This example explains the distributed execution model of Hyperflow. It demonstrates how HyperFlow can communicate with remote job executors using Redis. It is also useful for testing the implementation of the Hyperflow job executor.

The distributed execution architecture consists of:

1. Master components:
   • The Hyperflow engine - executes the workflow graph; for each workflow task it invokes the Job invoker function
   • Job invoker - Javascript function which creates jobs on a (remote) infrastructure to execute workflow tasks
   • Redis server - used for communication between the Hyperflow engine and Job executors on remote workers
2. Worker components:
   • Hyperflow job executor - receives the job command from the Hyperflow engine and spawns application software
   • Application software - software that actually performs workflow tasks

In this example:

• The workflow has two tasks (see workflow.json): one that executes job.js, the other which simply runs ls -l. Note that the commands to be executed are specified in workflow.json.
• The engine invokes the function submitRemoteJob (Job invoker) from functions.js. This function simulates submission of jobs by starting the Hyperflow job executor and communicating with it via Redis to run jobs.
• ../../../hyperflow-job-executor/handler.js represents a remote job executor which is passed two parameters: taskId and redis_url. The executor gets a jobMessage from HyperFlow, executes the command in a separate process, and then sends back a notification that the job has completed; taskId is used to construct appropriate Redis keys for this communication.
• On the HyperFlow engine side, the Job invoker can use two functions (provided by Hyperflow): context.sendMsgToJob to send a message to the job executor, and context.jobResult to wait for the notification from the executor. These functions return a Promise, so the async/await syntax can be used as shown in the example.
• The parameter to the context.jobResult function is a timeout in seconds (0 denotes infinity). One can use a retry library, such as promise-retry, to implement an exponential retry strategy.
• The Job invoker also gets the Redis URL in context.redis_url which can be passed to the remote job executors.

To run the workflow, execute the following commands:

1. First, clone the Hyperflow engine and the Hyperflow job executor:
   • git clone https://github.com/hyperflow
   • git clone https://github.com/hyperflow-wms/hyperflow-job-executor
   • cd hyperflow; npm install
   • cd ../hyperflow-job-executor; npm install
2. Start the redis server
3. To run the workflow:
   • cd ../hyperflow/examples/RemoteJobs
   • npm install (once)
   • hflow run .