def write_stage_info(self, query_id, prefix):
f = open("%s_stage_info" % prefix, "a")
last_stage_runtime = -1
last_stage_finish_time = 0
for stage in self.stages.values():
# This is a hack! Count the most recent stage with runtime > 1s as the "last".
# Shark produces 1-2 very short stages at the end that do not seem to do anything (and
# certainly aren't doing the output write we're trying to account for).
if (stage.finish_time() - stage.start_time) > 1000 and stage.finish_time() > last_stage_finish_time:
last_stage_finish_time = stage.finish_time()
last_stage_runtime = stage.finish_time() - stage.start_time
f.write("%s\t%s\t%s\n" % (query_id, last_stage_runtime, self.original_runtime()))
f.close()
def write_stage_info(self, query_id, prefix):
f = open("%s_stage_info" % prefix, "a")
last_stage_runtime = -1
last_stage_finish_time = 0
for stage in self.stages.values():
# This is a hack! Count the most recent stage with runtime > 1s as the "last".
# Shark produces 1-2 very short stages at the end that do not seem to do anything (and
# certainly aren't doing the output write we're trying to account for).
if (stage.finish_time() - stage.start_time) > 1000 and stage.finish_time() > last_stage_finish_time:
last_stage_finish_time = stage.finish_time()
last_stage_runtime = stage.finish_time() - stage.start_time
f.write("%s\t%s\t%s\n" % (query_id, last_stage_runtime, self.original_runtime()))
f.close()
def replace_stragglers_with_median_speedup(self, threshold_fn):
""" Returns how much faster the job would have run if there were no stragglers.
For each stage, passes the list of task runtimes into threshold_fn, which should
return a threshold runtime. Then, replaces all task runtimes greater than the given
threshold with the median runtime.
For example, to replace the tasks with the longest 5% of runtimes with the median:
self.replace_stragglers_with_median_speedup(lambda runtimes: numpy.percentile(runtimes, 95)
"""
self.print_heading("Computing speedup from replacing straggler tasks with median")
total_no_stragglers_runtime = 0
start_and_runtimes_for_combined_stages = []
original_start_and_runtimes_for_combined_stages = []
num_stragglers_combined_stages = 0
for id, stage in self.stages.iteritems():
runtimes = [task.runtime() for task in stage.tasks]
median_runtime = numpy.percentile(runtimes, 50)
threshold_runtime = threshold_fn(runtimes)
no_straggler_start_and_runtimes = []
num_stragglers = 0
sorted_stage_tasks = sorted(stage.tasks, key = lambda t: t.runtime())
for task in sorted_stage_tasks:
if task.runtime() >= threshold_runtime:
assert(median_runtime <= task.runtime())
no_straggler_start_and_runtimes.append((task.start_time, median_runtime))
num_stragglers += 1
else:
no_straggler_start_and_runtimes.append((task.start_time, task.runtime()))
if id in self.stages_to_combine:
start_and_runtimes_for_combined_stages.extend(no_straggler_start_and_runtimes)
original_start_and_runtimes_for_combined_stages.extend(
[(t.start_time, t.runtime()) for t in stage.tasks])
num_stragglers_combined_stages += num_stragglers
else:
max_concurrency = concurrency.get_max_concurrency(stage.tasks)
no_stragglers_runtime = simulate.simulate(
[x[1] for x in no_straggler_start_and_runtimes], max_concurrency)[0]
total_no_stragglers_runtime += no_stragglers_runtime
original_runtime = simulate.simulate(
[task.runtime() for task in sorted_stage_tasks], max_concurrency)[0]
print ("%s: Original: %s, Orig (sim): %s, no stragg: %s (%s stragglers)" %
(id, stage.finish_time() - stage.start_time, original_runtime, no_stragglers_runtime,
num_stragglers))
if len(start_and_runtimes_for_combined_stages) > 0:
original_start_time = min([x[0] for x in start_and_runtimes_for_combined_stages])
original_finish_time = max([x[0] + x[1] for x in start_and_runtimes_for_combined_stages])
start_and_runtimes_for_combined_stages.sort()
runtimes_for_combined_stages = [x[1] for x in start_and_runtimes_for_combined_stages]
new_runtime = simulate.simulate(
runtimes_for_combined_stages, self.combined_stages_concurrency)[0]
original_runtime = simulate.simulate(
[x[1] for x in sorted(original_start_and_runtimes_for_combined_stages)],
self.combined_stages_concurrency)[0]
print ("Combined: Original: %s, Orig (sim): %s, no stragg: %s (%s stragglers)" %
(original_finish_time - original_start_time, original_runtime, new_runtime,
num_stragglers_combined_stages))
total_no_stragglers_runtime += new_runtime
return total_no_stragglers_runtime * 1.0 / self.get_simulated_runtime()
def replace_stragglers_with_median_speedup(self, threshold_fn):
""" Returns how much faster the job would have run if there were no stragglers.
For each stage, passes the list of task runtimes into threshold_fn, which should
return a threshold runtime. Then, replaces all task runtimes greater than the given
threshold with the median runtime.
For example, to replace the tasks with the longest 5% of runtimes with the median:
self.replace_stragglers_with_median_speedup(lambda runtimes: numpy.percentile(runtimes, 95)
"""
self.print_heading("Computing speedup from replacing straggler tasks with median")
total_no_stragglers_runtime = 0
start_and_runtimes_for_combined_stages = []
original_start_and_runtimes_for_combined_stages = []
num_stragglers_combined_stages = 0
for id, stage in self.stages.iteritems():
runtimes = [task.runtime() for task in stage.tasks]
median_runtime = numpy.percentile(runtimes, 50)
threshold_runtime = threshold_fn(runtimes)
no_straggler_start_and_runtimes = []
num_stragglers = 0
sorted_stage_tasks = sorted(stage.tasks, key = lambda t: t.runtime())
for task in sorted_stage_tasks:
if task.runtime() >= threshold_runtime:
assert(median_runtime <= task.runtime())
no_straggler_start_and_runtimes.append((task.start_time, median_runtime))
num_stragglers += 1
else:
no_straggler_start_and_runtimes.append((task.start_time, task.runtime()))
if id in self.stages_to_combine:
start_and_runtimes_for_combined_stages.extend(no_straggler_start_and_runtimes)
original_start_and_runtimes_for_combined_stages.extend(
[(t.start_time, t.runtime()) for t in stage.tasks])
num_stragglers_combined_stages += num_stragglers
else:
max_concurrency = concurrency.get_max_concurrency(stage.tasks)
no_stragglers_runtime = simulate.simulate(
[x[1] for x in no_straggler_start_and_runtimes], max_concurrency)[0]
total_no_stragglers_runtime += no_stragglers_runtime
original_runtime = simulate.simulate(
[task.runtime() for task in sorted_stage_tasks], max_concurrency)[0]
print ("%s: Original: %s, Orig (sim): %s, no stragg: %s (%s stragglers)" %
(id, stage.finish_time() - stage.start_time, original_runtime, no_stragglers_runtime,
num_stragglers))
if len(start_and_runtimes_for_combined_stages) > 0:
original_start_time = min([x[0] for x in start_and_runtimes_for_combined_stages])
original_finish_time = max([x[0] + x[1] for x in start_and_runtimes_for_combined_stages])
start_and_runtimes_for_combined_stages.sort()
runtimes_for_combined_stages = [x[1] for x in start_and_runtimes_for_combined_stages]
new_runtime = simulate.simulate(
runtimes_for_combined_stages, self.combined_stages_concurrency)[0]
original_runtime = simulate.simulate(
[x[1] for x in sorted(original_start_and_runtimes_for_combined_stages)],
self.combined_stages_concurrency)[0]
print ("Combined: Original: %s, Orig (sim): %s, no stragg: %s (%s stragglers)" %
(original_finish_time - original_start_time, original_runtime, new_runtime,
num_stragglers_combined_stages))
total_no_stragglers_runtime += new_runtime
return total_no_stragglers_runtime * 1.0 / self.get_simulated_runtime()
def no_stragglers_perfect_parallelism_speedup(self):
""" Returns how fast the job would have run if time were perfectly spread across 32 slots. """
ideal_runtime = 0
total_runtime_combined_stages = 0
for id, stage in self.stages.iteritems():
if id in self.stages_to_combine:
total_runtime_combined_stages += stage.total_runtime()
else:
new_runtime = float(stage.total_runtime()) / concurrency.get_max_concurrency(stage.tasks)
print "New runtime: %s, original runtime: %s" % (new_runtime, stage.finish_time() - stage.start_time)
ideal_runtime += new_runtime
print "Total runtime combined: %s (concurrency %d" % (total_runtime_combined_stages, self.combined_stages_concurrency)
ideal_runtime += float(total_runtime_combined_stages) / self.combined_stages_concurrency
print "Getting simulated runtime"
simulated_actual_runtime = self.get_simulated_runtime()
print "Ideal runtime for all: %s, simulated: %s" % (ideal_runtime, simulated_actual_runtime)
return ideal_runtime / simulated_actual_runtime
def no_stragglers_perfect_parallelism_speedup(self):
""" Returns how fast the job would have run if time were perfectly spread across 32 slots. """
ideal_runtime = 0
total_runtime_combined_stages = 0
for id, stage in self.stages.iteritems():
if id in self.stages_to_combine:
total_runtime_combined_stages += stage.total_runtime()
else:
new_runtime = float(stage.total_runtime()) / concurrency.get_max_concurrency(stage.tasks)
print "New runtime: %s, original runtime: %s" % (new_runtime, stage.finish_time() - stage.start_time)
ideal_runtime += new_runtime
print "Total runtime combined: %s (concurrency %d" % (total_runtime_combined_stages, self.combined_stages_concurrency)
ideal_runtime += float(total_runtime_combined_stages) / self.combined_stages_concurrency
print "Getting simulated runtime"
simulated_actual_runtime = self.get_simulated_runtime()
print "Ideal runtime for all: %s, simulated: %s" % (ideal_runtime, simulated_actual_runtime)
return ideal_runtime / simulated_actual_runtime
