def test_update_sampler_adaptive_sampler():
error_reporter = mock.MagicMock()
error_reporter.error = mock.MagicMock()
remote_sampler = RemoteControlledSampler(
channel=mock.MagicMock(),
service_name='x',
error_reporter=error_reporter,
max_operations=10,
)
response = {
"strategyType":"RATE_LIMITING",
"operationSampling":
{
"defaultSamplingProbability":0.001,
"defaultLowerBoundTracesPerSecond":2,
"perOperationStrategies":
[
{
"operation":"op",
"probabilisticSampling":{
"samplingRate":0.002
}
}
]
}
}
remote_sampler._update_sampler(response)
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.001000, 2.000000, 10)'
new_response = {
"strategyType":"RATE_LIMITING",
"operationSampling":
{
"defaultSamplingProbability":0.51,
"defaultLowerBoundTracesPerSecond":3,
"perOperationStrategies":
[
{
"operation":"op",
"probabilisticSampling":{
"samplingRate":0.002
}
}
]
}
}
remote_sampler._update_sampler(new_response)
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.510000, 3.000000, 10)'
remote_sampler._update_sampler({"strategyType":"PROBABILISTIC","probabilisticSampling":{"samplingRate":0.004}})
assert '%s' % remote_sampler.sampler == 'ProbabilisticSampler(0.004)', \
'should not fail going from adaptive sampler to probabilistic sampler'
remote_sampler._update_sampler({"strategyType":"RATE_LIMITING","operationSampling":{"defaultSamplingProbability":0.4}})
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.400000, 0.001667, 10)'
remote_sampler.close()
def test_update_sampler(response, init_sampler, expected_sampler, err_count, err_msg, reference_equivalence, max_operations):
error_reporter = mock.MagicMock()
error_reporter.error = mock.MagicMock()
remote_sampler = RemoteControlledSampler(
channel=mock.MagicMock(),
service_name='x',
error_reporter=error_reporter,
max_operations=max_operations,
init_sampler=init_sampler,
)
# noinspection PyProtectedMember
remote_sampler._update_sampler(response)
assert error_reporter.error.call_count == err_count
if reference_equivalence:
assert remote_sampler.sampler is expected_sampler, err_msg
else:
assert remote_sampler.sampler == expected_sampler, err_msg
remote_sampler.close()
def test_update_sampler(response, init_sampler, expected_sampler,
err_count, err_msg, reference_equivalence, max_operations):
error_reporter = mock.MagicMock()
error_reporter.error = mock.MagicMock()
remote_sampler = RemoteControlledSampler(
channel=mock.MagicMock(),
service_name='x',
error_reporter=error_reporter,
max_operations=max_operations,
init_sampler=init_sampler,
)
# noinspection PyProtectedMember
remote_sampler._update_sampler(response)
assert error_reporter.error.call_count == err_count
if reference_equivalence:
assert remote_sampler.sampler is expected_sampler, err_msg
else:
assert remote_sampler.sampler == expected_sampler, err_msg
remote_sampler.close()
def test_update_sampler_adaptive_sampler():
error_reporter = mock.MagicMock()
error_reporter.error = mock.MagicMock()
remote_sampler = RemoteControlledSampler(
channel=mock.MagicMock(),
service_name='x',
error_reporter=error_reporter,
max_operations=10,
)
response = {
'strategyType': 'RATE_LIMITING',
'operationSampling': {
'defaultSamplingProbability':
0.001,
'defaultLowerBoundTracesPerSecond':
2,
'perOperationStrategies': [{
'operation': 'op',
'probabilisticSampling': {
'samplingRate': 0.002
}
}]
}
}
remote_sampler._update_sampler(response)
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.001000, 2.000000, 10)'
new_response = {
'strategyType': 'RATE_LIMITING',
'operationSampling': {
'defaultSamplingProbability':
0.51,
'defaultLowerBoundTracesPerSecond':
3,
'perOperationStrategies': [{
'operation': 'op',
'probabilisticSampling': {
'samplingRate': 0.002
}
}]
}
}
remote_sampler._update_sampler(new_response)
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.510000, 3.000000, 10)'
remote_sampler._update_sampler({
'strategyType': 'PROBABILISTIC',
'probabilisticSampling': {
'samplingRate': 0.004
}
})
assert '%s' % remote_sampler.sampler == 'ProbabilisticSampler(0.004)', \
'should not fail going from adaptive sampler to probabilistic sampler'
remote_sampler._update_sampler({
'strategyType': 'RATE_LIMITING',
'operationSampling': {
'defaultSamplingProbability': 0.4
}
})
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.400000, 0.001667, 10)'
remote_sampler.close()
def test_update_sampler_adaptive_sampler():
error_reporter = mock.MagicMock()
error_reporter.error = mock.MagicMock()
remote_sampler = RemoteControlledSampler(
channel=mock.MagicMock(),
service_name='x',
error_reporter=error_reporter,
max_operations=10,
)
response = {
'strategyType': 'RATE_LIMITING',
'operationSampling':
{
'defaultSamplingProbability': 0.001,
'defaultLowerBoundTracesPerSecond': 2,
'perOperationStrategies':
[
{
'operation': 'op',
'probabilisticSampling': {
'samplingRate': 0.002
}
}
]
}
}
remote_sampler._update_sampler(response)
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.001000, 2.000000, 10)'
new_response = {
'strategyType': 'RATE_LIMITING',
'operationSampling':
{
'defaultSamplingProbability': 0.51,
'defaultLowerBoundTracesPerSecond': 3,
'perOperationStrategies':
[
{
'operation': 'op',
'probabilisticSampling': {
'samplingRate': 0.002
}
}
]
}
}
remote_sampler._update_sampler(new_response)
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.510000, 3.000000, 10)'
remote_sampler._update_sampler(
{'strategyType': 'PROBABILISTIC', 'probabilisticSampling': {'samplingRate': 0.004}})
assert '%s' % remote_sampler.sampler == 'ProbabilisticSampler(0.004)', \
'should not fail going from adaptive sampler to probabilistic sampler'
remote_sampler._update_sampler({'strategyType': 'RATE_LIMITING',
'operationSampling': {'defaultSamplingProbability': 0.4}})
assert '%s' % remote_sampler.sampler == 'AdaptiveSampler(0.400000, 0.001667, 10)'
remote_sampler.close()