def test_populate_buckets(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
d = distribution.Distribution(
distribution.FixedWidthBucketer(10))
d.add(5)
d.add(15)
d.add(35)
d.add(65)
m._populate_value(pb, d)
self.assertEquals([1, 1, -1, 1, -2, 1], pb.distribution.bucket)
self.assertEquals(0, pb.distribution.underflow)
self.assertEquals(0, pb.distribution.overflow)
self.assertEquals(30, pb.distribution.mean)
pb = metrics_pb2.MetricsData()
d = distribution.Distribution(
distribution.FixedWidthBucketer(10, num_finite_buckets=1))
d.add(5)
d.add(15)
d.add(25)
m._populate_value(pb, d)
self.assertEquals([1], pb.distribution.bucket)
self.assertEquals(0, pb.distribution.underflow)
self.assertEquals(2, pb.distribution.overflow)
self.assertEquals(15, pb.distribution.mean)
def add(self, value, fields=None):
with self._thread_lock:
dist = self.get(fields)
if dist is None:
dist = distribution.Distribution(self.bucketer)
dist.add(value)
self._set_and_send_value(dist, fields)
def test_populate_canonical(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
m._populate_value(pb,
distribution.Distribution(distribution.GeometricBucketer()))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_10_P_0_2)
m._populate_value(pb,
distribution.Distribution(distribution.GeometricBucketer(2)))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_2)
m._populate_value(pb,
distribution.Distribution(distribution.GeometricBucketer(10)))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_10)
def test_populate_custom(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
m._populate_value(pb,
distribution.Distribution(distribution.GeometricBucketer(4)))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CUSTOM_PARAMETERIZED)
self.assertEquals(0, pb.distribution.width)
self.assertEquals(4, pb.distribution.growth_factor)
self.assertEquals(100, pb.distribution.num_buckets)
m._populate_value(pb,
distribution.Distribution(distribution.FixedWidthBucketer(10)))
self.assertEquals(pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CUSTOM_PARAMETERIZED)
self.assertEquals(10, pb.distribution.width)
self.assertEquals(0, pb.distribution.growth_factor)
self.assertEquals(100, pb.distribution.num_buckets)
def test_populate_buckets_last_zero(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
d = distribution.Distribution(
distribution.FixedWidthBucketer(10, num_finite_buckets=10))
d.add(5)
d.add(105)
m._populate_value(pb, d)
self.assertEquals([1], pb.distribution.bucket)
self.assertEquals(1, pb.distribution.overflow)
def test_populate_is_cumulative(self):
pb = metrics_pb2.MetricsData()
d = distribution.Distribution(
distribution.FixedWidthBucketer(10, num_finite_buckets=10))
m = metrics.CumulativeDistributionMetric('test')
m._populate_value(pb, d)
self.assertTrue(pb.distribution.is_cumulative)
m = metrics.NonCumulativeDistributionMetric('test2')
m._populate_value(pb, d)
self.assertFalse(pb.distribution.is_cumulative)
def test_populate_buckets_underflow(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
d = distribution.Distribution(
distribution.FixedWidthBucketer(10, num_finite_buckets=10))
d.add(-5)
d.add(-1000000)
m._populate_value(pb, d)
self.assertEquals([], pb.distribution.bucket)
self.assertEquals(2, pb.distribution.underflow)
self.assertEquals(0, pb.distribution.overflow)
self.assertEquals(-500002.5, pb.distribution.mean)
def test_overflow_bucket(self):
d = distribution.Distribution(
distribution.FixedWidthBucketer(width=10, num_finite_buckets=10))
d.add(100)
self.assertEqual(100, d.sum)
self.assertEqual(1, d.count)
self.assertEqual({11: 1}, d.buckets)
d.add(1000000)
self.assertEqual(1000100, d.sum)
self.assertEqual(2, d.count)
self.assertEqual({11: 2}, d.buckets)
def test_underflow_bucket(self):
d = distribution.Distribution(
distribution.FixedWidthBucketer(width=10))
d.add(-1)
self.assertEqual(-1, d.sum)
self.assertEqual(1, d.count)
self.assertEqual({0: 1}, d.buckets)
d.add(-1000000)
self.assertEqual(-1000001, d.sum)
self.assertEqual(2, d.count)
self.assertEqual({0: 2}, d.buckets)
def test_add_on_bucket_boundary(self):
d = distribution.Distribution(
distribution.FixedWidthBucketer(width=10))
d.add(10)
self.assertEqual(10, d.sum)
self.assertEqual(1, d.count)
self.assertEqual({2: 1}, d.buckets)
d.add(0)
self.assertEqual(10, d.sum)
self.assertEqual(2, d.count)
self.assertEqual({1: 1, 2: 1}, d.buckets)
def test_add(self):
d = distribution.Distribution(distribution.GeometricBucketer())
self.assertEqual(0, d.sum)
self.assertEqual(0, d.count)
self.assertEqual({}, d.buckets)
d.add(1)
d.add(10)
d.add(100)
self.assertEqual(111, d.sum)
self.assertEqual(3, d.count)
self.assertEqual({2: 1, 6: 1, 11: 1}, d.buckets)
d.add(50)
self.assertEqual(161, d.sum)
self.assertEqual(4, d.count)
self.assertEqual({2: 1, 6: 1, 10: 1, 11: 1}, d.buckets)
def test_set(self):
d = distribution.Distribution(
distribution.FixedWidthBucketer(10, num_finite_buckets=10))
d.add(1)
d.add(10)
d.add(100)
m = metrics.CumulativeDistributionMetric('test')
with self.assertRaises(TypeError):
m.set(d)
m = metrics.NonCumulativeDistributionMetric('test2')
m.set(d)
self.assertEquals(d, m.get())
with self.assertRaises(errors.MonitoringInvalidValueTypeError):
m.set(1)
with self.assertRaises(errors.MonitoringInvalidValueTypeError):
m.set('foo')
