mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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app/vmselect/promql: follow-up for ce4f26db02
- Document the bugfix at docs/CHANGELOG.md - Filter out NaN values before sorting as suggested at https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5509#discussion_r1447369218 - Revert unrelated changes in lib/filestream and lib/fs - Use simpler test at app/vmselect/promql/exec_test.go Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5509 Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5506
This commit is contained in:
parent
ce4f26db02
commit
388d020b7c
7 changed files with 45 additions and 304 deletions
|
@ -649,18 +649,26 @@ func newAggrFuncTopK(isReverse bool) aggrFunc {
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if err != nil {
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return nil, err
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}
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lt := lessWithNaNs
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if isReverse {
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lt = lessWithNaNsReversed
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}
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afe := func(tss []*timeseries, modififer *metricsql.ModifierExpr) []*timeseries {
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var tssNoNaNs []*timeseries
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for n := range tss[0].Values {
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sort.Slice(tss, func(i, j int) bool {
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a := tss[i].Values[n]
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b := tss[j].Values[n]
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return lt(a, b)
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// Drop series with NaNs at Values[n] before sorting.
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// This is needed for https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5506
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tssNoNaNs = tssNoNaNs[:0]
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for _, ts := range tss {
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if !math.IsNaN(ts.Values[n]) {
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tssNoNaNs = append(tssNoNaNs, ts)
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}
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}
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sort.Slice(tssNoNaNs, func(i, j int) bool {
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a := tssNoNaNs[i].Values[n]
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b := tssNoNaNs[j].Values[n]
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if isReverse {
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a, b = b, a
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}
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return a < b
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})
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fillNaNsAtIdx(n, ks[n], tss)
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fillNaNsAtIdx(n, ks[n], tssNoNaNs)
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}
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tss = removeEmptySeries(tss)
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reverseSeries(tss)
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@ -711,16 +719,31 @@ func getRangeTopKTimeseries(tss []*timeseries, modifier *metricsql.ModifierExpr,
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value: value,
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}
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}
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lt := lessWithNaNs
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// Drop maxs with NaNs before sorting.
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// This is needed for https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5506
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maxsNoNaNs := make([]tsWithValue, 0, len(maxs))
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for _, tsv := range maxs {
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if !math.IsNaN(tsv.value) {
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maxsNoNaNs = append(maxsNoNaNs, tsv)
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}
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}
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sort.Slice(maxsNoNaNs, func(i, j int) bool {
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a := maxsNoNaNs[i].value
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b := maxsNoNaNs[j].value
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if isReverse {
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lt = lessWithNaNsReversed
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a, b = b, a
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}
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sort.Slice(maxs, func(i, j int) bool {
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return lt(maxs[i].value, maxs[j].value)
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return a < b
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})
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for i := range maxs {
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tss[i] = maxs[i].ts
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for _, tsv := range maxs {
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if math.IsNaN(tsv.value) {
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maxsNoNaNs = append(maxsNoNaNs, tsv)
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}
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}
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for i := range maxsNoNaNs {
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tss[i] = maxsNoNaNs[i].ts
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}
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remainingSumTS := getRemainingSumTimeseries(tss, modifier, ks, remainingSumTagName)
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for i, k := range ks {
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fillNaNsAtIdx(i, k, tss)
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@ -1252,20 +1275,6 @@ func newAggrQuantileFunc(phis []float64) func(tss []*timeseries, modifier *metri
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}
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}
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func lessWithNaNs(a, b float64) bool {
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if math.IsNaN(a) {
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return !math.IsNaN(b)
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}
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return a < b
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}
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func lessWithNaNsReversed(a, b float64) bool {
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if math.IsNaN(a) {
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return true
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}
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return a > b
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}
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func floatToIntBounded(f float64) int {
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if f > math.MaxInt {
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return math.MaxInt
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@ -1,12 +1,8 @@
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package promql
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import (
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"log"
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"math"
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"reflect"
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"testing"
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"github.com/VictoriaMetrics/metricsql"
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)
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func TestModeNoNaNs(t *testing.T) {
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@ -38,268 +34,3 @@ func TestModeNoNaNs(t *testing.T) {
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f(1, []float64{2, 3, 3, 4, 4}, 3)
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f(1, []float64{4, 3, 2, 3, 4}, 3)
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}
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func TestLessWithNaNs(t *testing.T) {
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f := func(a, b float64, expectedResult bool) {
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t.Helper()
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result := lessWithNaNs(a, b)
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if result != expectedResult {
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t.Fatalf("unexpected result; got %v; want %v", result, expectedResult)
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}
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}
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f(nan, nan, false)
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f(nan, 1, true)
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f(1, nan, false)
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f(1, 2, true)
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f(2, 1, false)
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f(1, 1, false)
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}
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func TestLessWithNaNsReversed(t *testing.T) {
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f := func(a, b float64, expectedResult bool) {
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t.Helper()
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result := lessWithNaNsReversed(a, b)
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if result != expectedResult {
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t.Fatalf("unexpected result; got %v; want %v", result, expectedResult)
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}
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}
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f(nan, nan, true)
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f(nan, 1, true)
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f(1, nan, false)
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f(1, 2, false)
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f(2, 1, true)
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f(1, 1, false)
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}
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func TestTopK(t *testing.T) {
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f := func(all [][]*timeseries, expected []*timeseries, k int, reversed bool) {
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t.Helper()
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topKFunc := newAggrFuncTopK(reversed)
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actual, err := topKFunc(&aggrFuncArg{
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args: all,
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ae: &metricsql.AggrFuncExpr{
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Limit: 1,
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Modifier: metricsql.ModifierExpr{},
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},
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ec: nil,
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})
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if err != nil {
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log.Fatalf("failed to call topK, err=%v", err)
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}
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for i := range actual {
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if !eq(expected[i], actual[i]) {
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t.Fatalf("unexpected result: i:%v got:\n%v; want:\t%v", i, actual[i], expected[i])
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}
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}
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}
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f(newTestSeries(), []*timeseries{
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{
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Timestamps: []int64{1, 2, 3, 4, 5},
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Values: []float64{nan, nan, 3, 2, 1},
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},
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{
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Timestamps: []int64{1, 2, 3, 4, 5},
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Values: []float64{1, 2, 3, 4, 5},
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},
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{
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Timestamps: []int64{1, 2, 3, 4, 5},
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Values: []float64{2, 3, nan, nan, nan},
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},
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}, 2, true)
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f(newTestSeries(), []*timeseries{
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{
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Timestamps: []int64{1, 2, 3, 4, 5},
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Values: []float64{3, 4, 5, 6, 7},
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},
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{
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Timestamps: []int64{1, 2, 3, 4, 5},
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Values: []float64{nan, nan, 4, 5, 6},
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},
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{
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Timestamps: []int64{1, 2, 3, 4, 5},
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Values: []float64{5, 4, nan, nan, nan},
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},
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}, 2, false)
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f(newTestSeriesWithNaNsWithoutOverlap(), []*timeseries{
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{
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Values: []float64{nan, nan, nan, 2, 1},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{nan, nan, 5, 6, 7},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{2, 3, 4, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{1, 2, nan, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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}, 2, true)
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f(newTestSeriesWithNaNsWithoutOverlap(), []*timeseries{
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{
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Values: []float64{nan, nan, 5, 6, 7},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{nan, nan, 6, 2, 1},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{2, 3, nan, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{1, 2, nan, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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}, 2, false)
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f(newTestSeriesWithNaNsWithOverlap(), []*timeseries{
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{
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Values: []float64{nan, nan, nan, 2, 1},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{nan, nan, nan, 6, 7},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{1, 2, 3, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{2, 3, 4, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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}, 2, true)
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f(newTestSeriesWithNaNsWithOverlap(), []*timeseries{
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{
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Values: []float64{nan, nan, 5, 6, 7},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{nan, nan, 6, 2, 1},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{2, 3, nan, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{1, 2, nan, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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}, 2, false)
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}
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func newTestSeries() [][]*timeseries {
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return [][]*timeseries{
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{
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{
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Values: []float64{2, 2, 2, 2, 2},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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},
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{
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{
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Values: []float64{1, 2, 3, 4, 5},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{2, 3, 4, 5, 6},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{5, 4, 3, 2, 1},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{3, 4, 5, 6, 7},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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},
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}
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}
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func newTestSeriesWithNaNsWithoutOverlap() [][]*timeseries {
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return [][]*timeseries{
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{
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{
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Values: []float64{2, 2, 2, 2, 2},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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},
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{
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{
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Values: []float64{1, 2, nan, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{2, 3, 4, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{nan, nan, 6, 2, 1},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{nan, nan, 5, 6, 7},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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},
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}
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}
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func newTestSeriesWithNaNsWithOverlap() [][]*timeseries {
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return [][]*timeseries{
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{
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{
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Values: []float64{2, 2, 2, 2, 2},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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},
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{
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{
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Values: []float64{1, 2, 3, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{2, 3, 4, nan, nan},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{nan, nan, 6, 2, 1},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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{
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Values: []float64{nan, nan, 5, 6, 7},
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Timestamps: []int64{1, 2, 3, 4, 5},
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},
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},
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}
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}
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func eq(a, b *timeseries) bool {
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if !reflect.DeepEqual(a.Timestamps, b.Timestamps) {
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return false
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}
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for i := range a.Values {
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if !eqWithNan(a.Values[i], b.Values[i]) {
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return false
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}
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}
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return true
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}
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func eqWithNan(a, b float64) bool {
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if math.IsNaN(a) && math.IsNaN(b) {
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return true
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}
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if math.IsNaN(a) || math.IsNaN(b) {
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return false
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}
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return a == b
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}
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|
|
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@ -6590,7 +6590,7 @@ func TestExecSuccess(t *testing.T) {
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})
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t.Run(`bottomk(1)`, func(t *testing.T) {
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t.Parallel()
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q := `bottomk(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss"))`
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q := `bottomk(1, label_set(10, "foo", "bar") or label_set(time()/150, "baz", "sss") or label_set(time()<100, "a", "b"))`
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r1 := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, nan, 10, 10, 10},
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|
|
|
@ -51,6 +51,7 @@ The sandbox cluster installation is running under the constant load generated by
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* BUGFIX: [vmalert](https://docs.victoriametrics.com/vmalert.html): check `-external.url` schema when starting vmalert, must be `http` or `https`. Before, alertmanager could reject alert notifications if `-external.url` contained no or wrong schema.
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* BUGFIX: [vmalert](https://docs.victoriametrics.com/vmalert.html): automatically add `exported_` prefix for original evaluation result label if it's conflicted with external or reserved one, previously it was overridden. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5161).
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* BUGFIX: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): consistently sort results for `q1 or q2` query, so they do not change colors with each refresh in Grafana. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5393).
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* BUGFIX: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): properly return results from [bottomk](https://docs.victoriametrics.com/MetricsQL.html#bottomk) and `bottomk_*()` functions when some of these results contain NaN values. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5506). Thanks to @xiaozongyang for [the fix](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5509).
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* BUGFIX: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): properly handle queries, which wrap [rollup functions](https://docs.victoriametrics.com/MetricsQL.html#rollup-functions) with multiple arguments without explicitly specified lookbehind window in square brackets into [aggregate functions](https://docs.victoriametrics.com/MetricsQL.html#aggregate-functions). For example, `sum(quantile_over_time(0.5, process_resident_memory_bytes))` was resulting to `expecting at least 2 args to ...; got 1 args` error. Thanks to @atykhyy for [the pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5414).
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* BUGFIX: [vmctl](https://docs.victoriametrics.com/vmctl.html): retry on import errors in `vm-native` mode. Before, retries happened only on writes into a network connection between source and destination. But errors returned by server after all the data was transmitted were logged, but not retried.
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* BUGFIX: [vmagent](https://docs.victoriametrics.com/vmagent.html): properly assume role with [AWS IRSA authorization](https://docs.aws.amazon.com/eks/latest/userguide/iam-roles-for-service-accounts.html). Previously role chaining was not supported. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3822) for details.
|
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|
|
|
@ -334,6 +334,6 @@ var bwPool sync.Pool
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|
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type streamTracker struct {
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fd uintptr
|
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offset uint64 // nolint
|
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length uint64 // nolint
|
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offset uint64
|
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length uint64
|
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}
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|
|
|
@ -1,6 +1,6 @@
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package filestream
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||||
|
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func (st *streamTracker) adviseDontNeed(n int, fdatasync bool) error { // nolint
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func (st *streamTracker) adviseDontNeed(n int, fdatasync bool) error {
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return nil
|
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}
|
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|
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|
|
|
@ -4,7 +4,7 @@ import (
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|||
"os"
|
||||
)
|
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|
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func fadviseSequentialRead(f *os.File, prefetch bool) error { // nolint
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func fadviseSequentialRead(f *os.File, prefetch bool) error {
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// TODO: implement this properly
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return nil
|
||||
}
|
||||
|
|
Loading…
Reference in a new issue