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Performance improvements
* Speed up serialization of hostvars by simply using the internal dictionary used for cached lookups * Use blocking gets/puts on queues instead of spin locking * Merge sequential implicitly created blocks
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5 changed files with 57 additions and 42 deletions
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@ -92,40 +92,36 @@ class WorkerProcess(multiprocessing.Process):
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while True:
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task = None
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try:
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if not self._main_q.empty():
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debug("there's work to be done!")
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(host, task, basedir, job_vars, play_context, shared_loader_obj) = self._main_q.get(block=False)
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debug("got a task/handler to work on: %s" % task)
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(host, task, basedir, job_vars, play_context, shared_loader_obj) = self._main_q.get()
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debug("there's work to be done!")
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debug("got a task/handler to work on: %s" % task)
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# because the task queue manager starts workers (forks) before the
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# playbook is loaded, set the basedir of the loader inherted by
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# this fork now so that we can find files correctly
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self._loader.set_basedir(basedir)
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# because the task queue manager starts workers (forks) before the
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# playbook is loaded, set the basedir of the loader inherted by
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# this fork now so that we can find files correctly
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self._loader.set_basedir(basedir)
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# Serializing/deserializing tasks does not preserve the loader attribute,
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# since it is passed to the worker during the forking of the process and
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# would be wasteful to serialize. So we set it here on the task now, and
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# the task handles updating parent/child objects as needed.
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task.set_loader(self._loader)
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# Serializing/deserializing tasks does not preserve the loader attribute,
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# since it is passed to the worker during the forking of the process and
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# would be wasteful to serialize. So we set it here on the task now, and
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# the task handles updating parent/child objects as needed.
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task.set_loader(self._loader)
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# apply the given task's information to the connection info,
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# which may override some fields already set by the play or
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# the options specified on the command line
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new_play_context = play_context.set_task_and_variable_override(task=task, variables=job_vars)
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# apply the given task's information to the connection info,
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# which may override some fields already set by the play or
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# the options specified on the command line
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new_play_context = play_context.set_task_and_variable_override(task=task, variables=job_vars)
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# execute the task and build a TaskResult from the result
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debug("running TaskExecutor() for %s/%s" % (host, task))
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executor_result = TaskExecutor(host, task, job_vars, new_play_context, self._new_stdin, self._loader, shared_loader_obj).run()
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debug("done running TaskExecutor() for %s/%s" % (host, task))
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task_result = TaskResult(host, task, executor_result)
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# execute the task and build a TaskResult from the result
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debug("running TaskExecutor() for %s/%s" % (host, task))
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executor_result = TaskExecutor(host, task, job_vars, new_play_context, self._new_stdin, self._loader, shared_loader_obj).run()
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debug("done running TaskExecutor() for %s/%s" % (host, task))
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task_result = TaskResult(host, task, executor_result)
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# put the result on the result queue
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debug("sending task result")
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self._rslt_q.put(task_result, block=False)
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debug("done sending task result")
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else:
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time.sleep(0.1)
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# put the result on the result queue
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debug("sending task result")
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self._rslt_q.put(task_result)
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debug("done sending task result")
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except queue.Empty:
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pass
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