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f358fb72d1
VictoriaMetrics/app/vmselect/promql/exec_test.go
Aliaksandr Valialkin d410c78c7e app/vmselect/promql: fix calculations for histogram_share
2020-01-04 14:44:48 +02:00

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package promql
import (
"testing"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/app/vmselect/netstorage"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
)
func TestExecSuccess(t *testing.T) {
start := int64(1000e3)
end := int64(2000e3)
step := int64(200e3)
timestampsExpected := []int64{1000e3, 1200e3, 1400e3, 1600e3, 1800e3, 2000e3}
metricNameExpected := storage.MetricName{}
f := func(q string, resultExpected []netstorage.Result) {
t.Helper()
ec := &EvalConfig{
Start: start,
End: end,
Step: step,
Deadline: netstorage.NewDeadline(time.Minute),
}
for i := 0; i < 5; i++ {
result, err := Exec(ec, q, false)
if err != nil {
t.Fatalf(`unexpected error when executing %q: %s`, q, err)
}
testResultsEqual(t, result, resultExpected)
}
}
t.Run("simple-number", func(t *testing.T) {
t.Parallel()
q := `123`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{123, 123, 123, 123, 123, 123},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("simple-arithmetic", func(t *testing.T) {
t.Parallel()
q := `-1+2 *3 ^ 4+5%6`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{166, 166, 166, 166, 166, 166},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("simple-string", func(t *testing.T) {
t.Parallel()
q := `"foobar"`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run("simple-string-op-number", func(t *testing.T) {
t.Parallel()
q := `1+"foobar"*2%9`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run("scalar-vector-arithmetic", func(t *testing.T) {
t.Parallel()
q := `scalar(-1)+2 *vector(3) ^ scalar(4)+5`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{166, 166, 166, 166, 166, 166},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("scalar-string-nonnum", func(t *testing.T) {
q := `scalar("fooobar")`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run("scalar-string-num", func(t *testing.T) {
q := `scalar("-12.34")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-12.34, -12.34, -12.34, -12.34, -12.34, -12.34},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time()", func(t *testing.T) {
t.Parallel()
q := `time()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time() offset 0s", func(t *testing.T) {
t.Parallel()
q := `time() offset 0s`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{900, 1100, 1300, 1500, 1700, 1900},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("(a, b) offset 0s", func(t *testing.T) {
t.Parallel()
q := `sort((label_set(time(), "foo", "bar"), label_set(time()+10, "foo", "baz")) offset 0s)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{900, 1100, 1300, 1500, 1700, 1900},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{910, 1110, 1310, 1510, 1710, 1910},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("baz"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run("time()[:100s] offset 0s", func(t *testing.T) {
t.Parallel()
q := `time()[:100s] offset 0s`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time() offset 100s", func(t *testing.T) {
t.Parallel()
q := `time() offset 100s`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{800, 1000, 1200, 1400, 1600, 1800},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time() offset -100s", func(t *testing.T) {
t.Parallel()
q := `time() offset -100s`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("(a, b) offset 100s", func(t *testing.T) {
t.Parallel()
q := `sort((label_set(time(), "foo", "bar"), label_set(time()+10, "foo", "baz")) offset 100s)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{800, 1000, 1200, 1400, 1600, 1800},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{810, 1010, 1210, 1410, 1610, 1810},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("baz"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run("(a offset 100s, b offset 50s)", func(t *testing.T) {
t.Parallel()
q := `sort((label_set(time() offset 100s, "foo", "bar"), label_set(time()+10, "foo", "baz") offset 50s))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{800, 1000, 1200, 1400, 1600, 1800},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{860, 1060, 1260, 1460, 1660, 1860},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("baz"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run("(a offset 100s, b offset 50s) offset 400s", func(t *testing.T) {
t.Parallel()
q := `sort((label_set(time() offset 100s, "foo", "bar"), label_set(time()+10, "foo", "baz") offset 50s) offset 400s)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{300, 500, 700, 900, 1100, 1300},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{360, 560, 760, 960, 1160, 1360},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("baz"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run("(a offset -100s, b offset -50s) offset -400s", func(t *testing.T) {
t.Parallel()
q := `sort((label_set(time() offset -100s, "foo", "bar"), label_set(time()+10, "foo", "baz") offset -50s) offset -400s)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1260, 1460, 1660, 1860, 2060, 2260},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("baz"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1300, 1500, 1700, 1900, 2100, 2300},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run("time()[:100s] offset 100s", func(t *testing.T) {
t.Parallel()
q := `time()[:100s] offset 100s`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{900, 1100, 1300, 1500, 1700, 1900},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time()[300s:100s] offset 100s", func(t *testing.T) {
t.Parallel()
q := `time()[300s:100s] offset 100s`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{900, 1100, 1300, 1500, 1700, 1900},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time()[1.5i:0.5i] offset 0.5i", func(t *testing.T) {
t.Parallel()
q := `time()[1.5i:0.5i] offset 0.5i`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{900, 1100, 1300, 1500, 1700, 1900},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time()[300s] offset 100s", func(t *testing.T) {
t.Parallel()
q := `time()[300s] offset 100s`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{900, 1100, 1300, 1500, 1700, 1900},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time()[300s]", func(t *testing.T) {
t.Parallel()
q := `time()[300s]`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time() + time()", func(t *testing.T) {
t.Parallel()
q := `time() + time()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("timestamp(123)", func(t *testing.T) {
t.Parallel()
q := `timestamp(123)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("timestamp(time())", func(t *testing.T) {
t.Parallel()
q := `timestamp(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("timestamp(456/time()+123)", func(t *testing.T) {
t.Parallel()
q := `timestamp(456/time()+123)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("timestamp(time()>=1600)", func(t *testing.T) {
t.Parallel()
q := `timestamp(time()>=1600)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time()/100", func(t *testing.T) {
t.Parallel()
q := `time()/100`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 12, 14, 16, 18, 20},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("1e3/time()*2*9*7", func(t *testing.T) {
t.Parallel()
q := `1e3/time()*2*9*7`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{126, 105, 90, 78.75, 70, 63},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("minute()", func(t *testing.T) {
t.Parallel()
q := `minute()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{16, 20, 23, 26, 30, 33},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("day_of_month()", func(t *testing.T) {
t.Parallel()
q := `day_of_month(time()*1e4)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{26, 19, 12, 5, 28, 20},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("day_of_week()", func(t *testing.T) {
t.Parallel()
q := `day_of_week(time()*1e4)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 2, 5, 0, 2, 4},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("days_in_month()", func(t *testing.T) {
t.Parallel()
q := `days_in_month(time()*2e4)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{31, 31, 30, 31, 28, 30},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("hour()", func(t *testing.T) {
t.Parallel()
q := `hour(time()*1e4)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{17, 21, 0, 4, 8, 11},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("month()", func(t *testing.T) {
t.Parallel()
q := `month(time()*1e4)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{4, 5, 6, 7, 7, 8},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("year()", func(t *testing.T) {
t.Parallel()
q := `year(time()*1e5)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1973, 1973, 1974, 1975, 1975, 1976},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("minute(30*60+time())", func(t *testing.T) {
t.Parallel()
q := `minute(30*60+time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{46, 50, 53, 56, 0, 3},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("rate({})", func(t *testing.T) {
t.Parallel()
q := `rate({})`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run("abs(1500-time())", func(t *testing.T) {
t.Parallel()
q := `abs(1500-time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{500, 300, 100, 100, 300, 500},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("abs(-time()+1300)", func(t *testing.T) {
t.Parallel()
q := `abs(-time()+1300)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{300, 100, 100, 300, 500, 700},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("ceil(time() / 900)", func(t *testing.T) {
t.Parallel()
q := `ceil(time()/500)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 3, 3, 4, 4, 4},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("absent(time())", func(t *testing.T) {
t.Parallel()
q := `absent(time())`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run("absent_over_time(time())", func(t *testing.T) {
t.Parallel()
q := `absent_over_time(time())`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run("absent(123)", func(t *testing.T) {
t.Parallel()
q := `absent(123)`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run("absent(vector(scalar(123)))", func(t *testing.T) {
t.Parallel()
q := `absent(vector(scalar(123)))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run("absent(NaN)", func(t *testing.T) {
t.Parallel()
q := `absent(NaN)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("absent_over_time(nan[200s:10s])", func(t *testing.T) {
t.Parallel()
q := `absent_over_time(nan[200s:10s])`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`absent(scalar(multi-timeseries))`, func(t *testing.T) {
t.Parallel()
q := `
absent(label_set(scalar(1 or label_set(2, "xx", "foo")), "yy", "foo"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("yy"),
Value: []byte("foo"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`absent_over_time(scalar(multi-timeseries))`, func(t *testing.T) {
t.Parallel()
q := `
absent_over_time(label_set(scalar(1 or label_set(2, "xx", "foo")), "yy", "foo"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("yy"),
Value: []byte("foo"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`absent(time() > 1500)`, func(t *testing.T) {
t.Parallel()
q := `
absent(time() > 1500)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, nan, nan, nan},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("clamp_max(time(), 1400)", func(t *testing.T) {
t.Parallel()
q := `clamp_max(time(), 1400)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1400, 1400, 1400},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`clamp_max(alias(time(),"foobar"), 1400)`, func(t *testing.T) {
t.Parallel()
q := `clamp_max(alias(time(), "foobar"), 1400)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1400, 1400, 1400},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`CLAmp_MAx(alias(time(),"foobar"), 1400)`, func(t *testing.T) {
t.Parallel()
q := `CLAmp_MAx(alias(time(), "foobar"), 1400)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1400, 1400, 1400},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("clamp_min(time(), -time()+3000)", func(t *testing.T) {
t.Parallel()
q := `clamp_min(time(), -time()+2500)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1500, 1300, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("clamp_min(1500, time())", func(t *testing.T) {
t.Parallel()
q := `clamp_min(1500, time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1500, 1500, 1500, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("exp(time()/1e3)", func(t *testing.T) {
t.Parallel()
q := `exp(time()/1e3)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2.718281828459045, 3.3201169227365472, 4.0551999668446745, 4.953032424395115, 6.0496474644129465, 7.38905609893065},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("rand()", func(t *testing.T) {
t.Parallel()
q := `round(rand()/2)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("rand(0)", func(t *testing.T) {
t.Parallel()
q := `round(rand(0), 0.01)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.95, 0.24, 0.66, 0.05, 0.37, 0.28},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("rand_normal()", func(t *testing.T) {
t.Parallel()
q := `clamp_max(clamp_min(0, rand_normal()), 0)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("rand_normal(0)", func(t *testing.T) {
t.Parallel()
q := `round(rand_normal(0), 0.01)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-0.28, 0.57, -1.69, 0.2, 1.92, 0.9},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("rand_exponential()", func(t *testing.T) {
t.Parallel()
q := `clamp_max(clamp_min(0, rand_exponential()), 0)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("rand_exponential(0)", func(t *testing.T) {
t.Parallel()
q := `round(rand_exponential(0), 0.01)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{4.67, 0.16, 3.05, 0.06, 1.86, 0.78},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("pi()", func(t *testing.T) {
t.Parallel()
q := `pi()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{3.141592653589793, 3.141592653589793, 3.141592653589793, 3.141592653589793, 3.141592653589793, 3.141592653589793},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("sin()", func(t *testing.T) {
t.Parallel()
q := `sin(pi()*(2000-time())/1000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1.2246467991473515e-16, 0.5877852522924732, 0.9510565162951536, 0.9510565162951535, 0.5877852522924731, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("asin()", func(t *testing.T) {
t.Parallel()
q := `asin((2000-time())/1000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1.5707963267948966, 0.9272952180016123, 0.6435011087932843, 0.41151684606748806, 0.20135792079033082, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("cos()", func(t *testing.T) {
t.Parallel()
q := `cos(pi()*(2000-time())/1000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-1, -0.8090169943749475, -0.30901699437494734, 0.30901699437494745, 0.8090169943749473, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("acos()", func(t *testing.T) {
t.Parallel()
q := `acos((2000-time())/1000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0.6435011087932843, 0.9272952180016123, 1.1592794807274085, 1.3694384060045657, 1.5707963267948966},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("floor(time()/500)", func(t *testing.T) {
t.Parallel()
q := `floor(time()/500)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 3, 3, 4},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("sqrt(time())", func(t *testing.T) {
t.Parallel()
q := `sqrt(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{31.622776601683793, 34.64101615137755, 37.416573867739416, 40, 42.42640687119285, 44.721359549995796},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("ln(time())", func(t *testing.T) {
t.Parallel()
q := `ln(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.907755278982137, 7.090076835776092, 7.24422751560335, 7.3777589082278725, 7.495541943884256, 7.600902459542082},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("log2(time())", func(t *testing.T) {
t.Parallel()
q := `log2(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{9.965784284662087, 10.228818690495881, 10.451211111832329, 10.643856189774725, 10.813781191217037, 10.965784284662087},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("log10(time())", func(t *testing.T) {
t.Parallel()
q := `log10(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{3, 3.0791812460476247, 3.1461280356782377, 3.2041199826559246, 3.255272505103306, 3.3010299956639813},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run("time()*-1^0.5", func(t *testing.T) {
t.Parallel()
q := `time()*-1^0.5`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`alias()`, func(t *testing.T) {
t.Parallel()
q := `alias(time(), "foobar")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_set(tag)`, func(t *testing.T) {
t.Parallel()
q := `label_set(time(), "tagname", "tagvalue")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("tagname"),
Value: []byte("tagvalue"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_set(metricname)`, func(t *testing.T) {
t.Parallel()
q := `label_set(time(), "__name__", "foobar")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_set(metricname, tag)`, func(t *testing.T) {
t.Parallel()
q := `label_set(
label_set(time(), "__name__", "foobar"),
"tagname", "tagvalue"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
r.MetricName.Tags = []storage.Tag{{
Key: []byte("tagname"),
Value: []byte("tagvalue"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_set(del_metricname)`, func(t *testing.T) {
t.Parallel()
q := `label_set(
label_set(time(), "__name__", "foobar"),
"__name__", ""
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_set(del_tag)`, func(t *testing.T) {
t.Parallel()
q := `label_set(
label_set(time(), "tagname", "foobar"),
"tagname", ""
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_set(multi)`, func(t *testing.T) {
t.Parallel()
q := `label_set(time()+100, "t1", "v1", "t2", "v2", "__name__", "v3")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1300, 1500, 1700, 1900, 2100},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("v3")
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("t1"),
Value: []byte("v1"),
},
{
Key: []byte("t2"),
Value: []byte("v2"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_copy(new_tag)`, func(t *testing.T) {
t.Parallel()
q := `label_copy(
label_set(time(), "tagname", "foobar"),
"tagname", "xxx"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("tagname"),
Value: []byte("foobar"),
},
{
Key: []byte("xxx"),
Value: []byte("foobar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_move(new_tag)`, func(t *testing.T) {
t.Parallel()
q := `label_move(
label_set(time(), "tagname", "foobar"),
"tagname", "xxx"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("foobar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_copy(same_tag)`, func(t *testing.T) {
t.Parallel()
q := `label_copy(
label_set(time(), "tagname", "foobar"),
"tagname", "tagname"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("tagname"),
Value: []byte("foobar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_move(same_tag)`, func(t *testing.T) {
t.Parallel()
q := `label_move(
label_set(time(), "tagname", "foobar"),
"tagname", "tagname"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("tagname"),
Value: []byte("foobar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_copy(same_tag_nonexisting_src)`, func(t *testing.T) {
t.Parallel()
q := `label_copy(
label_set(time(), "tagname", "foobar"),
"non-existing-tag", "tagname"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_move(same_tag_nonexisting_src)`, func(t *testing.T) {
t.Parallel()
q := `label_move(
label_set(time(), "tagname", "foobar"),
"non-existing-tag", "tagname"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_copy(existing_tag)`, func(t *testing.T) {
t.Parallel()
q := `label_copy(
label_set(time(), "tagname", "foobar", "xx", "yy"),
"xx", "tagname"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("tagname"),
Value: []byte("yy"),
},
{
Key: []byte("xx"),
Value: []byte("yy"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_move(existing_tag)`, func(t *testing.T) {
t.Parallel()
q := `label_move(
label_set(time(), "tagname", "foobar", "xx", "yy"),
"xx", "tagname"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("tagname"),
Value: []byte("yy"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_copy(from_metric_group)`, func(t *testing.T) {
t.Parallel()
q := `label_copy(
label_set(time(), "tagname", "foobar", "__name__", "yy"),
"__name__", "aa"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("yy")
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("aa"),
Value: []byte("yy"),
},
{
Key: []byte("tagname"),
Value: []byte("foobar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_move(from_metric_group)`, func(t *testing.T) {
t.Parallel()
q := `label_move(
label_set(time(), "tagname", "foobar", "__name__", "yy"),
"__name__", "aa"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("aa"),
Value: []byte("yy"),
},
{
Key: []byte("tagname"),
Value: []byte("foobar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_copy(to_metric_group)`, func(t *testing.T) {
t.Parallel()
q := `label_copy(
label_set(time(), "tagname", "foobar"),
"tagname", "__name__"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("tagname"),
Value: []byte("foobar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_move(to_metric_group)`, func(t *testing.T) {
t.Parallel()
q := `label_move(
label_set(time(), "tagname", "foobar"),
"tagname", "__name__"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_keep(nolabels)`, func(t *testing.T) {
t.Parallel()
q := `label_keep(time(), "foo", "bar")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_keep(certain_labels)`, func(t *testing.T) {
t.Parallel()
q := `label_keep(label_set(time(), "foo", "bar", "__name__", "xxx", "q", "we"), "foo", "nonexisting-label")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_keep(metricname)`, func(t *testing.T) {
t.Parallel()
q := `label_keep(label_set(time(), "foo", "bar", "__name__", "xxx", "q", "we"), "nonexisting-label", "__name__")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("xxx")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_del(nolabels)`, func(t *testing.T) {
t.Parallel()
q := `label_del(time(), "foo", "bar")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_del(certain_labels)`, func(t *testing.T) {
t.Parallel()
q := `label_del(label_set(time(), "foo", "bar", "__name__", "xxx", "q", "we"), "foo", "nonexisting-label")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("xxx")
r.MetricName.Tags = []storage.Tag{{
Key: []byte("q"),
Value: []byte("we"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_del(metricname)`, func(t *testing.T) {
t.Parallel()
q := `label_del(label_set(time(), "foo", "bar", "__name__", "xxx", "q", "we"), "nonexisting-label", "__name__")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("q"),
Value: []byte("we"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_join(empty)`, func(t *testing.T) {
t.Parallel()
q := `label_join(vector(time()), "tt", "(sep)", "BAR")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_join(tt)`, func(t *testing.T) {
t.Parallel()
q := `label_join(vector(time()), "tt", "(sep)", "foo", "BAR")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("tt"),
Value: []byte("(sep)"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_join(__name__)`, func(t *testing.T) {
t.Parallel()
q := `label_join(time(), "__name__", "(sep)", "foo", "BAR", "")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("(sep)(sep)")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_join(label_join)`, func(t *testing.T) {
t.Parallel()
q := `label_join(label_join(time(), "__name__", "(sep)", "foo", "BAR"), "xxx", ",", "foobar", "__name__")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("(sep)")
r.MetricName.Tags = []storage.Tag{{
Key: []byte("xxx"),
Value: []byte(",(sep)"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_value()`, func(t *testing.T) {
t.Parallel()
q := `with (
x = (
label_set(time(), "foo", "123.456", "__name__", "aaa"),
label_set(-time(), "foo", "bar", "__name__", "bbb"),
label_set(-time(), "__name__", "bxs"),
label_set(-time(), "foo", "45", "bar", "xs"),
)
)
sort(x + label_value(x, "foo"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-955, -1155, -1355, -1555, -1755, -1955},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("bar"),
Value: []byte("xs"),
},
{
Key: []byte("foo"),
Value: []byte("45"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1123.456, 1323.456, 1523.456, 1723.456, 1923.456, 2123.456},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("123.456"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`label_transform(mismatch)`, func(t *testing.T) {
t.Parallel()
q := `label_transform(time(), "__name__", "foobar", "xx")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_transform(match)`, func(t *testing.T) {
t.Parallel()
q := `label_transform(
label_set(time(), "foo", "a.bar.baz"),
"foo", "\\.", "-")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("a-bar-baz"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_replace(mismatch)`, func(t *testing.T) {
t.Parallel()
q := `label_replace(time(), "__name__", "x${1}y", "foo", ".+")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_replace(match)`, func(t *testing.T) {
t.Parallel()
q := `label_replace(time(), "__name__", "x${1}y", "foo", ".*")`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("xy")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`label_replace(label_replace)`, func(t *testing.T) {
t.Parallel()
q := `
label_replace(
label_replace(
label_replace(time(), "__name__", "x${1}y", "foo", ".*"),
"xxx", "foo${1}bar(${1})", "__name__", "(.+)"),
"xxx", "AA$1", "xxx", "foox(.+)"
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("xy")
r.MetricName.Tags = []storage.Tag{{
Key: []byte("xxx"),
Value: []byte("AAybar(xy)"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`two_timeseries`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(time() or label_set(2, "xx", "foo"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("xx"),
Value: []byte("foo"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`round(time()/1e3)`, func(t *testing.T) {
t.Parallel()
q := `round(time()/1e3)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 2, 2, 2},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`round(time()/1e3, 0.5)`, func(t *testing.T) {
t.Parallel()
q := `round(time()/1e3, 0.5)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1.5, 1.5, 2, 2},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`round(-time()/1e3, 1)`, func(t *testing.T) {
t.Parallel()
q := `round(-time()/1e3, 0.5)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-1, -1, -1.5, -1.5, -2, -2},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`scalar(multi-timeseries)`, func(t *testing.T) {
t.Parallel()
q := `scalar(1 or label_set(2, "xx", "foo"))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`sort()`, func(t *testing.T) {
t.Parallel()
q := `sort(2 or label_set(1, "xx", "foo"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("xx"),
Value: []byte("foo"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`sort_desc()`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(1 or label_set(2, "xx", "foo"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("xx"),
Value: []byte("foo"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`a cmp scalar (leave MetricGroup)`, func(t *testing.T) {
t.Parallel()
q := `sort_desc((
label_set(time(), "__name__", "foo", "a", "x"),
label_set(time()+200, "__name__", "bar", "a", "x"),
) > 1300)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, 1400, 1600, 1800, 2000, 2200},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("bar")
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("a"),
Value: []byte("x"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("foo")
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("a"),
Value: []byte("x"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`a cmp bool scalar (drop MetricGroup)`, func(t *testing.T) {
t.Parallel()
q := `sort_desc((
label_set(time(), "__name__", "foo", "a", "x"),
label_set(time()+200, "__name__", "bar", "a", "y"),
) >= bool 1200)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("a"),
Value: []byte("y"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("a"),
Value: []byte("x"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`1 > 2`, func(t *testing.T) {
t.Parallel()
q := `1 > 2`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`vector(1) == bool time()`, func(t *testing.T) {
t.Parallel()
q := `vector(1) == bool time()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`vector(1) == time()`, func(t *testing.T) {
t.Parallel()
q := `vector(1) == time()`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`-1 < 2`, func(t *testing.T) {
t.Parallel()
q := `-1 < 2`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-1, -1, -1, -1, -1, -1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`time() > 2`, func(t *testing.T) {
t.Parallel()
q := `time() > 2`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`time() >= bool 2`, func(t *testing.T) {
t.Parallel()
q := `time() >= bool 2`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`time() and 2`, func(t *testing.T) {
t.Parallel()
q := `time() and 2`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`time() unless 2`, func(t *testing.T) {
t.Parallel()
q := `time() unless 2`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`timseries-with-tags unless 2`, func(t *testing.T) {
t.Parallel()
q := `label_set(time(), "foo", "bar") unless 2`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`scalar default scalar`, func(t *testing.T) {
t.Parallel()
q := `time() > 1400 default 123`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{123, 123, 123, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`vector default scalar`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(union(
label_set(time() > 1400, "__name__", "x", "foo", "bar"),
label_set(time() < 1700, "__name__", "y", "foo", "baz")) default 123)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{123, 123, 123, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("x")
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 123, 123},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("y")
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("baz"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`vector / scalar`, func(t *testing.T) {
t.Parallel()
q := `sort_desc((label_set(time(), "foo", "bar") or label_set(10, "foo", "qwert")) / 2)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{500, 600, 700, 800, 900, 1000},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{5, 5, 5, 5, 5, 5},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("qwert"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`vector * scalar`, func(t *testing.T) {
t.Parallel()
q := `sum(time()) * 2`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`scalar * vector`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(2 * (label_set(time(), "foo", "bar") or label_set(10, "foo", "qwert")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{20, 20, 20, 20, 20, 20},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("qwert"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`scalar * on() group_right vector`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(2 * on() group_right() (label_set(time(), "foo", "bar") or label_set(10, "foo", "qwert")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{20, 20, 20, 20, 20, 20},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("qwert"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`scalar * ignoring(foo) group_right vector`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(2 * ignoring(foo) group_right(a,foo) (label_set(time(), "foo", "bar") or label_set(10, "foo", "qwert")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{20, 20, 20, 20, 20, 20},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("qwert"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`scalar * ignoring(a) vector`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(label_set(2, "foo", "bar") * ignoring(a) (label_set(time(), "foo", "bar") or label_set(10, "foo", "qwert")))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`scalar * on(foo) vector`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(label_set(2, "foo", "bar", "aa", "bb") * on(foo) (label_set(time(), "foo", "bar", "xx", "yy") or label_set(10, "foo", "qwert")))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`vector * on(foo) scalar`, func(t *testing.T) {
t.Parallel()
q := `sort_desc((label_set(time(), "foo", "bar", "xx", "yy"), label_set(10, "foo", "qwert")) * on(foo) label_set(2, "foo","bar","aa","bb"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`vector * on(foo) group_left(additional_tag) duplicate_timeseries_differ_by_additional_tag`, func(t *testing.T) {
t.Parallel()
q := `sort(label_set(time()/10, "foo", "bar", "xx", "yy", "__name__", "qwert") + on(foo) group_left(op) (
label_set(time() < 1400, "foo", "bar", "op", "le"),
label_set(time() >= 1400, "foo", "bar", "op", "ge"),
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1320, nan, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("op"),
Value: []byte("le"),
},
{
Key: []byte("xx"),
Value: []byte("yy"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, 1540, 1760, 1980, 2200},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("op"),
Value: []byte("ge"),
},
{
Key: []byte("xx"),
Value: []byte("yy"),
},
}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`vector * on(foo) duplicate_nonoverlapping_timeseries`, func(t *testing.T) {
t.Parallel()
q := `label_set(time()/10, "foo", "bar", "xx", "yy", "__name__", "qwert") + on(foo) (
label_set(time() < 1400, "foo", "bar", "op", "le"),
label_set(time() >= 1400, "foo", "bar", "op", "ge"),
)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1320, 1540, 1760, 1980, 2200},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`vector * on(foo) group_left() duplicate_nonoverlapping_timeseries`, func(t *testing.T) {
t.Parallel()
q := `label_set(time()/10, "foo", "bar", "xx", "yy", "__name__", "qwert") + on(foo) group_left() (
label_set(time() < 1400, "foo", "bar", "op", "le"),
label_set(time() >= 1400, "foo", "bar", "op", "ge"),
)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1320, 1540, 1760, 1980, 2200},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xx"),
Value: []byte("yy"),
},
}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`vector * on(foo) group_left(__name__)`, func(t *testing.T) {
t.Parallel()
q := `label_set(time()/10, "foo", "bar", "xx", "yy", "__name__", "qwert") + on(foo) group_left(__name__)
label_set(time(), "foo", "bar", "__name__", "aaa")`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1320, 1540, 1760, 1980, 2200},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("aaa")
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xx"),
Value: []byte("yy"),
},
}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`vector * on(foo) group_right()`, func(t *testing.T) {
t.Parallel()
q := `sort(label_set(time()/10, "foo", "bar", "xx", "yy", "__name__", "qwert") + on(foo) group_right(xx) (
label_set(time(), "foo", "bar", "__name__", "aaa"),
label_set(time()+3, "foo", "bar", "__name__", "yyy","ppp", "123"),
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1320, 1540, 1760, 1980, 2200},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xx"),
Value: []byte("yy"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1103, 1323, 1543, 1763, 1983, 2203},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("ppp"),
Value: []byte("123"),
},
{
Key: []byte("xx"),
Value: []byte("yy"),
},
}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`vector * on() group_left scalar`, func(t *testing.T) {
t.Parallel()
q := `sort_desc((label_set(time(), "foo", "bar") or label_set(10, "foo", "qwert")) * on() group_left 2)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{20, 20, 20, 20, 20, 20},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("qwert"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`vector + vector matching`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(
(label_set(time(), "t1", "v1") or label_set(10, "t2", "v2"))
+
(label_set(100, "t1", "v1") or label_set(time(), "t2", "v2"))
)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1300, 1500, 1700, 1900, 2100},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("t1"),
Value: []byte("v1"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1010, 1210, 1410, 1610, 1810, 2010},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("t2"),
Value: []byte("v2"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`vector + vector partial matching`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(
(label_set(time(), "t1", "v1") or label_set(10, "t2", "v2"))
+
(label_set(100, "t1", "v1") or label_set(time(), "t2", "v3"))
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1300, 1500, 1700, 1900, 2100},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("t1"),
Value: []byte("v1"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`vector + vector no matching`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(
(label_set(time(), "t2", "v1") or label_set(10, "t2", "v2"))
+
(label_set(100, "t1", "v1") or label_set(time(), "t2", "v3"))
)`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`vector + vector on matching`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(
(label_set(time(), "t1", "v123", "t2", "v3") or label_set(10, "t2", "v2"))
+ on (foo, t2)
(label_set(100, "t1", "v1") or label_set(time(), "t2", "v3"))
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("t2"),
Value: []byte("v3"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`vector + vector on group_left matching`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(
(label_set(time(), "t1", "v123", "t2", "v3") or label_set(10, "t2", "v3", "xxx", "yy"))
+ on (foo, t2) group_left (t1, noxxx)
(label_set(100, "t1", "v1") or label_set(time(), "t2", "v3", "noxxx", "aa"))
)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("noxxx"),
Value: []byte("aa"),
},
{
Key: []byte("t1"),
Value: []byte("v123"),
},
{
Key: []byte("t2"),
Value: []byte("v3"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1010, 1210, 1410, 1610, 1810, 2010},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("noxxx"),
Value: []byte("aa"),
},
{
Key: []byte("t2"),
Value: []byte("v3"),
},
{
Key: []byte("xxx"),
Value: []byte("yy"),
},
}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`vector + vector on group_left (__name__)`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(
(union(label_set(time(), "t2", "v3", "__name__", "vv3", "x", "y"), label_set(10, "t2", "v3", "__name__", "yy")))
+ on (t2, dfdf) group_left (__name__, xxx)
(label_set(100, "t1", "v1") or label_set(time(), "t2", "v3", "__name__", "abc"))
)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("abc")
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("t2"),
Value: []byte("v3"),
},
{
Key: []byte("x"),
Value: []byte("y"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1010, 1210, 1410, 1610, 1810, 2010},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("abc")
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("t2"),
Value: []byte("v3"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`vector + vector ignoring matching`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(
(label_set(time(), "t1", "v123", "t2", "v3") or label_set(10, "t2", "v2"))
+ ignoring (foo, t1, bar)
(label_set(100, "t1", "v1") or label_set(time(), "t2", "v3"))
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("t2"),
Value: []byte("v3"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`vector + vector ignoring group_right matching`, func(t *testing.T) {
t.Parallel()
q := `sort_desc(
(label_set(time(), "t1", "v123", "t2", "v3") or label_set(10, "t2", "v321", "t1", "v123", "t32", "v32"))
+ ignoring (foo, t2) group_right ()
(label_set(100, "t1", "v123") or label_set(time(), "t1", "v123", "t2", "v3"))
)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2400, 2800, 3200, 3600, 4000},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("t1"),
Value: []byte("v123"),
},
{
Key: []byte("t2"),
Value: []byte("v3"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 1300, 1500, 1700, 1900, 2100},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("t1"),
Value: []byte("v123"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`histogram_quantile(scalar)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.6, time())`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`histogram_share(scalar)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(123, time())`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`histogram_quantile(single-value-no-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.6, label_set(100, "foo", "bar"))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-no-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(123, label_set(100, "foo", "bar"))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`histogram_quantile(single-value-invalid-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.6, label_set(100, "le", "foobar"))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-invalid-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(50, label_set(100, "le", "foobar"))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`histogram_quantile(single-value-valid-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.6, label_set(100, "le", "200"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{120, 120, 120, 120, 120, 120},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-valid-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(80, label_set(100, "le", "200"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.4, 0.4, 0.4, 0.4, 0.4, 0.4},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-valid-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(200, label_set(100, "le", "200"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-valid-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(300, label_set(100, "le", "200"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_quantile(single-value-valid-le, boundsLabel)`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram_quantile(0.6, label_set(100, "le", "200"), "foobar"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foobar"),
Value: []byte("lower"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{120, 120, 120, 120, 120, 120},
Timestamps: timestampsExpected,
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 200, 200, 200, 200, 200},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{{
Key: []byte("foobar"),
Value: []byte("upper"),
}}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`histogram_quantile(single-value-valid-le, boundsLabel)`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram_share(120, label_set(100, "le", "200"), "foobar"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foobar"),
Value: []byte("lower"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.6, 0.6, 0.6, 0.6, 0.6, 0.6},
Timestamps: timestampsExpected,
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{{
Key: []byte("foobar"),
Value: []byte("upper"),
}}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`histogram_quantile(single-value-valid-le-max-phi)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(1, (
label_set(100, "le", "200"),
label_set(0, "le", "55"),
))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 200, 200, 200, 200, 200},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-valid-le-max-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(200, (
label_set(100, "le", "200"),
label_set(0, "le", "55"),
))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_quantile(single-value-valid-le-min-phi)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0, (
label_set(100, "le", "200"),
label_set(0, "le", "55"),
))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{55, 55, 55, 55, 55, 55},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-valid-le-min-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(0, (
label_set(100, "le", "200"),
label_set(0, "le", "55"),
))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-valid-le-low-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(55, (
label_set(100, "le", "200"),
label_set(0, "le", "55"),
))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(single-value-valid-le-mid-le)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(105, (
label_set(100, "le", "200"),
label_set(0, "le", "55"),
))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.3448275862068966, 0.3448275862068966, 0.3448275862068966, 0.3448275862068966, 0.3448275862068966, 0.3448275862068966},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_quantile(single-value-valid-le-min-phi-no-zero-bucket)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0, label_set(100, "le", "200"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_quantile(scalar-phi)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(time() / 2 / 1e3, label_set(100, "le", "200"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{100, 120, 140, 160, 180, 200},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(scalar-phi)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(time() / 8, label_set(100, "le", "200"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.625, 0.75, 0.875, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_quantile(valid)`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram_quantile(0.6,
label_set(90, "foo", "bar", "le", "10")
or label_set(100, "foo", "bar", "le", "30")
or label_set(300, "foo", "bar", "le", "+Inf")
or label_set(200, "tag", "xx", "le", "10")
or label_set(300, "tag", "xx", "le", "30")
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{9, 9, 9, 9, 9, 9},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("tag"),
Value: []byte("xx"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{30, 30, 30, 30, 30, 30},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`histogram_share(valid)`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram_share(25,
label_set(90, "foo", "bar", "le", "10")
or label_set(100, "foo", "bar", "le", "30")
or label_set(300, "foo", "bar", "le", "+Inf")
or label_set(200, "tag", "xx", "le", "10")
or label_set(300, "tag", "xx", "le", "30")
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.325, 0.325, 0.325, 0.325, 0.325, 0.325},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.9166666666666666, 0.9166666666666666, 0.9166666666666666, 0.9166666666666666, 0.9166666666666666, 0.9166666666666666},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("tag"),
Value: []byte("xx"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`histogram_quantile(negative-bucket-count)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.6,
label_set(90, "foo", "bar", "le", "10")
or label_set(-100, "foo", "bar", "le", "30")
or label_set(300, "foo", "bar", "le", "+Inf")
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{30, 30, 30, 30, 30, 30},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_quantile(nan-bucket-count-some)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.6,
label_set(90, "foo", "bar", "le", "10")
or label_set(NaN, "foo", "bar", "le", "30")
or label_set(300, "foo", "bar", "le", "+Inf")
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{30, 30, 30, 30, 30, 30},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_quantile(normal-bucket-count)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.2,
label_set(0, "foo", "bar", "le", "10")
or label_set(100, "foo", "bar", "le", "30")
or label_set(300, "foo", "bar", "le", "+Inf")
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{22, 22, 22, 22, 22, 22},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_share(normal-bucket-count)`, func(t *testing.T) {
t.Parallel()
q := `histogram_share(35,
label_set(0, "foo", "bar", "le", "10")
or label_set(100, "foo", "bar", "le", "30")
or label_set(300, "foo", "bar", "le", "+Inf")
)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_quantile(normal-bucket-count, boundsLabel)`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram_quantile(0.2,
label_set(0, "foo", "bar", "le", "10")
or label_set(100, "foo", "bar", "le", "30")
or label_set(300, "foo", "bar", "le", "+Inf"),
"xxx"
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10, 10, 10},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xxx"),
Value: []byte("lower"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{22, 22, 22, 22, 22, 22},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{30, 30, 30, 30, 30, 30},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xxx"),
Value: []byte("upper"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`histogram_share(normal-bucket-count, boundsLabel)`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram_share(22,
label_set(0, "foo", "bar", "le", "10")
or label_set(100, "foo", "bar", "le", "30")
or label_set(300, "foo", "bar", "le", "+Inf"),
"xxx"
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xxx"),
Value: []byte("lower"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.2, 0.2, 0.2, 0.2, 0.2, 0.2},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xxx"),
Value: []byte("upper"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`histogram_quantile(zero-bucket-count)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.6,
label_set(0, "foo", "bar", "le", "10")
or label_set(0, "foo", "bar", "le", "30")
or label_set(0, "foo", "bar", "le", "+Inf")
)`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`histogram_quantile(nan-bucket-count-all)`, func(t *testing.T) {
t.Parallel()
q := `histogram_quantile(0.6,
label_set(nan, "foo", "bar", "le", "10")
or label_set(nan, "foo", "bar", "le", "30")
or label_set(nan, "foo", "bar", "le", "+Inf")
)`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`prometheus_buckets(missing-vmrange)`, func(t *testing.T) {
t.Parallel()
q := `sort(prometheus_buckets((
alias(label_set(time()/20, "foo", "bar", "le", "0.2"), "xyz"),
alias(label_set(time()/100, "foo", "bar", "vmrange", "foobar"), "xxx"),
alias(label_set(time()/100, "foo", "bar", "vmrange", "30...foobar"), "xxx"),
alias(label_set(time()/100, "foo", "bar", "vmrange", "30...40"), "xxx"),
alias(label_set(time()/80, "foo", "bar", "vmrange", "0...900", "le", "54"), "yyy"),
alias(label_set(time()/40, "foo", "bar", "vmrange", "900...+Inf", "le", "2343"), "yyy"),
)))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("xxx")
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("30"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 12, 14, 16, 18, 20},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("xxx")
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("40"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 12, 14, 16, 18, 20},
Timestamps: timestampsExpected,
}
r3.MetricName.MetricGroup = []byte("xxx")
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("+Inf"),
},
}
r4 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{12.5, 15, 17.5, 20, 22.5, 25},
Timestamps: timestampsExpected,
}
r4.MetricName.MetricGroup = []byte("yyy")
r4.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("900"),
},
}
r5 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{37.5, 45, 52.5, 60, 67.5, 75},
Timestamps: timestampsExpected,
}
r5.MetricName.MetricGroup = []byte("yyy")
r5.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("+Inf"),
},
}
r6 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{50, 60, 70, 80, 90, 100},
Timestamps: timestampsExpected,
}
r6.MetricName.MetricGroup = []byte("xyz")
r6.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("0.2"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3, r4, r5, r6}
f(q, resultExpected)
})
t.Run(`prometheus_buckets(valid)`, func(t *testing.T) {
t.Parallel()
q := `sort(prometheus_buckets((
alias(label_set(90, "foo", "bar", "vmrange", "0...0"), "xxx"),
alias(label_set(time()/20, "foo", "bar", "vmrange", "0...0.2"), "xxx"),
alias(label_set(time()/100, "foo", "bar", "vmrange", "0.2...40"), "xxx"),
alias(label_set(time()/10, "foo", "bar", "vmrange", "40...Inf"), "xxx"),
)))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{90, 90, 90, 90, 90, 90},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("xxx")
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("0"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{140, 150, 160, 170, 180, 190},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("xxx")
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("0.2"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{150, 162, 174, 186, 198, 210},
Timestamps: timestampsExpected,
}
r3.MetricName.MetricGroup = []byte("xxx")
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("40"),
},
}
r4 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{250, 282, 314, 346, 378, 410},
Timestamps: timestampsExpected,
}
r4.MetricName.MetricGroup = []byte("xxx")
r4.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("le"),
Value: []byte("Inf"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3, r4}
f(q, resultExpected)
})
t.Run(`median_over_time()`, func(t *testing.T) {
t.Parallel()
q := `median_over_time({})`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`sum(scalar)`, func(t *testing.T) {
t.Parallel()
q := `sum(123)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{123, 123, 123, 123, 123, 123},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum(scalar) by ()`, func(t *testing.T) {
t.Parallel()
q := `sum(123) by ()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{123, 123, 123, 123, 123, 123},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum(scalar) without ()`, func(t *testing.T) {
t.Parallel()
q := `sum(123) without ()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{123, 123, 123, 123, 123, 123},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`avg(scalar) without (xx, yy)`, func(t *testing.T) {
t.Parallel()
q := `avg without (xx, yy) (123)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{123, 123, 123, 123, 123, 123},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram(scalar)`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram(123)+(
label_set(0, "le", "1.0e2"),
label_set(0, "le", "1.5e2"),
label_set(1, "le", "+Inf"),
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("le"),
Value: []byte("1.0e2"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("le"),
Value: []byte("1.5e2"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("le"),
Value: []byte("+Inf"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`histogram(vector)`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram((
label_set(1, "foo", "bar"),
label_set(1.1, "xx", "yy"),
alias(1.15, "foobar"),
))+(
label_set(0, "le", "9.5e-1"),
label_set(0, "le", "1.0e0"),
label_set(0, "le", "1.5e0"),
label_set(1, "le", "+Inf"),
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("le"),
Value: []byte("9.5e-1"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("le"),
Value: []byte("1.0e0"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{3, 3, 3, 3, 3, 3},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("le"),
Value: []byte("1.5e0"),
},
}
r4 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{4, 4, 4, 4, 4, 4},
Timestamps: timestampsExpected,
}
r4.MetricName.Tags = []storage.Tag{
{
Key: []byte("le"),
Value: []byte("+Inf"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3, r4}
f(q, resultExpected)
})
t.Run(`avg(scalar) wiTHout (xx, yy)`, func(t *testing.T) {
t.Parallel()
q := `avg wiTHout (xx, yy) (123)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{123, 123, 123, 123, 123, 123},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum(time)`, func(t *testing.T) {
t.Parallel()
q := `sum(time()/100)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 12, 14, 16, 18, 20},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`geomean(time)`, func(t *testing.T) {
t.Parallel()
q := `geomean(time()/100)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 12, 14, 16, 18, 20},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`geomean_over_time(time)`, func(t *testing.T) {
t.Parallel()
q := `round(geomean_over_time(alias(time()/100, "foobar")[3i]), 0.1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.8, 8.8, 10.9, 12.9, 14.9, 16.9},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("foobar")
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum2(time)`, func(t *testing.T) {
t.Parallel()
q := `sum2(time()/100)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{100, 144, 196, 256, 324, 400},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum2_over_time(time)`, func(t *testing.T) {
t.Parallel()
q := `sum2_over_time(alias(time()/100, "foobar")[3i])`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{155, 251, 371, 515, 683, 875},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum(multi-vector)`, func(t *testing.T) {
t.Parallel()
q := `sum(label_set(10, "foo", "bar") or label_set(time()/100, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{20, 22, 24, 26, 28, 30},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`geomean(multi-vector)`, func(t *testing.T) {
t.Parallel()
q := `round(geomean(label_set(10, "foo", "bar") or label_set(time()/100, "baz", "sss")), 0.1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 11, 11.8, 12.6, 13.4, 14.1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum2(multi-vector)`, func(t *testing.T) {
t.Parallel()
q := `sum2(label_set(10, "foo", "bar") or label_set(time()/100, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 244, 296, 356, 424, 500},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sqrt(sum2(multi-vector))`, func(t *testing.T) {
t.Parallel()
q := `round(sqrt(sum2(label_set(10, "foo", "bar") or label_set(time()/100, "baz", "sss"))))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{14, 16, 17, 19, 21, 22},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`avg(multi-vector)`, func(t *testing.T) {
t.Parallel()
q := `avg(label_set(10, "foo", "bar") or label_set(time()/100, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 11, 12, 13, 14, 15},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`stddev(multi-vector)`, func(t *testing.T) {
t.Parallel()
q := `stddev(label_set(10, "foo", "bar") or label_set(time()/100, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 1, 2, 3, 4, 5},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`count(multi-vector)`, func(t *testing.T) {
t.Parallel()
q := `count(label_set(time()<1500, "foo", "bar") or label_set(time()<1800, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 1, nan, nan},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum(multi-vector) by (known-tag)`, func(t *testing.T) {
t.Parallel()
q := `sort(sum(label_set(10, "foo", "bar") or label_set(time()/100, "baz", "sss")) by (foo))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10, 10, 10},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 12, 14, 16, 18, 20},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`sum(multi-vector) by (known-tags)`, func(t *testing.T) {
t.Parallel()
q := `sum(label_set(10, "foo", "bar", "baz", "sss", "x", "y") or label_set(time()/100, "baz", "sss", "foo", "bar")) by (foo, baz, foo)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{20, 22, 24, 26, 28, 30},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("baz"),
Value: []byte("sss"),
},
{
Key: []byte("foo"),
Value: []byte("bar"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`sum(multi-vector) by (__name__)`, func(t *testing.T) {
t.Parallel()
q := `sort(sum(label_set(10, "__name__", "bar", "baz", "sss", "x", "y") or label_set(time()/100, "baz", "sss", "__name__", "aaa")) by (__name__))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10, 10, 10},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("bar")
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 12, 14, 16, 18, 20},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("aaa")
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`min(multi-vector) by (unknown-tag)`, func(t *testing.T) {
t.Parallel()
q := `min(label_set(10, "foo", "bar") or label_set(time()/100/1.5, "baz", "sss")) by (unknowntag)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, 10, 10, 10},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`max(multi-vector) by (unknown-tag)`, func(t *testing.T) {
t.Parallel()
q := `max(label_set(10, "foo", "bar") or label_set(time()/100/1.5, "baz", "sss")) by (unknowntag)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`histogram_over_time`, func(t *testing.T) {
t.Parallel()
q := `sort(histogram_over_time(alias(label_set(rand(0)*1.3+1.1, "foo", "bar"), "xxx")[200s:5s]))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{13, 14, 12, 8, 12, 13},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("vmrange"),
Value: []byte("1.0e0...1.5e0"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{14, 15, 12, 13, 15, 11},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("vmrange"),
Value: []byte("2.0e0...2.5e0"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{13, 11, 16, 19, 13, 16},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("vmrange"),
Value: []byte("1.5e0...2.0e0"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`sum(histogram_over_time) by (vmrange)`, func(t *testing.T) {
t.Parallel()
q := `sort(sum(histogram_over_time(alias(label_set(rand(0)*1.3+1.1, "foo", "bar"), "xxx")[200s:5s])) by (vmrange))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{13, 14, 12, 8, 12, 13},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("vmrange"),
Value: []byte("1.0e0...1.5e0"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{14, 15, 12, 13, 15, 11},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("vmrange"),
Value: []byte("2.0e0...2.5e0"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{13, 11, 16, 19, 13, 16},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("vmrange"),
Value: []byte("1.5e0...2.0e0"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`sum(histogram_over_time)`, func(t *testing.T) {
t.Parallel()
q := `sum(histogram_over_time(alias(label_set(rand(0)*1.3+1.1, "foo", "bar"), "xxx")[200s:5s]))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{40, 40, 40, 40, 40, 40},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`topk_max(histogram_over_time)`, func(t *testing.T) {
t.Parallel()
q := `topk_max(1, histogram_over_time(alias(label_set(rand(0)*1.3+1.1, "foo", "bar"), "xxx")[200s:5s]))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{13, 11, 16, 19, 13, 16},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("vmrange"),
Value: []byte("1.5e0...2.0e0"),
},
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`share_gt_over_time`, func(t *testing.T) {
t.Parallel()
q := `share_gt_over_time(rand(0)[200s:10s], 0.7)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.35, 0.3, 0.5, 0.3, 0.3, 0.25},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`share_le_over_time`, func(t *testing.T) {
t.Parallel()
q := `share_le_over_time(rand(0)[200s:10s], 0.7)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.65, 0.7, 0.5, 0.7, 0.7, 0.75},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`increases_over_time`, func(t *testing.T) {
t.Parallel()
q := `increases_over_time(rand(0)[200s:10s])`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{11, 9, 9, 12, 9, 8},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`decreases_over_time`, func(t *testing.T) {
t.Parallel()
q := `decreases_over_time(rand(0)[200s:10s])`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{9, 11, 11, 8, 11, 12},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`limitk(-1)`, func(t *testing.T) {
t.Parallel()
q := `limitk(-1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`limitk(1)`, func(t *testing.T) {
t.Parallel()
q := `limitk(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10, 10, 10},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`limitk(10)`, func(t *testing.T) {
t.Parallel()
q := `sort(limitk(10, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10, 10, 10},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`topk(-1)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk(-1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`topk(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`topk_min(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk_min(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`bottomk_min(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(bottomk_min(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`topk_max(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk_max(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`bottomk_max(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(bottomk_max(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`topk_avg(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk_avg(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`bottomk_avg(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(bottomk_avg(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`topk_median(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk_median(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`bottomk_median(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(bottomk_median(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`topk(1, nan_timeseries)`, func(t *testing.T) {
t.Parallel()
q := `topk(1, label_set(NaN, "foo", "bar") or label_set(time()/150, "baz", "sss")) default 0`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`topk(2)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk(2, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10, 10, 10},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`topk(NaN)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk(NaN, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`topk(100500)`, func(t *testing.T) {
t.Parallel()
q := `sort(topk(100500, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10, 10, 10},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`bottomk(1)`, func(t *testing.T) {
t.Parallel()
q := `sort(bottomk(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("baz"),
Value: []byte("sss"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, 10, 10, 10},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`keep_last_value()`, func(t *testing.T) {
t.Parallel()
q := `keep_last_value(label_set(time() < 1300 default time() > 1700, "__name__", "foobar", "x", "y"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1200, 1200, 1800, 2000},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("foobar")
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("x"),
Value: []byte("y"),
}}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`distinct_over_time([500s])`, func(t *testing.T) {
t.Parallel()
q := `distinct_over_time((time() < 1700)[500s])`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{3, 3, 3, 3, 2, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`distinct_over_time([2.5i])`, func(t *testing.T) {
t.Parallel()
q := `distinct_over_time((time() < 1700)[2.5i])`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{3, 3, 3, 3, 2, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`distinct()`, func(t *testing.T) {
t.Parallel()
q := `distinct(union(
1+time() > 1100,
label_set(time() > 1700, "foo", "bar"),
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, 1, 1, 1, 2, 2},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r1}
f(q, resultExpected)
})
t.Run(`if-default`, func(t *testing.T) {
t.Parallel()
q := `time() if time() > 1400 default -time()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-1000, -1200, -1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ifnot-default`, func(t *testing.T) {
t.Parallel()
q := `time() ifnot time() > 1400 default -time()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, -1600, -1800, -2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`quantile(-2)`, func(t *testing.T) {
t.Parallel()
q := `quantile(-2, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, 10, 10, 10},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`quantile(0.2)`, func(t *testing.T) {
t.Parallel()
q := `quantile(0.2, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, 10, 10, 10},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`quantile(0.5)`, func(t *testing.T) {
t.Parallel()
q := `quantile(0.5, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`median()`, func(t *testing.T) {
t.Parallel()
q := `median(label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`median(3-timeseries)`, func(t *testing.T) {
t.Parallel()
q := `median(union(label_set(10, "foo", "bar"), label_set(time()/150, "baz", "sss"), time()/200))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6.666666666666667, 8, 9.333333333333334, 10, 10, 10},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`quantile(3)`, func(t *testing.T) {
t.Parallel()
q := `quantile(3, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`quantile(NaN)`, func(t *testing.T) {
t.Parallel()
q := `quantile(NaN, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{10, 10, 10, 10.666666666666666, 12, 13.333333333333334},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`range_quantile(0.5)`, func(t *testing.T) {
t.Parallel()
q := `range_quantile(0.5, time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1600, 1600, 1600, 1600, 1600, 1600},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`range_median()`, func(t *testing.T) {
t.Parallel()
q := `range_median(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1600, 1600, 1600, 1600, 1600, 1600},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ttf(2000-time())`, func(t *testing.T) {
t.Parallel()
q := `ttf(2000-time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 866.6666666666666, 688.8888888888889, 496.2962962962963, 298.7654320987655, 99.58847736625516},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ttf(1000-time())`, func(t *testing.T) {
t.Parallel()
q := `ttf(1000-time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ttf(1500-time())`, func(t *testing.T) {
t.Parallel()
q := `ttf(1500-time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{500, 366.6666666666667, 188.8888888888889, 62.962962962962976, 20.987654320987662, 6.995884773662555},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ru(time(), 2000)`, func(t *testing.T) {
t.Parallel()
q := `ru(time(), 2000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{50, 40, 30, 20, 10, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ru(time() offset 100s, 2000)`, func(t *testing.T) {
t.Parallel()
q := `ru(time() offset 100s, 2000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{60, 50, 40, 30, 20, 10},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ru(time() offset 0.5i, 2000)`, func(t *testing.T) {
t.Parallel()
q := `ru(time() offset 0.5i, 2000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{60, 50, 40, 30, 20, 10},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ru(time() offset 1i, 2000)`, func(t *testing.T) {
t.Parallel()
q := `ru(time() offset 1i, 2000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{65, 55.00000000000001, 45, 35, 25, 15},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ru(time(), 1600)`, func(t *testing.T) {
t.Parallel()
q := `ru(time(), 1600)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{37.5, 25, 12.5, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`ru(1500-time(), 1000)`, func(t *testing.T) {
t.Parallel()
q := `ru(1500-time(), 1000)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{50, 70, 90, 100, 100, 100},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`integrate(1)`, func(t *testing.T) {
t.Parallel()
q := `integrate(1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 200, 200, 200, 200, 200},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`integrate(time())`, func(t *testing.T) {
t.Parallel()
q := `integrate(time()*1e-3)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{160, 200, 240.00000000000003, 280, 320, 360},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rate(time())`, func(t *testing.T) {
t.Parallel()
q := `rate(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rate(2000-time())`, func(t *testing.T) {
t.Parallel()
q := `rate(2000-time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{5.5, 4.5, 3.5, 2.5, 1.5, 0.5},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rate((2000-time())[100s])`, func(t *testing.T) {
t.Parallel()
q := `rate((2000-time())[100s])`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{5.5, 4.5, 3.5, 2.5, 1.5, 0.5},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rate((2000-time())[100s:])`, func(t *testing.T) {
t.Parallel()
q := `rate((2000-time())[100s:])`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{5.5, 4.5, 3.5, 2.5, 1.5, 0.5},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rate((2000-time())[100s:100s])`, func(t *testing.T) {
t.Parallel()
q := `rate((2000-time())[100s:100s])`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{5.5, 4.5, 6.5, 4.5, 2.5, 0.5},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rate((2000-time())[100s:100s] offset 100s)`, func(t *testing.T) {
t.Parallel()
q := `rate((2000-time())[100s:100s] offset 100s)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{6, 5, 7.5, 5.5, 3.5, 1.5},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rate((2000-time())[100s:100s] offset 100s)[:] offset 100s`, func(t *testing.T) {
t.Parallel()
q := `rate((2000-time())[100s:100s] offset 100s)[:] offset 100s`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{7, 6, 5, 7.5, 5.5, 3.5},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`increase(time())`, func(t *testing.T) {
t.Parallel()
q := `increase(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 200, 200, 200, 200, 200},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`increase(2000-time())`, func(t *testing.T) {
t.Parallel()
q := `increase(2000-time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1100, 900, 700, 500, 300, 100},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`running_max(1)`, func(t *testing.T) {
t.Parallel()
q := `running_max(1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`running_min(abs(1500-time()))`, func(t *testing.T) {
t.Parallel()
q := `running_min(abs(1500-time()))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{500, 300, 100, 100, 100, 100},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`running_max(abs(1300-time()))`, func(t *testing.T) {
t.Parallel()
q := `running_max(abs(1300-time()))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{300, 300, 300, 300, 500, 700},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`running_sum(1)`, func(t *testing.T) {
t.Parallel()
q := `running_sum(1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 2, 3, 4, 5, 6},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`running_sum(time())`, func(t *testing.T) {
t.Parallel()
q := `running_sum(time()/1e3)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 2.2, 3.6, 5.2, 7, 9},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`running_avg(time())`, func(t *testing.T) {
t.Parallel()
q := `running_avg(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1100, 1200, 1300, 1400, 1500},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`smooth_exponential(time(), 1)`, func(t *testing.T) {
t.Parallel()
q := `smooth_exponential(time(), 1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`smooth_exponential(time(), 0)`, func(t *testing.T) {
t.Parallel()
q := `smooth_exponential(time(), 0)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1000, 1000, 1000, 1000, 1000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`smooth_exponential(time(), 0.5)`, func(t *testing.T) {
t.Parallel()
q := `smooth_exponential(time(), 0.5)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1100, 1250, 1425, 1612.5, 1806.25},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`remove_resets()`, func(t *testing.T) {
t.Parallel()
q := `remove_resets( abs(1500-time()) )`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{500, 800, 900, 900, 1100, 1300},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`range_avg(time())`, func(t *testing.T) {
t.Parallel()
q := `range_avg(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1500, 1500, 1500, 1500, 1500, 1500},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`range_min(time())`, func(t *testing.T) {
t.Parallel()
q := `range_min(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1000, 1000, 1000, 1000, 1000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`range_first(time())`, func(t *testing.T) {
t.Parallel()
q := `range_first(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1000, 1000, 1000, 1000, 1000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`range_max(time())`, func(t *testing.T) {
t.Parallel()
q := `range_max(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2000, 2000, 2000, 2000, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`range_last(time())`, func(t *testing.T) {
t.Parallel()
q := `range_last(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2000, 2000, 2000, 2000, 2000, 2000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`deriv(1)`, func(t *testing.T) {
t.Parallel()
q := `deriv(1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`deriv(time())`, func(t *testing.T) {
t.Parallel()
q := `deriv(2*time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`deriv(-time())`, func(t *testing.T) {
t.Parallel()
q := `deriv(-time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-1, -1, -1, -1, -1, -1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`delta(time())`, func(t *testing.T) {
t.Parallel()
q := `delta(time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 200, 200, 200, 200, 200},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`delta(delta(time()))`, func(t *testing.T) {
t.Parallel()
q := `delta(delta(2*time()))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`delta(-time())`, func(t *testing.T) {
t.Parallel()
q := `delta(-time())`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{-200, -200, -200, -200, -200, -200},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`delta(1)`, func(t *testing.T) {
t.Parallel()
q := `delta(1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 0, 0, 0, 0, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`median_over_time("foo")`, func(t *testing.T) {
t.Parallel()
q := `median_over_time("foo")`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`median_over_time(12)`, func(t *testing.T) {
t.Parallel()
q := `median_over_time(12)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{12, 12, 12, 12, 12, 12},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`rollup_candlestick()`, func(t *testing.T) {
t.Parallel()
q := `sort(rollup_candlestick(round(rand(0),0.01)[:10s]))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.02, 0.02, 0.03, 0, 0.03, 0.02},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("low"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.32, 0.82, 0.13, 0.28, 0.86, 0.57},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("close"),
}}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.9, 0.32, 0.82, 0.13, 0.28, 0.86},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("open"),
}}
r4 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0.9, 0.94, 0.97, 0.93, 0.98, 0.92},
Timestamps: timestampsExpected,
}
r4.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("high"),
}}
resultExpected := []netstorage.Result{r1, r2, r3, r4}
f(q, resultExpected)
})
t.Run(`rollup_increase()`, func(t *testing.T) {
t.Parallel()
q := `sort(rollup_increase(time()))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 200, 200, 200, 200, 200},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("min"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 200, 200, 200, 200, 200},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("max"),
}}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{200, 200, 200, 200, 200, 200},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("avg"),
}}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`rollup()`, func(t *testing.T) {
t.Parallel()
q := `sort(rollup(time()[:50s]))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{800, 1000, 1200, 1400, 1600, 1800},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("min"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{925, 1125, 1325, 1525, 1725, 1925},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("avg"),
}}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("max"),
}}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`rollup_deriv()`, func(t *testing.T) {
t.Parallel()
q := `sort(rollup_deriv(time()[100s:50s]))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("min"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("max"),
}}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{{
Key: []byte("rollup"),
Value: []byte("avg"),
}}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`{}`, func(t *testing.T) {
t.Parallel()
q := `{}`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`rate({}[:5s])`, func(t *testing.T) {
t.Parallel()
q := `rate({}[:5s])`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`start()`, func(t *testing.T) {
t.Parallel()
q := `time() - start()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{0, 200, 400, 600, 800, 1000},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`end()`, func(t *testing.T) {
t.Parallel()
q := `end() - time()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 800, 600, 400, 200, 0},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`step()`, func(t *testing.T) {
t.Parallel()
q := `time() / step()`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{5, 6, 7, 8, 9, 10},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`lag()`, func(t *testing.T) {
t.Parallel()
q := `lag(time()[60s:17s])`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{14, 10, 6, 2, 15, 11},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`()`, func(t *testing.T) {
t.Parallel()
q := `()`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`union()`, func(t *testing.T) {
t.Parallel()
q := `union()`
resultExpected := []netstorage.Result{}
f(q, resultExpected)
})
t.Run(`union(1)`, func(t *testing.T) {
t.Parallel()
q := `union(1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`(1)`, func(t *testing.T) {
t.Parallel()
q := `(1)`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`union(identical_labels)`, func(t *testing.T) {
t.Parallel()
q := `union(label_set(1, "foo", "bar"), label_set(2, "foo", "bar"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`(identical_labels)`, func(t *testing.T) {
t.Parallel()
q := `(label_set(1, "foo", "bar"), label_set(2, "foo", "bar"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`union(identical_labels_with_names)`, func(t *testing.T) {
t.Parallel()
q := `union(label_set(1, "foo", "bar", "__name__", "xx"), label_set(2, "__name__", "xx", "foo", "bar"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("xx")
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`(identical_labels_with_names)`, func(t *testing.T) {
t.Parallel()
q := `(label_set(1, "foo", "bar", "__name__", "xx"), label_set(2, "__name__", "xx", "foo", "bar"))`
r := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r.MetricName.MetricGroup = []byte("xx")
r.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r}
f(q, resultExpected)
})
t.Run(`union(identical_labels_different_names)`, func(t *testing.T) {
t.Parallel()
q := `union(label_set(1, "foo", "bar", "__name__", "xx"), label_set(2, "__name__", "yy", "foo", "bar"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("xx")
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("yy")
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`(identical_labels_different_names)`, func(t *testing.T) {
t.Parallel()
q := `(label_set(1, "foo", "bar", "__name__", "xx"), label_set(2, "__name__", "yy", "foo", "bar"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("xx")
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("yy")
r2.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1, r2}
f(q, resultExpected)
})
t.Run(`((1),(2,3))`, func(t *testing.T) {
t.Parallel()
q := `((
alias(1, "x1"),
),(
alias(2, "x2"),
alias(3, "x3"),
))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r1.MetricName.MetricGroup = []byte("x1")
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("x2")
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{3, 3, 3, 3, 3, 3},
Timestamps: timestampsExpected,
}
r3.MetricName.MetricGroup = []byte("x3")
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
t.Run(`union(more-than-two)`, func(t *testing.T) {
t.Parallel()
q := `union(
label_set(1, "foo", "bar", "__name__", "xx"),
label_set(2, "__name__", "yy", "foo", "bar"),
label_set(time(), "qwe", "123") or label_set(3, "__name__", "rt"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{{
Key: []byte("qwe"),
Value: []byte("123"),
}}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{3, 3, 3, 3, 3, 3},
Timestamps: timestampsExpected,
}
r2.MetricName.MetricGroup = []byte("rt")
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r3.MetricName.MetricGroup = []byte("xx")
r3.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
r4 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 2, 2, 2, 2, 2},
Timestamps: timestampsExpected,
}
r4.MetricName.MetricGroup = []byte("yy")
r4.MetricName.Tags = []storage.Tag{{
Key: []byte("foo"),
Value: []byte("bar"),
}}
resultExpected := []netstorage.Result{r1, r2, r3, r4}
f(q, resultExpected)
})
t.Run(`count_values`, func(t *testing.T) {
t.Parallel()
q := `count_values("xxx", label_set(10, "foo", "bar") or label_set(time()/100, "foo", "bar", "baz", "xx"))`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{2, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("10"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, 1, nan, nan, nan, nan},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("12"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, 1, nan, nan, nan},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("14"),
},
}
r4 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, 1, nan, nan},
Timestamps: timestampsExpected,
}
r4.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("16"),
},
}
r5 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, nan, 1, nan},
Timestamps: timestampsExpected,
}
r5.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("18"),
},
}
r6 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, nan, nan, 1},
Timestamps: timestampsExpected,
}
r6.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("20"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3, r4, r5, r6}
f(q, resultExpected)
})
t.Run(`count_values by (xxx)`, func(t *testing.T) {
t.Parallel()
q := `count_values("xxx", label_set(10, "foo", "bar", "xxx", "aaa") or label_set(floor(time()/600), "foo", "bar", "baz", "xx")) by (xxx)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, nan, nan, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("1"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, 1, 1, 1, nan, nan},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("2"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, nan, 1, 1},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("3"),
},
}
r4 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, 1, 1, 1, 1, 1},
Timestamps: timestampsExpected,
}
r4.MetricName.Tags = []storage.Tag{
{
Key: []byte("xxx"),
Value: []byte("10"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3, r4}
f(q, resultExpected)
})
t.Run(`count_values without (baz)`, func(t *testing.T) {
t.Parallel()
q := `count_values("xxx", label_set(floor(time()/600), "foo", "bar")) without (baz)`
r1 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{1, nan, nan, nan, nan, nan},
Timestamps: timestampsExpected,
}
r1.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xxx"),
Value: []byte("1"),
},
}
r2 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, 1, 1, 1, nan, nan},
Timestamps: timestampsExpected,
}
r2.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xxx"),
Value: []byte("2"),
},
}
r3 := netstorage.Result{
MetricName: metricNameExpected,
Values: []float64{nan, nan, nan, nan, 1, 1},
Timestamps: timestampsExpected,
}
r3.MetricName.Tags = []storage.Tag{
{
Key: []byte("foo"),
Value: []byte("bar"),
},
{
Key: []byte("xxx"),
Value: []byte("3"),
},
}
resultExpected := []netstorage.Result{r1, r2, r3}
f(q, resultExpected)
})
}
func TestExecError(t *testing.T) {
f := func(q string) {
t.Helper()
ec := &EvalConfig{
Start: 1000,
End: 2000,
Step: 100,
Deadline: netstorage.NewDeadline(time.Minute),
}
for i := 0; i < 4; i++ {
rv, err := Exec(ec, q, false)
if err == nil {
t.Fatalf(`expecting non-nil error on %q`, q)
}
if rv != nil {
t.Fatalf(`expecting nil rv`)
}
rv, err = Exec(ec, q, true)
if err == nil {
t.Fatalf(`expecting non-nil error on %q`, q)
}
if rv != nil {
t.Fatalf(`expecting nil rv`)
}
}
}
// Empty expr
f("")
f(" ")
// Invalid expr
f("1-")
// Non-existing func
f(`nonexisting()`)
// Invalid number of args
f(`range_quantile()`)
f(`range_quantile(1, 2, 3)`)
f(`range_median()`)
f(`abs()`)
f(`abs(1,2)`)
f(`absent(1, 2)`)
f(`clamp_max()`)
f(`clamp_min(1,2,3)`)
f(`hour(1,2)`)
f(`label_join()`)
f(`label_replace(1)`)
f(`label_transform(1)`)
f(`label_set()`)
f(`label_set(1, "foo")`)
f(`label_del()`)
f(`label_keep()`)
f(`round()`)
f(`round(1,2,3)`)
f(`scalar()`)
f(`sort(1,2)`)
f(`sort_desc()`)
f(`timestamp()`)
f(`vector()`)
f(`histogram_quantile()`)
f(`sum()`)
f(`count_values()`)
f(`quantile()`)
f(`topk()`)
f(`topk_min()`)
f(`topk_max()`)
f(`topk_avg()`)
f(`topk_median()`)
f(`limitk()`)
f(`bottomk()`)
f(`bottomk_min()`)
f(`bottomk_max()`)
f(`bottomk_avg()`)
f(`bottomk_median()`)
f(`time(123)`)
f(`start(1)`)
f(`end(1)`)
f(`step(1)`)
f(`running_sum(1, 2)`)
f(`range_sum(1, 2)`)
f(`range_first(1, 2)`)
f(`range_last(1, 2)`)
f(`smooth_exponential()`)
f(`smooth_exponential(1)`)
f(`remove_resets()`)
f(`sin()`)
f(`cos()`)
f(`asin()`)
f(`acos()`)
f(`rand(123, 456)`)
f(`rand_normal(123, 456)`)
f(`rand_exponential(122, 456)`)
f(`pi(123)`)
f(`label_copy()`)
f(`label_move()`)
f(`median_over_time()`)
f(`median()`)
f(`median("foo", "bar")`)
f(`keep_last_value()`)
f(`distinct_over_time()`)
f(`distinct()`)
f(`alias()`)
f(`alias(1)`)
f(`alias(1, "foo", "bar")`)
f(`lifetime()`)
f(`lag()`)
// Invalid argument type
f(`median_over_time({}, 2)`)
f(`smooth_exponential(1, 1 or label_set(2, "x", "y"))`)
f(`count_values(1, 2)`)
f(`count_values(1 or label_set(2, "xx", "yy"), 2)`)
f(`quantile(1 or label_set(2, "xx", "foo"), 1)`)
f(`clamp_max(1, 1 or label_set(2, "xx", "foo"))`)
f(`clamp_min(1, 1 or label_set(2, "xx", "foo"))`)
f(`topk(label_set(2, "xx", "foo") or 1, 12)`)
f(`topk_avg(label_set(2, "xx", "foo") or 1, 12)`)
f(`limitk(label_set(2, "xx", "foo") or 1, 12)`)
f(`round(1, 1 or label_set(2, "xx", "foo"))`)
f(`histogram_quantile(1 or label_set(2, "xx", "foo"), 1)`)
f(`label_set(1, 2, 3)`)
f(`label_set(1, "foo", (label_set(1, "foo", bar") or label_set(2, "xxx", "yy")))`)
f(`label_set(1, "foo", 3)`)
f(`label_del(1, 2)`)
f(`label_copy(1, 2)`)
f(`label_move(1, 2, 3)`)
f(`label_move(1, "foo", 3)`)
f(`label_keep(1, 2)`)
f(`label_join(1, 2, 3)`)
f(`label_join(1, "foo", 2)`)
f(`label_join(1, "foo", "bar", 2)`)
f(`label_replace(1, 2, 3, 4, 5)`)
f(`label_replace(1, "foo", 3, 4, 5)`)
f(`label_replace(1, "foo", "bar", 4, 5)`)
f(`label_replace(1, "foo", "bar", "baz", 5)`)
f(`label_replace(1, "foo", "bar", "baz", "invalid(regexp")`)
f(`label_transform(1, 2, 3, 4)`)
f(`label_transform(1, "foo", 3, 4)`)
f(`label_transform(1, "foo", "bar", 4)`)
f(`label_transform(1, "foo", "invalid(regexp", "baz`)
f(`alias(1, 2)`)
// Duplicate timeseries
f(`(label_set(1, "foo", "bar") or label_set(2, "foo", "baz"))
+ on(xx)
(label_set(1, "foo", "bar") or label_set(2, "foo", "baz"))`)
// Invalid binary op groupings
f(`1 + group_left() (label_set(1, "foo", bar"), label_set(2, "foo", "baz"))`)
f(`1 + on() group_left() (label_set(1, "foo", bar"), label_set(2, "foo", "baz"))`)
f(`1 + on(a) group_left(b) (label_set(1, "foo", bar"), label_set(2, "foo", "baz"))`)
f(`label_set(1, "foo", "bar") + on(foo) group_left() (label_set(1, "foo", "bar", "a", "b"), label_set(1, "foo", "bar", "a", "c"))`)
f(`(label_set(1, "foo", bar"), label_set(2, "foo", "baz")) + group_right 1`)
f(`(label_set(1, "foo", bar"), label_set(2, "foo", "baz")) + on() group_right 1`)
f(`(label_set(1, "foo", bar"), label_set(2, "foo", "baz")) + on(a) group_right(b,c) 1`)
f(`(label_set(1, "foo", bar"), label_set(2, "foo", "baz")) + on() 1`)
f(`(label_set(1, "foo", "bar", "a", "b"), label_set(1, "foo", "bar", "a", "c")) + on(foo) group_right() label_set(1, "foo", "bar")`)
f(`1 + on() (label_set(1, "foo", bar"), label_set(2, "foo", "baz"))`)
// duplicate metrics after binary op
f(`(
label_set(time(), "__name__", "foo", "a", "x"),
label_set(time()+200, "__name__", "bar", "a", "x"),
) > bool 1300`)
f(`(
label_set(time(), "__name__", "foo", "a", "x"),
label_set(time()+200, "__name__", "bar", "a", "x"),
) + 10`)
// Invalid aggregates
f(`sum(1, 2)`)
f(`sum(1) foo (bar)`)
f(`sum foo () (bar)`)
f(`sum(foo) by (1)`)
f(`count(foo) without ("bar")`)
// With expressions
f(`ttf()`)
f(`ttf(1, 2)`)
f(`ru()`)
f(`ru(1)`)
f(`ru(1,3,3)`)
}
func testResultsEqual(t *testing.T, result, resultExpected []netstorage.Result) {
t.Helper()
if len(result) != len(resultExpected) {
t.Fatalf(`unexpected timeseries count; got %d; want %d`, len(result), len(resultExpected))
}
for i := range result {
r := &result[i]
rExpected := &resultExpected[i]
testMetricNamesEqual(t, &r.MetricName, &rExpected.MetricName, i)
testRowsEqual(t, r.Values, r.Timestamps, rExpected.Values, rExpected.Timestamps)
}
}
func testMetricNamesEqual(t *testing.T, mn, mnExpected *storage.MetricName, pos int) {
t.Helper()
if string(mn.MetricGroup) != string(mnExpected.MetricGroup) {
t.Fatalf(`unexpected MetricGroup at #%d; got %q; want %q`, pos, mn.MetricGroup, mnExpected.MetricGroup)
}
if len(mn.Tags) != len(mnExpected.Tags) {
t.Fatalf(`unexpected tags count at #%d; got %d; want %d`, pos, len(mn.Tags), len(mnExpected.Tags))
}
for i := range mn.Tags {
tag := &mn.Tags[i]
tagExpected := &mnExpected.Tags[i]
if string(tag.Key) != string(tagExpected.Key) {
t.Fatalf(`unexpected tag key at #%d,%d; got %q; want %q`, pos, i, tag.Key, tagExpected.Key)
}
if string(tag.Value) != string(tagExpected.Value) {
t.Fatalf(`unexpected tag value for key %q at #%d,%d; got %q; want %q`, tag.Key, pos, i, tag.Value, tagExpected.Value)
}
}
}
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