Monitor states
Flux helps you monitor states in your metrics and events:
If you’re just getting started with Flux queries, check out the following:
- Get started with Flux for a conceptual overview of Flux.
- Execute queries to discover a variety of ways to run your queries.
Find how long a state persists
Use stateDuration() to calculate the duration of consecutive rows with a specified state. For each consecutive point that matches the specified state, stateDuration()
increments and stores the duration (in the specified unit) in a user-defined column.
Include the following information:
- Column to search: any tag key, tag value, field key, field value, or measurement.
- Value: the value (or state) to search for in the specified column.
- State duration column: a new column to store the state duration─the length of time that the specified value persists.
- Unit: the unit of time (
1s
(by default),1m
,1h
) used to increment the state duration.
data
|> stateDuration(fn: (r) => r.column_to_search == "value_to_search_for", column: "state_duration", unit: 1s)
- For the first point that evaluates
true
, the state duration is set to0
. For each consecutive point that evaluatestrue
, the state duration increases by the time interval between each consecutive point (in specified units). - If the state is
false
, the state duration is reset to-1
.
Example query with stateDuration()
The following query searches the doors
bucket over the past 5 minutes to find how many seconds a door has been closed
.
from(bucket: "doors")
|> range(start: -5m)
|> stateDuration(fn: (r) => r._value == "closed", column: "door_closed", unit: 1s)
In this example, door_closed
is the State duration column. If you write data to the doors
bucket every minute, the state duration increases by 60s
for each consecutive point where _value
is closed
. If _value
is not closed
, the state duration is reset to 0
.
Query results
Results for the example query above may look like this (for simplicity, we’ve omitted the measurement, tag, and field columns):
_time | _value | door_closed |
---|---|---|
2019-10-26T17:39:16Z | closed | 0 |
2019-10-26T17:40:16Z | closed | 60 |
2019-10-26T17:41:16Z | closed | 120 |
2019-10-26T17:42:16Z | open | -1 |
2019-10-26T17:43:16Z | closed | 0 |
2019-10-26T17:44:27Z | closed | 60 |
Count the number of consecutive states
Use the stateCount() function and include the following information:
- Column to search: any tag key, tag value, field key, field value, or measurement.
- Value: to search for in the specified column.
- State count column: a new column to store the state count─the number of consecutive records in which the specified value exists.
|> stateCount(
fn: (r) => r.column_to_search == "value_to_search_for",
column: "state_count",
)
- For the first point that evaluates
true
, the state count is set to1
. For each consecutive point that evaluatestrue
, the state count increases by 1. - If the state is
false
, the state count is reset to-1
.
Example query with stateCount()
The following query searches the doors
bucket over the past 5 minutes and calculates how many points have closed
as their _value
.
from(bucket: "doors")
|> range(start: -5m)
|> stateCount(fn: (r) => r._value == "closed", column: "door_closed")
This example stores the state count in the door_closed
column. If you write data to the doors
bucket every minute, the state count increases by 1
for each consecutive point where _value
is closed
. If _value
is not closed
, the state count is reset to -1
.
Query results
Results for the example query above may look like this (for simplicity, we’ve omitted the measurement, tag, and field columns):
_time | _value | door_closed |
---|---|---|
2019-10-26T17:39:16Z | closed | 1 |
2019-10-26T17:40:16Z | closed | 2 |
2019-10-26T17:41:16Z | closed | 3 |
2019-10-26T17:42:16Z | open | -1 |
2019-10-26T17:43:16Z | closed | 1 |
2019-10-26T17:44:27Z | closed | 2 |
Example query to count machine state
The following query checks the machine state every minute (idle, assigned, or busy). InfluxDB searches the servers
bucket over the past hour and counts records with a machine state of idle
, assigned
or busy
.
from(bucket: "servers")
|> range(start: -1h)
|> filter(fn: (r) => r.machine_state == "idle" or r.machine_state == "assigned" or r.machine_state == "busy")
|> stateCount(fn: (r) => r.machine_state == "busy", column: "_count")
|> stateCount(fn: (r) => r.machine_state == "assigned", column: "_count")
|> stateCount(fn: (r) => r.machine_state == "idle", column: "_count")