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For an overview of how to use php-resque, see README.md.

The following is a step-by-step breakdown of how php-resque operates.

Enqueue Job

What happens when you call Resque::enqueue()?

  1. Resque::enqueue() calls Resque_Job::create() with the same arguments it received.
  2. Resque_Job::create() checks that your $args (the third argument) are either null or in an array
  3. Resque_Job::create() generates a job ID (a "token" in most of the docs)
  4. Resque_Job::create() pushes the job to the requested queue (first argument)
  5. Resque_Job::create(), if status monitoring is enabled for the job (fourth argument), calls Resque_Job_Status::create() with the job ID as its only argument
  6. Resque_Job_Status::create() creates a key in Redis with the job ID in its name, and the current status (as well as a couple of timestamps) as its value, then returns control to Resque_Job::create()
  7. Resque_Job::create() returns control to Resque::enqueue(), with the job ID as a return value
  8. Resque::enqueue() triggers the afterEnqueue event, then returns control to your application, again with the job ID as its return value

Workers At Work

How do the workers process the queues?

  1. Resque_Worker::work(), the main loop of the worker process, calls Resque_Worker->reserve() to check for a job
  2. Resque_Worker->reserve() checks whether to use blocking pops or not (from BLOCKING), then acts accordingly:
  • Blocking Pop
    1. Resque_Worker->reserve() calls Resque_Job::reserveBlocking() with the entire queue list and the timeout (from INTERVAL) as arguments
    2. Resque_Job::reserveBlocking() calls Resque::blpop() (which in turn calls Redis' blpop, after prepping the queue list for the call, then processes the response for consistency with other aspects of the library, before finally returning control [and the queue/content of the retrieved job, if any] to Resque_Job::reserveBlocking())
    3. Resque_Job::reserveBlocking() checks whether the job content is an array (it should contain the job's type [class], payload [args], and ID), and aborts processing if not
    4. Resque_Job::reserveBlocking() creates a new Resque_Job object with the queue and content as constructor arguments to initialize the job itself, and returns it, along with control of the process, to Resque_Worker->reserve()
  • Queue Polling
    1. Resque_Worker->reserve() iterates through the queue list, calling Resque_Job::reserve() with the current queue's name as the sole argument on each pass
    2. Resque_Job::reserve() passes the queue name on to Resque::pop(), which in turn calls Redis' lpop with the same argument, then returns control (and the job content, if any) to Resque_Job::reserve()
    3. Resque_Job::reserve() checks whether the job content is an array (as before, it should contain the job's type [class], payload [args], and ID), and aborts processing if not
    4. Resque_Job::reserve() creates a new Resque_Job object in the same manner as above, and also returns this object (along with control of the process) to Resque_Worker->reserve()
  1. In either case, Resque_Worker->reserve() returns the new Resque_Job object, along with control, up to Resque_Worker::work(); if no job is found, it simply returns FALSE
  • No Jobs
    1. If blocking mode is not enabled, Resque_Worker::work() sleeps for INTERVAL seconds; it calls usleep() for this, so fractional seconds are supported
  • Job Reserved
    1. Resque_Worker::work() triggers a beforeFork event
    2. Resque_Worker::work() calls Resque_Worker->workingOn() with the new Resque_Job object as its argument
    3. Resque_Worker->workingOn() does some reference assignments to help keep track of the worker/job relationship, then updates the job status from WAITING to RUNNING
    4. Resque_Worker->workingOn() stores the new Resque_Job object's payload in a Redis key associated to the worker itself (this is to prevent the job from being lost indefinitely, but does rely on that PID never being allocated on that host to a different worker process), then returns control to Resque_Worker::work()
    5. Resque_Worker::work() forks a child process to run the actual perform()
    6. The next steps differ between the worker and the child, now running in separate processes:
    • Worker
      1. The worker waits for the job process to complete
      2. If the exit status is not 0, the worker calls Resque_Job->fail() with a Resque_Job_DirtyExitException as its only argument.
      3. Resque_Job->fail() triggers an onFailure event
      4. Resque_Job->fail() updates the job status from RUNNING to FAILED
      5. Resque_Job->fail() calls Resque_Failure::create() with the job payload, the Resque_Job_DirtyExitException, the internal ID of the worker, and the queue name as arguments
      6. Resque_Failure::create() creates a new object of whatever type has been set as the Resque_Failure "backend" handler; by default, this is a Resque_Failure_Redis object, whose constructor simply collects the data passed into Resque_Failure::create() and pushes it into Redis in the failed queue
      7. Resque_Job->fail() increments two failure counters in Redis: one for a total count, and one for the worker
      8. Resque_Job->fail() returns control to the worker (still in Resque_Worker::work()) without a value
    • Job
      1. The job calls Resque_Worker->perform() with the Resque_Job as its only argument.
      2. Resque_Worker->perform() sets up a try...catch block so it can properly handle exceptions by marking jobs as failed (by calling Resque_Job->fail(), as above)
      3. Inside the try...catch, Resque_Worker->perform() triggers an afterFork event
      4. Still inside the try...catch, Resque_Worker->perform() calls Resque_Job->perform() with no arguments
      5. Resque_Job->perform() calls Resque_Job->getInstance() with no arguments
      6. If Resque_Job->getInstance() has already been called, it returns the existing instance; otherwise:
      7. Resque_Job->getInstance() checks that the job's class (type) exists and has a perform() method; if not, in either case, it throws an exception which will be caught by Resque_Worker->perform()
      8. Resque_Job->getInstance() creates an instance of the job's class, and initializes it with a reference to the Resque_Job itself, the job's arguments (which it gets by calling Resque_Job->getArguments(), which in turn simply returns the value of args[0], or an empty array if no arguments were passed), and the queue name
      9. Resque_Job->getInstance() returns control, along with the job class instance, to Resque_Job->perform()
      10. Resque_Job->perform() sets up its own try...catch block to handle Resque_Job_DontPerform exceptions; any other exceptions are passed up to Resque_Worker->perform()
      11. Resque_Job->perform() triggers a beforePerform event
      12. Resque_Job->perform() calls setUp() on the instance, if it exists
      13. Resque_Job->perform() calls perform() on the instance
      14. Resque_Job->perform() calls tearDown() on the instance, if it exists
      15. Resque_Job->perform() triggers an afterPerform event
      16. The try...catch block ends, suppressing Resque_Job_DontPerform exceptions by returning control, and the value FALSE, to Resque_Worker->perform(); any other situation returns the value TRUE along with control, instead
      17. The try...catch block in Resque_Worker->perform() ends
      18. Resque_Worker->perform() updates the job status from RUNNING to COMPLETE, then returns control, with no value, to the worker (again still in Resque_Worker::work())
      19. Resque_Worker::work() calls exit(0) to terminate the job process cleanly
    • SPECIAL CASE: Non-forking OS (Windows)
      1. Same as the job above, except it doesn't call exit(0) when done
    1. Resque_Worker::work() calls Resque_Worker->doneWorking() with no arguments
    2. Resque_Worker->doneWorking() increments two processed counters in Redis: one for a total count, and one for the worker
    3. Resque_Worker->doneWorking() deletes the Redis key set in Resque_Worker->workingOn(), then returns control, with no value, to Resque_Worker::work()
  1. Resque_Worker::work() returns control to the beginning of the main loop, where it will wait for the next job to become available, and start this process all over again