def test_sample_data_over_time_1():
time = MockedTime()
percentile = RollingPercentile(time, 60000, 12, 1000, True)
previous_time = 0
for time_millis, latency in sample_data_holder_1:
time.increment(time_millis - previous_time)
previous_time = time_millis
percentile.add_value(latency)
print('0.01', percentile.percentile(0.01))
print('Median', percentile.percentile(50))
print('90th', percentile.percentile(90))
print('99th', percentile.percentile(99))
print('99.5th', percentile.percentile(99.5))
print('99.99', percentile.percentile(99.99))
print('Median', percentile.percentile(50))
print('Median', percentile.percentile(50))
print('Median', percentile.percentile(50))
# In a loop as a use case was found where very different values were
# calculated in subsequent requests.
for _ in range(10):
percentile50 = percentile.percentile(50)
if percentile50 > 5:
pytest.fail('We expect around 2 but got: {}'.format(percentile50))
percentile995 = percentile.percentile(99.5)
if percentile995 < 20:
msg = 'We expect to see some high values over 20 but got: {}'
pytest.fail(msg.format(percentile995))
def test_value_is_zero_after_rolling_window_passes_and_no_traffic():
time = MockedTime()
percentile = RollingPercentile(time, 60000, 12, 1000, True)
percentile.add_value(1000)
percentile.add_value(1000)
percentile.add_value(1000)
percentile.add_value(2000)
percentile.add_value(4000)
assert percentile.buckets.size == 1
# No bucket turnover yet so percentile not yet generated
assert percentile.percentile(50) == 0
time.increment(6000)
# Still only 1 bucket until we touch it again
assert percentile.buckets.size == 1
# A bucket has been created so we have a new percentile
assert percentile.percentile(50) == 1500
# Let 1 minute pass
time.increment(60000)
# No data in a minute should mean all buckets are empty (or reset) so we
# should not have any percentiles
assert percentile.percentile(50) == 0
def test_rolling():
time = MockedTime()
percentile = RollingPercentile(time, 60000, 12, 1000, True)
percentile.add_value(1000)
percentile.add_value(1000)
percentile.add_value(1000)
percentile.add_value(2000)
assert percentile.buckets.size == 1
# No bucket turnover yet so percentile not yet generated
assert percentile.percentile(50) == 0
time.increment(6000)
# Still only 1 bucket until we touch it again
assert percentile.buckets.size == 1
# A bucket has been created so we have a new percentile
assert percentile.percentile(50) == 1000
# Now 2 buckets since getting a percentile causes bucket retrieval
assert percentile.buckets.size == 2
percentile.add_value(1000)
percentile.add_value(500)
assert percentile.buckets.size == 2
percentile.add_value(200)
percentile.add_value(200)
percentile.add_value(1600)
percentile.add_value(200)
percentile.add_value(1600)
percentile.add_value(1600)
# We haven't progressed to a new bucket so the percentile should be the
# same and ignore the most recent bucket
assert percentile.percentile(50) == 1000
# Increment to another bucket so we include all of the above in the
# PercentileSnapshot
time.increment(6000)
# The rolling version should have the same data as creating a snapshot
# like this
snapshot = PercentileSnapshot(1000, 1000, 1000, 2000, 1000, 500, 200, 200,
1600, 200, 1600, 1600)
assert snapshot.percentile(0.15) == percentile.percentile(0.15)
assert snapshot.percentile(0.50) == percentile.percentile(0.50)
assert snapshot.percentile(0.90) == percentile.percentile(0.90)
assert snapshot.percentile(0.995) == percentile.percentile(0.995)
# mean = 1000+1000+1000+2000+1000+500+200+200+1600+200+1600+1600/12
assert snapshot.mean() == 991
def test_does_nothing_when_disabled():
time = MockedTime()
percentile = RollingPercentile(time, 60000, 12, 1000, False)
previous_time = 0
for time_millis, latency in sample_data_holder_2:
time.increment(time_millis - previous_time)
previous_time = time_millis
percentile.add_value(latency)
assert percentile.percentile(50) == -1
assert percentile.percentile(75) == -1
assert percentile.mean() == -1
def test_sample_data_over_time_2():
time = MockedTime()
percentile = RollingPercentile(time, 60000, 12, 1000, True)
previous_time = 0
for time_millis, latency in sample_data_holder_2:
time.increment(time_millis - previous_time)
previous_time = time_millis
percentile.add_value(latency)
print('0.01', percentile.percentile(0.01))
print('Median', percentile.percentile(50))
print('90th', percentile.percentile(90))
print('99th', percentile.percentile(99))
print('99.5th', percentile.percentile(99.5))
print('99.99', percentile.percentile(99.99))
percentile50 = percentile.percentile(50)
if percentile50 > 90 or percentile50 < 50:
pytest.fail('We expect around 60-70 but got: {}'.format(percentile50))
percentile99 = percentile.percentile(99)
if percentile99 < 400:
msg = 'We expect to see some high values over 400 but got: {}'
pytest.fail(msg.format(percentile99))