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app/vmselect/promql: consistently replace NaN data points with non-NaN values for range_first and range_last functions
It is expected that range_first and range_last functions return non-nan const value across all the points if the original series contains at least a single non-NaN value. Previously this rule was violated for NaN data points in the original series. This could confuse users. While at it, add tests for series with NaN values across all the range_* and running_* functions, in order to maintain consistent handling of NaN values across these functions.
This commit is contained in:
Aliaksandr Valialkin
parent
9ebc056861
commit
2a17cddf3d
3 changed files with 232 additions and 8 deletions
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@ -7261,6 +7261,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_trim_outliers(time() > 1200)`, func(t *testing.T) {
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t.Parallel()
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q := `range_trim_outliers(0.5, time() > 1200)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, nan, 1600, 1800, nan},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_trim_spikes()`, func(t *testing.T) {
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t.Parallel()
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q := `range_trim_spikes(0.2, time())`
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@ -7272,6 +7283,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_trim_spikes(time() > 1200 <= 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_trim_spikes(0.2, time() > 1200 <= 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, nan, 1600, nan, nan},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_trim_zscore()`, func(t *testing.T) {
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t.Parallel()
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q := `range_trim_zscore(0.9, time())`
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@ -7283,6 +7305,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_trim_zscore(time() > 1200 <= 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_trim_zscore(0.9, time() > 1200 <= 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, nan, 1600, nan, nan},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_zscore()`, func(t *testing.T) {
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t.Parallel()
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q := `round(range_zscore(time()), 0.1)`
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@ -7294,6 +7327,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_zscore(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `round(range_zscore(time() > 1200 < 1800), 0.1)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, -1, 1, nan, nan},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_quantile(0.5)`, func(t *testing.T) {
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t.Parallel()
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q := `range_quantile(0.5, time())`
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@ -7305,6 +7349,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_quantile(0.5, time() > 1200 < 2000)`, func(t *testing.T) {
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t.Parallel()
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q := `range_quantile(0.5, time() > 1200 < 2000)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{1600, 1600, 1600, 1600, 1600, 1600},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_stddev()`, func(t *testing.T) {
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t.Parallel()
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q := `round(range_stddev(time()),0.01)`
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@ -7316,6 +7371,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_stddev(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `round(range_stddev(time() > 1200 < 1800),0.01)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{100, 100, 100, 100, 100, 100},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_stdvar()`, func(t *testing.T) {
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t.Parallel()
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q := `round(range_stdvar(time()),0.01)`
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@ -7327,6 +7393,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_stdvar(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `round(range_stdvar(time() > 1200 < 1800),0.01)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{10000, 10000, 10000, 10000, 10000, 10000},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_median()`, func(t *testing.T) {
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t.Parallel()
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q := `range_median(time())`
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@ -7687,6 +7764,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`running_min(abs(1500-time()) < 400 > 100)`, func(t *testing.T) {
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t.Parallel()
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q := `running_min(abs(1500-time()) < 400 > 100)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, 300, 300, 300, 300, 300},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`running_max(abs(1300-time()))`, func(t *testing.T) {
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t.Parallel()
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q := `running_max(abs(1300-time()))`
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@ -7698,6 +7786,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`running_max(abs(1300-time()) > 300 < 700)`, func(t *testing.T) {
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t.Parallel()
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q := `running_max(abs(1300-time()) > 300 < 700)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, nan, nan, 500, 500},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`running_sum(1)`, func(t *testing.T) {
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t.Parallel()
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q := `running_sum(1)`
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@ -7720,6 +7819,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`running_sum(time() > 1.2 < 1.8)`, func(t *testing.T) {
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t.Parallel()
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q := `running_sum(time()/1e3 > 1.2 < 1.8)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, 1.4, 3, 3, 3},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`running_avg(time())`, func(t *testing.T) {
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t.Parallel()
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q := `running_avg(time())`
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@ -7731,6 +7841,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`running_avg(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `running_avg(time() > 1200 < 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, 1400, 1500, 1500, 1500},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`smooth_exponential(time(), 1)`, func(t *testing.T) {
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t.Parallel()
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q := `smooth_exponential(time(), 1)`
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@ -7811,6 +7932,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_min(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_min(time() > 1200 < 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{1400, 1400, 1400, 1400, 1400, 1400},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_normalize(time(),alias(-time(),"negative"))`, func(t *testing.T) {
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t.Parallel()
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q := `range_normalize(time(),alias(-time(), "negative"))`
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@ -7828,6 +7960,23 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r1, r2}
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f(q, resultExpected)
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})
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t.Run(`range_normalize(time() > 1200 < 1800,alias(-(time() > 1400 < 2000),"negative"))`, func(t *testing.T) {
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t.Parallel()
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q := `range_normalize(time() > 1200 < 1800,alias(-(time() > 1200 < 2000), "negative"))`
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r1 := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, 0, 1, nan, nan},
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Timestamps: timestampsExpected,
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}
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r2 := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{nan, nan, 1, 0.5, 0, nan},
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Timestamps: timestampsExpected,
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}
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r2.MetricName.MetricGroup = []byte("negative")
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resultExpected := []netstorage.Result{r1, r2}
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f(q, resultExpected)
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})
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t.Run(`range_first(time())`, func(t *testing.T) {
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t.Parallel()
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q := `range_first(time())`
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@ -7839,6 +7988,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_first(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_first(time() > 1200 < 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{1400, 1400, 1400, 1400, 1400, 1400},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_mad(time())`, func(t *testing.T) {
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t.Parallel()
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q := `range_mad(time())`
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@ -7850,6 +8010,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_mad(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_mad(time() > 1200 < 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{100, 100, 100, 100, 100, 100},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_max(time())`, func(t *testing.T) {
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t.Parallel()
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q := `range_max(time())`
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@ -7861,6 +8032,39 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_max(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_max(time() > 1200 < 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{1600, 1600, 1600, 1600, 1600, 1600},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_sum(time())`, func(t *testing.T) {
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t.Parallel()
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q := `range_sum(time())`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{9000, 9000, 9000, 9000, 9000, 9000},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_sum(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_sum(time() > 1200 < 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{3000, 3000, 3000, 3000, 3000, 3000},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_last(time())`, func(t *testing.T) {
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t.Parallel()
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q := `range_last(time())`
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@ -7872,6 +8076,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_last(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_last(time() > 1200 < 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{1600, 1600, 1600, 1600, 1600, 1600},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_linear_regression(time())`, func(t *testing.T) {
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t.Parallel()
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q := `range_linear_regression(time())`
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@ -7894,6 +8109,17 @@ func TestExecSuccess(t *testing.T) {
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_linear_regression(time() > 1200 < 1800)`, func(t *testing.T) {
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t.Parallel()
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q := `range_linear_regression(time() > 1200 < 1800)`
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r := netstorage.Result{
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MetricName: metricNameExpected,
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Values: []float64{1000, 1200, 1400, 1600, 1800, 2000},
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Timestamps: timestampsExpected,
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}
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resultExpected := []netstorage.Result{r}
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f(q, resultExpected)
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})
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t.Run(`range_linear_regression(100/time())`, func(t *testing.T) {
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t.Parallel()
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q := `sort_desc(round((
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@ -1544,10 +1544,8 @@ func transformRangeFirst(tfa *transformFuncArg) ([]*timeseries, error) {
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continue
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}
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vFirst := values[0]
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for i, v := range values {
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if math.IsNaN(v) {
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continue
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}
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values = ts.Values
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for i := range values {
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values[i] = vFirst
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}
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}
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@ -1571,10 +1569,8 @@ func setLastValues(tss []*timeseries) {
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continue
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}
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vLast := values[len(values)-1]
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for i, v := range values {
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if math.IsNaN(v) {
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continue
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}
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values = ts.Values
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for i := range values {
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values[i] = vLast
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}
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}
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@ -40,6 +40,8 @@ See also [LTS releases](https://docs.victoriametrics.com/lts-releases/).
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* BUGFIX: [vmalert](https://docs.victoriametrics.com/vmalert): do not send notifications without labels to Alertmanager. Such notifications are rejected by Alertmanager anyway. Before, vmalert could send alert notifications even if no label-value pairs left after applying `alert_relabel_configs` from [notifier config](https://docs.victoriametrics.com/vmalert/#notifier-configuration-file).
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* BUGFIX: [vmalert](https://docs.victoriametrics.com/vmalert/): properly update value of variable `$activeAt` in rules annotation during replay mode. Before, `$activeAt` could have provided incorrect values during replay.
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* BUGFIX: [MetricsQL](https://docs.victoriametrics.com/metricsql/): properly handle `c1 AND c2` and `c1 OR c1` queries for constants `c1` and `c2`. Previously such queries could return unexpected results. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6637).
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* BUGFIX: [MetricsQL](https://docs.victoriametrics.com/metricsql/): consistently return the first non-`NaN` value from [`range_first`](https://docs.victoriametrics.com/metricsql/#range_first) function across all the returned data points. Previously `NaN` data points weren't replaced with the first non-`NaN` value.
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* BUGFIX: [MetricsQL](https://docs.victoriametrics.com/metricsql/): consistently return the last non-`NaN` value from [`range_last`](https://docs.victoriametrics.com/metricsql/#range_last) function across all the returned data points. Previously `NaN` data points weren't replaced with the last non-`NaN` value.
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* BUGFIX: all VictoriaMetrics components: increase default value of `-loggerMaxArgLen` cmd-line flag from 1000 to 5000. This should improve visibility on errors produced by very long queries.
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## [v1.103.0](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.103.0)
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