Changes to support ramp-up feature (#725)

Signed-off-by: Rishabh Singh <[email protected]>

Author: rishabh6788

.pylintrc

@@ -360,7 +360,7 @@ indent-after-paren=4
 indent-string='    '
 
 # Maximum number of characters on a single line.
-max-line-length=140
+max-line-length=180
 
 # Maximum number of lines in a module.
 max-module-lines=1000

osbenchmark/resources/workload-schema.json

@@ -28,6 +28,11 @@
                 "type": "integer",
                 "minimum": 1
               },
+              "ramp-up-time-period": {
+                "type": "integer",
+                "minimum": 0,
+                "description": "Defines the time period in seconds to gradually increase the number of clients."
+              },
               "warmup-time-period": {
                 "type": "integer",
                 "minimum": 0,
@@ -75,6 +80,11 @@
                       "minimum": 1,
                       "description": "Defines the number of times to run the operation."
                     },
+                    "ramp-up-time-period": {
+                      "type": "integer",
+                      "minimum": 0,
+                      "description": "Defines the time period in seconds to gradually increase the number of clients."
+                    },
                     "warmup-time-period": {
                       "type": "integer",
                       "minimum": 0,
@@ -146,6 +156,11 @@
             "minimum": 1,
             "description": "Defines the number of times to run the operation."
           },
+          "ramp-up-time-period": {
+            "type": "integer",
+            "minimum": 0,
+            "description": "Defines the time period in seconds to gradually increase the number of clients."
+          },
           "warmup-time-period": {
             "type": "integer",
             "minimum": 0,

osbenchmark/worker_coordinator/worker_coordinator.py

@@ -1522,7 +1522,7 @@ def os_clients(all_hosts, all_client_options):
             #
             # Now we need to ensure that we start partitioning parameters correctly in both cases. And that means we
             # need to start from (client) index 0 in both cases instead of 0 for indexA and 4 for indexB.
-            schedule = schedule_for(task, task_allocation.client_index_in_task, params_per_task[task])
+            schedule = schedule_for(task_allocation, params_per_task[task])
             async_executor = AsyncExecutor(
                 client_id, task, schedule, opensearch, self.sampler, self.cancel, self.complete,
                 task.error_behavior(self.abort_on_error), self.cfg)
@@ -1607,6 +1607,15 @@ async def __call__(self, *args, **kwargs):
         # lazily initialize the schedule
         self.logger.debug("Initializing schedule for client id [%s].", self.client_id)
         schedule = self.schedule_handle()
+        self.schedule_handle.start()
+        rampup_wait_time = self.schedule_handle.ramp_up_wait_time
+        if rampup_wait_time:
+            self.logger.info("client id [%s] waiting [%.2f]s for ramp-up.", self.client_id, rampup_wait_time)
+            await asyncio.sleep(rampup_wait_time)
+
+        if rampup_wait_time:
+            console.println(f" Client id {self.client_id} is running now.")
+
         self.logger.debug("Entering main loop for client id [%s].", self.client_id)
         # noinspection PyBroadException
         try:
@@ -1806,18 +1815,28 @@ def __repr__(self, *args, **kwargs):
 
 
 class TaskAllocation:
-    def __init__(self, task, client_index_in_task):
+    def __init__(self, task, client_index_in_task, global_client_index, total_clients):
+        """
+        :param task: The current task which is always a leaf task.
+        :param client_index_in_task: The task-specific index for the allocated client.
+        :param global_client_index:  The globally unique index for the allocated client across
+                                     all concurrently executed tasks.
+        :param total_clients: The total number of clients executing tasks concurrently.
+        """
         self.task = task
         self.client_index_in_task = client_index_in_task
+        self.global_client_index = global_client_index
+        self.total_clients = total_clients
 
     def __hash__(self):
-        return hash(self.task) ^ hash(self.client_index_in_task)
+        return hash(self.task) ^ hash(self.global_client_index)
 
     def __eq__(self, other):
-        return isinstance(other, type(self)) and self.task == other.task and self.client_index_in_task == other.client_index_in_task
+        return isinstance(other, type(self)) and self.task == other.task and self.global_client_index == other.global_client_index
 
     def __repr__(self, *args, **kwargs):
-        return "TaskAllocation [%d/%d] for %s" % (self.client_index_in_task, self.task.clients, self.task)
+        return f"TaskAllocation [{self.client_index_in_task}/{self.task.clients}] for {self.task} " \
+               f"and [{self.global_client_index}/{self.total_clients}] in total"
 
 
 class Allocator:
@@ -1858,12 +1877,16 @@ def allocations(self):
             clients_executing_completing_task = []
             for sub_task in task:
                 for client_index in range(start_client_index, start_client_index + sub_task.clients):
-                    # this is the actual client that will execute the task. It may differ from the logical one in case we over-commit (i.e.
-                    # more tasks than actually available clients)
                     physical_client_index = client_index % max_clients
                     if sub_task.completes_parent:
                         clients_executing_completing_task.append(physical_client_index)
-                    allocations[physical_client_index].append(TaskAllocation(sub_task, client_index - start_client_index))
+                    ta = TaskAllocation(task = sub_task,
+                                        client_index_in_task = client_index - start_client_index,
+                                        global_client_index=client_index,
+                                        # if task represents a parallel structure this is the total number of clients
+                                        # executing sub-tasks concurrently.
+                                        total_clients=task.clients)
+                    allocations[physical_client_index].append(ta)
                 start_client_index += sub_task.clients
 
             # uneven distribution between tasks and clients, e.g. there are 5 (parallel) tasks but only 2 clients. Then, one of them
@@ -1941,7 +1964,7 @@ def clients(self):
 
 # Runs a concrete schedule on one worker client
 # Needs to determine the runners and concrete iterations per client.
-def schedule_for(task, client_index, parameter_source):
+def schedule_for(task_allocation, parameter_source):
     """
     Calculates a client's schedule for a given task.
 
@@ -1951,15 +1974,17 @@ def schedule_for(task, client_index, parameter_source):
     :return: A generator for the operations the given client needs to perform for this task.
     """
     logger = logging.getLogger(__name__)
+    task = task_allocation.task
     op = task.operation
-    num_clients = task.clients
     sched = scheduler.scheduler_for(task)
+
+    client_index = task_allocation.client_index_in_task
     # guard all logging statements with the client index and only emit them for the first client. This information is
     # repetitive and may cause issues in thespian with many clients (an excessive number of actor messages is sent).
     if client_index == 0:
         logger.info("Choosing [%s] for [%s].", sched, task)
     runner_for_op = runner.runner_for(op.type)
-    params_for_op = parameter_source.partition(client_index, num_clients)
+    params_for_op = parameter_source.partition(client_index, task.clients)
     if hasattr(sched, "parameter_source"):
         if client_index == 0:
             logger.debug("Setting parameter source [%s] for scheduler [%s]", params_for_op, sched)
@@ -1992,7 +2017,7 @@ def schedule_for(task, client_index, parameter_source):
         else:
             logger.info("%s schedule will determine when the schedule for [%s] terminates.", str(loop_control), task.name)
 
-    return ScheduleHandle(task.name, sched, loop_control, runner_for_op, params_for_op)
+    return ScheduleHandle(task_allocation, sched, loop_control, runner_for_op, params_for_op)
 
 
 def requires_time_period_schedule(task, task_runner, params):
@@ -2009,27 +2034,40 @@ def requires_time_period_schedule(task, task_runner, params):
 
 
 class ScheduleHandle:
-    def __init__(self, task_name, sched, task_progress_control, runner, params):
+    def __init__(self, task_allocation, sched, task_progress_control, runner, params):
         """
         Creates a generator that will yield individual task invocations for the provided schedule.
 
-        :param task_name: The name of the task for which the schedule is generated.
+        :param task_allocation: The task allocation for which the schedule is generated.
         :param sched: The scheduler for this task.
         :param task_progress_control: Controls how and how often this generator will loop.
         :param runner: The runner for a given operation.
         :param params: The parameter source for a given operation.
         :return: A generator for the corresponding parameters.
         """
-        self.task_name = task_name
+        self.task_allocation = task_allocation
         self.sched = sched
         self.task_progress_control = task_progress_control
         self.runner = runner
         self.params = params
         # TODO: Can we offload the parameter source execution to a different thread / process? Is this too heavy-weight?
-        #from concurrent.futures import ThreadPoolExecutor
-        #import asyncio
-        #self.io_pool_exc = ThreadPoolExecutor(max_workers=1)
-        #self.loop = asyncio.get_event_loop()
+        # from concurrent.futures import ThreadPoolExecutor
+        # import asyncio
+        # self.io_pool_exc = ThreadPoolExecutor(max_workers=1)
+        # self.loop = asyncio.get_event_loop()
+    @property
+    def ramp_up_wait_time(self):
+        """
+        :return: the number of seconds to wait until this client should start so load can gradually ramp-up.
+        """
+        ramp_up_time_period = self.task_allocation.task.ramp_up_time_period
+        if ramp_up_time_period:
+            return ramp_up_time_period * (self.task_allocation.global_client_index / self.task_allocation.total_clients)
+        else:
+            return 0
+
+    def start(self):
+        self.task_progress_control.start()
 
     def before_request(self, now):
         self.sched.before_request(now)
@@ -2041,20 +2079,18 @@ async def __call__(self):
         next_scheduled = 0
         if self.task_progress_control.infinite:
             param_source_knows_progress = hasattr(self.params, "percent_completed")
-            self.task_progress_control.start()
             while True:
                 try:
                     next_scheduled = self.sched.next(next_scheduled)
                     # does not contribute at all to completion. Hence, we cannot define completion.
                     percent_completed = self.params.percent_completed if param_source_knows_progress else None
-                    #current_params = await self.loop.run_in_executor(self.io_pool_exc, self.params.params)
+                    # current_params = await self.loop.run_in_executor(self.io_pool_exc, self.params.params)
                     yield (next_scheduled, self.task_progress_control.sample_type, percent_completed, self.runner,
                            self.params.params())
                     self.task_progress_control.next()
                 except StopIteration:
                     return
         else:
-            self.task_progress_control.start()
             while not self.task_progress_control.completed:
                 try:
                     next_scheduled = self.sched.next(next_scheduled)

osbenchmark/workload/loader.py

@@ -1765,14 +1765,24 @@ def parse_parallel(self, ops_spec, ops, test_procedure_name):
         default_iterations = self._r(ops_spec, "iterations", error_ctx="parallel", mandatory=False)
         default_warmup_time_period = self._r(ops_spec, "warmup-time-period", error_ctx="parallel", mandatory=False)
         default_time_period = self._r(ops_spec, "time-period", error_ctx="parallel", mandatory=False)
+        default_ramp_up_time_period = self._r(ops_spec, "ramp-up-time-period", error_ctx="parallel", mandatory=False)
         clients = self._r(ops_spec, "clients", error_ctx="parallel", mandatory=False)
         completed_by = self._r(ops_spec, "completed-by", error_ctx="parallel", mandatory=False)
 
         # now descent to each operation
         tasks = []
         for task in self._r(ops_spec, "tasks", error_ctx="parallel"):
             tasks.append(self.parse_task(task, ops, test_procedure_name, default_warmup_iterations, default_iterations,
-                                         default_warmup_time_period, default_time_period, completed_by))
+                                         default_warmup_time_period, default_time_period, default_ramp_up_time_period, completed_by))
+
+        for task in tasks:
+            if task.ramp_up_time_period != default_ramp_up_time_period:
+                if default_ramp_up_time_period is None:
+                    self._error(f"task '{task.name}' in 'parallel' element of test-procedure '{test_procedure_name}' specifies "
+                                f"a ramp-up-time-period but it is only allowed on the 'parallel' element.")
+                else:
+                    self._error(f"task '{task.name}' specifies a different ramp-up-time-period than its enclosing "
+                                f"'parallel' element in test-procedure '{test_procedure_name}'.")
         if completed_by:
             completion_task = None
             for task in tasks:
@@ -1788,7 +1798,8 @@ def parse_parallel(self, ops_spec, ops, test_procedure_name):
         return workload.Parallel(tasks, clients)
 
     def parse_task(self, task_spec, ops, test_procedure_name, default_warmup_iterations=None, default_iterations=None,
-                   default_warmup_time_period=None, default_time_period=None, completed_by_name=None):
+                   default_warmup_time_period=None, default_time_period=None, default_ramp_up_time_period=None,
+                   completed_by_name=None):
 
         op_spec = task_spec["operation"]
         if isinstance(op_spec, str) and op_spec in ops:
@@ -1811,6 +1822,8 @@ def parse_task(self, task_spec, ops, test_procedure_name, default_warmup_iterati
                                                      default_value=default_warmup_time_period),
                           time_period=self._r(task_spec, "time-period", error_ctx=op.name, mandatory=False,
                                               default_value=default_time_period),
+                          ramp_up_time_period=self._r(task_spec, "ramp-up-time-period", error_ctx=op.name,
+                                                         mandatory=False, default_value=default_ramp_up_time_period),
                           clients=self._r(task_spec, "clients", error_ctx=op.name, mandatory=False, default_value=1),
                           completes_parent=(task_name == completed_by_name),
                           schedule=schedule,
@@ -1819,11 +1832,25 @@ def parse_task(self, task_spec, ops, test_procedure_name, default_warmup_iterati
         if task.warmup_iterations is not None and task.time_period is not None:
             self._error(
                 "Operation '%s' in test_procedure '%s' defines '%d' warmup iterations and a time period of '%d' seconds. Please do not "
-                        "mix time periods and iterations." % (op.name, test_procedure_name, task.warmup_iterations, task.time_period))
+                "mix time periods and iterations." % (op.name, test_procedure_name, task.warmup_iterations, task.time_period))
         elif task.warmup_time_period is not None and task.iterations is not None:
             self._error(
                 "Operation '%s' in test_procedure '%s' defines a warmup time period of '%d' seconds and '%d' iterations. Please do not "
-                        "mix time periods and iterations." % (op.name, test_procedure_name, task.warmup_time_period, task.iterations))
+                "mix time periods and iterations." % (op.name, test_procedure_name, task.warmup_time_period, task.iterations))
+
+        if (task.warmup_iterations is not None or task.iterations is not None) and task.ramp_up_time_period is not None:
+            self._error(f"Operation '{op.name}' in test_procedure '{test_procedure_name}' defines a ramp-up time period of "
+                        f"{task.ramp_up_time_period} seconds as well as {task.warmup_iterations} warmup iterations and "
+                        f"{task.iterations} iterations but mixing time periods and iterations is not allowed.")
+
+        if task.ramp_up_time_period is not None:
+            if task.warmup_time_period is None:
+                self._error(f"Operation '{op.name}' in test_procedure '{test_procedure_name}' defines a ramp-up time period of "
+                            f"{task.ramp_up_time_period} seconds but no warmup-time-period.")
+            elif task.warmup_time_period < task.ramp_up_time_period:
+                self._error(f"The warmup-time-period of operation '{op.name}' in test_procedure '{test_procedure_name}' is "
+                            f"{task.warmup_time_period} seconds but must be greater than or equal to the "
+                            f"ramp-up-time-period of {task.ramp_up_time_period} seconds.")
 
         return task