func TestPrintDistribution(t *testing.T) {
var (
quantiles = []int{50, 90, 95, 99}
h = expvar.NewHistogram("test_print_distribution", 0, 100, 3, quantiles...)
seed = int64(555)
mean = int64(5)
stdev = int64(1)
)
teststat.PopulateNormalHistogram(t, h, seed, mean, stdev)
var buf bytes.Buffer
metrics.PrintDistribution(&buf, h)
t.Logf("\n%s\n", buf.String())
// Count the number of bar chart characters.
// We should have ca. 100 in any distribution with a small-enough stdev.
var n int
for _, r := range buf.String() {
if r == '#' {
n++
}
}
if want, have, tol := 100, n, 5; int(math.Abs(float64(want-have))) > tol {
t.Errorf("want %d, have %d (tolerance %d)", want, have, tol)
}
}
func TestHistogramQuantiles(t *testing.T) {
metricName := "test_histogram"
quantiles := []int{50, 90, 95, 99}
h := expvar.NewHistogram(metricName, 0, 100, 3, quantiles...)
const seed, mean, stdev int64 = 424242, 50, 10
teststat.PopulateNormalHistogram(t, h, seed, mean, stdev)
teststat.AssertExpvarNormalHistogram(t, metricName, mean, stdev, quantiles)
}
func TestHistogramQuantiles(t *testing.T) {
var (
name = "test_histogram"
quantiles = []int{50, 90, 95, 99}
h = expvar.NewHistogram(name, 0, 100, 3, quantiles...).With(metrics.Field{Key: "ignored", Value: "field"})
)
const seed, mean, stdev int64 = 424242, 50, 10
teststat.PopulateNormalHistogram(t, h, seed, mean, stdev)
teststat.AssertExpvarNormalHistogram(t, name, mean, stdev, quantiles)
}
func TestPrometheusSummary(t *testing.T) {
h := prometheus.NewSummary(stdprometheus.SummaryOpts{
Namespace: "test",
Subsystem: "prometheus_summary_histogram",
Name: "foobar",
Help: "Qwerty asdf.",
}, []string{})
const mean, stdev int64 = 50, 10
teststat.PopulateNormalHistogram(t, h, 34, mean, stdev)
teststat.AssertPrometheusNormalSummary(t, "test_prometheus_summary_histogram_foobar", mean, stdev)
}
func TestHistogram(t *testing.T) {
log.SetOutput(ioutil.Discard)
defer circonusgometrics.Reset()
var (
name = "test_histogram"
result []string
mtx sync.Mutex
onceDecode sync.Once
)
s := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
type postHistogram struct {
Value []string `json:"_value"`
}
onceDecode.Do(func() {
m := map[string]postHistogram{}
json.NewDecoder(r.Body).Decode(&m)
mtx.Lock()
defer mtx.Unlock()
result = m[name].Value
})
}))
defer s.Close()
circonusgometrics.WithSubmissionUrl(s.URL)
circonusgometrics.WithInterval(submissionInterval)
h := NewHistogram(name)
var (
seed = int64(123)
mean = int64(500)
stdev = int64(123)
min = int64(0)
max = 2 * mean
)
teststat.PopulateNormalHistogram(t, h, seed, mean, stdev)
onceStart.Do(func() { circonusgometrics.Start() })
if err := within(time.Second, func() bool {
mtx.Lock()
defer mtx.Unlock()
return len(result) > 0
}); err != nil {
t.Fatalf("error collecting results: %v", err)
}
teststat.AssertCirconusNormalHistogram(t, mean, stdev, min, max, result)
}
func TestPrometheusHistogram(t *testing.T) {
buckets := []float64{20, 40, 60, 80, 100}
h := prometheus.NewHistogram(stdprometheus.HistogramOpts{
Namespace: "test",
Subsystem: "prometheus_histogram_histogram",
Name: "quux",
Help: "Qwerty asdf.",
Buckets: buckets,
}, []string{})
const mean, stdev int64 = 50, 10
teststat.PopulateNormalHistogram(t, h, 34, mean, stdev)
teststat.AssertPrometheusBucketedHistogram(t, "test_prometheus_histogram_histogram_quux_bucket", mean, stdev, buckets)
}
func TestScaledHistogram(t *testing.T) {
var (
quantiles = []int{50, 90, 99}
scale = int64(10)
metricName = "test_scaled_histogram"
)
var h metrics.Histogram
h = expvar.NewHistogram(metricName, 0, 1000, 3, quantiles...)
h = metrics.NewScaledHistogram(h, scale)
h = h.With(metrics.Field{Key: "a", Value: "b"})
const seed, mean, stdev = 333, 500, 100 // input values
teststat.PopulateNormalHistogram(t, h, seed, mean, stdev) // will be scaled down
assertExpvarNormalHistogram(t, metricName, mean/scale, stdev/scale, quantiles)
}
func TestMultiHistogram(t *testing.T) {
quantiles := []int{50, 90, 99}
h := metrics.NewMultiHistogram(
"multiomicron",
expvar.NewHistogram("omicron", 0, 100, 3, quantiles...),
prometheus.NewSummary(stdprometheus.SummaryOpts{
Namespace: "test",
Subsystem: "multi_histogram",
Name: "nu",
Help: "Nu histogram.",
}, []string{}),
)
const seed, mean, stdev int64 = 123, 50, 10
teststat.PopulateNormalHistogram(t, h, seed, mean, stdev)
assertExpvarNormalHistogram(t, "omicron", mean, stdev, quantiles)
assertPrometheusNormalHistogram(t, `test_multi_histogram_nu`, mean, stdev)
}
func TestHistogramQuantiles(t *testing.T) {
prefix := "prefix."
e := NewEmitter("", "", prefix, time.Second, log.NewNopLogger())
var (
name = "test_histogram_quantiles"
quantiles = []int{50, 90, 95, 99}
)
h, err := e.NewHistogram(name, 0, 100, 3, quantiles...)
if err != nil {
t.Fatalf("unable to create test histogram: %v", err)
}
h = h.With(metrics.Field{Key: "ignored", Value: "field"})
const seed, mean, stdev int64 = 424242, 50, 10
teststat.PopulateNormalHistogram(t, h, seed, mean, stdev)
// flush the current metrics into a buffer to examine
var b bytes.Buffer
e.flush(&b)
teststat.AssertGraphiteNormalHistogram(t, prefix, name, mean, stdev, quantiles, b.String())
}
func TestHistogram(t *testing.T) {
// Prometheus reports histograms as a count of observations that fell into
// each predefined bucket, with the bucket value representing a global upper
// limit. That is, the count monotonically increases over the buckets. This
// requires a different strategy to test.
s := httptest.NewServer(stdprometheus.UninstrumentedHandler())
defer s.Close()
scrape := func() string {
resp, _ := http.Get(s.URL)
buf, _ := ioutil.ReadAll(resp.Body)
return string(buf)
}
namespace, subsystem, name := "test", "prometheus", "histogram"
re := regexp.MustCompile(namespace + `_` + subsystem + `_` + name + `_bucket{x="1",le="([0-9]+|\+Inf)"} ([0-9\.]+)`)
numStdev := 3
bucketMin := (teststat.Mean - (numStdev * teststat.Stdev))
bucketMax := (teststat.Mean + (numStdev * teststat.Stdev))
if bucketMin < 0 {
bucketMin = 0
}
bucketCount := 10
bucketDelta := (bucketMax - bucketMin) / bucketCount
buckets := []float64{}
for i := bucketMin; i <= bucketMax; i += bucketDelta {
buckets = append(buckets, float64(i))
}
histogram := NewHistogramFrom(stdprometheus.HistogramOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: name,
Help: "This is the help string for the histogram.",
Buckets: buckets,
}, []string{"x"}).With("x", "1")
// Can't TestHistogram, because Prometheus Histograms don't dynamically
// compute quantiles. Instead, they fill up buckets. So, let's populate the
// histogram kind of manually.
teststat.PopulateNormalHistogram(histogram, rand.Int())
// Then, we use ExpectedObservationsLessThan to validate.
for _, line := range strings.Split(scrape(), "\n") {
match := re.FindStringSubmatch(line)
if match == nil {
continue
}
bucket, _ := strconv.ParseInt(match[1], 10, 64)
have, _ := strconv.ParseInt(match[2], 10, 64)
want := teststat.ExpectedObservationsLessThan(bucket)
if match[1] == "+Inf" {
want = int64(teststat.Count) // special case
}
// Unfortunately, we observe experimentally that Prometheus is quite
// imprecise at the extremes. I'm setting a very high tolerance for now.
// It would be great to dig in and figure out whether that's a problem
// with my Expected calculation, or in Prometheus.
tolerance := 0.25
if delta := math.Abs(float64(want) - float64(have)); (delta / float64(want)) > tolerance {
t.Errorf("Bucket %d: want %d, have %d (%.1f%%)", bucket, want, have, (100.0 * delta / float64(want)))
}
}
}
