package promql import ( "math" "testing" "time" "github.com/VictoriaMetrics/VictoriaMetrics/app/vmselect/netstorage" "github.com/VictoriaMetrics/VictoriaMetrics/app/vmselect/searchutils" "github.com/VictoriaMetrics/VictoriaMetrics/lib/auth" "github.com/VictoriaMetrics/VictoriaMetrics/lib/storage" "github.com/VictoriaMetrics/metricsql" ) func TestEscapeDots(t *testing.T) { f := func(s, resultExpected string) { t.Helper() result := escapeDots(s) if result != resultExpected { t.Fatalf("unexpected result for escapeDots(%q); got\n%s\nwant\n%s", s, result, resultExpected) } } f("", "") f("a", "a") f("foobar", "foobar") f(".", `\.`) f(".*", `.*`) f(".+", `.+`) f("..", `\.\.`) f("foo.b.{2}ar..+baz.*", `foo\.b.{2}ar\..+baz.*`) } func TestEscapeDotsInRegexpLabelFilters(t *testing.T) { f := func(s, resultExpected string) { t.Helper() e, err := metricsql.Parse(s) if err != nil { t.Fatalf("unexpected error in metricsql.Parse(%q): %s", s, err) } e = escapeDotsInRegexpLabelFilters(e) result := e.AppendString(nil) if string(result) != resultExpected { t.Fatalf("unexpected result for escapeDotsInRegexpLabelFilters(%q);\ngot\n%s\nwant\n%s", s, result, resultExpected) } } f("2", "2") f(`foo.bar + 123`, `foo.bar + 123`) f(`foo{bar=~"baz.xx.yyy"}`, `foo{bar=~"baz\\.xx\\.yyy"}`) f(`foo(a.b{c="d.e",x=~"a.b.+[.a]",y!~"aaa.bb|cc.dd"}) + x.y(1,sum({x=~"aa.bb"}))`, `foo(a.b{c="d.e", x=~"a\\.b.+[\\.a]", y!~"aaa\\.bb|cc\\.dd"}) + x.y(1, sum({x=~"aa\\.bb"}))`) } func TestExecSuccess(t *testing.T) { accountID := uint32(123) projectID := uint32(567) start := int64(1000e3) end := int64(2000e3) step := int64(200e3) timestampsExpected := []int64{1000e3, 1200e3, 1400e3, 1600e3, 1800e3, 2000e3} metricNameExpected := storage.MetricName{ AccountID: accountID, ProjectID: projectID, } f := func(q string, resultExpected []netstorage.Result) { t.Helper() ec := &EvalConfig{ AuthToken: &auth.Token{ AccountID: accountID, ProjectID: projectID, }, Start: start, End: end, Step: step, MaxSeries: 1000, Deadline: searchutils.NewDeadline(time.Now(), time.Minute, ""), RoundDigits: 100, } for i := 0; i < 5; i++ { result, err := Exec(nil, 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("bitmap_and(0xB3, 0x11)", func(t *testing.T) { t.Parallel() q := `bitmap_and(0xB3, 0x11)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{17, 17, 17, 17, 17, 17}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("bitmap_and(time(), 0x11)", func(t *testing.T) { t.Parallel() q := `bitmap_and(time(), 0x11)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0, 16, 16, 0, 0, 16}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("bitmap_or(0xA2, 0x11)", func(t *testing.T) { t.Parallel() q := `bitmap_or(0xA2, 0x11)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{179, 179, 179, 179, 179, 179}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("bitmap_or(time(), 0x11)", func(t *testing.T) { t.Parallel() q := `bitmap_or(time(), 0x11)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1017, 1201, 1401, 1617, 1817, 2001}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("bitmap_xor(0xB3, 0x11)", func(t *testing.T) { t.Parallel() q := `bitmap_xor(0xB3, 0x11)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{162, 162, 162, 162, 162, 162}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("bitmap_xor(time(), 0x11)", func(t *testing.T) { t.Parallel() q := `bitmap_xor(time(), 0x11)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1017, 1185, 1385, 1617, 1817, 1985}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("timezone_offset(UTC)", func(t *testing.T) { t.Parallel() q := `timezone_offset("UTC")` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0, 0, 0, 0, 0, 0}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("timezone_offset(America/New_York)", func(t *testing.T) { t.Parallel() q := `timezone_offset("America/New_York")` loc, err := time.LoadLocation("America/New_York") if err != nil { t.Fatalf("cannot obtain timezone: %s", err) } at := time.Unix(timestampsExpected[0]/1000, 0) _, offset := at.In(loc).Zone() off := float64(offset) r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{off, off, off, off, off, off}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("timezone_offset(Local)", func(t *testing.T) { t.Parallel() q := `timezone_offset("Local")` loc, err := time.LoadLocation("Local") if err != nil { t.Fatalf("cannot obtain timezone: %s", err) } at := time.Unix(timestampsExpected[0]/1000, 0) _, offset := at.In(loc).Zone() off := float64(offset) r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{off, off, off, off, off, off}, 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{1000, 1200, 1400, 1600, 1800, 2000}, 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{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1010, 1210, 1410, 1610, 1810, 2010}, 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()[:100] offset 0", func(t *testing.T) { t.Parallel() q := `time()[:100] offset 0` 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 1h40s0ms", func(t *testing.T) { t.Parallel() q := `time() offset 1h40s0ms` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{-2800, -2600, -2400, -2200, -2000, -1800}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("time() offset 3640", func(t *testing.T) { t.Parallel() q := `time() offset 3640` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{-2800, -2600, -2400, -2200, -2000, -1800}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("time() offset -1h40s0ms", func(t *testing.T) { t.Parallel() q := `time() offset -1h40s0ms` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{4600, 4800, 5000, 5200, 5400, 5600}, 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{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) 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{400, 600, 800, 1000, 1200, 1400}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{410, 610, 810, 1010, 1210, 1410}, 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{1400, 1600, 1800, 2000, 2200, 2400}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1410, 1610, 1810, 2010, 2210, 2410}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("baz"), }} resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run("1h", func(t *testing.T) { t.Parallel() q := `1h` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{3600, 3600, 3600, 3600, 3600, 3600}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("sum_over_time(time()[1h]) / 1h", func(t *testing.T) { t.Parallel() q := `sum_over_time(time()[1h]) / 1h` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{-3.5, -2.5, -1.5, -0.5, 0.5, 1.5}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} 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()[300:100] offset 100", func(t *testing.T) { t.Parallel() q := `time()[300:100] offset 100` 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{800, 1000, 1200, 1400, 1600, 1800}, 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("timestamp(alias(time()>=1600))", func(t *testing.T) { t.Parallel() q := `timestamp(alias(time()>=1600,"foo"))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("tlast_change_over_time(hit_last)", func(t *testing.T) { t.Parallel() q := `tlast_change_over_time( time()[1h] )` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("tlast_change_over_time(hit_middle)", func(t *testing.T) { t.Parallel() q := `tlast_change_over_time( (time() >=bool 1600)[1h] )` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 1600, 1600, 1600}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("tlast_change_over_time(miss)", func(t *testing.T) { t.Parallel() q := `tlast_change_over_time( 1[1h] )` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run("timestamp_with_name(alias(time()>=1600))", func(t *testing.T) { t.Parallel() q := `timestamp_with_name(alias(time()>=1600,"foo"))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("foo") 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(`minute(series_with_NaNs)`, func(t *testing.T) { t.Parallel() q := `minute(time() <= 1200 or time() > 1600)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{16, 20, nan, nan, 30, 33}, 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("present_over_time(time())", func(t *testing.T) { t.Parallel() q := `present_over_time(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("present_over_time(time()[100:300])", func(t *testing.T) { t.Parallel() q := `present_over_time(time()[100:300])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, 1, nan, nan, 1, nan}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("present_over_time(time()<10m)", func(t *testing.T) { t.Parallel() q := `present_over_time(time()<1600)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, nan, nan, nan}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} 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, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`absent_over_time(non-nan)`, func(t *testing.T) { t.Parallel() q := ` absent_over_time(time())` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`absent_over_time(nan)`, func(t *testing.T) { t.Parallel() q := ` absent_over_time((time() < 1500)[300s:])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, nan, 1, 1}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`absent_over_time(multi-ts)`, func(t *testing.T) { t.Parallel() q := ` absent_over_time(( alias((time() < 1400)[200s:], "one"), alias((time() > 1600)[200s:], "two"), ))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 1, nan, nan}, Timestamps: timestampsExpected, } 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(time(), 1400, 1800)", func(t *testing.T) { t.Parallel() q := `clamp(time(), 1400, 1800)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1400, 1400, 1400, 1600, 1800, 1800}, 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(alias(time()/1e3, "foobar"))` 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("exp(time()/1e3) keep_metric_names", func(t *testing.T) { t.Parallel() q := `exp(alias(time()/1e3, "foobar")) keep_metric_names` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2.718281828459045, 3.3201169227365472, 4.0551999668446745, 4.953032424395115, 6.0496474644129465, 7.38905609893065}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("foobar") resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("time() @ 1h", func(t *testing.T) { t.Parallel() q := `time() @ 1h` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{3600, 3600, 3600, 3600, 3600, 3600}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("time() @ start()", func(t *testing.T) { t.Parallel() q := `time() @ start()` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1000, 1000, 1000, 1000, 1000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("time() @ end()", func(t *testing.T) { t.Parallel() q := `time() @ end()` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2000, 2000, 2000, 2000, 2000, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("time() @ end() offset 10m", func(t *testing.T) { t.Parallel() q := `time() @ end() offset 10m` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1400, 1400, 1400, 1400, 1400, 1400}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("time() @ (end()-10m)", func(t *testing.T) { t.Parallel() q := `time() @ (end()-10m)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1400, 1400, 1400, 1400, 1400, 1400}, 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("now()", func(t *testing.T) { t.Parallel() q := `round(now()/now())` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, 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("sinh()", func(t *testing.T) { t.Parallel() q := `sinh(pi()*(2000-time())/1000)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{11.548739357257748, 6.132140673514712, 3.217113080357038, 1.6144880404748523, 0.6704839982471175, 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("asinh(sinh)", func(t *testing.T) { t.Parallel() q := `asinh(sinh((2000-time())/1000))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 0.8000000000000002, 0.6, 0.4000000000000001, 0.2, 0}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("atan2()", func(t *testing.T) { t.Parallel() q := `time() atan2 time()/10` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.07853981633974483, 0.07853981633974483, 0.07853981633974483, 0.07853981633974483, 0.07853981633974483, 0.07853981633974483}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("atan()", func(t *testing.T) { t.Parallel() q := `atan((2000-time())/1000)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.7853981633974483, 0.6747409422235526, 0.5404195002705842, 0.3805063771123649, 0.19739555984988078, 0}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("atanh(tanh)", func(t *testing.T) { t.Parallel() q := `atanh(tanh((2000-time())/1000))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 0.8000000000000002, 0.6, 0.4000000000000001, 0.2, 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("acosh(cosh)", func(t *testing.T) { t.Parallel() q := `acosh(cosh((2000-time())/1000))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 0.8000000000000002, 0.5999999999999999, 0.40000000000000036, 0.20000000000000023, 0}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("rad(deg)", func(t *testing.T) { t.Parallel() q := `rad(deg(time()/500))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2, 2.3999999999999995, 2.8, 3.2, 3.6, 4}, 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()*(-4)^0.5", func(t *testing.T) { t.Parallel() q := `time()*(-4)^0.5` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run("time()*-4^0.5", func(t *testing.T) { t.Parallel() q := `time()*-4^0.5` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{-2000, -2400, -2800, -3200, -3600, -4000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run("default_for_nan_series", func(t *testing.T) { t.Parallel() q := `label_set(0, "foo", "bar")/0 default 7` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{7, 7, 7, 7, 7, 7}, Timestamps: timestampsExpected, } r.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} resultExpected := []netstorage.Result{r} 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_map(match)`, func(t *testing.T) { t.Parallel() q := `sort(label_map(( label_set(time(), "label", "v1"), label_set(time()+100, "label", "v2"), label_set(time()+200, "label", "v3"), label_set(time()+300, "x", "y"), label_set(time()+400, "label", "v4"), ), "label", "v1", "foo", "v2", "bar", "", "qwe", "v4", ""))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("label"), Value: []byte("foo"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1100, 1300, 1500, 1700, 1900, 2100}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("label"), Value: []byte("bar"), }} r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1200, 1400, 1600, 1800, 2000, 2200}, Timestamps: timestampsExpected, } r3.MetricName.Tags = []storage.Tag{{ Key: []byte("label"), Value: []byte("v3"), }} r4 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1300, 1500, 1700, 1900, 2100, 2300}, Timestamps: timestampsExpected, } r4.MetricName.Tags = []storage.Tag{ { Key: []byte("label"), Value: []byte("qwe"), }, { Key: []byte("x"), Value: []byte("y"), }, } r5 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1400, 1600, 1800, 2000, 2200, 2400}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r1, r2, r3, r4, r5} f(q, resultExpected) }) t.Run(`label_uppercase`, func(t *testing.T) { t.Parallel() q := `label_uppercase( label_set(time(), "foo", "bAr", "XXx", "yyy", "zzz", "abc"), "foo", "XXx", "aaa" )` 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("YYY"), }, { Key: []byte("foo"), Value: []byte("BAR"), }, { Key: []byte("zzz"), Value: []byte("abc"), }, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`label_lowercase`, func(t *testing.T) { t.Parallel() q := `label_lowercase( label_set(time(), "foo", "bAr", "XXx", "yyy", "zzz", "aBc"), "foo", "XXx", "aaa" )` 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("yyy"), }, { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("zzz"), Value: []byte("aBc"), }, } 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, } r.MetricName.Tags = []storage.Tag{ { Key: []byte("tagname"), Value: []byte("foobar"), }, } 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, } r.MetricName.Tags = []storage.Tag{ { Key: []byte("tagname"), Value: []byte("foobar"), }, } 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(`drop_common_labels(single_series)`, func(t *testing.T) { t.Parallel() q := `drop_common_labels(label_set(time(), "foo", "bar", "__name__", "xxx", "q", "we"))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`drop_common_labels(multi_series)`, func(t *testing.T) { t.Parallel() q := `sort_desc(drop_common_labels(( label_set(time(), "foo", "bar", "__name__", "xxx", "q", "we"), label_set(time()/10, "foo", "bar", "__name__", "yyy"), )))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("xxx") r1.MetricName.Tags = []storage.Tag{{ Key: []byte("q"), Value: []byte("we"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{100, 120, 140, 160, 180, 200}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("yyy") resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`drop_common_labels(multi_args)`, func(t *testing.T) { t.Parallel() q := `sort(drop_common_labels( label_set(time(), "foo", "bar", "__name__", "xxx", "q", "we"), label_set(time()/10, "foo", "bar", "__name__", "xxx"), ))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{100, 120, 140, 160, 180, 200}, Timestamps: timestampsExpected, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("q"), Value: []byte("we"), }} resultExpected := []netstorage.Result{r1, r2} 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() > 1500, "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{nan, nan, nan, 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(nonexisting_src)`, func(t *testing.T) { t.Parallel() q := `label_replace(time(), "__name__", "x${1}y", "foo", ".+")` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`label_replace(mismatch)`, func(t *testing.T) { t.Parallel() q := `label_replace(label_set(time(), "foo", "foobar"), "__name__", "x${1}y", "foo", "bar(.+)")` 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("foobar"), }} 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(`label_match()`, func(t *testing.T) { t.Parallel() q := ` label_match(( alias(time(), "foo"), alias(2*time(), "bar"), ), "__name__", "f.+")` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("foo") resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`label_mismatch()`, func(t *testing.T) { t.Parallel() q := ` label_mismatch(( alias(time(), "foo"), alias(2*time(), "bar"), ), "__name__", "f.+")` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2000, 2400, 2800, 3200, 3600, 4000}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("bar") resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`label_graphite_group()`, func(t *testing.T) { t.Parallel() q := `sort(label_graphite_group(( alias(1, "foo.bar.baz"), alias(2, "abc"), label_set(alias(3, "a.xx.zz.asd"), "qwe", "rty"), ), 1, 3))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("bar.") r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2, 2, 2, 2, 2, 2}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte(".") r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{3, 3, 3, 3, 3, 3}, Timestamps: timestampsExpected, } r3.MetricName.MetricGroup = []byte("xx.asd") r3.MetricName.Tags = []storage.Tag{{ Key: []byte("qwe"), Value: []byte("rty"), }} resultExpected := []netstorage.Result{r1, r2, r3} f(q, resultExpected) }) t.Run(`limit_offset`, func(t *testing.T) { t.Parallel() q := `limit_offset(1, 1, sort_by_label(( label_set(time()*1, "foo", "y"), label_set(time()*2, "foo", "a"), label_set(time()*3, "foo", "x"), ), "foo"))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{3000, 3600, 4200, 4800, 5400, 6000}, Timestamps: timestampsExpected, } r.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("x"), }} resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`limit_offset NaN`, func(t *testing.T) { t.Parallel() // q returns 3 time series, where foo=3 contains only NaN values // limit_offset suppose to apply offset for non-NaN series only q := `limit_offset(1, 1, sort_by_label_desc(( label_set(time()*1, "foo", "1"), label_set(time()*2, "foo", "2"), label_set(time()*3, "foo", "3"), ) < 3000, "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("1"), }} resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`sum(label_graphite_group)`, func(t *testing.T) { t.Parallel() q := `sort(sum by (__name__) ( label_graphite_group(( alias(1, "foo.bar.baz"), alias(2, "x.y.z"), alias(3, "qe.bar.qqq"), ), 1) ))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2, 2, 2, 2, 2, 2}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("y") r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{4, 4, 4, 4, 4, 4}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("bar") resultExpected := []netstorage.Result{r1, r2} 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(`sgn(time()-1400)`, func(t *testing.T) { t.Parallel() q := `sgn(time()-1400)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{-1, -1, 0, 1, 1, 1}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} 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(`sort_by_label()`, func(t *testing.T) { t.Parallel() q := `sort_by_label(( alias(1, "foo"), alias(2, "bar"), ), "__name__")` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2, 2, 2, 2, 2, 2}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("bar") r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("foo") resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`sort_by_label_desc()`, func(t *testing.T) { t.Parallel() q := `sort_by_label_desc(( alias(1, "foo"), alias(2, "bar"), ), "__name__")` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("foo") r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2, 2, 2, 2, 2, 2}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("bar") resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`sort_by_label(multiple_labels)`, func(t *testing.T) { t.Parallel() q := `sort_by_label(( label_set(1, "x", "b", "y", "aa"), label_set(2, "x", "a", "y", "aa"), ), "y", "x")` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2, 2, 2, 2, 2, 2}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{ { Key: []byte("x"), Value: []byte("a"), }, { Key: []byte("y"), Value: []byte("aa"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{ { Key: []byte("x"), Value: []byte("b"), }, { Key: []byte("y"), Value: []byte("aa"), }, } resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`scalar < time()`, func(t *testing.T) { t.Parallel() q := `123 < 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() > scalar`, func(t *testing.T) { t.Parallel() q := `time() > 1234` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`time() >bool scalar`, func(t *testing.T) { t.Parallel() q := `time() >bool 1234` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0, 0, 1, 1, 1, 1}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`nan >bool scalar1`, func(t *testing.T) { t.Parallel() q := `(time() > 1234) >bool 1450` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, 0, 1, 1, 1}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`nan!=bool scalar`, func(t *testing.T) { t.Parallel() q := `(time() > 1234) !=bool 1400` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, 0, 1, 1, 1}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`scalar!=bool nan`, func(t *testing.T) { t.Parallel() q := `1400 !=bool (time() > 1234)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, 0, 1, 1, 1}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`scalar > time()`, func(t *testing.T) { t.Parallel() q := `123 > time()` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`time() < scalar`, func(t *testing.T) { t.Parallel() q := `time() < 123` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`scalar1 < time() < scalar2`, func(t *testing.T) { t.Parallel() q := `1300 < time() < 1700` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, 1400, 1600, nan, nan}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} 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(`compare_to_nan_right`, func(t *testing.T) { t.Parallel() q := `1 != 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(`compare_to_nan_left`, func(t *testing.T) { t.Parallel() q := `nan != 1` 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() and time() > 1300`, func(t *testing.T) { t.Parallel() q := `time() and time() > 1300` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, 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(`time() unless time() > 1500`, func(t *testing.T) { t.Parallel() q := `time() unless time() > 1500` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, nan, nan, nan}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`scalar or scalar`, func(t *testing.T) { t.Parallel() q := `time() > 1400 or 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(`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(`scalar default scalar_from_vector`, func(t *testing.T) { t.Parallel() q := `time() > 1400 default scalar(label_set(123, "foo", "bar"))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{123, 123, 123, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`scalar default vector1`, func(t *testing.T) { t.Parallel() q := `time() > 1400 default label_set(123, "foo", "bar")` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`scalar default vector2`, func(t *testing.T) { t.Parallel() q := `time() > 1400 default ( label_set(123, "foo", "bar"), label_set(456, "__name__", "xxx"), )` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{456, 456, 456, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`scalar default NaN`, func(t *testing.T) { t.Parallel() q := `time() > 1400 default (time() < -100)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 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(label_set(2, "a", "2") * ignoring(foo,a) group_right(a) (label_set(time(), "foo", "bar", "a", "1"), 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("a"), Value: []byte("2"), }, { 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("a"), Value: []byte("2"), }, { 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"), label_set(10, "t2", "v3", "xxx", "yy")) + on (foo, t2) group_left (t1, noxxx) (label_set(100, "t1", "v1"), 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("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-inf-le)`, func(t *testing.T) { t.Parallel() q := `histogram_quantile(0.6, label_set(100, "le", "+Inf"))` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`histogram_quantile(zero-value-inf-le)`, func(t *testing.T) { t.Parallel() q := `histogram_quantile(0.6, ( label_set(100, "le", "+Inf"), label_set(0, "le", "42"), ))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{42, 42, 42, 42, 42, 42}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} 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(`stdvar_over_time()`, func(t *testing.T) { t.Parallel() q := `round(stdvar_over_time(rand(0)[200s:5s]), 0.001)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.082, 0.088, 0.092, 0.075, 0.101, 0.08}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`histogram_stdvar()`, func(t *testing.T) { t.Parallel() q := `round(histogram_stdvar(histogram_over_time(rand(0)[200s:5s])), 0.001)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.079, 0.089, 0.089, 0.071, 0.1, 0.082}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`stddev_over_time()`, func(t *testing.T) { t.Parallel() q := `round(stddev_over_time(rand(0)[200s:5s]), 0.001)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.286, 0.297, 0.303, 0.274, 0.318, 0.283}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`histogram_stddev()`, func(t *testing.T) { t.Parallel() q := `round(histogram_stddev(histogram_over_time(rand(0)[200s:5s])), 0.001)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.281, 0.299, 0.298, 0.267, 0.316, 0.286}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`avg_over_time()`, func(t *testing.T) { t.Parallel() q := `round(avg_over_time(rand(0)[200s:5s]), 0.001)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.521, 0.518, 0.509, 0.544, 0.511, 0.504}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`histogram_avg()`, func(t *testing.T) { t.Parallel() q := `round(histogram_avg(histogram_over_time(rand(0)[200s:5s])), 0.001)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.519, 0.521, 0.503, 0.543, 0.511, 0.506}, 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(duplicate-le)`, func(t *testing.T) { // See https://github.com/VictoriaMetrics/VictoriaMetrics/pull/3225 t.Parallel() q := `round(sort(histogram_quantile(0.6, label_set(90, "foo", "bar", "le", "5") or label_set(100, "foo", "bar", "le", "5.0") or label_set(200, "foo", "bar", "le", "6.0") or label_set(300, "foo", "bar", "le", "+Inf") )), 0.1)` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{4.7, 4.7, 4.7, 4.7, 4.7, 4.7}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} resultExpected := []netstorage.Result{r1} 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 := `round(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") ),0.01)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{18.57, 18.57, 18.57, 18.57, 18.57, 18.57}, 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_quantiles()`, func(t *testing.T) { t.Parallel() q := `sort_by_label(histogram_quantiles("phi", 0.2, 0.3, label_set(0, "foo", "bar", "le", "10") or label_set(100, "foo", "bar", "le", "30") or label_set(300, "foo", "bar", "le", "+Inf") ), "phi")` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{22, 22, 22, 22, 22, 22}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("phi"), Value: []byte("0.2"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{28, 28, 28, 28, 28, 28}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("phi"), Value: []byte("0.3"), }, } resultExpected := []netstorage.Result{r1, r2} 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(`buckets_limit(zero)`, func(t *testing.T) { t.Parallel() q := `buckets_limit(0, ( alias(label_set(100, "le", "inf", "x", "y"), "metric"), alias(label_set(50, "le", "120", "x", "y"), "metric"), ))` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`buckets_limit(unused)`, func(t *testing.T) { t.Parallel() q := `sort(buckets_limit(5, ( alias(label_set(100, "le", "inf", "x", "y"), "metric"), alias(label_set(50, "le", "120", "x", "y"), "metric"), )))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{50, 50, 50, 50, 50, 50}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("metric") r1.MetricName.Tags = []storage.Tag{ { Key: []byte("le"), Value: []byte("120"), }, { Key: []byte("x"), Value: []byte("y"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{100, 100, 100, 100, 100, 100}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("metric") r2.MetricName.Tags = []storage.Tag{ { Key: []byte("le"), Value: []byte("inf"), }, { Key: []byte("x"), Value: []byte("y"), }, } resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`buckets_limit(used)`, func(t *testing.T) { t.Parallel() q := `sort(buckets_limit(2, ( alias(label_set(100, "le", "inf", "x", "y"), "metric"), alias(label_set(98, "le", "300", "x", "y"), "metric"), alias(label_set(52, "le", "200", "x", "y"), "metric"), alias(label_set(50, "le", "120", "x", "y"), "metric"), alias(label_set(20, "le", "70", "x", "y"), "metric"), alias(label_set(10, "le", "30", "x", "y"), "metric"), alias(label_set(9, "le", "10", "x", "y"), "metric"), )))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{9, 9, 9, 9, 9, 9}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("metric") r1.MetricName.Tags = []storage.Tag{ { Key: []byte("le"), Value: []byte("10"), }, { Key: []byte("x"), Value: []byte("y"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{98, 98, 98, 98, 98, 98}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("metric") r2.MetricName.Tags = []storage.Tag{ { Key: []byte("le"), Value: []byte("300"), }, { Key: []byte("x"), Value: []byte("y"), }, } r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{100, 100, 100, 100, 100, 100}, Timestamps: timestampsExpected, } r3.MetricName.MetricGroup = []byte("metric") r3.MetricName.Tags = []storage.Tag{ { Key: []byte("le"), Value: []byte("inf"), }, { Key: []byte("x"), Value: []byte("y"), }, } resultExpected := []netstorage.Result{r1, r2, r3} 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(zero-vmrange-value)`, func(t *testing.T) { t.Parallel() q := `sort(prometheus_buckets(label_set(0, "vmrange", "0...0")))` 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("+Inf"), }, } resultsExpected := []netstorage.Result{r1} f(q, resultsExpected) }) 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(`prometheus_buckets(overlapped ranges)`, 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()/20, "foo", "bar", "vmrange", "0.2...0.25"), "xxx"), alias(label_set(time()/20, "foo", "bar", "vmrange", "0...0.26"), "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{190, 210, 230, 250, 270, 290}, Timestamps: timestampsExpected, } r3.MetricName.MetricGroup = []byte("xxx") r3.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("le"), Value: []byte("0.25"), }, } r4 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{240, 270, 300, 330, 360, 390}, Timestamps: timestampsExpected, } r4.MetricName.MetricGroup = []byte("xxx") r4.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("le"), Value: []byte("0.26"), }, } r5 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{250, 282, 314, 346, 378, 410}, Timestamps: timestampsExpected, } r5.MetricName.MetricGroup = []byte("xxx") r5.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("le"), Value: []byte("40"), }, } r6 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{350, 402, 454, 506, 558, 610}, Timestamps: timestampsExpected, } r6.MetricName.MetricGroup = []byte("xxx") r6.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("le"), Value: []byte("Inf"), }, } resultExpected := []netstorage.Result{r1, r2, r3, r4, r5, r6} f(q, resultExpected) }) t.Run(`prometheus_buckets(overlapped ranges at the end)`, 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()/20, "foo", "bar", "vmrange", "0.2...0.25"), "xxx"), alias(label_set(time()/20, "foo", "bar", "vmrange", "0...0.25"), "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{190, 210, 230, 250, 270, 290}, Timestamps: timestampsExpected, } r3.MetricName.MetricGroup = []byte("xxx") r3.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("le"), Value: []byte("0.25"), }, } r4 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{200, 222, 244, 266, 288, 310}, Timestamps: timestampsExpected, } r4.MetricName.MetricGroup = []byte("xxx") r4.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("le"), Value: []byte("40"), }, } r5 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{300, 342, 384, 426, 468, 510}, Timestamps: timestampsExpected, } r5.MetricName.MetricGroup = []byte("xxx") r5.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("le"), Value: []byte("Inf"), }, } resultExpected := []netstorage.Result{r1, r2, r3, r4, r5} 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(multi-args)`, func(t *testing.T) { t.Parallel() q := `sum(1, 2, 3)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{6, 6, 6, 6, 6, 6}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`sum(union-args)`, func(t *testing.T) { t.Parallel() q := `sum((1, 2, 3))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, 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(`mode()`, func(t *testing.T) { t.Parallel() q := `mode(( alias(3, "m1"), alias(2, "m2"), alias(3, "m3"), alias(4, "m4"), alias(3, "m5"), alias(2, "m6"), ))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{3, 3, 3, 3, 3, 3}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`zscore()`, func(t *testing.T) { t.Parallel() q := `sort_by_label(round(zscore(( label_set(time()/100+10, "k", "v1"), label_set(time()/200+5, "k", "v2"), label_set(time()/110-10, "k", "v3"), label_set(time()/90-5, "k", "v4"), )), 0.001), "k")` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1.482, 1.511, 1.535, 1.552, 1.564, 1.57}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("k"), Value: []byte("v1"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.159, 0.058, -0.042, -0.141, -0.237, -0.329}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("k"), Value: []byte("v2"), }} r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{-1.285, -1.275, -1.261, -1.242, -1.219, -1.193}, Timestamps: timestampsExpected, } r3.MetricName.Tags = []storage.Tag{{ Key: []byte("k"), Value: []byte("v3"), }} r4 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{-0.356, -0.294, -0.232, -0.17, -0.108, -0.048}, Timestamps: timestampsExpected, } r4.MetricName.Tags = []storage.Tag{{ Key: []byte("k"), Value: []byte("v4"), }} 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(`histogram(scalar)`, func(t *testing.T) { t.Parallel() q := `sort(histogram(123)+( label_set(0, "le", "1.000e+02"), label_set(0, "le", "1.136e+02"), label_set(0, "le", "1.292e+02"), 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("1.136e+02"), }, } 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("1.292e+02"), }, } 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", "8.799e-01"), label_set(0, "le", "1.000e+00"), label_set(0, "le", "1.292e+00"), 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("8.799e-01"), }, } 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("1.000e+00"), }, } 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("1.292e+00"), }, } 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{7.8, 9.9, 11.9, 13.9, 15.9, 17.9}, 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{200, 308, 440, 596, 776, 980}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`range_over_time(time)`, func(t *testing.T) { t.Parallel() q := `range_over_time(alias(time()/100, "foobar")[3i])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{4, 4, 4, 4, 4, 4}, 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-tag) limit 1`, func(t *testing.T) { t.Parallel() q := `sum(label_set(10, "foo", "bar") or label_set(time()/100, "baz", "sss")) by (foo) limit 1` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, 10, 10, 10}, Timestamps: timestampsExpected, } r.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} resultExpected := []netstorage.Result{r} 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(`quantile_over_time`, func(t *testing.T) { t.Parallel() q := `quantile_over_time(0.9, label_set(round(rand(0), 0.01), "__name__", "foo", "xx", "yy")[200s:5s])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.893, 0.892, 0.9510000000000001, 0.8730000000000001, 0.9250000000000002, 0.891}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("foo") r.MetricName.Tags = []storage.Tag{ { Key: []byte("xx"), Value: []byte("yy"), }, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`quantiles_over_time(single_sample)`, func(t *testing.T) { t.Parallel() q := `sort_by_label( quantiles_over_time("phi", 0.5, 0.9, time()[100s:100s] ), "phi", )` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{ { Key: []byte("phi"), Value: []byte("0.5"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{ { Key: []byte("phi"), Value: []byte("0.9"), }, } resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`quantiles_over_time(multiple_samples)`, func(t *testing.T) { t.Parallel() q := `sort_by_label( quantiles_over_time("phi", 0.5, 0.9, label_set(round(rand(0), 0.01), "__name__", "foo", "xx", "yy")[200s:5s] ), "phi", )` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.46499999999999997, 0.57, 0.485, 0.54, 0.555, 0.515}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("foo") r1.MetricName.Tags = []storage.Tag{ { Key: []byte("phi"), Value: []byte("0.5"), }, { Key: []byte("xx"), Value: []byte("yy"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.893, 0.892, 0.9510000000000001, 0.8730000000000001, 0.9250000000000002, 0.891}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("foo") r2.MetricName.Tags = []storage.Tag{ { Key: []byte("phi"), Value: []byte("0.9"), }, { Key: []byte("xx"), Value: []byte("yy"), }, } resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`histogram_over_time`, func(t *testing.T) { t.Parallel() q := `sort_by_label(histogram_over_time(alias(label_set(rand(0)*1.3+1.1, "foo", "bar"), "xxx")[200s:5s]), "vmrange")` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 2, 2, 2, nan, 1}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("vmrange"), Value: []byte("1.000e+00...1.136e+00"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{3, 3, 4, 2, 8, 3}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("vmrange"), Value: []byte("1.136e+00...1.292e+00"), }, } r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{7, 7, 5, 3, 3, 9}, Timestamps: timestampsExpected, } r3.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("vmrange"), Value: []byte("1.292e+00...1.468e+00"), }, } r4 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{7, 4, 6, 5, 6, 4}, Timestamps: timestampsExpected, } r4.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("vmrange"), Value: []byte("1.468e+00...1.668e+00"), }, } r5 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{6, 6, 9, 13, 7, 7}, Timestamps: timestampsExpected, } r5.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("vmrange"), Value: []byte("1.668e+00...1.896e+00"), }, } r6 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{5, 9, 4, 6, 7, 9}, Timestamps: timestampsExpected, } r6.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("vmrange"), Value: []byte("1.896e+00...2.154e+00"), }, } r7 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{11, 9, 10, 9, 9, 7}, Timestamps: timestampsExpected, } r7.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("vmrange"), Value: []byte("2.154e+00...2.448e+00"), }, } resultExpected := []netstorage.Result{r1, r2, r3, r4, r5, r6, r7} f(q, resultExpected) }) t.Run(`sum(histogram_over_time) by (vmrange)`, func(t *testing.T) { t.Parallel() q := `sort_by_label( buckets_limit( 3, sum(histogram_over_time(alias(label_set(rand(0)*1.3+1.1, "foo", "bar"), "xxx")[200s:5s])) by (vmrange) ), "le" )` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{40, 40, 40, 40, 40, 40}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{ { Key: []byte("le"), Value: []byte("+Inf"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0, 0, 0, 0, 0, 0}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{ { Key: []byte("le"), Value: []byte("1.000e+00"), }, } r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{40, 40, 40, 40, 40, 40}, Timestamps: timestampsExpected, } r3.MetricName.Tags = []storage.Tag{ { Key: []byte("le"), Value: []byte("2.448e+00"), }, } 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(`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{6, 6, 9, 13, 7, 7}, Timestamps: timestampsExpected, } r.MetricName.Tags = []storage.Tag{ { Key: []byte("foo"), Value: []byte("bar"), }, { Key: []byte("vmrange"), Value: []byte("1.668e+00...1.896e+00"), }, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`duration_over_time`, func(t *testing.T) { t.Parallel() q := `duration_over_time((time()<1200)[600s:10s], 20s)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{590, 580, 380, 180, nan, nan}, Timestamps: timestampsExpected, } 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(`count_gt_over_time`, func(t *testing.T) { t.Parallel() q := `count_gt_over_time(rand(0)[200s:10s], 0.7)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{7, 6, 10, 6, 6, 5}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`count_le_over_time`, func(t *testing.T) { t.Parallel() q := `count_le_over_time(rand(0)[200s:10s], 0.7)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{13, 14, 10, 14, 14, 15}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`count_eq_over_time`, func(t *testing.T) { t.Parallel() q := `count_eq_over_time(round(5*rand(0))[200s:10s], 1)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2, 4, 5, 2, 6, 6}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`count_ne_over_time`, func(t *testing.T) { t.Parallel() q := `count_ne_over_time(round(5*rand(0))[200s:10s], 1)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{18, 16, 15, 18, 14, 14}, 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, "xbaz", "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(`any()`, func(t *testing.T) { t.Parallel() q := `any(label_set(10, "__name__", "x", "foo", "bar") or label_set(time()/150, "__name__", "y", "baz", "sss"))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, 10, 10, 10}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("x") r.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`any(empty-series)`, func(t *testing.T) { t.Parallel() q := `any(label_set(time()<0, "foo", "bar"))` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`group() by (test)`, func(t *testing.T) { t.Parallel() q := `group(( label_set(5, "__name__", "data", "test", "three samples", "point", "a"), label_set(6, "__name__", "data", "test", "three samples", "point", "b"), label_set(7, "__name__", "data", "test", "three samples", "point", "c"), )) by (test)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = nil r.MetricName.Tags = []storage.Tag{{ Key: []byte("test"), Value: []byte("three samples"), }} resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`group() without (point)`, func(t *testing.T) { t.Parallel() q := `group(( label_set(5, "__name__", "data", "test", "three samples", "point", "a"), label_set(6, "__name__", "data", "test", "three samples", "point", "b"), label_set(7, "__name__", "data", "test", "three samples", "point", "c"), )) without (point)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = nil r.MetricName.Tags = []storage.Tag{{ Key: []byte("test"), Value: []byte("three samples"), }} resultExpected := []netstorage.Result{r} 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 := `topk(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"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, nan, nan, nan}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} 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, 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(`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{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_max(1)`, func(t *testing.T) { t.Parallel() q := `topk_max(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, 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, remaining_sum)`, func(t *testing.T) { t.Parallel() q := `sort_desc(topk_max(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"), "remaining_sum=foo"))` 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"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, 10, 10, 10}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{ { Key: []byte("remaining_sum"), Value: []byte("foo"), }, } resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`topk_max(2, remaining_sum)`, func(t *testing.T) { t.Parallel() q := `sort_desc(topk_max(2, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"), "remaining_sum"))` 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"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, 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(`topk_max(3, remaining_sum)`, func(t *testing.T) { t.Parallel() q := `sort_desc(topk_max(3, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"), "remaining_sum"))` 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"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, 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(`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, 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(`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{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(`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{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_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{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_last(1)`, func(t *testing.T) { t.Parallel() q := `sort(topk_last(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, 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()/15, "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(`bottomk_last(1)`, func(t *testing.T) { t.Parallel() q := `sort(bottomk_last(1, label_set(10, "foo", "bar") or label_set(time()/15, "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(`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 := `bottomk(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 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, nan, nan, nan}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("baz"), Value: []byte("sss"), }} 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(`keep_next_value()`, func(t *testing.T) { t.Parallel() q := `keep_next_value(label_set(time() < 1300 default time() > 1700, "__name__", "foobar", "x", "y"))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1800, 1800, 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(`interpolate()`, func(t *testing.T) { t.Parallel() q := `interpolate(label_set(time() < 1300 default time() > 1700, "__name__", "foobar", "x", "y"))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 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(`interpolate(tail)`, func(t *testing.T) { t.Parallel() q := `interpolate(time() < 1300)` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1200, 1200, 1200, 1200}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r1} f(q, resultExpected) }) t.Run(`interpolate(head)`, func(t *testing.T) { t.Parallel() q := `interpolate(time() > 1500)` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1600, 1600, 1600, 1600, 1800, 2000}, Timestamps: timestampsExpected, } 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(`vector2 if vector1`, func(t *testing.T) { t.Parallel() q := `( label_set(time()/10, "x", "y"), label_set(time(), "foo", "bar", "__name__", "x"), ) if ( label_set(time()>1400, "foo", "bar"), )` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("x") r.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`vector2 if vector2`, func(t *testing.T) { t.Parallel() q := `sort(( label_set(time()/10, "x", "y"), label_set(time(), "foo", "bar", "__name__", "x"), ) if ( label_set(time()>1400, "foo", "bar"), label_set(time()<1400, "x", "y"), ))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{100, 120, nan, nan, nan, nan}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("x"), Value: []byte("y"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("x") r2.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`scalar if vector1`, func(t *testing.T) { t.Parallel() q := `time() if ( label_set(123, "foo", "bar"), )` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`scalar if vector2`, func(t *testing.T) { t.Parallel() q := `time() if ( label_set(123, "foo", "bar"), alias(time() > 1400, "xxx"), )` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{nan, nan, nan, 1600, 1800, 2000}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} 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(`ifnot`, func(t *testing.T) { t.Parallel() q := `time() ifnot time() > 1400` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, nan, nan, nan}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`ifnot-no-matching-timeseries`, func(t *testing.T) { t.Parallel() q := `label_set(time(), "foo", "bar") ifnot label_set(time() > 1400, "x", "y")` 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(`quantile(-2)`, func(t *testing.T) { t.Parallel() q := `quantile(-2, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))` inf := math.Inf(-1) r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{inf, inf, inf, inf, inf, inf}, 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{7.333333333333334, 8.4, 9.466666666666669, 10.133333333333333, 10.4, 10.666666666666668}, 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{8.333333333333334, 9, 9.666666666666668, 10.333333333333332, 11, 11.666666666666668}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`quantiles("phi", 0.2, 0.5)`, func(t *testing.T) { t.Parallel() q := `sort(quantiles("phi", 0.2, 0.5, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss")))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{7.333333333333334, 8.4, 9.466666666666669, 10.133333333333333, 10.4, 10.666666666666668}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("phi"), Value: []byte("0.2"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{8.333333333333334, 9, 9.666666666666668, 10.333333333333332, 11, 11.666666666666668}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("phi"), Value: []byte("0.5"), }} resultExpected := []netstorage.Result{r1, r2} 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{8.333333333333334, 9, 9.666666666666668, 10.333333333333332, 11, 11.666666666666668}, 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"))` inf := math.Inf(+1) r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{inf, inf, inf, inf, inf, inf}, 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"))` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`mad()`, func(t *testing.T) { t.Parallel() q := `mad( alias(time(), "metric1"), alias(time()*1.5, "metric2"), label_set(time()*0.9, "baz", "sss"), )` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{100, 120, 140, 160, 180, 200}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`outliers_mad(1)`, func(t *testing.T) { t.Parallel() q := `outliers_mad(1, ( alias(time(), "metric1"), alias(time()*1.5, "metric2"), label_set(time()*0.9, "baz", "sss"), ))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1500, 1800, 2100, 2400, 2700, 3000}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("metric2") resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`outliers_mad(5)`, func(t *testing.T) { t.Parallel() q := `outliers_mad(5, ( alias(time(), "metric1"), alias(time()*1.5, "metric2"), label_set(time()*0.9, "baz", "sss"), ))` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`outliersk(0)`, func(t *testing.T) { t.Parallel() q := `outliersk(0, ( label_set(1300, "foo", "bar"), label_set(time(), "baz", "sss"), ))` resultExpected := []netstorage.Result{} f(q, resultExpected) }) t.Run(`outliersk(1)`, func(t *testing.T) { t.Parallel() q := `outliersk(1, ( label_set(2000, "foo", "bar"), label_set(time(), "baz", "sss"), ))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r.MetricName.Tags = []storage.Tag{{ Key: []byte("baz"), Value: []byte("sss"), }} resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`outliersk(3)`, func(t *testing.T) { t.Parallel() q := `sort_desc(outliersk(3, ( label_set(1300, "foo", "bar"), label_set(time(), "baz", "sss"), )))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("baz"), Value: []byte("sss"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1300, 1300, 1300, 1300, 1300, 1300}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("foo"), Value: []byte("bar"), }} resultExpected := []netstorage.Result{r1, r2} 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, // time() results in [1000 1200 1400 1600 1800 2000] Values: []float64{1500, 1500, 1500, 1500, 1500, 1500}, 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, // time() results in [1000 1200 1400 1600 1800 2000] Values: []float64{1500, 1500, 1500, 1500, 1500, 1500}, 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 1.5i, 2000)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{70, 60, 50, 40, 30, 20}, 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(`mode_over_time()`, func(t *testing.T) { t.Parallel() q := `mode_over_time(round(time()/500)[100s:1s])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{2, 2, 3, 3, 4, 4}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`rate_over_sum()`, func(t *testing.T) { t.Parallel() q := `rate_over_sum(round(time()/500)[100s:5s])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.4, 0.4, 0.6, 0.6, 0.71, 0.8}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`zscore_over_time(rand)`, func(t *testing.T) { t.Parallel() q := `round(zscore_over_time(rand(0)[100s:10s]), 0.01)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{-1.17, -0.08, 0.98, 0.67, 1.61, 1.55}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`zscore_over_time(const)`, func(t *testing.T) { t.Parallel() q := `zscore_over_time(1[100s:10s])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0, 0, 0, 0, 0, 0}, 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()/1e3)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{160, 200, 240, 280, 320, 360}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`rate(time())`, func(t *testing.T) { t.Parallel() q := `rate(label_set(alias(time(), "foo"), "x", "y"))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r.MetricName.Tags = []storage.Tag{ { Key: []byte("x"), Value: []byte("y"), }, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`rate(time()) keep_metric_names`, func(t *testing.T) { t.Parallel() q := `rate(label_set(alias(time(), "foo"), "x", "y")) keep_metric_names` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("foo") r.MetricName.Tags = []storage.Tag{ { Key: []byte("x"), Value: []byte("y"), }, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`sum(rate(time()) keep_metric_names) by (__name__)`, func(t *testing.T) { t.Parallel() q := `sum(rate(label_set(alias(time(), "foo"), "x", "y")) keep_metric_names) by (__name__)` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("foo") 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{0, 0, 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{0, 0, 3.5, 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{0, 0, 0, 3.5, 5.5, 3.5}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`increase_pure(time())`, func(t *testing.T) { t.Parallel() q := `increase_pure(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(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{1000, 800, 600, 400, 200, 0}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`increase_prometheus(time())`, func(t *testing.T) { t.Parallel() q := `increase_prometheus(time())` f(q, nil) }) t.Run(`increase_prometheus(time()[201s])`, func(t *testing.T) { t.Parallel() q := `increase_prometheus(time()[201s])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{200, 200, 200, 200, 200, 200}, 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(`remove_resets(sum)`, func(t *testing.T) { t.Parallel() q := `remove_resets(sum( alias(time(), "full"), alias(time()/5 < 300, "partial"), ))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1200, 1440, 1680, 1680, 1880, 2080}, 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(N)`, func(t *testing.T) { t.Parallel() q := `deriv(1000)` 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(`delta_prometheus(time())`, func(t *testing.T) { t.Parallel() q := `delta_prometheus(time())` f(q, nil) }) t.Run(`delta_prometheus(time()[201s])`, func(t *testing.T) { t.Parallel() q := `delta_prometheus(time()[201s])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{200, 200, 200, 200, 200, 200}, 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(`hoeffding_bound_lower()`, func(t *testing.T) { t.Parallel() q := `hoeffding_bound_lower(0.9, rand(0)[:10s])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.2516770508510652, 0.2830570387745462, 0.27716232108436645, 0.3679356319931767, 0.3168460474120903, 0.23156726248243734}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`hoeffding_bound_upper()`, func(t *testing.T) { t.Parallel() q := `hoeffding_bound_upper(0.9, alias(rand(0), "foobar")[:10s])` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.6510581320042821, 0.7261021731890429, 0.7245290097397009, 0.8113950442584258, 0.7736122275568004, 0.6658564048254882}, Timestamps: timestampsExpected, } r.MetricName.MetricGroup = []byte("foobar") resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`aggr_over_time(single-func)`, func(t *testing.T) { t.Parallel() q := `round(aggr_over_time("increase", rand(0)[:10s]),0.01)` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{5.47, 6.64, 6.84, 7.24, 5.17, 6.59}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("increase"), }} resultExpected := []netstorage.Result{r1} f(q, resultExpected) }) t.Run(`aggr_over_time(multi-func)`, func(t *testing.T) { t.Parallel() q := `sort(aggr_over_time(("min_over_time", "count_over_time", "max_over_time"), round(rand(0),0.1)[:10s]))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0, 0, 0, 0, 0, 0}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("min_over_time"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.8, 0.9, 1, 0.9, 1, 0.9}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("max_over_time"), }} r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{20, 20, 20, 20, 20, 20}, Timestamps: timestampsExpected, } r3.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("count_over_time"), }} resultExpected := []netstorage.Result{r1, r2, r3} f(q, resultExpected) }) t.Run(`avg(aggr_over_time(multi-func))`, func(t *testing.T) { t.Parallel() q := `avg(aggr_over_time(("min_over_time", "max_over_time"), time()[:10s]))` r := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{905, 1105, 1305, 1505, 1705, 1905}, Timestamps: timestampsExpected, } resultExpected := []netstorage.Result{r} f(q, resultExpected) }) t.Run(`avg(aggr_over_time(multi-func)) by (rollup)`, func(t *testing.T) { t.Parallel() q := `sort(avg(aggr_over_time(("min_over_time", "max_over_time"), time()[:10s])) by (rollup))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{810, 1010, 1210, 1410, 1610, 1810}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("min_over_time"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1000, 1200, 1400, 1600, 1800, 2000}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("max_over_time"), }} resultExpected := []netstorage.Result{r1, r2} f(q, resultExpected) }) t.Run(`rollup_candlestick()`, func(t *testing.T) { t.Parallel() q := `sort(rollup_candlestick(alias(round(rand(0),0.01),"foobar")[:10s]))` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.02, 0.02, 0.03, 0, 0.03, 0.02}, Timestamps: timestampsExpected, } r1.MetricName.MetricGroup = []byte("foobar") r1.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("low"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.9, 0.32, 0.82, 0.13, 0.28, 0.86}, Timestamps: timestampsExpected, } r2.MetricName.MetricGroup = []byte("foobar") r2.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("open"), }} r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.1, 0.04, 0.49, 0.46, 0.57, 0.92}, Timestamps: timestampsExpected, } r3.MetricName.MetricGroup = []byte("foobar") r3.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("close"), }} r4 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{0.9, 0.94, 0.97, 0.93, 0.98, 0.92}, Timestamps: timestampsExpected, } r4.MetricName.MetricGroup = []byte("foobar") 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_scrape_interval()`, func(t *testing.T) { t.Parallel() q := `sort_by_label(rollup_scrape_interval(1[5m:10s]), "rollup")` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, 10, 10, 10}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("avg"), }} r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, 10, 10, 10}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("max"), }} r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{10, 10, 10, 10, 10, 10}, Timestamps: timestampsExpected, } r3.MetricName.Tags = []storage.Tag{{ Key: []byte("rollup"), Value: []byte("min"), }} 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{850, 1050, 1250, 1450, 1650, 1850}, 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_big_numbers`, func(t *testing.T) { t.Parallel() q := `sort_by_label( count_values("xxx", (alias(772424014, "first"), alias(772424230, "second"))), "xxx" )` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r1.MetricName.Tags = []storage.Tag{ { Key: []byte("xxx"), Value: []byte("772424014"), }, } r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } r2.MetricName.Tags = []storage.Tag{ { Key: []byte("xxx"), Value: []byte("772424230"), }, } resultExpected := []netstorage.Result{r1, r2} 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"), }, } // expected sorted output for strings 1, 10, 2, 3 resultExpected := []netstorage.Result{r1, r4, r2, r3} 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) }) t.Run(`result sorting`, func(t *testing.T) { t.Parallel() q := `label_set(1, "instance", "localhost:1001", "type", "free") or label_set(1, "instance", "localhost:1001", "type", "buffers") or label_set(1, "instance", "localhost:1000", "type", "buffers") or label_set(1, "instance", "localhost:1000", "type", "free") ` r1 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } testAddLabels(t, &r1.MetricName, "instance", "localhost:1000", "type", "buffers") r2 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } testAddLabels(t, &r2.MetricName, "instance", "localhost:1000", "type", "free") r3 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } testAddLabels(t, &r3.MetricName, "instance", "localhost:1001", "type", "buffers") r4 := netstorage.Result{ MetricName: metricNameExpected, Values: []float64{1, 1, 1, 1, 1, 1}, Timestamps: timestampsExpected, } testAddLabels(t, &r4.MetricName, "instance", "localhost:1001", "type", "free") resultExpected := []netstorage.Result{r1, r2, r3, r4} f(q, resultExpected) }) } func TestExecError(t *testing.T) { f := func(q string) { t.Helper() ec := &EvalConfig{ AuthToken: &auth.Token{ AccountID: 123, ProjectID: 567, }, Start: 1000, End: 2000, Step: 100, MaxSeries: 1000, Deadline: searchutils.NewDeadline(time.Now(), time.Minute, ""), RoundDigits: 100, } for i := 0; i < 4; i++ { rv, err := Exec(nil, 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(nil, 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()`) 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_map()`) f(`label_map(1)`) f(`label_del()`) f(`label_keep()`) f(`label_match()`) f(`label_mismatch()`) f(`label_graphite_group()`) f(`round()`) f(`round(1,2,3)`) f(`sgn()`) f(`scalar()`) f(`sort(1,2)`) f(`sort_desc()`) f(`sort_by_label()`) f(`sort_by_label_desc()`) f(`timestamp()`) f(`timestamp_with_name()`) f(`vector()`) f(`histogram_quantile()`) f(`histogram_quantiles()`) f(`sum()`) f(`count_values()`) f(`quantile()`) f(`any()`) f(`group()`) f(`topk()`) f(`topk_min()`) f(`topk_max()`) f(`topk_avg()`) f(`topk_median()`) f(`topk_last()`) f(`limitk()`) f(`bottomk()`) f(`bottomk_min()`) f(`bottomk_max()`) f(`bottomk_avg()`) f(`bottomk_median()`) f(`bottomk_last()`) 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(`sinh()`) f(`cos()`) f(`cosh()`) f(`asin()`) f(`asinh()`) f(`acos()`) f(`acosh()`) f(`rand(123, 456)`) f(`rand_normal(123, 456)`) f(`rand_exponential(122, 456)`) f(`pi(123)`) f(`now(123)`) f(`label_copy()`) f(`label_move()`) f(`median_over_time()`) f(`median()`) f(`keep_last_value()`) f(`keep_next_value()`) f(`interpolate()`) f(`distinct_over_time()`) f(`distinct()`) f(`alias()`) f(`alias(1)`) f(`alias(1, "foo", "bar")`) f(`lifetime()`) f(`lag()`) f(`aggr_over_time()`) f(`aggr_over_time(foo)`) f(`aggr_over_time("foo", bar, 1)`) f(`sum(aggr_over_time())`) f(`sum(aggr_over_time(foo))`) f(`count(aggr_over_time("foo", bar, 1))`) f(`hoeffding_bound_lower()`) f(`hoeffding_bound_lower(1)`) f(`hoeffding_bound_lower(0.99, foo, 1)`) f(`hoeffding_bound_upper()`) f(`hoeffding_bound_upper(1)`) f(`hoeffding_bound_upper(0.99, foo, 1)`) f(`mad()`) f(`outliers_mad()`) f(`outliers_mad(1)`) f(`outliersk()`) f(`outliersk(1)`) f(`mode_over_time()`) f(`rate_over_sum()`) f(`zscore_over_time()`) f(`mode()`) f(`zscore()`) f(`prometheus_buckets()`) f(`buckets_limit()`) f(`buckets_limit(1)`) f(`duration_over_time()`) f(`share_le_over_time()`) f(`share_gt_over_time()`) f(`count_le_over_time()`) f(`count_gt_over_time()`) f(`count_eq_over_time()`) f(`count_ne_over_time()`) f(`timezone_offset()`) f(`bitmap_and()`) f(`bitmap_or()`) f(`bitmap_xor()`) f(`quantiles()`) f(`limit_offset()`) f(`increase()`) f(`increase_prometheus()`) f(`changes()`) f(`changes_prometheus()`) f(`delta()`) f(`delta_prometheus()`) // 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(`limit_offet((alias(1,"foo"),alias(2,"bar")), 2, 10)`) f(`limit_offet(1, (alias(1,"foo"),alias(2,"bar")), 10)`) f(`round(1, 1 or label_set(2, "xx", "foo"))`) f(`histogram_quantile(1 or label_set(2, "xx", "foo"), 1)`) f(`histogram_quantiles("foo", 1 or label_set(2, "xxx", "foo"), 2)`) 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(`label_match(1, 2, 3)`) f(`label_mismatch(1, 2, 3)`) f(`label_uppercase()`) f(`label_lowercase()`) f(`alias(1, 2)`) f(`aggr_over_time(1, 2)`) f(`aggr_over_time(("foo", "bar"), 3)`) f(`outliersk((label_set(1, "foo", "bar"), label_set(2, "x", "y")), 123)`) // 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) 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 mn.AccountID != mnExpected.AccountID { t.Fatalf(`unexpected accountID; got %d; want %d`, mn.AccountID, mnExpected.AccountID) } if mn.ProjectID != mnExpected.ProjectID { t.Fatalf(`unexpected projectID; got %d; want %d`, mn.ProjectID, mnExpected.ProjectID) } if string(mn.MetricGroup) != string(mnExpected.MetricGroup) { t.Fatalf(`unexpected MetricGroup at #%d; got %q; want %q; metricGot=%s, metricExpected=%s`, pos, mn.MetricGroup, mnExpected.MetricGroup, mn.String(), mnExpected.String()) } if len(mn.Tags) != len(mnExpected.Tags) { t.Fatalf(`unexpected tags count at #%d; got %d; want %d; metricGot=%s, metricExpected=%s`, pos, len(mn.Tags), len(mnExpected.Tags), mn.String(), mnExpected.String()) } 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; metricGot=%s, metricExpected=%s`, pos, i, tag.Key, tagExpected.Key, mn.String(), mnExpected.String()) } if string(tag.Value) != string(tagExpected.Value) { t.Fatalf(`unexpected tag value for key %q at #%d,%d; got %q; want %q; metricGot=%s, metricExpected=%s`, tag.Key, pos, i, tag.Value, tagExpected.Value, mn.String(), mnExpected.String()) } } } func testAddLabels(t *testing.T, mn *storage.MetricName, labels ...string) { t.Helper() if len(labels)%2 > 0 { t.Fatalf("uneven number of labels passed: %v", labels) } for i := 0; i < len(labels); i += 2 { mn.Tags = append(mn.Tags, storage.Tag{ Key: []byte(labels[i]), Value: []byte(labels[i+1]), }) } }