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5bd0d00f8c
Signed-off-by: Linas Medziunas <linas.medziunas@gmail.com> Signed-off-by: Björn Rabenstein <github@rabenste.in> Signed-off-by: beorn7 <beorn@grafana.com> Co-authored-by: Björn Rabenstein <github@rabenste.in> Co-authored-by: beorn7 <beorn@grafana.com>
1172 lines
39 KiB
Plaintext
1172 lines
39 KiB
Plaintext
# 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_with_nhcb 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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# Another test histogram, where q(1/6), q(1/2), and q(5/6) are each in
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# the middle of a bucket and should therefore be 1, 3, and 5,
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# respectively.
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load_with_nhcb 5m
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testhistogram2_bucket{le="0"} 0+0x10
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testhistogram2_bucket{le="2"} 0+1x10
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testhistogram2_bucket{le="4"} 0+2x10
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testhistogram2_bucket{le="6"} 0+3x10
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testhistogram2_bucket{le="+Inf"} 0+3x10
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# Another test histogram, this time without any observations in the +Inf bucket.
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# This enables a meaningful calculation of standard deviation and variance.
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load_with_nhcb 5m
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testhistogram3_bucket{le="0", start="positive"} 0+0x10
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testhistogram3_bucket{le="0.1", start="positive"} 0+5x10
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testhistogram3_bucket{le=".2", start="positive"} 0+7x10
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testhistogram3_bucket{le="1e0", start="positive"} 0+11x10
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testhistogram3_bucket{le="+Inf", start="positive"} 0+11x10
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testhistogram3_sum{start="positive"} 0+33x10
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testhistogram3_count{start="positive"} 0+11x10
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testhistogram3_bucket{le="-.25", start="negative"} 0+0x10
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testhistogram3_bucket{le="-.2", start="negative"} 0+1x10
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testhistogram3_bucket{le="-0.1", start="negative"} 0+2x10
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testhistogram3_bucket{le="0.3", start="negative"} 0+2x10
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testhistogram3_bucket{le="+Inf", start="negative"} 0+2x10
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testhistogram3_sum{start="negative"} 0+8x10
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testhistogram3_count{start="negative"} 0+2x10
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# Now a more realistic histogram per job and instance to test aggregation.
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load_with_nhcb 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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# Different le representations in one histogram.
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load_with_nhcb 5m
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mixed_bucket{job="job1", instance="ins1", le="0.1"} 0+1x10
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mixed_bucket{job="job1", instance="ins1", le="0.2"} 0+1x10
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mixed_bucket{job="job1", instance="ins1", le="2e-1"} 0+1x10
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mixed_bucket{job="job1", instance="ins1", le="2.0e-1"} 0+1x10
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mixed_bucket{job="job1", instance="ins1", le="+Inf"} 0+4x10
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mixed_bucket{job="job1", instance="ins2", le="+inf"} 0+0x10
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mixed_bucket{job="job1", instance="ins2", le="+Inf"} 0+0x10
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# Test histogram_count.
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eval instant at 50m histogram_count(testhistogram3)
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expect no_warn
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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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expect no_warn
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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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expect no_warn
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{start="positive"} 330
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{start="negative"} 80
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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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expect no_warn
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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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expect no_warn
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{start="positive"} 3
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{start="negative"} 4
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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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expect no_warn
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{start="positive"} 2.7435461458749795
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{start="negative"} 4.187667907081458
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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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expect no_warn
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{start="positive"} 7.527045454545455
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{start="negative"} 17.5365625
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# Test histogram_fraction.
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#
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eval instant at 50m histogram_fraction(0, 4, testhistogram2)
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expect no_warn
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{} 0.6666666666666666
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eval instant at 50m histogram_fraction(0, 4, testhistogram2_bucket)
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expect no_warn
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{} 0.6666666666666666
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eval instant at 50m histogram_fraction(0, 6, testhistogram2)
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expect no_warn
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{} 1
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eval instant at 50m histogram_fraction(0, 6, testhistogram2_bucket)
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expect no_warn
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{} 1
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eval instant at 50m histogram_fraction(0, 3.5, testhistogram2)
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expect no_warn
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{} 0.5833333333333334
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eval instant at 50m histogram_fraction(0, 3.5, testhistogram2_bucket)
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expect no_warn
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{} 0.5833333333333334
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eval instant at 50m histogram_fraction(0, 0.2, testhistogram3)
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expect no_warn
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{start="positive"} 0.6363636363636364
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{start="negative"} 0
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eval instant at 50m histogram_fraction(0, 0.2, testhistogram3_bucket)
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expect no_warn
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{start="positive"} 0.6363636363636364
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{start="negative"} 0
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eval instant at 50m histogram_fraction(0, 0.2, rate(testhistogram3[10m]))
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expect no_warn
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{start="positive"} 0.6363636363636364
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{start="negative"} 0
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eval instant at 50m histogram_fraction(0, 0.2, rate(testhistogram3_bucket[10m]))
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expect no_warn
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{start="positive"} 0.6363636363636364
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{start="negative"} 0
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# Positive buckets, lower falls in the first bucket.
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load_with_nhcb 5m
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positive_buckets_lower_falls_in_the_first_bucket_bucket{le="1"} 1+0x10
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positive_buckets_lower_falls_in_the_first_bucket_bucket{le="2"} 3+0x10
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positive_buckets_lower_falls_in_the_first_bucket_bucket{le="3"} 6+0x10
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positive_buckets_lower_falls_in_the_first_bucket_bucket{le="+Inf"} 100+0x10
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# - Bucket [0, 1]: contributes 1.0 observation (full bucket).
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# - Bucket [1, 2]: contributes (1.5-1)/(2-1) * (3-1) = 0.5 * 2 = 1.0 observations.
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# Total: (1.0 + 1.0) / 100.0 = 0.02
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eval instant at 50m histogram_fraction(0, 1.5, positive_buckets_lower_falls_in_the_first_bucket_bucket)
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expect no_warn
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{} 0.02
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eval instant at 50m histogram_fraction(0, 1.5, positive_buckets_lower_falls_in_the_first_bucket)
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expect no_warn
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{} 0.02
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# Negative buckets, lower falls in the first bucket.
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load_with_nhcb 5m
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negative_buckets_lower_falls_in_the_first_bucket_bucket{le="-3"} 10+0x10
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negative_buckets_lower_falls_in_the_first_bucket_bucket{le="-2"} 12+0x10
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negative_buckets_lower_falls_in_the_first_bucket_bucket{le="-1"} 15+0x10
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negative_buckets_lower_falls_in_the_first_bucket_bucket{le="+Inf"} 100+0x10
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# - Bucket [-Inf, -3]: contributes zero observations (no interpolation with infinite width bucket).
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# - Bucket [-3, -2]: contributes 12-10 = 2.0 observations (full bucket).
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# Total: 2.0 / 100.0 = 0.02
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eval instant at 50m histogram_fraction(-4, -2, negative_buckets_lower_falls_in_the_first_bucket_bucket)
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expect no_warn
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{} 0.02
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eval instant at 50m histogram_fraction(-4, -2, negative_buckets_lower_falls_in_the_first_bucket)
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expect no_warn
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{} 0.02
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# Lower is -Inf.
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load_with_nhcb 5m
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lower_is_negative_Inf_bucket{le="-3"} 10+0x10
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lower_is_negative_Inf_bucket{le="-2"} 12+0x10
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lower_is_negative_Inf_bucket{le="-1"} 15+0x10
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lower_is_negative_Inf_bucket{le="+Inf"} 100+0x10
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# - Bucket [-Inf, -3]: contributes 10.0 observations (full bucket).
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# - Bucket [-3, -2]: contributes 12-10 = 2.0 observations (full bucket).
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# - Bucket [-2, -1]: contributes (-1.5-(-2))/(-1-(-2)) * (15-12) = 0.5 * 3 = 1.5 observations.
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# Total: (10.0 + 2.0 + 1.5) / 100.0 = 0.135
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eval instant at 50m histogram_fraction(-Inf, -1.5, lower_is_negative_Inf_bucket)
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expect no_warn
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{} 0.135
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eval instant at 50m histogram_fraction(-Inf, -1.5, lower_is_negative_Inf)
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expect no_warn
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{} 0.135
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# Lower is -Inf and upper is +Inf (positive buckets).
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load_with_nhcb 5m
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lower_is_negative_Inf_and_upper_is_positive_Inf__positive_buckets__bucket{le="1"} 1+0x10
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lower_is_negative_Inf_and_upper_is_positive_Inf__positive_buckets__bucket{le="2"} 3+0x10
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lower_is_negative_Inf_and_upper_is_positive_Inf__positive_buckets__bucket{le="3"} 6+0x10
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lower_is_negative_Inf_and_upper_is_positive_Inf__positive_buckets__bucket{le="+Inf"} 100+0x10
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# Range [-Inf, +Inf] captures all observations.
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eval instant at 50m histogram_fraction(-Inf, +Inf, lower_is_negative_Inf_and_upper_is_positive_Inf__positive_buckets__bucket)
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expect no_warn
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{} 1.0
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eval instant at 50m histogram_fraction(-Inf, +Inf, lower_is_negative_Inf_and_upper_is_positive_Inf__positive_buckets_)
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expect no_warn
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{} 1.0
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# Lower is -Inf and upper is +Inf (negative buckets).
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load_with_nhcb 5m
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lower_is_negative_Inf_and_upper_is_positive_Inf__negative_buckets__bucket{le="-3"} 10+0x10
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lower_is_negative_Inf_and_upper_is_positive_Inf__negative_buckets__bucket{le="-2"} 12+0x10
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lower_is_negative_Inf_and_upper_is_positive_Inf__negative_buckets__bucket{le="-1"} 15+0x10
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lower_is_negative_Inf_and_upper_is_positive_Inf__negative_buckets__bucket{le="+Inf"} 100+0x10
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# Range [-Inf, +Inf] captures all observations.
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eval instant at 50m histogram_fraction(-Inf, +Inf, lower_is_negative_Inf_and_upper_is_positive_Inf__negative_buckets__bucket)
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expect no_warn
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{} 1.0
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eval instant at 50m histogram_fraction(-Inf, +Inf, lower_is_negative_Inf_and_upper_is_positive_Inf__negative_buckets_)
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expect no_warn
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{} 1.0
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# Lower and upper fall in last bucket (positive buckets).
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load_with_nhcb 5m
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lower_and_upper_fall_in_last_bucket__positive_buckets__bucket{le="1"} 1+0x10
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lower_and_upper_fall_in_last_bucket__positive_buckets__bucket{le="2"} 3+0x10
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lower_and_upper_fall_in_last_bucket__positive_buckets__bucket{le="3"} 6+0x10
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lower_and_upper_fall_in_last_bucket__positive_buckets__bucket{le="+Inf"} 100+0x10
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# - Bucket [3, +Inf]: contributes zero observations (no interpolation with infinite width bucket).
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# Total: 0.0 / 100.0 = 0.0
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eval instant at 50m histogram_fraction(4, 5, lower_and_upper_fall_in_last_bucket__positive_buckets__bucket)
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expect no_warn
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{} 0.0
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eval instant at 50m histogram_fraction(4, 5, lower_and_upper_fall_in_last_bucket__positive_buckets_)
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expect no_warn
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{} 0.0
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# Lower and upper fall in last bucket (negative buckets).
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load_with_nhcb 5m
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lower_and_upper_fall_in_last_bucket__negative_buckets__bucket{le="-3"} 10+0x10
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lower_and_upper_fall_in_last_bucket__negative_buckets__bucket{le="-2"} 12+0x10
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lower_and_upper_fall_in_last_bucket__negative_buckets__bucket{le="-1"} 15+0x10
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lower_and_upper_fall_in_last_bucket__negative_buckets__bucket{le="+Inf"} 100+0x10
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# - Bucket [-1, +Inf]: contributes zero observations (no interpolation with infinite width bucket).
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# Total: 0.0 / 100.0 = 0.0
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eval instant at 50m histogram_fraction(0, 1, lower_and_upper_fall_in_last_bucket__negative_buckets__bucket)
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expect no_warn
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{} 0.0
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eval instant at 50m histogram_fraction(0, 1, lower_and_upper_fall_in_last_bucket__negative_buckets_)
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expect no_warn
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{} 0.0
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# Upper falls in last bucket.
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load_with_nhcb 5m
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upper_falls_in_last_bucket_bucket{le="1"} 1+0x10
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upper_falls_in_last_bucket_bucket{le="2"} 3+0x10
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upper_falls_in_last_bucket_bucket{le="3"} 6+0x10
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upper_falls_in_last_bucket_bucket{le="+Inf"} 100+0x10
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# - Bucket [2, 3]: 6-3 = 3.0 observations (full bucket).
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# - Bucket [3, +Inf]: contributes zero observations (no interpolation with infinite width bucket).
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# Total: 3.0 / 100.0 = 0.03
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eval instant at 50m histogram_fraction(2, 5, upper_falls_in_last_bucket_bucket)
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expect no_warn
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{} 0.03
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eval instant at 50m histogram_fraction(2, 5, upper_falls_in_last_bucket)
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expect no_warn
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{} 0.03
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# Upper is +Inf.
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load_with_nhcb 5m
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upper_is_positive_Inf_bucket{le="1"} 1+0x10
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upper_is_positive_Inf_bucket{le="2"} 3+0x10
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upper_is_positive_Inf_bucket{le="3"} 6+0x10
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upper_is_positive_Inf_bucket{le="+Inf"} 100+0x10
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# All observations in +Inf bucket: 100-6 = 94.0 observations.
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# Total: 94.0 / 100.0 = 0.94
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eval instant at 50m histogram_fraction(400, +Inf, upper_is_positive_Inf_bucket)
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expect no_warn
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{} 0.94
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eval instant at 50m histogram_fraction(400, +Inf, upper_is_positive_Inf)
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expect no_warn
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{} 0.94
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# Lower equals upper.
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load_with_nhcb 5m
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lower_equals_upper_bucket{le="1"} 1+0x10
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lower_equals_upper_bucket{le="2"} 3+0x10
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lower_equals_upper_bucket{le="3"} 6+0x10
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lower_equals_upper_bucket{le="+Inf"} 100+0x10
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# No observations can be captured in a zero-width range.
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eval instant at 50m histogram_fraction(2, 2, lower_equals_upper_bucket)
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expect no_warn
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{} 0.0
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eval instant at 50m histogram_fraction(2, 2, lower_equals_upper)
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expect no_warn
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{} 0.0
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# Lower greater than upper.
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load_with_nhcb 5m
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lower_greater_than_upper_bucket{le="1"} 1+0x10
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lower_greater_than_upper_bucket{le="2"} 3+0x10
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lower_greater_than_upper_bucket{le="3"} 6+0x10
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lower_greater_than_upper_bucket{le="+Inf"} 100+0x10
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eval instant at 50m histogram_fraction(3, 2, lower_greater_than_upper_bucket)
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expect no_warn
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{} 0.0
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eval instant at 50m histogram_fraction(3, 2, lower_greater_than_upper)
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expect no_warn
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{} 0.0
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# Single bucket.
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load_with_nhcb 5m
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single_bucket_bucket{le="+Inf"} 100+0x10
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# - Bucket [0, +Inf]: contributes zero observations (no interpolation with infinite width bucket).
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# Total: 0.0 / 100.0 = 0.0
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eval instant at 50m histogram_fraction(0, 1, single_bucket_bucket)
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expect no_warn
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{} 0.0
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eval instant at 50m histogram_fraction(0, 1, single_bucket)
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expect no_warn
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{} 0.0
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# All zero counts.
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load_with_nhcb 5m
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all_zero_counts_bucket{le="1"} 0+0x10
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all_zero_counts_bucket{le="2"} 0+0x10
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all_zero_counts_bucket{le="3"} 0+0x10
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all_zero_counts_bucket{le="+Inf"} 0+0x10
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eval instant at 50m histogram_fraction(0, 5, all_zero_counts_bucket)
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expect no_warn
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{} NaN
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eval instant at 50m histogram_fraction(0, 5, all_zero_counts)
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expect no_warn
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{} NaN
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# Lower exactly on bucket boundary.
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load_with_nhcb 5m
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lower_exactly_on_bucket_boundary_bucket{le="1"} 1+0x10
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lower_exactly_on_bucket_boundary_bucket{le="2"} 3+0x10
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lower_exactly_on_bucket_boundary_bucket{le="3"} 6+0x10
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lower_exactly_on_bucket_boundary_bucket{le="+Inf"} 100+0x10
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# - Bucket [2, 3]: 6-3 = 3.0 observations (full bucket).
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# - Bucket [3, +Inf]: contributes zero observations (no interpolation with infinite width bucket).
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# Total: 3.0 / 100.0 = 0.03
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eval instant at 50m histogram_fraction(2, 3.5, lower_exactly_on_bucket_boundary_bucket)
|
|
expect no_warn
|
|
{} 0.03
|
|
|
|
eval instant at 50m histogram_fraction(2, 3.5, lower_exactly_on_bucket_boundary)
|
|
expect no_warn
|
|
{} 0.03
|
|
|
|
# Upper exactly on bucket boundary.
|
|
load_with_nhcb 5m
|
|
upper_exactly_on_bucket_boundary_bucket{le="1"} 1+0x10
|
|
upper_exactly_on_bucket_boundary_bucket{le="2"} 3+0x10
|
|
upper_exactly_on_bucket_boundary_bucket{le="3"} 6+0x10
|
|
upper_exactly_on_bucket_boundary_bucket{le="+Inf"} 100+0x10
|
|
|
|
# - Bucket [0, 1]: (1.0-0.5)/(1.0-0.0) * 1.0 = 0.5 * 1.0 = 0.5 observations.
|
|
# - Bucket [1, 2]: 3-1 = 2.0 observations (full bucket).
|
|
# Total: (0.5 + 2.0) / 100.0 = 0.025
|
|
|
|
eval instant at 50m histogram_fraction(0.5, 2, upper_exactly_on_bucket_boundary_bucket)
|
|
expect no_warn
|
|
{} 0.025
|
|
|
|
eval instant at 50m histogram_fraction(0.5, 2, upper_exactly_on_bucket_boundary)
|
|
expect no_warn
|
|
{} 0.025
|
|
|
|
# Both bounds exactly on bucket boundaries.
|
|
load_with_nhcb 5m
|
|
both_bounds_exactly_on_bucket_boundaries_bucket{le="1"} 1+0x10
|
|
both_bounds_exactly_on_bucket_boundaries_bucket{le="2"} 3+0x10
|
|
both_bounds_exactly_on_bucket_boundaries_bucket{le="3"} 6+0x10
|
|
both_bounds_exactly_on_bucket_boundaries_bucket{le="+Inf"} 100+0x10
|
|
|
|
# - Bucket [1, 2]: 3-1 = 2.0 observations (full bucket).
|
|
# - Bucket [2, 3]: 6-3 = 3.0 observations (full bucket).
|
|
# Total: (2.0 + 3.0) / 100.0 = 0.05
|
|
|
|
eval instant at 50m histogram_fraction(1, 3, both_bounds_exactly_on_bucket_boundaries_bucket)
|
|
expect no_warn
|
|
{} 0.05
|
|
|
|
eval instant at 50m histogram_fraction(1, 3, both_bounds_exactly_on_bucket_boundaries)
|
|
expect no_warn
|
|
{} 0.05
|
|
|
|
# Fractional bucket bounds.
|
|
load_with_nhcb 5m
|
|
fractional_bucket_bounds_bucket{le="0.5"} 2.5+0x10
|
|
fractional_bucket_bounds_bucket{le="1"} 7.5+0x10
|
|
fractional_bucket_bounds_bucket{le="+Inf"} 100+0x10
|
|
|
|
# - Bucket [0, 0.5]: (0.5-0.1)/(0.5-0.0) * 2.5 = 0.8 * 2.5 = 2.0 observations.
|
|
# - Bucket [0.5, 1.0]: (0.75-0.5)/(1.0-0.5) * (7.5-2.5) = 0.5 * 5.0 = 2.5 observations.
|
|
# Total: (2.0 + 2.5) / 100.0 = 0.045
|
|
|
|
eval instant at 50m histogram_fraction(0.1, 0.75, fractional_bucket_bounds_bucket)
|
|
expect no_warn
|
|
{} 0.045
|
|
|
|
eval instant at 50m histogram_fraction(0.1, 0.75, fractional_bucket_bounds)
|
|
expect no_warn
|
|
{} 0.045
|
|
|
|
# Range crosses zero.
|
|
load_with_nhcb 5m
|
|
range_crosses_zero_bucket{le="-2"} 5+0x10
|
|
range_crosses_zero_bucket{le="-1"} 10+0x10
|
|
range_crosses_zero_bucket{le="0"} 15+0x10
|
|
range_crosses_zero_bucket{le="1"} 20+0x10
|
|
range_crosses_zero_bucket{le="+Inf"} 100+0x10
|
|
|
|
# - Bucket [-1, 0]: 15-10 = 5.0 observations (full bucket).
|
|
# - Bucket [0, 1]: 20-15 = 5.0 observations (full bucket).
|
|
# Total: (5.0 + 5.0) / 100.0 = 0.1
|
|
|
|
eval instant at 50m histogram_fraction(-1, 1, range_crosses_zero_bucket)
|
|
expect no_warn
|
|
{} 0.1
|
|
|
|
eval instant at 50m histogram_fraction(-1, 1, range_crosses_zero)
|
|
expect no_warn
|
|
{} 0.1
|
|
|
|
# Lower is NaN.
|
|
load_with_nhcb 5m
|
|
lower_is_NaN_bucket{le="1"} 1+0x10
|
|
lower_is_NaN_bucket{le="+Inf"} 100+0x10
|
|
|
|
eval instant at 50m histogram_fraction(NaN, 1, lower_is_NaN_bucket)
|
|
expect no_warn
|
|
{} NaN
|
|
|
|
eval instant at 50m histogram_fraction(NaN, 1, lower_is_NaN)
|
|
expect no_warn
|
|
{} NaN
|
|
|
|
# Upper is NaN.
|
|
load_with_nhcb 5m
|
|
upper_is_NaN_bucket{le="1"} 1+0x10
|
|
upper_is_NaN_bucket{le="+Inf"} 100+0x10
|
|
|
|
eval instant at 50m histogram_fraction(0, NaN, upper_is_NaN_bucket)
|
|
expect no_warn
|
|
{} NaN
|
|
|
|
eval instant at 50m histogram_fraction(0, NaN, upper_is_NaN)
|
|
expect no_warn
|
|
{} NaN
|
|
|
|
# Range entirely below all buckets.
|
|
load_with_nhcb 5m
|
|
range_entirely_below_all_buckets_bucket{le="1"} 1+0x10
|
|
range_entirely_below_all_buckets_bucket{le="2"} 3+0x10
|
|
range_entirely_below_all_buckets_bucket{le="+Inf"} 10+0x10
|
|
|
|
eval instant at 50m histogram_fraction(-10, -5, range_entirely_below_all_buckets_bucket)
|
|
expect no_warn
|
|
{} 0.0
|
|
|
|
eval instant at 50m histogram_fraction(-10, -5, range_entirely_below_all_buckets)
|
|
expect no_warn
|
|
{} 0.0
|
|
|
|
# Range entirely above all buckets.
|
|
load_with_nhcb 5m
|
|
range_entirely_above_all_buckets_bucket{le="1"} 1+0x10
|
|
range_entirely_above_all_buckets_bucket{le="2"} 3+0x10
|
|
range_entirely_above_all_buckets_bucket{le="+Inf"} 10+0x10
|
|
|
|
eval instant at 50m histogram_fraction(5, 10, range_entirely_above_all_buckets_bucket)
|
|
expect no_warn
|
|
{} 0.0
|
|
|
|
eval instant at 50m histogram_fraction(5, 10, range_entirely_above_all_buckets)
|
|
expect no_warn
|
|
{} 0.0
|
|
|
|
|
|
# In the classic histogram, we can access the corresponding bucket (if
|
|
# it exists) and divide by the count to get the same result.
|
|
|
|
eval instant at 50m testhistogram3_bucket{le=".2"} / ignoring(le) testhistogram3_count
|
|
expect no_warn
|
|
{start="positive"} 0.6363636363636364
|
|
|
|
eval instant at 50m rate(testhistogram3_bucket{le=".2"}[10m]) / ignoring(le) rate(testhistogram3_count[10m])
|
|
expect no_warn
|
|
{start="positive"} 0.6363636363636364
|
|
|
|
# Test histogram_quantile, native and classic.
|
|
|
|
eval instant at 50m histogram_quantile(0, testhistogram3)
|
|
expect no_warn
|
|
{start="positive"} 0
|
|
{start="negative"} -0.25
|
|
|
|
eval instant at 50m histogram_quantile(0, testhistogram3_bucket)
|
|
expect no_warn
|
|
{start="positive"} 0
|
|
{start="negative"} -0.25
|
|
|
|
eval instant at 50m histogram_quantile(0.25, testhistogram3)
|
|
expect no_warn
|
|
{start="positive"} 0.055
|
|
{start="negative"} -0.225
|
|
|
|
eval instant at 50m histogram_quantile(0.25, testhistogram3_bucket)
|
|
expect no_warn
|
|
{start="positive"} 0.055
|
|
{start="negative"} -0.225
|
|
|
|
eval instant at 50m histogram_quantile(0.5, testhistogram3)
|
|
expect no_warn
|
|
{start="positive"} 0.125
|
|
{start="negative"} -0.2
|
|
|
|
eval instant at 50m histogram_quantile(0.5, testhistogram3_bucket)
|
|
expect no_warn
|
|
{start="positive"} 0.125
|
|
{start="negative"} -0.2
|
|
|
|
eval instant at 50m histogram_quantile(0.75, testhistogram3)
|
|
expect no_warn
|
|
{start="positive"} 0.45
|
|
{start="negative"} -0.15
|
|
|
|
eval instant at 50m histogram_quantile(0.75, testhistogram3_bucket)
|
|
expect no_warn
|
|
{start="positive"} 0.45
|
|
{start="negative"} -0.15
|
|
|
|
eval instant at 50m histogram_quantile(1, testhistogram3)
|
|
expect no_warn
|
|
{start="positive"} 1
|
|
{start="negative"} -0.1
|
|
|
|
eval instant at 50m histogram_quantile(1, testhistogram3_bucket)
|
|
expect no_warn
|
|
{start="positive"} 1
|
|
{start="negative"} -0.1
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram3, "q", 0, 0.25, 0.5, 0.75, 1)
|
|
expect no_warn
|
|
{q="0.0", start="positive"} 0
|
|
{q="0.0", start="negative"} -0.25
|
|
{q="0.25", start="positive"} 0.055
|
|
{q="0.25", start="negative"} -0.225
|
|
{q="0.5", start="positive"} 0.125
|
|
{q="0.5", start="negative"} -0.2
|
|
{q="0.75", start="positive"} 0.45
|
|
{q="0.75", start="negative"} -0.15
|
|
{q="1.0", start="positive"} 1
|
|
{q="1.0", start="negative"} -0.1
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram3_bucket, "q", 0, 0.25, 0.5, 0.75, 1)
|
|
expect no_warn
|
|
{q="0.0", start="positive"} 0
|
|
{q="0.0", start="negative"} -0.25
|
|
{q="0.25", start="positive"} 0.055
|
|
{q="0.25", start="negative"} -0.225
|
|
{q="0.5", start="positive"} 0.125
|
|
{q="0.5", start="negative"} -0.2
|
|
{q="0.75", start="positive"} 0.45
|
|
{q="0.75", start="negative"} -0.15
|
|
{q="1.0", start="positive"} 1
|
|
{q="1.0", start="negative"} -0.1
|
|
|
|
# Break label set uniqueness.
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram3, "start", 0, 0.25, 0.5, 0.75, 1)
|
|
expect fail
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram3_bucket, "start", 0, 0.25, 0.5, 0.75, 1)
|
|
expect fail
|
|
|
|
# Quantile too low.
|
|
|
|
eval instant at 50m histogram_quantile(-0.1, testhistogram)
|
|
expect warn
|
|
{start="positive"} -Inf
|
|
{start="negative"} -Inf
|
|
|
|
eval instant at 50m histogram_quantile(-0.1, testhistogram_bucket)
|
|
expect warn
|
|
{start="positive"} -Inf
|
|
{start="negative"} -Inf
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram, "q", -0.1)
|
|
expect warn
|
|
{q="-0.1", start="positive"} -Inf
|
|
{q="-0.1", start="negative"} -Inf
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram_bucket, "q", -0.1)
|
|
expect warn
|
|
{q="-0.1", start="positive"} -Inf
|
|
{q="-0.1", start="negative"} -Inf
|
|
|
|
# Quantile too high.
|
|
|
|
eval instant at 50m histogram_quantile(1.01, testhistogram)
|
|
expect warn
|
|
{start="positive"} +Inf
|
|
{start="negative"} +Inf
|
|
|
|
eval instant at 50m histogram_quantile(1.01, testhistogram_bucket)
|
|
expect warn
|
|
{start="positive"} +Inf
|
|
{start="negative"} +Inf
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram, "q", 1.01)
|
|
expect warn
|
|
{q="1.01", start="positive"} +Inf
|
|
{q="1.01", start="negative"} +Inf
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram_bucket, "q", 1.01)
|
|
expect warn
|
|
{q="1.01", start="positive"} +Inf
|
|
{q="1.01", start="negative"} +Inf
|
|
|
|
# Quantile invalid.
|
|
|
|
eval instant at 50m histogram_quantile(NaN, testhistogram)
|
|
expect warn
|
|
{start="positive"} NaN
|
|
{start="negative"} NaN
|
|
|
|
eval instant at 50m histogram_quantile(NaN, testhistogram_bucket)
|
|
expect warn
|
|
{start="positive"} NaN
|
|
{start="negative"} NaN
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram, "q", NaN)
|
|
expect warn
|
|
{q="NaN", start="positive"} NaN
|
|
{q="NaN", start="negative"} NaN
|
|
|
|
eval instant at 50m histogram_quantiles(testhistogram_bucket, "q", NaN)
|
|
expect warn
|
|
{q="NaN", start="positive"} NaN
|
|
{q="NaN", start="negative"} NaN
|
|
|
|
eval instant at 50m histogram_quantile(NaN, non_existent)
|
|
expect warn msg: PromQL warning: quantile value should be between 0 and 1, got NaN
|
|
|
|
eval instant at 50m histogram_quantiles(non_existent, "q", NaN)
|
|
expect warn msg: PromQL warning: quantile value should be between 0 and 1, got NaN
|
|
|
|
# Quantile value in lowest bucket.
|
|
|
|
eval instant at 50m histogram_quantile(0, testhistogram)
|
|
expect no_warn
|
|
{start="positive"} 0
|
|
{start="negative"} -0.2
|
|
|
|
eval instant at 50m histogram_quantile(0, testhistogram_bucket)
|
|
expect no_warn
|
|
{start="positive"} 0
|
|
{start="negative"} -0.2
|
|
|
|
# Quantile value in highest bucket.
|
|
|
|
eval instant at 50m histogram_quantile(1, testhistogram)
|
|
expect no_warn
|
|
{start="positive"} 1
|
|
{start="negative"} 0.3
|
|
|
|
eval instant at 50m histogram_quantile(1, testhistogram_bucket)
|
|
expect no_warn
|
|
{start="positive"} 1
|
|
{start="negative"} 0.3
|
|
|
|
# Finally some useful quantiles.
|
|
|
|
eval instant at 50m histogram_quantile(0.2, testhistogram)
|
|
expect no_warn
|
|
{start="positive"} 0.048
|
|
{start="negative"} -0.2
|
|
|
|
eval instant at 50m histogram_quantile(0.2, testhistogram_bucket)
|
|
expect no_warn
|
|
{start="positive"} 0.048
|
|
{start="negative"} -0.2
|
|
|
|
eval instant at 50m histogram_quantile(0.5, testhistogram)
|
|
expect no_warn
|
|
{start="positive"} 0.15
|
|
{start="negative"} -0.15
|
|
|
|
eval instant at 50m histogram_quantile(0.5, testhistogram_bucket)
|
|
expect no_warn
|
|
{start="positive"} 0.15
|
|
{start="negative"} -0.15
|
|
|
|
eval instant at 50m histogram_quantile(0.8, testhistogram)
|
|
expect no_warn
|
|
{start="positive"} 0.72
|
|
{start="negative"} 0.3
|
|
|
|
eval instant at 50m histogram_quantile(0.8, testhistogram_bucket)
|
|
expect no_warn
|
|
{start="positive"} 0.72
|
|
{start="negative"} 0.3
|
|
|
|
# More realistic with rates.
|
|
eval instant at 50m histogram_quantile(0.2, rate(testhistogram[10m]))
|
|
expect no_warn
|
|
{start="positive"} 0.048
|
|
{start="negative"} -0.2
|
|
|
|
eval instant at 50m histogram_quantile(0.2, rate(testhistogram_bucket[10m]))
|
|
expect no_warn
|
|
{start="positive"} 0.048
|
|
{start="negative"} -0.2
|
|
|
|
eval instant at 50m histogram_quantile(0.5, rate(testhistogram[10m]))
|
|
expect no_warn
|
|
{start="positive"} 0.15
|
|
{start="negative"} -0.15
|
|
|
|
eval instant at 50m histogram_quantile(0.5, rate(testhistogram_bucket[10m]))
|
|
expect no_warn
|
|
{start="positive"} 0.15
|
|
{start="negative"} -0.15
|
|
|
|
eval instant at 50m histogram_quantile(0.8, rate(testhistogram[10m]))
|
|
expect no_warn
|
|
{start="positive"} 0.72
|
|
{start="negative"} 0.3
|
|
|
|
eval instant at 50m histogram_quantile(0.8, rate(testhistogram_bucket[10m]))
|
|
expect no_warn
|
|
{start="positive"} 0.72
|
|
{start="negative"} 0.3
|
|
|
|
# Want results exactly in the middle of the bucket.
|
|
|
|
eval instant at 7m histogram_quantile(1./6., testhistogram2)
|
|
expect no_warn
|
|
{} 1
|
|
|
|
eval instant at 7m histogram_quantile(1./6., testhistogram2_bucket)
|
|
expect no_warn
|
|
{} 1
|
|
|
|
eval instant at 7m histogram_quantile(0.5, testhistogram2)
|
|
expect no_warn
|
|
{} 3
|
|
|
|
eval instant at 7m histogram_quantile(0.5, testhistogram2_bucket)
|
|
expect no_warn
|
|
{} 3
|
|
|
|
eval instant at 7m histogram_quantile(5./6., testhistogram2)
|
|
expect no_warn
|
|
{} 5
|
|
|
|
eval instant at 7m histogram_quantile(5./6., testhistogram2_bucket)
|
|
expect no_warn
|
|
{} 5
|
|
|
|
eval instant at 47m histogram_quantile(1./6., rate(testhistogram2[15m]))
|
|
expect no_warn
|
|
{} 1
|
|
|
|
eval instant at 47m histogram_quantile(1./6., rate(testhistogram2_bucket[15m]))
|
|
expect no_warn
|
|
{} 1
|
|
|
|
eval instant at 47m histogram_quantile(0.5, rate(testhistogram2[15m]))
|
|
expect no_warn
|
|
{} 3
|
|
|
|
eval instant at 47m histogram_quantile(0.5, rate(testhistogram2_bucket[15m]))
|
|
expect no_warn
|
|
{} 3
|
|
|
|
eval instant at 47m histogram_quantile(5./6., rate(testhistogram2[15m]))
|
|
expect no_warn
|
|
{} 5
|
|
|
|
eval instant at 47m histogram_quantile(5./6., rate(testhistogram2_bucket[15m]))
|
|
expect no_warn
|
|
{} 5
|
|
|
|
# Aggregated histogram: Everything in one. Note how native histograms
|
|
# don't require aggregation by le.
|
|
|
|
eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds[10m])))
|
|
expect no_warn
|
|
{} 0.075
|
|
|
|
eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[10m])) by (le))
|
|
expect no_warn
|
|
{} 0.075
|
|
|
|
eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds[10m])))
|
|
expect no_warn
|
|
{} 0.1277777777777778
|
|
|
|
eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[10m])) by (le))
|
|
expect no_warn
|
|
{} 0.1277777777777778
|
|
|
|
# Aggregated histogram: Everything in one. Now with avg, which does not change anything.
|
|
|
|
eval instant at 50m histogram_quantile(0.3, avg(rate(request_duration_seconds[10m])))
|
|
expect no_warn
|
|
{} 0.075
|
|
|
|
eval instant at 50m histogram_quantile(0.3, avg(rate(request_duration_seconds_bucket[10m])) by (le))
|
|
expect no_warn
|
|
{} 0.075
|
|
|
|
eval instant at 50m histogram_quantile(0.5, avg(rate(request_duration_seconds[10m])))
|
|
expect no_warn
|
|
{} 0.12777777777777778
|
|
|
|
eval instant at 50m histogram_quantile(0.5, avg(rate(request_duration_seconds_bucket[10m])) by (le))
|
|
expect no_warn
|
|
{} 0.12777777777777778
|
|
|
|
# Aggregated histogram: By instance.
|
|
|
|
eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds[10m])) by (instance))
|
|
expect no_warn
|
|
{instance="ins1"} 0.075
|
|
{instance="ins2"} 0.075
|
|
|
|
eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[10m])) by (le, instance))
|
|
expect no_warn
|
|
{instance="ins1"} 0.075
|
|
{instance="ins2"} 0.075
|
|
|
|
eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds[10m])) by (instance))
|
|
expect no_warn
|
|
{instance="ins1"} 0.1333333333
|
|
{instance="ins2"} 0.125
|
|
|
|
eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[10m])) by (le, instance))
|
|
expect no_warn
|
|
{instance="ins1"} 0.1333333333
|
|
{instance="ins2"} 0.125
|
|
|
|
# Aggregated histogram: By job.
|
|
eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds[10m])) by (job))
|
|
expect no_warn
|
|
{job="job1"} 0.1
|
|
{job="job2"} 0.0642857142857143
|
|
|
|
eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds_bucket[10m])) by (le, job))
|
|
expect no_warn
|
|
{job="job1"} 0.1
|
|
{job="job2"} 0.0642857142857143
|
|
|
|
eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds[10m])) by (job))
|
|
expect no_warn
|
|
{job="job1"} 0.14
|
|
{job="job2"} 0.1125
|
|
|
|
eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[10m])) by (le, job))
|
|
expect no_warn
|
|
{job="job1"} 0.14
|
|
{job="job2"} 0.1125
|
|
|
|
# Aggregated histogram: By job and instance.
|
|
eval instant at 50m histogram_quantile(0.3, sum(rate(request_duration_seconds[10m])) by (job, instance))
|
|
expect no_warn
|
|
{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(0.3, sum(rate(request_duration_seconds_bucket[10m])) by (le, job, instance))
|
|
expect no_warn
|
|
{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[10m])) by (job, instance))
|
|
expect no_warn
|
|
{instance="ins1", job="job1"} 0.15
|
|
{instance="ins2", job="job1"} 0.1333333333333333
|
|
{instance="ins1", job="job2"} 0.1
|
|
{instance="ins2", job="job2"} 0.1166666666666667
|
|
|
|
eval instant at 50m histogram_quantile(0.5, sum(rate(request_duration_seconds_bucket[10m])) by (le, job, instance))
|
|
expect no_warn
|
|
{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[10m]))
|
|
expect no_warn
|
|
{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(0.3, rate(request_duration_seconds_bucket[10m]))
|
|
expect no_warn
|
|
{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[10m]))
|
|
expect no_warn
|
|
{instance="ins1", job="job1"} 0.15
|
|
{instance="ins2", job="job1"} 0.13333333333333333
|
|
{instance="ins1", job="job2"} 0.1
|
|
{instance="ins2", job="job2"} 0.11666666666666667
|
|
|
|
eval instant at 50m histogram_quantile(0.5, rate(request_duration_seconds_bucket[10m]))
|
|
expect no_warn
|
|
{instance="ins1", job="job1"} 0.15
|
|
{instance="ins2", job="job1"} 0.13333333333333333
|
|
{instance="ins1", job="job2"} 0.1
|
|
{instance="ins2", job="job2"} 0.11666666666666667
|
|
|
|
# All NHCBs summed into one.
|
|
eval instant at 50m sum(request_duration_seconds)
|
|
expect no_warn
|
|
{} {{schema:-53 count:250 custom_values:[0.1 0.2] buckets:[100 90 60]}}
|
|
|
|
eval instant at 50m sum(request_duration_seconds{job="job1",instance="ins1"} + ignoring(job,instance) request_duration_seconds{job="job1",instance="ins2"} + ignoring(job,instance) request_duration_seconds{job="job2",instance="ins1"} + ignoring(job,instance) request_duration_seconds{job="job2",instance="ins2"})
|
|
expect no_warn
|
|
{} {{schema:-53 count:250 custom_values:[0.1 0.2] buckets:[100 90 60]}}
|
|
|
|
eval instant at 50m avg(request_duration_seconds)
|
|
expect no_warn
|
|
{} {{schema:-53 count:62.5 custom_values:[0.1 0.2] buckets:[25 22.5 15]}}
|
|
|
|
# To verify the result above, calculate from classic histogram as well.
|
|
eval instant at 50m avg (request_duration_seconds_bucket{le="0.1"})
|
|
expect no_warn
|
|
{} 25
|
|
|
|
eval instant at 50m avg (request_duration_seconds_bucket{le="0.2"}) - avg (request_duration_seconds_bucket{le="0.1"})
|
|
expect no_warn
|
|
{} 22.5
|
|
|
|
eval instant at 50m avg (request_duration_seconds_bucket{le="+Inf"}) - avg (request_duration_seconds_bucket{le="0.2"})
|
|
expect no_warn
|
|
{} 15
|
|
|
|
eval instant at 50m count(request_duration_seconds)
|
|
expect no_warn
|
|
{} 4
|
|
|
|
# A histogram with nonmonotonic bucket counts. This may happen when recording
|
|
# rule evaluation or federation races scrape ingestion, causing some buckets
|
|
# counts to be derived from fewer samples.
|
|
|
|
load 5m
|
|
nonmonotonic_bucket{le="0.1"} 0+2x10
|
|
nonmonotonic_bucket{le="1"} 0+1x10
|
|
nonmonotonic_bucket{le="10"} 0+5x10
|
|
nonmonotonic_bucket{le="100"} 0+4x10
|
|
nonmonotonic_bucket{le="1000"} 0+9x10
|
|
nonmonotonic_bucket{le="+Inf"} 0+8x10
|
|
|
|
# Nonmonotonic buckets, triggering an info annotation.
|
|
eval instant at 50m histogram_quantile(0.01, nonmonotonic_bucket)
|
|
expect info
|
|
{} 0.0045
|
|
|
|
eval instant at 50m histogram_quantile(0.5, nonmonotonic_bucket)
|
|
expect info
|
|
{} 8.5
|
|
|
|
eval instant at 50m histogram_quantile(0.99, nonmonotonic_bucket)
|
|
expect info
|
|
{} 979.75
|
|
|
|
eval instant at 50m histogram_quantiles(nonmonotonic_bucket, "q", 0.01, 0.5, 0.99)
|
|
expect info
|
|
{q="0.01"} 0.0045
|
|
{q="0.5"} 8.5
|
|
{q="0.99"} 979.75
|
|
|
|
# Buckets with different representations of the same upper bound.
|
|
eval instant at 50m histogram_quantile(0.5, rate(mixed_bucket[10m]))
|
|
{instance="ins1", job="job1"} 0.15
|
|
{instance="ins2", job="job1"} NaN
|
|
|
|
eval instant at 50m histogram_quantile(0.5, rate(mixed[10m]))
|
|
{instance="ins1", job="job1"} 0.2
|
|
{instance="ins2", job="job1"} NaN
|
|
|
|
eval instant at 50m histogram_quantile(0.75, rate(mixed_bucket[10m]))
|
|
{instance="ins1", job="job1"} 0.2
|
|
{instance="ins2", job="job1"} NaN
|
|
|
|
eval instant at 50m histogram_quantile(1, rate(mixed_bucket[10m]))
|
|
{instance="ins1", job="job1"} 0.2
|
|
{instance="ins2", job="job1"} NaN
|
|
|
|
load_with_nhcb 5m
|
|
empty_bucket{le="0.1", job="job1", instance="ins1"} 0x10
|
|
empty_bucket{le="0.2", job="job1", instance="ins1"} 0x10
|
|
empty_bucket{le="+Inf", job="job1", instance="ins1"} 0x10
|
|
|
|
eval instant at 50m histogram_quantile(0.2, rate(empty_bucket[10m]))
|
|
{instance="ins1", job="job1"} NaN
|
|
|
|
# Load a duplicate histogram with a different name to test failure scenario on multiple histograms with the same label set.
|
|
# https://github.com/prometheus/prometheus/issues/9910
|
|
load_with_nhcb 5m
|
|
request_duration_seconds2_bucket{job="job1", instance="ins1", le="0.1"} 0+1x10
|
|
request_duration_seconds2_bucket{job="job1", instance="ins1", le="0.2"} 0+3x10
|
|
request_duration_seconds2_bucket{job="job1", instance="ins1", le="+Inf"} 0+4x10
|
|
|
|
eval instant at 50m histogram_quantile(0.99, {__name__=~"request_duration_seconds\\d*_bucket"})
|
|
expect fail
|
|
|
|
eval instant at 50m histogram_quantiles({__name__=~"request_duration_seconds\\d*_bucket"}, "q", 0.99)
|
|
expect fail
|
|
|
|
eval instant at 50m histogram_quantile(0.99, {__name__=~"request_duration_seconds\\d*"})
|
|
expect fail
|
|
|
|
eval instant at 50m histogram_quantiles({__name__=~"request_duration_seconds\\d*"}, "q", 0.99)
|
|
expect fail
|
|
|
|
# Histogram with constant buckets.
|
|
load_with_nhcb 1m
|
|
const_histogram_bucket{le="0.0"} 1 1 1 1 1
|
|
const_histogram_bucket{le="1.0"} 1 1 1 1 1
|
|
const_histogram_bucket{le="2.0"} 1 1 1 1 1
|
|
const_histogram_bucket{le="+Inf"} 1 1 1 1 1
|
|
|
|
# There is no change to the bucket count over time, thus rate is 0 in each bucket.
|
|
eval instant at 5m rate(const_histogram_bucket[5m])
|
|
{le="0.0"} 0
|
|
{le="1.0"} 0
|
|
{le="2.0"} 0
|
|
{le="+Inf"} 0
|
|
|
|
# Native histograms do not represent empty buckets, so here the zeros are implicit.
|
|
eval instant at 5m rate(const_histogram[5m])
|
|
{} {{schema:-53 sum:0 count:0 custom_values:[0.0 1.0 2.0]}}
|
|
|
|
# Zero buckets mean no observations, so there is no value that observations fall below,
|
|
# which means that any quantile is a NaN.
|
|
eval instant at 5m histogram_quantile(1.0, sum by (le) (rate(const_histogram_bucket[5m])))
|
|
{} NaN
|
|
|
|
eval instant at 5m histogram_quantile(1.0, sum(rate(const_histogram[5m])))
|
|
{} NaN
|
|
|
|
load_with_nhcb 1m
|
|
histogram_over_time_bucket{le="0"} 0 1 3 9
|
|
histogram_over_time_bucket{le="1"} 2 3 3 9
|
|
histogram_over_time_bucket{le="2"} 3 8 5 10
|
|
histogram_over_time_bucket{le="4"} 3 10 6 18
|
|
|
|
# Test custom buckets with sum_over_time, avg_over_time.
|
|
eval instant at 3m sum_over_time(histogram_over_time[4m:1m])
|
|
{} {{schema:-53 count:37 custom_values:[0 1 2 4] buckets:[13 4 9 11]}}
|
|
|
|
eval instant at 3m avg_over_time(histogram_over_time[4m:1m])
|
|
{} {{schema:-53 count:9.25 custom_values:[0 1 2 4] buckets:[3.25 1 2.25 2.75]}}
|
|
|
|
# Test custom buckets with counter reset
|
|
load_with_nhcb 5m
|
|
histogram_with_reset_bucket{le="1"} 1 3 9
|
|
histogram_with_reset_bucket{le="2"} 3 3 9
|
|
histogram_with_reset_bucket{le="4"} 8 5 12
|
|
histogram_with_reset_bucket{le="8"} 10 6 18
|
|
histogram_with_reset_sum{} 36 16 61
|
|
|
|
eval instant at 10m increase(histogram_with_reset[15m])
|
|
{} {{schema:-53 count:27 sum:91.5 custom_values:[1 2 4 8] counter_reset_hint:gauge buckets:[13.5 0 4.5 9]}}
|
|
|
|
eval instant at 10m resets(histogram_with_reset[15m])
|
|
{} 1
|
|
|
|
eval instant at 10m histogram_count(increase(histogram_with_reset[15m]))
|
|
{} 27
|
|
|
|
eval instant at 10m histogram_sum(increase(histogram_with_reset[15m]))
|
|
{} 91.5
|
|
|
|
clear
|
|
|
|
# Test histogram_quantile(s) and histogram_fraction with conflicting classic and native histograms.
|
|
load 1m
|
|
series{host="a"} {{schema:0 sum:5 count:4 buckets:[9 2 1]}}
|
|
series{host="a", le="0.1"} 2
|
|
series{host="a", le="1"} 3
|
|
series{host="a", le="10"} 5
|
|
series{host="a", le="100"} 6
|
|
series{host="a", le="1000"} 8
|
|
series{host="a", le="+Inf"} 9
|
|
|
|
eval instant at 0 histogram_quantile(0.8, series)
|
|
expect no_info
|
|
expect warn msg: PromQL warning: vector contains a mix of classic and native histograms for metric name "series"
|
|
# Should return no results.
|
|
|
|
eval instant at 0 histogram_quantiles(series, "q", 0.1, 0.2)
|
|
expect no_info
|
|
expect warn msg: PromQL warning: vector contains a mix of classic and native histograms for metric name "series"
|
|
# Should return no results.
|
|
|
|
eval instant at 0 histogram_fraction(-Inf, 1, series)
|
|
expect no_info
|
|
expect warn msg: PromQL warning: vector contains a mix of classic and native histograms for metric name "series"
|
|
# Should return no results.
|