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c46074f4dd
The basic idea here is that the previous code was always doing incremental calculation of the mean value, which is more costly and can be less precise. It protects against overflows, but in most cases, an overflow doesn't happen anyway. The other idea applied here is to expand on #14074, where Kahan summation was applied to sum(). With this commit, the average is calculated in a conventional way (adding everything up and divide in the end) as long as the sum isn't overflowing float64. This is combined with Kahan summation so that the avg aggregation, in most cases, is really equivalent to the sum aggregation with a following division (which is the user's expectation as avg is supposed to be syntactic sugar for sum with a following divison). If the sum hits ±Inf, the calculation reverts to incremental calculation of the mean value. Kahan summation is also applied here, although it cannot fully compensate for the numerical errors introduced by the incremental mean calculation. (The tests added in this commit would fail if incremental mean calculation was always used.) Signed-off-by: beorn7 <beorn@grafana.com>
575 lines
20 KiB
Plaintext
575 lines
20 KiB
Plaintext
load 5m
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http_requests{job="api-server", instance="0", group="production"} 0+10x10
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http_requests{job="api-server", instance="1", group="production"} 0+20x10
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http_requests{job="api-server", instance="0", group="canary"} 0+30x10
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http_requests{job="api-server", instance="1", group="canary"} 0+40x10
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http_requests{job="app-server", instance="0", group="production"} 0+50x10
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http_requests{job="app-server", instance="1", group="production"} 0+60x10
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http_requests{job="app-server", instance="0", group="canary"} 0+70x10
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http_requests{job="app-server", instance="1", group="canary"} 0+80x10
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load 5m
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foo{job="api-server", instance="0", region="europe"} 0+90x10
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foo{job="api-server"} 0+100x10
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# Simple sum.
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eval instant at 50m SUM BY (group) (http_requests{job="api-server"})
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{group="canary"} 700
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{group="production"} 300
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eval instant at 50m SUM BY (group) (((http_requests{job="api-server"})))
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{group="canary"} 700
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{group="production"} 300
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# Test alternative "by"-clause order.
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eval instant at 50m sum by (group) (http_requests{job="api-server"})
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{group="canary"} 700
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{group="production"} 300
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# Simple average.
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eval instant at 50m avg by (group) (http_requests{job="api-server"})
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{group="canary"} 350
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{group="production"} 150
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# Simple count.
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eval instant at 50m count by (group) (http_requests{job="api-server"})
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{group="canary"} 2
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{group="production"} 2
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# Simple without.
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eval instant at 50m sum without (instance) (http_requests{job="api-server"})
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{group="canary",job="api-server"} 700
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{group="production",job="api-server"} 300
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# Empty by.
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eval instant at 50m sum by () (http_requests{job="api-server"})
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{} 1000
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# No by/without.
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eval instant at 50m sum(http_requests{job="api-server"})
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{} 1000
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# Empty without.
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eval instant at 50m sum without () (http_requests{job="api-server",group="production"})
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{group="production",job="api-server",instance="0"} 100
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{group="production",job="api-server",instance="1"} 200
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# Without with mismatched and missing labels. Do not do this.
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eval instant at 50m sum without (instance) (http_requests{job="api-server"} or foo)
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{group="canary",job="api-server"} 700
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{group="production",job="api-server"} 300
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{region="europe",job="api-server"} 900
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{job="api-server"} 1000
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# Lower-cased aggregation operators should work too.
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eval instant at 50m sum(http_requests) by (job) + min(http_requests) by (job) + max(http_requests) by (job) + avg(http_requests) by (job)
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{job="app-server"} 4550
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{job="api-server"} 1750
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# Test alternative "by"-clause order.
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eval instant at 50m sum by (group) (http_requests{job="api-server"})
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{group="canary"} 700
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{group="production"} 300
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# Test both alternative "by"-clause orders in one expression.
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# Public health warning: stick to one form within an expression (or even
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# in an organization), or risk serious user confusion.
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eval instant at 50m sum(sum by (group) (http_requests{job="api-server"})) by (job)
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{} 1000
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eval instant at 50m SUM(http_requests)
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{} 3600
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eval instant at 50m SUM(http_requests{instance="0"}) BY(job)
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{job="api-server"} 400
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{job="app-server"} 1200
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eval instant at 50m SUM(http_requests) BY (job)
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{job="api-server"} 1000
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{job="app-server"} 2600
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# Non-existent labels mentioned in BY-clauses shouldn't propagate to output.
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eval instant at 50m SUM(http_requests) BY (job, nonexistent)
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{job="api-server"} 1000
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{job="app-server"} 2600
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eval instant at 50m COUNT(http_requests) BY (job)
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{job="api-server"} 4
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{job="app-server"} 4
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eval instant at 50m SUM(http_requests) BY (job, group)
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{group="canary", job="api-server"} 700
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{group="canary", job="app-server"} 1500
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{group="production", job="api-server"} 300
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{group="production", job="app-server"} 1100
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eval instant at 50m AVG(http_requests) BY (job)
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{job="api-server"} 250
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{job="app-server"} 650
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eval instant at 50m MIN(http_requests) BY (job)
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{job="api-server"} 100
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{job="app-server"} 500
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eval instant at 50m MAX(http_requests) BY (job)
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{job="api-server"} 400
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{job="app-server"} 800
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eval instant at 50m abs(-1 * http_requests{group="production",job="api-server"})
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{group="production", instance="0", job="api-server"} 100
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{group="production", instance="1", job="api-server"} 200
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eval instant at 50m floor(0.004 * http_requests{group="production",job="api-server"})
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{group="production", instance="0", job="api-server"} 0
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{group="production", instance="1", job="api-server"} 0
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eval instant at 50m ceil(0.004 * http_requests{group="production",job="api-server"})
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{group="production", instance="0", job="api-server"} 1
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{group="production", instance="1", job="api-server"} 1
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eval instant at 50m round(0.004 * http_requests{group="production",job="api-server"})
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{group="production", instance="0", job="api-server"} 0
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{group="production", instance="1", job="api-server"} 1
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# Round should correctly handle negative numbers.
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eval instant at 50m round(-1 * (0.004 * http_requests{group="production",job="api-server"}))
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{group="production", instance="0", job="api-server"} 0
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{group="production", instance="1", job="api-server"} -1
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# Round should round half up.
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eval instant at 50m round(0.005 * http_requests{group="production",job="api-server"})
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{group="production", instance="0", job="api-server"} 1
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{group="production", instance="1", job="api-server"} 1
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eval instant at 50m round(-1 * (0.005 * http_requests{group="production",job="api-server"}))
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{group="production", instance="0", job="api-server"} 0
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{group="production", instance="1", job="api-server"} -1
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eval instant at 50m round(1 + 0.005 * http_requests{group="production",job="api-server"})
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{group="production", instance="0", job="api-server"} 2
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{group="production", instance="1", job="api-server"} 2
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eval instant at 50m round(-1 * (1 + 0.005 * http_requests{group="production",job="api-server"}))
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{group="production", instance="0", job="api-server"} -1
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{group="production", instance="1", job="api-server"} -2
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# Round should accept the number to round nearest to.
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eval instant at 50m round(0.0005 * http_requests{group="production",job="api-server"}, 0.1)
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{group="production", instance="0", job="api-server"} 0.1
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{group="production", instance="1", job="api-server"} 0.1
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eval instant at 50m round(2.1 + 0.0005 * http_requests{group="production",job="api-server"}, 0.1)
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{group="production", instance="0", job="api-server"} 2.2
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{group="production", instance="1", job="api-server"} 2.2
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eval instant at 50m round(5.2 + 0.0005 * http_requests{group="production",job="api-server"}, 0.1)
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{group="production", instance="0", job="api-server"} 5.3
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{group="production", instance="1", job="api-server"} 5.3
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# Round should work correctly with negative numbers and multiple decimal places.
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eval instant at 50m round(-1 * (5.2 + 0.0005 * http_requests{group="production",job="api-server"}), 0.1)
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{group="production", instance="0", job="api-server"} -5.2
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{group="production", instance="1", job="api-server"} -5.3
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# Round should work correctly with big toNearests.
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eval instant at 50m round(0.025 * http_requests{group="production",job="api-server"}, 5)
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{group="production", instance="0", job="api-server"} 5
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{group="production", instance="1", job="api-server"} 5
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eval instant at 50m round(0.045 * http_requests{group="production",job="api-server"}, 5)
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{group="production", instance="0", job="api-server"} 5
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{group="production", instance="1", job="api-server"} 10
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# Standard deviation and variance.
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eval instant at 50m stddev(http_requests)
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{} 229.12878474779
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eval instant at 50m stddev by (instance)(http_requests)
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{instance="0"} 223.60679774998
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{instance="1"} 223.60679774998
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eval instant at 50m stdvar(http_requests)
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{} 52500
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eval instant at 50m stdvar by (instance)(http_requests)
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{instance="0"} 50000
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{instance="1"} 50000
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# Float precision test for standard deviation and variance
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clear
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load 5m
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http_requests{job="api-server", instance="0", group="production"} 0+1.33x10
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http_requests{job="api-server", instance="1", group="production"} 0+1.33x10
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http_requests{job="api-server", instance="0", group="canary"} 0+1.33x10
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eval instant at 50m stddev(http_requests)
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{} 0.0
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eval instant at 50m stdvar(http_requests)
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{} 0.0
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# Regression test for missing separator byte in labelsToGroupingKey.
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clear
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load 5m
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label_grouping_test{a="aa", b="bb"} 0+10x10
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label_grouping_test{a="a", b="abb"} 0+20x10
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eval instant at 50m sum(label_grouping_test) by (a, b)
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{a="a", b="abb"} 200
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{a="aa", b="bb"} 100
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# Tests for min/max.
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clear
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load 5m
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http_requests{job="api-server", instance="0", group="production"} 1
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http_requests{job="api-server", instance="1", group="production"} 2
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http_requests{job="api-server", instance="0", group="canary"} NaN
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http_requests{job="api-server", instance="1", group="canary"} 3
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http_requests{job="api-server", instance="2", group="canary"} 4
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eval instant at 0m max(http_requests)
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{} 4
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eval instant at 0m min(http_requests)
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{} 1
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eval instant at 0m max by (group) (http_requests)
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{group="production"} 2
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{group="canary"} 4
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eval instant at 0m min by (group) (http_requests)
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{group="production"} 1
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{group="canary"} 3
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clear
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# Tests for topk/bottomk.
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load 5m
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http_requests{job="api-server", instance="0", group="production"} 0+10x10
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http_requests{job="api-server", instance="1", group="production"} 0+20x10
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http_requests{job="api-server", instance="2", group="production"} NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
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http_requests{job="api-server", instance="0", group="canary"} 0+30x10
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http_requests{job="api-server", instance="1", group="canary"} 0+40x10
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http_requests{job="app-server", instance="0", group="production"} 0+50x10
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http_requests{job="app-server", instance="1", group="production"} 0+60x10
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http_requests{job="app-server", instance="0", group="canary"} 0+70x10
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http_requests{job="app-server", instance="1", group="canary"} 0+80x10
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foo 3+0x10
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eval_ordered instant at 50m topk(3, http_requests)
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http_requests{group="canary", instance="1", job="app-server"} 800
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http_requests{group="canary", instance="0", job="app-server"} 700
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http_requests{group="production", instance="1", job="app-server"} 600
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eval_ordered instant at 50m topk((3), (http_requests))
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http_requests{group="canary", instance="1", job="app-server"} 800
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http_requests{group="canary", instance="0", job="app-server"} 700
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http_requests{group="production", instance="1", job="app-server"} 600
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eval_ordered instant at 50m topk(5, http_requests{group="canary",job="app-server"})
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http_requests{group="canary", instance="1", job="app-server"} 800
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http_requests{group="canary", instance="0", job="app-server"} 700
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eval_ordered instant at 50m bottomk(3, http_requests)
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http_requests{group="production", instance="0", job="api-server"} 100
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http_requests{group="production", instance="1", job="api-server"} 200
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http_requests{group="canary", instance="0", job="api-server"} 300
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eval_ordered instant at 50m bottomk(5, http_requests{group="canary",job="app-server"})
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http_requests{group="canary", instance="0", job="app-server"} 700
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http_requests{group="canary", instance="1", job="app-server"} 800
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eval instant at 50m topk by (group) (1, http_requests)
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http_requests{group="production", instance="1", job="app-server"} 600
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http_requests{group="canary", instance="1", job="app-server"} 800
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eval instant at 50m bottomk by (group) (2, http_requests)
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http_requests{group="canary", instance="0", job="api-server"} 300
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http_requests{group="canary", instance="1", job="api-server"} 400
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http_requests{group="production", instance="0", job="api-server"} 100
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http_requests{group="production", instance="1", job="api-server"} 200
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eval_ordered instant at 50m bottomk by (group) (2, http_requests{group="production"})
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http_requests{group="production", instance="0", job="api-server"} 100
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http_requests{group="production", instance="1", job="api-server"} 200
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# Test NaN is sorted away from the top/bottom.
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eval_ordered instant at 50m topk(3, http_requests{job="api-server",group="production"})
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http_requests{job="api-server", instance="1", group="production"} 200
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http_requests{job="api-server", instance="0", group="production"} 100
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http_requests{job="api-server", instance="2", group="production"} NaN
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eval_ordered instant at 50m bottomk(3, http_requests{job="api-server",group="production"})
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http_requests{job="api-server", instance="0", group="production"} 100
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http_requests{job="api-server", instance="1", group="production"} 200
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http_requests{job="api-server", instance="2", group="production"} NaN
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# Test topk and bottomk allocate min(k, input_vector) for results vector
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eval_ordered instant at 50m bottomk(9999999999, http_requests{job="app-server",group="canary"})
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http_requests{group="canary", instance="0", job="app-server"} 700
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http_requests{group="canary", instance="1", job="app-server"} 800
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eval_ordered instant at 50m topk(9999999999, http_requests{job="api-server",group="production"})
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http_requests{job="api-server", instance="1", group="production"} 200
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http_requests{job="api-server", instance="0", group="production"} 100
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http_requests{job="api-server", instance="2", group="production"} NaN
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# Bug #5276.
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eval_ordered instant at 50m topk(scalar(foo), http_requests)
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http_requests{group="canary", instance="1", job="app-server"} 800
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http_requests{group="canary", instance="0", job="app-server"} 700
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http_requests{group="production", instance="1", job="app-server"} 600
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clear
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# Tests for count_values.
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load 5m
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version{job="api-server", instance="0", group="production"} 6
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version{job="api-server", instance="1", group="production"} 6
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version{job="api-server", instance="2", group="production"} 6
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version{job="api-server", instance="0", group="canary"} 8
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version{job="api-server", instance="1", group="canary"} 8
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version{job="app-server", instance="0", group="production"} 6
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version{job="app-server", instance="1", group="production"} 6
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version{job="app-server", instance="0", group="canary"} 7
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version{job="app-server", instance="1", group="canary"} 7
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eval instant at 5m count_values("version", version)
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{version="6"} 5
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{version="7"} 2
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{version="8"} 2
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eval instant at 5m count_values(((("version"))), version)
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{version="6"} 5
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{version="7"} 2
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{version="8"} 2
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eval instant at 5m count_values without (instance)("version", version)
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{job="api-server", group="production", version="6"} 3
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{job="api-server", group="canary", version="8"} 2
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{job="app-server", group="production", version="6"} 2
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{job="app-server", group="canary", version="7"} 2
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# Overwrite label with output. Don't do this.
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eval instant at 5m count_values without (instance)("job", version)
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{job="6", group="production"} 5
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{job="8", group="canary"} 2
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{job="7", group="canary"} 2
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# Overwrite label with output. Don't do this.
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eval instant at 5m count_values by (job, group)("job", version)
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{job="6", group="production"} 5
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{job="8", group="canary"} 2
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{job="7", group="canary"} 2
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# Tests for quantile.
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clear
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load 10s
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data{test="two samples",point="a"} 0
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data{test="two samples",point="b"} 1
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data{test="three samples",point="a"} 0
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data{test="three samples",point="b"} 1
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data{test="three samples",point="c"} 2
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data{test="uneven samples",point="a"} 0
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data{test="uneven samples",point="b"} 1
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data{test="uneven samples",point="c"} 4
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foo .8
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eval instant at 1m quantile without(point)(0.8, data)
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{test="two samples"} 0.8
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{test="three samples"} 1.6
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{test="uneven samples"} 2.8
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# Bug #5276.
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eval instant at 1m quantile without(point)(scalar(foo), data)
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{test="two samples"} 0.8
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{test="three samples"} 1.6
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{test="uneven samples"} 2.8
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eval instant at 1m quantile without(point)((scalar(foo)), data)
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{test="two samples"} 0.8
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{test="three samples"} 1.6
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{test="uneven samples"} 2.8
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eval_warn instant at 1m quantile without(point)(NaN, data)
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{test="two samples"} NaN
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{test="three samples"} NaN
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{test="uneven samples"} NaN
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# Tests for group.
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clear
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load 10s
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data{test="two samples",point="a"} 0
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data{test="two samples",point="b"} 1
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data{test="three samples",point="a"} 0
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data{test="three samples",point="b"} 1
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data{test="three samples",point="c"} 2
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data{test="uneven samples",point="a"} 0
|
|
data{test="uneven samples",point="b"} 1
|
|
data{test="uneven samples",point="c"} 4
|
|
foo .8
|
|
|
|
eval instant at 1m group without(point)(data)
|
|
{test="two samples"} 1
|
|
{test="three samples"} 1
|
|
{test="uneven samples"} 1
|
|
|
|
eval instant at 1m group(foo)
|
|
{} 1
|
|
|
|
# Tests for avg.
|
|
clear
|
|
|
|
load 10s
|
|
data{test="ten",point="a"} 8
|
|
data{test="ten",point="b"} 10
|
|
data{test="ten",point="c"} 12
|
|
data{test="inf",point="a"} 0
|
|
data{test="inf",point="b"} Inf
|
|
data{test="inf",point="d"} Inf
|
|
data{test="inf",point="c"} 0
|
|
data{test="-inf",point="a"} -Inf
|
|
data{test="-inf",point="b"} -Inf
|
|
data{test="-inf",point="c"} 0
|
|
data{test="inf2",point="a"} Inf
|
|
data{test="inf2",point="b"} 0
|
|
data{test="inf2",point="c"} Inf
|
|
data{test="-inf2",point="a"} -Inf
|
|
data{test="-inf2",point="b"} 0
|
|
data{test="-inf2",point="c"} -Inf
|
|
data{test="inf3",point="b"} Inf
|
|
data{test="inf3",point="d"} Inf
|
|
data{test="inf3",point="c"} Inf
|
|
data{test="inf3",point="d"} -Inf
|
|
data{test="-inf3",point="b"} -Inf
|
|
data{test="-inf3",point="d"} -Inf
|
|
data{test="-inf3",point="c"} -Inf
|
|
data{test="-inf3",point="c"} Inf
|
|
data{test="nan",point="a"} -Inf
|
|
data{test="nan",point="b"} 0
|
|
data{test="nan",point="c"} Inf
|
|
data{test="big",point="a"} 9.988465674311579e+307
|
|
data{test="big",point="b"} 9.988465674311579e+307
|
|
data{test="big",point="c"} 9.988465674311579e+307
|
|
data{test="big",point="d"} 9.988465674311579e+307
|
|
data{test="-big",point="a"} -9.988465674311579e+307
|
|
data{test="-big",point="b"} -9.988465674311579e+307
|
|
data{test="-big",point="c"} -9.988465674311579e+307
|
|
data{test="-big",point="d"} -9.988465674311579e+307
|
|
data{test="bigzero",point="a"} -9.988465674311579e+307
|
|
data{test="bigzero",point="b"} -9.988465674311579e+307
|
|
data{test="bigzero",point="c"} 9.988465674311579e+307
|
|
data{test="bigzero",point="d"} 9.988465674311579e+307
|
|
|
|
eval instant at 1m avg(data{test="ten"})
|
|
{} 10
|
|
|
|
eval instant at 1m avg(data{test="inf"})
|
|
{} Inf
|
|
|
|
eval instant at 1m avg(data{test="inf2"})
|
|
{} Inf
|
|
|
|
eval instant at 1m avg(data{test="inf3"})
|
|
{} NaN
|
|
|
|
eval instant at 1m avg(data{test="-inf"})
|
|
{} -Inf
|
|
|
|
eval instant at 1m avg(data{test="-inf2"})
|
|
{} -Inf
|
|
|
|
eval instant at 1m avg(data{test="-inf3"})
|
|
{} NaN
|
|
|
|
eval instant at 1m avg(data{test="nan"})
|
|
{} NaN
|
|
|
|
eval instant at 1m avg(data{test="big"})
|
|
{} 9.988465674311579e+307
|
|
|
|
eval instant at 1m avg(data{test="-big"})
|
|
{} -9.988465674311579e+307
|
|
|
|
eval instant at 1m avg(data{test="bigzero"})
|
|
{} 0
|
|
|
|
# Test summing and averaging extreme values.
|
|
clear
|
|
|
|
load 10s
|
|
data{test="ten",point="a"} 2
|
|
data{test="ten",point="b"} 8
|
|
data{test="ten",point="c"} 1e+100
|
|
data{test="ten",point="d"} -1e100
|
|
data{test="pos_inf",group="1",point="a"} Inf
|
|
data{test="pos_inf",group="1",point="b"} 2
|
|
data{test="pos_inf",group="2",point="a"} 2
|
|
data{test="pos_inf",group="2",point="b"} Inf
|
|
data{test="neg_inf",group="1",point="a"} -Inf
|
|
data{test="neg_inf",group="1",point="b"} 2
|
|
data{test="neg_inf",group="2",point="a"} 2
|
|
data{test="neg_inf",group="2",point="b"} -Inf
|
|
data{test="inf_inf",point="a"} Inf
|
|
data{test="inf_inf",point="b"} -Inf
|
|
data{test="nan",group="1",point="a"} NaN
|
|
data{test="nan",group="1",point="b"} 2
|
|
data{test="nan",group="2",point="a"} 2
|
|
data{test="nan",group="2",point="b"} NaN
|
|
|
|
eval instant at 1m sum(data{test="ten"})
|
|
{} 10
|
|
|
|
eval instant at 1m avg(data{test="ten"})
|
|
{} 2.5
|
|
|
|
eval instant at 1m sum by (group) (data{test="pos_inf"})
|
|
{group="1"} Inf
|
|
{group="2"} Inf
|
|
|
|
eval instant at 1m avg by (group) (data{test="pos_inf"})
|
|
{group="1"} Inf
|
|
{group="2"} Inf
|
|
|
|
eval instant at 1m sum by (group) (data{test="neg_inf"})
|
|
{group="1"} -Inf
|
|
{group="2"} -Inf
|
|
|
|
eval instant at 1m avg by (group) (data{test="neg_inf"})
|
|
{group="1"} -Inf
|
|
{group="2"} -Inf
|
|
|
|
eval instant at 1m sum(data{test="inf_inf"})
|
|
{} NaN
|
|
|
|
eval instant at 1m avg(data{test="inf_inf"})
|
|
{} NaN
|
|
|
|
eval instant at 1m sum by (group) (data{test="nan"})
|
|
{group="1"} NaN
|
|
{group="2"} NaN
|
|
|
|
eval instant at 1m avg by (group) (data{test="nan"})
|
|
{group="1"} NaN
|
|
{group="2"} NaN
|
|
|
|
clear
|
|
|
|
# Test that aggregations are deterministic.
|
|
# Commented because it is flaky in range mode.
|
|
#load 10s
|
|
# up{job="prometheus"} 1
|
|
# up{job="prometheus2"} 1
|
|
#
|
|
#eval instant at 1m count(topk(1,max(up) without()) == topk(1,max(up) without()) == topk(1,max(up) without()) == topk(1,max(up) without()) == topk(1,max(up) without()))
|
|
# {} 1
|