# README
Events Package
Use this Flux Package to calculate the time between a record and the next record. The function events.duration peeks at the next record and calculates the duration an between records and associates it with the start of the event. For the final record it can be compared against a stop column or a timestamp. This function differs to existing elapsed which removes the first entry and stateDuration which totalized on a function.
See also
events.duration
duration calculates the duration of the event.
| Name | Type | Description |
|---|---|---|
| unit | duration | Units of state duration 'ns', 'us', 'µs', 'ms', 's', 'm', 'h' |
| columnName | string | The name of the result column. Default duration |
| timeColumn | string | The name of the time column, default _time |
| stopColumn | string | The name of the stop column, default _stop |
| stop | time | Optional. If provided, it will be used instead of the stop column |
Basic Example:
import "contrib/tomhollingworth/events"
from(bucket: "example-bucket")
|> range(start: -24h)
|> events.duration()
Last Record Duration
The last record needs a time to compare to. The following strategy is implemented:
- Use
stopif provided. - If no
stoptime is provided, then use the value from thestopColumncolumn on the last record. - If no
stopColumnis provided then use_stopby default.
Comparison to other functions
Consider the following dataset of a door opening and closing:
import "csv"
inData = "
#datatype,string,long,dateTime:RFC3339,string,string
#group,false,true,false,false,false
#default,,,,,
,result,table,_time,_value,_field
,,0,2020-01-01T08:00:00Z,Closed,value
,,0,2020-01-01T08:15:00Z,Open,value
,,0,2020-01-01T08:15:08Z,Closed,value
,,0,2020-01-01T08:21:00Z,Open,value
,,0,2020-01-01T08:21:07Z,Closed,value
,,0,2020-01-01T08:24:00Z,Open,value
,,0,2020-01-01T08:24:12Z,Closed,value
"
csv.from(csv: inData)
|> range(start: 2020-01-01T08:00:00Z, stop: 2020-01-01T08:30:00Z)
|> elapsed() yields the following. The first record is dropped and durations are associated with subsequent records. Totalizing on filter on value and summing the elapsed column would have the duration swapped between open and closed.
-, result, table, _start, _stop, _time, _value, _field
+, result, table, _start, _stop, _time, _value, _field, elapsed
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:00:00Z, Closed, value
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:10:00Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:10:00Z, Closed, value, 1600
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:00Z, Open, value, 1300
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:08Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:08Z, Closed, value, 8
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:00Z, Open, value, 1352
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:07Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:07Z, Closed, value, 7
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:00Z, Open, value, 173
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:12Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:12Z, Closed, value, 12
|> stateDuration(fn: (r) => true) yields the following. The duration is continuously totalized. For a particular state we could also include that in our stateDuration function, however time is counted twice on subsequent events. Totalizing this would have that time counted twice.
-, result, table, _start, _stop, _time, _value, _field
+, result, table, _start, _stop, _time, _value, _field, stateDuration
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:00:00Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:00:00Z, Closed, value, 0
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:10:00Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:10:00Z, Closed, value, 600
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:00Z, Open, value, 900
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:08Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:08Z, Closed, value, 908
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:00Z, Open, value, 1260
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:07Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:07Z, Closed, value, 1267
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:00Z, Open, value, 1440
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:12Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:12Z, Closed, value, 1452
|> events.duration() yields the following.
-, result, table, _start, _stop, _time, _value, _field
+, result, table, _start, _stop, _time, _value, _field, duration
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:00:00Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:00:00Z, Closed, value, 600
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:10:00Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:10:00Z, Closed, value, 300
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:00Z, Open, value, 8
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:08Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:15:08Z, Closed, value, 352
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:00Z, Open, value, 7
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:07Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:21:07Z, Closed, value, 173
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:00Z, Open, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:00Z, Open, value, 12
-, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:12Z, Closed, value
+, , 0, 2020-01-01T08:00:00Z, 2020-01-01T08:30:00Z, 2020-01-01T08:24:12Z, Closed, value, 348
Contact
- Author: Tom Hollingworth
- Email: [email protected]
- Github: @tomhollingworth
- Influx Community Slack: @tomhollingworth
# Functions
No description provided by the author
# Constants
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# Structs
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