30 lines
1.6 KiB
Plaintext
30 lines
1.6 KiB
Plaintext
import "strings"
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import "date"
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myWindowPeriod = if int(v: v.windowPeriod) > int(v: 2m) then duration(v: int(v: v.windowPeriod) * 30) else duration(v: int(v: v.windowPeriod) * 15)
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result = from(bucket: "poseidon/autogen")
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|> range(start: date.truncate(t: v.timeRangeStart, unit: 1m), stop: date.truncate(t: v.timeRangeStop, unit: 1m))
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|> filter(fn: (r) => r["_measurement"] == "poseidon_used_runners")
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|> filter(fn: (r) => contains(value: r["environment_id"], set: ${environment_ids:json}))
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|> filter(fn: (r) => (not exists r.stage) or contains(value: r["stage"], set: ${stages:json}))
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|> filter(fn: (r) => r["event_type"] == "creation")
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|> group(columns: ["environment_id", "stage"], mode:"by")
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|> aggregateWindow(every: 1m, fn: count, createEmpty: true)
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|> keep(columns: ["_value", "_time", "environment_id", "stage"])
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|> aggregateWindow(every: myWindowPeriod, fn: mean, createEmpty: true)
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envMapping = from(bucket: "poseidon/autogen")
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|> range(start: -1y)
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|> filter(fn: (r) => r["_measurement"] == "poseidon_environments")
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|> filter(fn: (r) => r["event_type"] == "creation")
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|> group(columns: ["id", "stage"], mode:"by")
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|> last()
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|> keep(columns: ["id", "image", "stage"])
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|> rename(columns: {id: "environment_id"})
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|> map(fn: (r) => ({ r with image: strings.substring(v: r.stage, start: 0, end: 1) + r.environment_id + "/" + strings.trimPrefix(v: r.image, prefix: "openhpi/co_execenv_")}))
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join(tables: {key1: result, key2: envMapping}, on: ["environment_id", "stage"], method: "inner")
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|> keep(columns: ["_value", "image", "_time"])
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|> group(columns: ["image"], mode: "by")
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|> rename(columns: {_value: ""})
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