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"""A microbenchmark for measuring DistributionAccumulator performance
This runs a sequence of distribution.update for random input value to calculate
average update time per input.
A typical update operation should run into 0.6 microseconds
Run as
python -m apache_beam.tools.distribution_counter_microbenchmark
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import random
import sys
import time
from builtins import range
from apache_beam.tools import utils
[docs]def run_benchmark(num_runs=100, num_input=10000, seed=time.time()):
total_time = 0
random.seed(seed)
lower_bound = 0
upper_bound = sys.maxsize
inputs = generate_input_values(num_input, lower_bound, upper_bound)
from apache_beam.transforms import DataflowDistributionCounter
print("Number of runs:", num_runs)
print("Input size:", num_input)
print("Input sequence from %d to %d" % (lower_bound, upper_bound))
print("Random seed:", seed)
for i in range(num_runs):
counter = DataflowDistributionCounter()
start = time.time()
counter.add_inputs_for_test(inputs)
time_cost = time.time() - start
print("Run %d: Total time cost %g sec" % (i+1, time_cost))
total_time += time_cost / num_input
print("Per element update time cost:", total_time / num_runs)
if __name__ == '__main__':
utils.check_compiled(
'apache_beam.transforms.cy_dataflow_distribution_counter')
run_benchmark()