flux_gen.go

// DO NOT EDIT: This file is autogenerated via the builtin command.

package monitor

import (
	ast "github.com/influxdata/flux/ast"
	runtime "github.com/influxdata/flux/runtime"
)

func init() {
	runtime.RegisterPackage(pkgAST)
}

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				Source: "package monitor\n\nimport \"experimental\"\nimport \"influxdata/influxdb/v1\"\nimport \"influxdata/influxdb\"\n\nbucket = \"_monitoring\"\n\n// Write persists the check statuses\noption write = (tables=<-) => tables |> experimental.to(bucket: bucket)\n\n// Log records notification events\noption log = (tables=<-) => tables |> experimental.to(bucket: bucket)\n\n// From retrieves the check statuses that have been stored.\nfrom = (start, stop=now(), fn=(r) => true) =>\n    influxdb.from(bucket: bucket)\n        |> range(start: start, stop: stop)\n        |> filter(fn: (r) => r._measurement == \"statuses\")\n        |> filter(fn: fn)\n        |> v1.fieldsAsCols()\n\n// levels describing the result of a check\nlevelOK = \"ok\"\nlevelInfo = \"info\"\nlevelWarn = \"warn\"\nlevelCrit = \"crit\"\nlevelUnknown = \"unknown\"\n\n_stateChanges = (fromLevel=\"any\", toLevel=\"any\", tables=<-) => {\n    toLevelFilter = if toLevel == \"any\" then (r) => r._level != fromLevel and exists r._level\n                   else (r) => r._level == toLevel\n\n    fromLevelFilter = if fromLevel == \"any\" then (r) => r._level != toLevel and exists r._level\n                   else (r) => r._level == fromLevel\n\n    return tables\n        |> map(fn: (r) => ({r with level_value: if toLevelFilter(r: r) then 1\n                                                else if fromLevelFilter(r: r) then 0\n                                                else -10}))\n        |> duplicate(column: \"_level\", as: \"____temp_level____\")\n        |> drop(columns: [\"_level\"])\n        |> rename(columns: {\"____temp_level____\": \"_level\"})\n        |> sort(columns: [\"_source_timestamp\"], desc: false)\n        |> difference(columns: [\"level_value\"])\n        |> filter(fn: (r) => r.level_value == 1)\n        |> drop(columns: [\"level_value\"])\n        |> experimental.group(mode: \"extend\", columns: [\"_level\"])\n}\n\n// stateChangesOnly takes a stream of tables that contains a _level column and\n// returns a stream of tables where each record in a table represents a state change\n// of the _level column.\n// Statuses are sorted by source timestamp, because default sort order of statuses may differ\n// (`_time` column holds the time when check was executed) and that could result in detecting\n// status changes at the wrong time or even false changes.\nstateChangesOnly = (tables=<-) => {\n    return tables\n        |> map(fn: (r) => ({r with level_value: if r._level == levelCrit then 4\n                                                else if r._level == levelWarn then 3\n                                                else if r._level == levelInfo then 2\n                                                else if r._level == levelOK then 1\n                                                else 0}))\n        |> duplicate(column: \"_level\", as: \"____temp_level____\")\n        |> drop(columns: [\"_level\"])\n        |> rename(columns: {\"____temp_level____\": \"_level\"})\n        |> sort(columns: [\"_source_timestamp\"], desc: false)\n        |> difference(columns: [\"level_value\"])\n        |> filter(fn: (r) => r.level_value != 0)\n        |> drop(columns: [\"level_value\"])\n        |> experimental.group(mode: \"extend\", columns: [\"_level\"])\n}\n\n// StateChanges takes a stream of tables, fromLevel, and toLevel and returns\n// a stream of tables where status has gone from fromLevel to toLevel.\n//\n// StateChanges only operates on data with data where r._level exists.\nstateChanges = (fromLevel=\"any\", toLevel=\"any\", tables=<-) => {\n    return if fromLevel == \"any\" and toLevel == \"any\" then tables |> stateChangesOnly()\n           else tables |> _stateChanges(fromLevel: fromLevel, toLevel: toLevel)\n}\n\n// Notify will call the endpoint and log the results.\nnotify = (tables=<-, endpoint, data) =>\n    tables\n        |> experimental.set(o: data)\n        |> experimental.group(mode: \"extend\", columns: experimental.objectKeys(o: data))\n        |> map(fn: (r) => ({r with\n            _measurement: \"notifications\",\n            _status_timestamp: int(v: r._time),\n            _time: now(),\n        }))\n        |> endpoint()\n        |> experimental.group(mode: \"extend\", columns: [\"_sent\"])\n        |> log()\n\n// Logs retrieves notification events that have been logged.\nlogs = (start, stop=now(), fn) =>\n    influxdb.from(bucket: bucket)\n        |> range(start: start, stop: stop)\n        |> filter(fn: (r) => r._measurement == \"notifications\")\n        |> filter(fn: fn)\n        |> v1.fieldsAsCols()\n\n// Deadman takes in a stream of tables and reports which tables\n// were observed strictly before t and which were observed after.\n//\ndeadman = (t, tables=<-) => tables\n    |> max(column: \"_time\")\n    |> map(fn: (r) => ( {r with dead: r._time < t} ))\n\n// Check performs a check against its input using the given ok, info, warn and crit functions\n// and writes the result to a system bucket.\ncheck = (\n    tables=<-,\n    data,\n    messageFn,\n    crit=(r) => false,\n    warn=(r) => false,\n    info=(r) => false,\n    ok=(r) => true\n) =>\n    tables\n        |> experimental.set(o: data.tags)\n        |> experimental.group(mode: \"extend\", columns: experimental.objectKeys(o: data.tags))\n        |> map(fn: (r) => ({r with\n            _measurement: \"statuses\",\n            _source_measurement: r._measurement,\n            _type: data._type,\n            _check_id:  data._check_id,\n            _check_name: data._check_name,\n            _level:\n                if crit(r: r) then levelCrit\n                else if warn(r: r) then levelWarn\n                else if info(r: r) then levelInfo\n                else if ok(r: r) then levelOK\n                else levelUnknown,\n            _source_timestamp: int(v:r._time),\n            _time: now(),\n        }))\n        |> map(fn: (r) => ({r with\n            _message: messageFn(r: r),\n        }))\n        |> experimental.group(mode: \"extend\", columns: [\"_source_measurement\", \"_type\", \"_check_id\", \"_check_name\", \"_level\"])\n        |> write()",
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