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promql: Add NHCB tests
This adds equivalent NHCB tests to the existing classic histogram tests. Signed-off-by: beorn7 <[email protected]>
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‎promql/promqltest/testdata/histograms.test

+181-10
Original file line numberDiff line numberDiff line change
@@ -73,22 +73,32 @@ eval instant at 50m histogram_count(testhistogram3)
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{start="positive"} 110
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{start="negative"} 20
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# Classic way of accessing the count still works.
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eval instant at 50m testhistogram3_count
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testhistogram3_count{start="positive"} 110
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testhistogram3_count{start="negative"} 20
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# Test histogram_sum.
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eval instant at 50m histogram_sum(testhistogram3)
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{start="positive"} 330
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{start="negative"} 80
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# Test histogram_avg.
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# Classic way of accessing the sum still works.
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eval instant at 50m testhistogram3_sum
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testhistogram3_sum{start="positive"} 330
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testhistogram3_sum{start="negative"} 80
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# Test histogram_avg. This has no classic equivalent.
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eval instant at 50m histogram_avg(testhistogram3)
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{start="positive"} 3
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{start="negative"} 4
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# Test histogram_stddev.
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# Test histogram_stddev. This has no classic equivalent.
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eval instant at 50m histogram_stddev(testhistogram3)
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{start="positive"} 2.8189265757336734
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{start="negative"} 4.182715937754936
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# Test histogram_stdvar.
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# Test histogram_stdvar. This has no classic equivalent.
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eval instant at 50m histogram_stdvar(testhistogram3)
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{start="positive"} 7.946347039377573
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{start="negative"} 17.495112615949154
@@ -103,156 +113,315 @@ eval instant at 50m histogram_fraction(0, 0.2, rate(testhistogram3[5m]))
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{start="positive"} 0.6363636363636364
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{start="negative"} 0
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# Test histogram_quantile.
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# In the classic histogram, we can access the corresponding bucket (if
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# it exists) and divide by the count to get the same result.
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eval instant at 50m testhistogram3_bucket{le=".2"} / ignoring(le) testhistogram3_count
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{start="positive"} 0.6363636363636364
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eval instant at 50m rate(testhistogram3_bucket{le=".2"}[5m]) / ignoring(le) rate(testhistogram3_count[5m])
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{start="positive"} 0.6363636363636364
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# Test histogram_quantile, native and classic.
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eval instant at 50m histogram_quantile(0, testhistogram3)
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{start="positive"} 0
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{start="negative"} -0.25
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eval instant at 50m histogram_quantile(0, testhistogram3_bucket)
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{start="positive"} 0
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{start="negative"} -0.25
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eval instant at 50m histogram_quantile(0.25, testhistogram3)
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{start="positive"} 0.055
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{start="negative"} -0.225
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eval instant at 50m histogram_quantile(0.25, testhistogram3_bucket)
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{start="positive"} 0.055
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{start="negative"} -0.225
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eval instant at 50m histogram_quantile(0.5, testhistogram3)
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{start="positive"} 0.125
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{start="negative"} -0.2
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eval instant at 50m histogram_quantile(0.5, testhistogram3_bucket)
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{start="positive"} 0.125
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{start="negative"} -0.2
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eval instant at 50m histogram_quantile(0.75, testhistogram3)
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{start="positive"} 0.45
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{start="negative"} -0.15
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eval instant at 50m histogram_quantile(0.75, testhistogram3_bucket)
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{start="positive"} 0.45
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{start="negative"} -0.15
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eval instant at 50m histogram_quantile(1, testhistogram3)
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{start="positive"} 1
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{start="negative"} -0.1
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eval instant at 50m histogram_quantile(1, testhistogram3_bucket)
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{start="positive"} 1
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{start="negative"} -0.1
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# Quantile too low.
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eval_warn instant at 50m histogram_quantile(-0.1, testhistogram)
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{start="positive"} -Inf
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{start="negative"} -Inf
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eval_warn 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_warn instant at 50m histogram_quantile(1.01, testhistogram)
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{start="positive"} +Inf
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{start="negative"} +Inf
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eval_warn 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 invalid.
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eval_warn instant at 50m histogram_quantile(NaN, testhistogram)
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{start="positive"} NaN
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{start="negative"} NaN
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eval_warn instant at 50m histogram_quantile(NaN, testhistogram_bucket)
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{start="positive"} NaN
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{start="negative"} NaN
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# Quantile value in lowest bucket.
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eval instant at 50m histogram_quantile(0, testhistogram)
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{start="positive"} 0
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{start="negative"} -0.2
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eval instant at 50m histogram_quantile(0, testhistogram_bucket)
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{start="positive"} 0
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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)
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{start="positive"} 1
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{start="negative"} 0.3
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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)
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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(0.2, 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)
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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(0.5, testhistogram_bucket)
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{start="positive"} 0.15
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{start="negative"} -0.15
161234

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eval instant at 50m histogram_quantile(0.8, testhistogram)
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{start="positive"} 0.72
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{start="negative"} 0.3
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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[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(0.2, rate(testhistogram_bucket[5m]))
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{start="positive"} 0.048
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{start="negative"} -0.2
170252

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eval instant at 50m histogram_quantile(0.5, rate(testhistogram[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(0.5, 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[5m]))
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{start="positive"} 0.72
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{start="negative"} 0.3
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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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# Want results exactly in the middle of the bucket.
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eval instant at 7m histogram_quantile(1./6., testhistogram2)
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{} 1
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eval instant at 7m histogram_quantile(1./6., testhistogram2_bucket)
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{} 1
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eval instant at 7m histogram_quantile(0.5, testhistogram2)
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{} 3
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eval instant at 7m histogram_quantile(0.5, testhistogram2_bucket)
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{} 3
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eval instant at 7m histogram_quantile(5./6., testhistogram2)
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{} 5
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eval instant at 7m histogram_quantile(5./6., testhistogram2_bucket)
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{} 5
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eval instant at 47m histogram_quantile(1./6., rate(testhistogram2[15m]))
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{} 1
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eval instant at 47m histogram_quantile(1./6., rate(testhistogram2_bucket[15m]))
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{} 1
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eval instant at 47m histogram_quantile(0.5, rate(testhistogram2[15m]))
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{} 3
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eval instant at 47m histogram_quantile(0.5, rate(testhistogram2_bucket[15m]))
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{} 3
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eval instant at 47m histogram_quantile(5./6., rate(testhistogram2[15m]))
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{} 5
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eval instant at 47m histogram_quantile(5./6., rate(testhistogram2_bucket[15m]))
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{} 5
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# Aggregated histogram: Everything in one.
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# Aggregated histogram: Everything in one. Note how native histograms
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# don't require aggregation by le.
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eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds[5m])))
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{} 0.075
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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[5m])))
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{} 0.1277777777777778
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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[5m])))
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{} 0.075
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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[5m])))
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{} 0.12777777777777778
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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 instance.
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eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds[5m])) by (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(0.3, 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[5m])) by (instance))
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{instance="ins1"} 0.1333333333
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{instance="ins2"} 0.125
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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 job.
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eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds[5m])) by (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(0.3, 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[5m])) by (job))
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{job="job1"} 0.14
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{job="job2"} 0.1125
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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[5m])) by (job, instance))
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{instance="ins1", job="job1"} 0.11
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{instance="ins2", job="job1"} 0.09
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{instance="ins1", job="job2"} 0.06
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{instance="ins2", job="job2"} 0.0675
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eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[5m])) by (le, job, instance))
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{instance="ins1", job="job1"} 0.11
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{instance="ins2", job="job1"} 0.09
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{instance="ins1", job="job2"} 0.06
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{instance="ins2", job="job2"} 0.0675
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eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds[5m])) by (job, instance))
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{instance="ins1", job="job1"} 0.15
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{instance="ins2", job="job1"} 0.1333333333333333
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{instance="ins1", job="job2"} 0.1
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{instance="ins2", job="job2"} 0.1166666666666667
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eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[5m])) by (le, job, instance))
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{instance="ins1", job="job1"} 0.15
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{instance="ins2", job="job1"} 0.1333333333333333
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{instance="ins1", job="job2"} 0.1
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{instance="ins2", job="job2"} 0.1166666666666667
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# The unaggregated histogram for comparison. Same result as the previous one.
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eval instant at 50m histogram_quantile(0.3, rate(request_duration_seconds[5m]))
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{instance="ins1", job="job1"} 0.11
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{instance="ins2", job="job1"} 0.09
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{instance="ins1", job="job2"} 0.06
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{instance="ins2", job="job2"} 0.0675
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eval instant at 50m histogram_quantile(0.3, rate(request_duration_seconds_bucket[5m]))
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{instance="ins1", job="job1"} 0.11
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{instance="ins2", job="job1"} 0.09
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{instance="ins1", job="job2"} 0.06
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{instance="ins2", job="job2"} 0.0675
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eval instant at 50m histogram_quantile(0.5, rate(request_duration_seconds[5m]))
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{instance="ins1", job="job1"} 0.15
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{instance="ins2", job="job1"} 0.13333333333333333
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{instance="ins1", job="job2"} 0.1
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{instance="ins2", job="job2"} 0.11666666666666667
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eval instant at 50m histogram_quantile(0.5, rate(request_duration_seconds_bucket[5m]))
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{instance="ins1", job="job1"} 0.15
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{instance="ins2", job="job1"} 0.13333333333333333
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{instance="ins1", job="job2"} 0.1
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{instance="ins2", job="job2"} 0.11666666666666667
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# All NHCBs summed into one.
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eval instant at 50m sum(request_duration_seconds)
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{} {{schema:-53 count:250 custom_values:[0.1 0.2] buckets:[100 90 60]}}
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@@ -303,11 +472,13 @@ load_with_nhcb 5m
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eval instant at 50m histogram_quantile(0.2, rate(empty_bucket[5m]))
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{instance="ins1", job="job1"} NaN
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# Load a duplicate histogram with a different name to test failure scenario on multiple histograms with the same label set
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# Load a duplicate histogram with a different name to test failure scenario on multiple histograms with the same label set.
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# https://github.com/prometheus/prometheus/issues/9910
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load_with_nhcb 5m
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request_duration_seconds2_bucket{job="job1", instance="ins1", le="0.1"} 0+1x10
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request_duration_seconds2_bucket{job="job1", instance="ins1", le="0.2"} 0+3x10
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request_duration_seconds2_bucket{job="job1", instance="ins1", le="+Inf"} 0+4x10
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request_duration_seconds2_bucket{job="job1", instance="ins1", le="0.1"} 0+1x10
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request_duration_seconds2_bucket{job="job1", instance="ins1", le="0.2"} 0+3x10
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request_duration_seconds2_bucket{job="job1", instance="ins1", le="+Inf"} 0+4x10
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eval_fail instant at 50m histogram_quantile(0.99, {__name__=~"request_duration_seconds\\d*_bucket"})
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eval_fail instant at 50m histogram_quantile(0.99, {__name__=~"request_duration_seconds\\d*_bucket$"})
484+
eval_fail instant at 50m histogram_quantile(0.99, {__name__=~"request_duration_seconds\\d*"})

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