Migrate histogram tests to test language.
This commit is contained in:
Fabian Reinartz
parent
03094eff04
commit
eba07a7d3d
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@ -627,14 +627,6 @@ func TestExpressions(t *testing.T) {
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`x{y="testvalue"} => 100 @[%v]`,
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`label_grouping_test{a="a", b="abb"} => 200 @[%v]`,
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`label_grouping_test{a="aa", b="bb"} => 100 @[%v]`,
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`testhistogram_bucket{le="0.1", start="positive"} => 50 @[%v]`,
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`testhistogram_bucket{le=".2", start="positive"} => 70 @[%v]`,
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`testhistogram_bucket{le="1e0", start="positive"} => 110 @[%v]`,
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`testhistogram_bucket{le="+Inf", start="positive"} => 120 @[%v]`,
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`testhistogram_bucket{le="-.2", start="negative"} => 10 @[%v]`,
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`testhistogram_bucket{le="-0.1", start="negative"} => 20 @[%v]`,
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`testhistogram_bucket{le="0.3", start="negative"} => 20 @[%v]`,
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`testhistogram_bucket{le="+Inf", start="negative"} => 30 @[%v]`,
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`request_duration_seconds_bucket{instance="ins1", job="job1", le="0.1"} => 10 @[%v]`,
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`request_duration_seconds_bucket{instance="ins1", job="job1", le="0.2"} => 30 @[%v]`,
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`request_duration_seconds_bucket{instance="ins1", job="job1", le="+Inf"} => 40 @[%v]`,
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@ -934,182 +926,6 @@ func TestExpressions(t *testing.T) {
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`{a="aa", b="bb"} => 100 @[%v]`,
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},
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},
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// Quantile too low.
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{
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expr: `histogram_quantile(-0.1, testhistogram_bucket)`,
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output: []string{
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`{start="positive"} => -Inf @[%v]`,
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`{start="negative"} => -Inf @[%v]`,
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},
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},
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// Quantile too high.
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{
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expr: `histogram_quantile(1.01, testhistogram_bucket)`,
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output: []string{
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`{start="positive"} => +Inf @[%v]`,
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`{start="negative"} => +Inf @[%v]`,
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},
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},
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// Quantile value in lowest bucket, which is positive.
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{
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expr: `histogram_quantile(0, testhistogram_bucket{start="positive"})`,
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output: []string{
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`{start="positive"} => 0 @[%v]`,
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},
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},
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// Quantile value in lowest bucket, which is negative.
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{
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expr: `histogram_quantile(0, testhistogram_bucket{start="negative"})`,
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output: []string{
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`{start="negative"} => -0.2 @[%v]`,
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},
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},
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// Quantile value in highest bucket.
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{
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expr: `histogram_quantile(1, testhistogram_bucket)`,
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output: []string{
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`{start="positive"} => 1 @[%v]`,
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`{start="negative"} => 0.3 @[%v]`,
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},
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},
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// Finally some useful quantiles.
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{
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expr: `histogram_quantile(0.2, testhistogram_bucket)`,
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output: []string{
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`{start="positive"} => 0.048 @[%v]`,
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`{start="negative"} => -0.2 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.5, testhistogram_bucket)`,
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output: []string{
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`{start="positive"} => 0.15 @[%v]`,
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`{start="negative"} => -0.15 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.8, testhistogram_bucket)`,
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output: []string{
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`{start="positive"} => 0.72 @[%v]`,
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`{start="negative"} => 0.3 @[%v]`,
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},
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},
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// More realistic with rates.
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{
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expr: `histogram_quantile(0.2, rate(testhistogram_bucket[5m]))`,
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output: []string{
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`{start="positive"} => 0.048 @[%v]`,
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`{start="negative"} => -0.2 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.5, rate(testhistogram_bucket[5m]))`,
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output: []string{
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`{start="positive"} => 0.15 @[%v]`,
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`{start="negative"} => -0.15 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.8, rate(testhistogram_bucket[5m]))`,
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output: []string{
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`{start="positive"} => 0.72 @[%v]`,
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`{start="negative"} => 0.3 @[%v]`,
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},
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},
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// Aggregated histogram: Everything in one.
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{
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expr: `histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le))`,
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output: []string{
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`{} => 0.075 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le))`,
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output: []string{
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`{} => 0.1277777777777778 @[%v]`,
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},
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},
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// Aggregated histogram: Everything in one. Now with avg, which does not change anything.
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{
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expr: `histogram_quantile(0.3, avg(rate(request_duration_seconds_bucket[5m])) by (le))`,
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output: []string{
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`{} => 0.075 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.5, avg(rate(request_duration_seconds_bucket[5m])) by (le))`,
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output: []string{
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`{} => 0.12777777777777778 @[%v]`,
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},
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},
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// Aggregated histogram: By job.
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{
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expr: `histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le, instance))`,
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output: []string{
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`{instance="ins1"} => 0.075 @[%v]`,
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`{instance="ins2"} => 0.075 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le, instance))`,
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output: []string{
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`{instance="ins1"} => 0.1333333333 @[%v]`,
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`{instance="ins2"} => 0.125 @[%v]`,
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},
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},
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// Aggregated histogram: By instance.
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{
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expr: `histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le, job))`,
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output: []string{
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`{job="job1"} => 0.1 @[%v]`,
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`{job="job2"} => 0.0642857142857143 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le, job))`,
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output: []string{
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`{job="job1"} => 0.14 @[%v]`,
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`{job="job2"} => 0.1125 @[%v]`,
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},
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},
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// Aggregated histogram: By job and instance.
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{
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expr: `histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le, job, instance))`,
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output: []string{
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`{instance="ins1", job="job1"} => 0.11 @[%v]`,
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`{instance="ins2", job="job1"} => 0.09 @[%v]`,
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`{instance="ins1", job="job2"} => 0.06 @[%v]`,
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`{instance="ins2", job="job2"} => 0.0675 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le, job, instance))`,
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output: []string{
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`{instance="ins1", job="job1"} => 0.15 @[%v]`,
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`{instance="ins2", job="job1"} => 0.1333333333333333 @[%v]`,
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`{instance="ins1", job="job2"} => 0.1 @[%v]`,
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`{instance="ins2", job="job2"} => 0.1166666666666667 @[%v]`,
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},
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},
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// The unaggregated histogram for comparison. Same result as the previous one.
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{
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expr: `histogram_quantile(0.3, rate(request_duration_seconds_bucket[5m]))`,
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output: []string{
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`{instance="ins1", job="job1"} => 0.11 @[%v]`,
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`{instance="ins2", job="job1"} => 0.09 @[%v]`,
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`{instance="ins1", job="job2"} => 0.06 @[%v]`,
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`{instance="ins2", job="job2"} => 0.0675 @[%v]`,
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},
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},
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{
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expr: `histogram_quantile(0.5, rate(request_duration_seconds_bucket[5m]))`,
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output: []string{
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`{instance="ins1", job="job1"} => 0.15 @[%v]`,
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`{instance="ins2", job="job1"} => 0.13333333333333333 @[%v]`,
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`{instance="ins1", job="job2"} => 0.1 @[%v]`,
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`{instance="ins2", job="job2"} => 0.11666666666666667 @[%v]`,
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},
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},
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{
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expr: `12.34e6`,
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output: []string{`scalar: 12340000 @[%v]`},
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@ -209,91 +209,6 @@ var testMatrix = Matrix{
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},
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Values: getTestValueStream(0, 200, 20, testStartTime),
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},
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// Two histograms with 4 buckets each (*_sum and *_count not included,
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// only buckets). Lowest bucket for one histogram < 0, for the other >
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// 0. They have the same name, just separated by label. Not useful in
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// practice, but can happen (if clients change bucketing), and the
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// server has to cope with it.
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{
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Metric: clientmodel.COWMetric{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "testhistogram_bucket",
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"le": "0.1",
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"start": "positive",
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},
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},
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Values: getTestValueStream(0, 50, 5, testStartTime),
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},
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{
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Metric: clientmodel.COWMetric{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "testhistogram_bucket",
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"le": ".2",
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"start": "positive",
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},
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},
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Values: getTestValueStream(0, 70, 7, testStartTime),
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},
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{
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Metric: clientmodel.COWMetric{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "testhistogram_bucket",
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"le": "1e0",
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"start": "positive",
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},
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},
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Values: getTestValueStream(0, 110, 11, testStartTime),
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},
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{
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Metric: clientmodel.COWMetric{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "testhistogram_bucket",
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"le": "+Inf",
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"start": "positive",
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},
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},
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Values: getTestValueStream(0, 120, 12, testStartTime),
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},
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{
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Metric: clientmodel.COWMetric{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "testhistogram_bucket",
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"le": "-.2",
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"start": "negative",
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},
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},
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Values: getTestValueStream(0, 10, 1, testStartTime),
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},
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{
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Metric: clientmodel.COWMetric{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "testhistogram_bucket",
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"le": "-0.1",
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"start": "negative",
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},
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},
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Values: getTestValueStream(0, 20, 2, testStartTime),
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},
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{
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Metric: clientmodel.COWMetric{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "testhistogram_bucket",
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"le": "0.3",
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"start": "negative",
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},
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},
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Values: getTestValueStream(0, 20, 2, testStartTime),
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},
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{
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Metric: clientmodel.COWMetric{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "testhistogram_bucket",
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"le": "+Inf",
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"start": "negative",
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},
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},
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Values: getTestValueStream(0, 30, 3, testStartTime),
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},
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// Now a more realistic histogram per job and instance to test aggregation.
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{
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Metric: clientmodel.COWMetric{
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@ -0,0 +1,141 @@
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# Two histograms with 4 buckets each (x_sum and x_count not included,
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# only buckets). Lowest bucket for one histogram < 0, for the other >
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# 0. They have the same name, just separated by label. Not useful in
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# practice, but can happen (if clients change bucketing), and the
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# server has to cope with it.
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# Test histogram.
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load 5m
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testhistogram_bucket{le="0.1", start="positive"} 0+5x10
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testhistogram_bucket{le=".2", start="positive"} 0+7x10
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testhistogram_bucket{le="1e0", start="positive"} 0+11x10
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testhistogram_bucket{le="+Inf", start="positive"} 0+12x10
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testhistogram_bucket{le="-.2", start="negative"} 0+1x10
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testhistogram_bucket{le="-0.1", start="negative"} 0+2x10
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testhistogram_bucket{le="0.3", start="negative"} 0+2x10
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testhistogram_bucket{le="+Inf", start="negative"} 0+3x10
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# Now a more realistic histogram per job and instance to test aggregation.
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load 5m
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request_duration_seconds_bucket{job="job1", instance="ins1", le="0.1"} 0+1x10
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request_duration_seconds_bucket{job="job1", instance="ins1", le="0.2"} 0+3x10
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request_duration_seconds_bucket{job="job1", instance="ins1", le="+Inf"} 0+4x10
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request_duration_seconds_bucket{job="job1", instance="ins2", le="0.1"} 0+2x10
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request_duration_seconds_bucket{job="job1", instance="ins2", le="0.2"} 0+5x10
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request_duration_seconds_bucket{job="job1", instance="ins2", le="+Inf"} 0+6x10
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request_duration_seconds_bucket{job="job2", instance="ins1", le="0.1"} 0+3x10
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request_duration_seconds_bucket{job="job2", instance="ins1", le="0.2"} 0+4x10
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request_duration_seconds_bucket{job="job2", instance="ins1", le="+Inf"} 0+6x10
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request_duration_seconds_bucket{job="job2", instance="ins2", le="0.1"} 0+4x10
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request_duration_seconds_bucket{job="job2", instance="ins2", le="0.2"} 0+7x10
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request_duration_seconds_bucket{job="job2", instance="ins2", le="+Inf"} 0+9x10
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# Quantile too low.
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eval instant at 50m histogram_quantile(-0.1, testhistogram_bucket)
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{start="positive"} -Inf
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{start="negative"} -Inf
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# Quantile too high.
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eval instant at 50m histogram_quantile(1.01, testhistogram_bucket)
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{start="positive"} +Inf
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{start="negative"} +Inf
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# Quantile value in lowest bucket, which is positive.
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eval instant at 50m histogram_quantile(0, testhistogram_bucket{start="positive"})
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{start="positive"} 0
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# Quantile value in lowest bucket, which is negative.
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eval instant at 50m histogram_quantile(0, testhistogram_bucket{start="negative"})
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{start="negative"} -0.2
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# Quantile value in highest bucket.
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eval instant at 50m histogram_quantile(1, testhistogram_bucket)
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{start="positive"} 1
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{start="negative"} 0.3
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# Finally some useful quantiles.
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eval instant at 50m histogram_quantile(0.2, testhistogram_bucket)
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{start="positive"} 0.048
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{start="negative"} -0.2
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eval instant at 50m histogram_quantile(0.5, testhistogram_bucket)
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{start="positive"} 0.15
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{start="negative"} -0.15
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eval instant at 50m histogram_quantile(0.8, testhistogram_bucket)
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{start="positive"} 0.72
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{start="negative"} 0.3
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# More realistic with rates.
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eval instant at 50m histogram_quantile(0.2, rate(testhistogram_bucket[5m]))
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{start="positive"} 0.048
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{start="negative"} -0.2
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eval instant at 50m histogram_quantile(0.5, rate(testhistogram_bucket[5m]))
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{start="positive"} 0.15
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{start="negative"} -0.15
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eval instant at 50m histogram_quantile(0.8, rate(testhistogram_bucket[5m]))
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{start="positive"} 0.72
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{start="negative"} 0.3
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# Aggregated histogram: Everything in one.
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eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le))
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{} 0.075
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eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le))
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{} 0.1277777777777778
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# Aggregated histogram: Everything in one. Now with avg, which does not change anything.
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eval instant at 50m histogram_quantile(0.3, avg(rate(request_duration_seconds_bucket[5m])) by (le))
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{} 0.075
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eval instant at 50m histogram_quantile(0.5, avg(rate(request_duration_seconds_bucket[5m])) by (le))
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{} 0.12777777777777778
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# Aggregated histogram: By job.
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eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le, instance))
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{instance="ins1"} 0.075
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{instance="ins2"} 0.075
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eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le, instance))
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{instance="ins1"} 0.1333333333
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{instance="ins2"} 0.125
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# Aggregated histogram: By instance.
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eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le, job))
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{job="job1"} 0.1
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{job="job2"} 0.0642857142857143
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eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le, job))
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{job="job1"} 0.14
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{job="job2"} 0.1125
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# Aggregated histogram: By job and instance.
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eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le, job, instance))
|
||||
{instance="ins1", job="job1"} 0.11
|
||||
{instance="ins2", job="job1"} 0.09
|
||||
{instance="ins1", job="job2"} 0.06
|
||||
{instance="ins2", job="job2"} 0.0675
|
||||
|
||||
eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le, job, instance))
|
||||
{instance="ins1", job="job1"} 0.15
|
||||
{instance="ins2", job="job1"} 0.1333333333333333
|
||||
{instance="ins1", job="job2"} 0.1
|
||||
{instance="ins2", job="job2"} 0.1166666666666667
|
||||
|
||||
# The unaggregated histogram for comparison. Same result as the previous one.
|
||||
eval instant at 50m histogram_quantile(0.3, rate(request_duration_seconds_bucket[5m]))
|
||||
{instance="ins1", job="job1"} 0.11
|
||||
{instance="ins2", job="job1"} 0.09
|
||||
{instance="ins1", job="job2"} 0.06
|
||||
{instance="ins2", job="job2"} 0.0675
|
||||
|
||||
eval instant at 50m histogram_quantile(0.5, rate(request_duration_seconds_bucket[5m]))
|
||||
{instance="ins1", job="job1"} 0.15
|
||||
{instance="ins2", job="job1"} 0.13333333333333333
|
||||
{instance="ins1", job="job2"} 0.1
|
||||
{instance="ins2", job="job2"} 0.11666666666666667
|
||||
Loading…
Reference in New Issue