Distributed Task Scheduler

Simple Distributed Task Scheduler using Redis.

The application starts a web-server that exposes one REST API to schedule tasks that should get processed in the future:

POST 'http://localhost:8888/api/v1/schedule'

Request:
body -
{
  "time": 1640212236,
  "type": "MY_TASK",
  "input": {}
}

* time - Unix timestamps in seconds
* type - Task type (see TaskType enum class)
* input - Task input

Response:
status code - 200
body -
{
  "id": "6874ba39-29d5-4c6e-aaae-a957e2e75423"
}

* id - task unique id

When the API is invoked, the task is added to a sorted-set with time as the score.

"TaskSampler" responsible for polling tasks from that sorted-set and if it`s time to get processed, the task is removed from the sorted-set and added to another list that holds tasks to process now.

"TaskProcessor" responsible for polling the tasks from that list and process them.

Notes:

• Distributed processing is achieved using redis-locks.

• Vertx Verticles used to scale the number of samplers and processors easily.

Building

To launch your tests:

./gradlew clean test

To package your application:

./gradlew clean assemble

To run your application:

./gradlew clean run

How To

To run Redis docker container

docker run --name my-redis -p 6379:6379 --restart always --detach redis

To open redis-cli in the container

docker exec -it my-redis redis-cli

To launch redis & app using docker compose

docker-compose up -d

Examples:

Print Message Task

Request:

curl --location --request POST 'http://localhost:8888/api/v1/schedule' \
--header 'Content-Type: application/json' \
--data-raw '{
    "type": "PRINT_MESSAGE",
    "time": 1640428140,
    "input": {
        "message": "hello world"
    }
}'

Result:

2021-12-25T10:29:00,194 [TaskProcessor-0] INFO  com.task_scheduler.task.impl.PrintMessageTask - "hello world"

Adding a new task:

1. Add your new type to "TaskType" enum.

2. Impl "TaskHandler" for that new type.

3. Add the new type to the "tasks" map in "TasksHandlerProvider" class.