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817 lines
27 KiB
Plaintext
817 lines
27 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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http_requests_histogram{job="api-server", instance="3", group="canary"} {{schema:2 count:4 sum:10 buckets:[1 0 0 0 1 0 0 1 1]}}
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eval instant at 0m max(http_requests)
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{} 4
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# The histogram is ignored here so the result doesn't change but it has an info annotation now.
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eval_info instant at 0m max({job="api-server"})
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{} 4
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# The histogram is ignored here so there is no result but it has an info annotation now.
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eval_info instant at 0m max(http_requests_histogram)
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eval instant at 0m min(http_requests)
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{} 1
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# The histogram is ignored here so the result doesn't change but it has an info annotation now.
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eval_info instant at 0m min({job="api-server"})
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{} 1
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# The histogram is ignored here so there is no result but it has an info annotation now.
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eval_info instant at 0m min(http_requests_histogram)
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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 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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http_requests_histogram{job="app-server", instance="2", group="canary"} {{schema:0 sum:10 count:10}}x11
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http_requests_histogram{job="api-server", instance="3", group="production"} {{schema:0 sum:20 count:20}}x11
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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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# Tests for histogram: should ignore histograms.
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eval_info instant at 50m topk(100, http_requests_histogram)
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#empty
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eval_info range from 0 to 50m step 5m topk(100, http_requests_histogram)
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#empty
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eval_info instant at 50m topk(1, {__name__=~"http_requests(_histogram)?"})
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{__name__="http_requests", group="canary", instance="1", job="app-server"} 800
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eval_info instant at 50m count(topk(1000, {__name__=~"http_requests(_histogram)?"}))
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{} 9
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eval_info range from 0 to 50m step 5m count(topk(1000, {__name__=~"http_requests(_histogram)?"}))
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{} 9x10
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eval_info instant at 50m topk by (instance) (1, {__name__=~"http_requests(_histogram)?"})
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{__name__="http_requests", group="canary", instance="0", job="app-server"} 700
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{__name__="http_requests", group="canary", instance="1", job="app-server"} 800
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{__name__="http_requests", group="production", instance="2", job="api-server"} NaN
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eval_info instant at 50m bottomk(100, http_requests_histogram)
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#empty
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eval_info range from 0 to 50m step 5m bottomk(100, http_requests_histogram)
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#empty
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eval_info instant at 50m bottomk(1, {__name__=~"http_requests(_histogram)?"})
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{__name__="http_requests", group="production", instance="0", job="api-server"} 100
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eval_info instant at 50m count(bottomk(1000, {__name__=~"http_requests(_histogram)?"}))
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{} 9
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eval_info range from 0 to 50m step 5m count(bottomk(1000, {__name__=~"http_requests(_histogram)?"}))
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{} 9x10
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eval_info instant at 50m bottomk by (instance) (1, {__name__=~"http_requests(_histogram)?"})
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{__name__="http_requests", group="production", instance="0", job="api-server"} 100
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{__name__="http_requests", group="production", instance="1", job="api-server"} 200
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{__name__="http_requests", group="production", instance="2", job="api-server"} NaN
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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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version{job="app-server", instance="2", group="canary"} {{schema:0 sum:10 count:20 z_bucket_w:0.001 z_bucket:2 buckets:[1 2] n_buckets:[1 2]}}
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version{job="app-server", instance="3", group="canary"} {{schema:0 sum:10 count:20 z_bucket_w:0.001 z_bucket:2 buckets:[1 2] n_buckets:[1 2]}}
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eval instant at 1m 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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{version="{count:20, sum:10, [-2,-1):2, [-1,-0.5):1, [-0.001,0.001]:2, (0.5,1]:1, (1,2]:2}"} 2
|
|
|
|
eval instant at 1m count_values(((("version"))), version)
|
|
{version="6"} 5
|
|
{version="7"} 2
|
|
{version="8"} 2
|
|
{version="{count:20, sum:10, [-2,-1):2, [-1,-0.5):1, [-0.001,0.001]:2, (0.5,1]:1, (1,2]:2}"} 2
|
|
|
|
eval instant at 1m count_values without (instance)("version", version)
|
|
{job="api-server", group="production", version="6"} 3
|
|
{job="api-server", group="canary", version="8"} 2
|
|
{job="app-server", group="production", version="6"} 2
|
|
{job="app-server", group="canary", version="7"} 2
|
|
{job="app-server", group="canary", version="{count:20, sum:10, [-2,-1):2, [-1,-0.5):1, [-0.001,0.001]:2, (0.5,1]:1, (1,2]:2}"} 2
|
|
|
|
# Overwrite label with output. Don't do this.
|
|
eval instant at 1m count_values without (instance)("job", version)
|
|
{job="6", group="production"} 5
|
|
{job="8", group="canary"} 2
|
|
{job="7", group="canary"} 2
|
|
{job="{count:20, sum:10, [-2,-1):2, [-1,-0.5):1, [-0.001,0.001]:2, (0.5,1]:1, (1,2]:2}", group="canary"} 2
|
|
|
|
# Overwrite label with output. Don't do this.
|
|
eval instant at 1m count_values by (job, group)("job", version)
|
|
{job="6", group="production"} 5
|
|
{job="8", group="canary"} 2
|
|
{job="7", group="canary"} 2
|
|
{job="{count:20, sum:10, [-2,-1):2, [-1,-0.5):1, [-0.001,0.001]:2, (0.5,1]:1, (1,2]:2}", group="canary"} 2
|
|
|
|
# Tests for quantile.
|
|
clear
|
|
|
|
load 10s
|
|
data{test="two samples",point="a"} 0
|
|
data{test="two samples",point="b"} 1
|
|
data{test="three samples",point="a"} 0
|
|
data{test="three samples",point="b"} 1
|
|
data{test="three samples",point="c"} 2
|
|
data{test="uneven samples",point="a"} 0
|
|
data{test="uneven samples",point="b"} 1
|
|
data{test="uneven samples",point="c"} 4
|
|
data_histogram{test="histogram sample", point="c"} {{schema:2 count:4 sum:10 buckets:[1 0 0 0 1 0 0 1 1]}}
|
|
foo .8
|
|
|
|
eval instant at 1m quantile without(point)(0.8, data)
|
|
{test="two samples"} 0.8
|
|
{test="three samples"} 1.6
|
|
{test="uneven samples"} 2.8
|
|
|
|
# The histogram is ignored here so the result doesn't change but it has an info annotation now.
|
|
eval_info instant at 1m quantile without(point)(0.8, {__name__=~"data(_histogram)?"})
|
|
{test="two samples"} 0.8
|
|
{test="three samples"} 1.6
|
|
{test="uneven samples"} 2.8
|
|
|
|
# The histogram is ignored here so there is no result but it has an info annotation now.
|
|
eval_info instant at 1m quantile(0.8, data_histogram)
|
|
|
|
# Bug #5276.
|
|
eval instant at 1m quantile without(point)(scalar(foo), data)
|
|
{test="two samples"} 0.8
|
|
{test="three samples"} 1.6
|
|
{test="uneven samples"} 2.8
|
|
|
|
|
|
eval instant at 1m quantile without(point)((scalar(foo)), data)
|
|
{test="two samples"} 0.8
|
|
{test="three samples"} 1.6
|
|
{test="uneven samples"} 2.8
|
|
|
|
eval_warn instant at 1m quantile without(point)(NaN, data)
|
|
{test="two samples"} NaN
|
|
{test="three samples"} NaN
|
|
{test="uneven samples"} NaN
|
|
|
|
# Tests for group.
|
|
clear
|
|
|
|
load 10s
|
|
data{test="two samples",point="a"} 0
|
|
data{test="two samples",point="b"} 1
|
|
data{test="three samples",point="a"} 0
|
|
data{test="three samples",point="b"} 1
|
|
data{test="three samples",point="c"} 2
|
|
data{test="uneven samples",point="a"} 0
|
|
data{test="uneven samples",point="b"} 1
|
|
data{test="uneven samples",point="c"} 4
|
|
data{test="histogram sample",point="c"} {{schema:0 sum:0 count:0}}
|
|
foo .8
|
|
|
|
eval instant at 1m group without(point)(data)
|
|
{test="two samples"} 1
|
|
{test="three samples"} 1
|
|
{test="uneven samples"} 1
|
|
{test="histogram sample"} 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
|
|
data{test="value is nan"} NaN
|
|
|
|
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
|
|
|
|
# If NaN is in the mix, the result is NaN.
|
|
eval instant at 1m avg(data)
|
|
{} NaN
|
|
|
|
# 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
|
|
|
|
clear
|
|
|
|
# Test stddev produces consistent results regardless the order the data is loaded in.
|
|
load 5m
|
|
series{label="a"} 1
|
|
series{label="b"} 2
|
|
series{label="c"} {{schema:1 sum:15 count:10 buckets:[3 2 5 7 9]}}
|
|
|
|
# The histogram is ignored here so the result doesn't change but it has an info annotation now.
|
|
eval_info instant at 0m stddev(series)
|
|
{} 0.5
|
|
|
|
eval_info instant at 0m stdvar(series)
|
|
{} 0.25
|
|
|
|
# The histogram is ignored here so there is no result but it has an info annotation now.
|
|
eval_info instant at 0m stddev({label="c"})
|
|
|
|
eval_info instant at 0m stdvar({label="c"})
|
|
|
|
eval_info instant at 0m stddev by (label) (series)
|
|
{label="a"} 0
|
|
{label="b"} 0
|
|
|
|
eval_info instant at 0m stdvar by (label) (series)
|
|
{label="a"} 0
|
|
{label="b"} 0
|
|
|
|
clear
|
|
|
|
load 5m
|
|
series{label="a"} {{schema:1 sum:15 count:10 buckets:[3 2 5 7 9]}}
|
|
series{label="b"} 1
|
|
series{label="c"} 2
|
|
|
|
eval_info instant at 0m stddev(series)
|
|
{} 0.5
|
|
|
|
eval_info instant at 0m stdvar(series)
|
|
{} 0.25
|
|
|
|
eval_info instant at 0m stddev by (label) (series)
|
|
{label="b"} 0
|
|
{label="c"} 0
|
|
|
|
eval_info instant at 0m stdvar by (label) (series)
|
|
{label="b"} 0
|
|
{label="c"} 0
|
|
|
|
clear
|
|
|
|
load 5m
|
|
series{label="a"} 1
|
|
series{label="b"} 2
|
|
series{label="c"} NaN
|
|
|
|
eval instant at 0m stddev(series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stdvar(series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stddev by (label) (series)
|
|
{label="a"} 0
|
|
{label="b"} 0
|
|
{label="c"} NaN
|
|
|
|
eval instant at 0m stdvar by (label) (series)
|
|
{label="a"} 0
|
|
{label="b"} 0
|
|
{label="c"} NaN
|
|
|
|
clear
|
|
|
|
load 5m
|
|
series{label="a"} NaN
|
|
series{label="b"} 1
|
|
series{label="c"} 2
|
|
|
|
eval instant at 0m stddev(series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stdvar(series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stddev by (label) (series)
|
|
{label="a"} NaN
|
|
{label="b"} 0
|
|
{label="c"} 0
|
|
|
|
eval instant at 0m stdvar by (label) (series)
|
|
{label="a"} NaN
|
|
{label="b"} 0
|
|
{label="c"} 0
|
|
|
|
clear
|
|
|
|
load 5m
|
|
series NaN
|
|
|
|
eval instant at 0m stddev(series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stdvar(series)
|
|
{} NaN
|
|
|
|
clear
|
|
|
|
load 5m
|
|
series{label="a"} 1
|
|
series{label="b"} 2
|
|
series{label="c"} inf
|
|
|
|
eval instant at 0m stddev (series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stdvar (series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stddev by (label) (series)
|
|
{label="a"} 0
|
|
{label="b"} 0
|
|
{label="c"} NaN
|
|
|
|
eval instant at 0m stdvar by (label) (series)
|
|
{label="a"} 0
|
|
{label="b"} 0
|
|
{label="c"} NaN
|
|
|
|
clear
|
|
|
|
load 5m
|
|
series{label="a"} inf
|
|
series{label="b"} 1
|
|
series{label="c"} 2
|
|
|
|
eval instant at 0m stddev(series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stdvar(series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stddev by (label) (series)
|
|
{label="a"} NaN
|
|
{label="b"} 0
|
|
{label="c"} 0
|
|
|
|
eval instant at 0m stdvar by (label) (series)
|
|
{label="a"} NaN
|
|
{label="b"} 0
|
|
{label="c"} 0
|
|
|
|
clear
|
|
|
|
load 5m
|
|
series inf
|
|
|
|
eval instant at 0m stddev(series)
|
|
{} NaN
|
|
|
|
eval instant at 0m stdvar(series)
|
|
{} NaN
|