password` with the password of the user `postgres` in the file [application.properties](src/main/resources/application.properties).
3. Run the command from project's root to launch the application. This will launch the application on `8080` port.
```bash
$ mvn clean quarkus:dev
```
4. The API can be accessed using the URL `http://localhost:8080/api`.
## Storing Logs
- Make a post call to `/api/store` with one log entry as payload. For example:
```bash
$ curl -X POST -H "Content-Type: application/json" -d '{
"userId": "ABC123XYZ",
"sessionId": "XYZ456ABC",
"actions": [
{
"time": "2018-10-18T21:37:28-06:00",
"type": "CLICK",
"properties": {
"locationX": 52,
"locationY": 11
}
},
{
"time": "2018-10-18T21:37:30-06:00",
"type": "VIEW",
"properties": {
"viewedId": "FDJKLHSLD"
}
},
{
"time": "2018-10-18T21:37:30-06:00",
"type": "NAVIGATE",
"properties": {
"pageFrom": "communities",
"pageTo": "inventory"
}
}
]
}' 'http://localhost:8080/api/store'
```
- Make a post call to `/api/storeall` with array of log entries as payload. For example:
```bash
$ curl -X POST -H "Content-Type: application/json" -d '[
{
"userId": "USER123",
"sessionId": "SESSION123",
"actions": [
{
"time": "2022-06-01T21:37:28-06:00",
"type": "CLICK",
"properties": {
"locationX": 52,
"locationY": 11
}
},
{
"time": "2022-06-01T21:37:30-06:00",
"type": "VIEW",
"properties": {
"viewedId": "QWERTY"
}
},
{
"time": "2022-06-01T21:37:30-06:00",
"type": "NAVIGATE",
"properties": {
"pageFrom": "page1",
"pageTo": "page2"
}
}
]
},
{
"userId": "USER123",
"sessionId": "SESSION456",
"actions": [
{
"time": "2022-06-15T21:37:28-06:00",
"type": "CLICK",
"properties": {
"locationX": 52,
"locationY": 11
}
},
{
"time": "2022-06-15T21:37:30-06:00",
"type": "VIEW",
"properties": {
"viewedId": "ASDFG"
}
},
{
"time": "2022-06-15T21:37:30-06:00",
"type": "NAVIGATE",
"properties": {
"pageFrom": "page5",
"pageTo": "page3"
}
}
]
},
{
"userId": "USER456",
"sessionId": "SESSION789",
"actions": [
{
"time": "2022-06-25T21:37:28-06:00",
"type": "CLICK",
"properties": {
"locationX": 52,
"locationY": 11
}
},
{
"time": "2022-06-25T21:37:30-06:00",
"type": "VIEW",
"properties": {
"viewedId": "ZXCVB"
}
},
{
"time": "2022-06-25T21:37:30-06:00",
"type": "NAVIGATE",
"properties": {
"pageFrom": "page8",
"pageTo": "page12"
}
}
]
}
]' 'http://localhost:8080/api/storeall'
```
## Retrieving Logs
- Make a get call to `/api/retrieve/all` to retrieve all logs. For example:
```bash
$ curl -X GET 'http://localhost:8080/api/retrieve/all'
```
- Make a get call to `/api/retrieve` with parameters to retrieve logs based on user, time range, or log type. Any combination of these parameters can be used. For example:
```bash
$ curl -X GET 'http://localhost:8080/api/retrieve?user=USER123&type=NAVIGATE&startTime=2022-06-01T21:37:30-06:00&endTime=2022-06-25T21:37:28-06:00'
```
## Follow-up Questions
To make cloud scalable and to query millions of data points:
- Add indexes to the database
- Cache REST endpoints
- Load balance the servers
- Add unit tests with maximum coverage
- Scale the database horizontally