Beta Functions

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Beta functions are available by editing the query JSON directly.

Default Zero

Function	Description	Example
`default_zero()`	Adds a default value to sparse metrics.	`default_zero(system.load.1{*})`

The default_zero function fills empty intervals using interpolation (if interpolation is enabled, which is the default for GAUGE type metrics) or the value 0. Like most functions, it is evaluated after time and space aggregation.

Use Cases

The default_zero function is intended to address the following use cases (though it may also work for other use cases):

Aligning gauges as 0 when performing arithmetic on sparse metrics (note: COUNT or RATE type metrics queried as_count() or as_rate() are always aligned as 0, so using default_zero does not change how they are aligned; it only affects GAUGE type metrics).
Resolving monitors from a no-data condition. This works for both simple and multi-alerts, but the value 0 must not cause the monitor to trigger. For example, this would not work for a monitor with the query avg(last_10m):avg:system.cpu.idle{*} < 10 because this monitor triggers (instead of resolving) when it evaluates to 0. Avoid using this function for error rate monitors with as_count() queries (see this article for details).
Filling in empty intervals in sparse (but nonempty) series for visual reasons or to affect the min/max/average of a timeseries in a monitor evaluation.
Showing the value 0 on the query value widget when there is no data.

Example

To demonstrate how the default_zero function works, consider this single point created for a custom metric using DogStatsD:

$ echo -n "custom_metric:1|g" | nc -4u -w0 127.0.0.1 8125

When this metric is queried over the past 30 minutes, there is a single timestamp, because only one of the query’s rollup intervals has a point:

avg:custom_metric{*}

+---------------------+---------------+
| Timestamp           | custom_metric |
+---------------------+---------------+
| ---------           | ---------     |
| 2019-04-17 17:45:00 | 1             |
+---------------------+---------------+

The default_zero function interpolates this point five minutes forward in time (the default interpolation limit for gauges), then fills the remaining empty intervals with zeros:

default_zero(avg:custom_metric{*})

+---------------------+-----------------------------+
| Timestamp           | default_zero(custom_metric) |
+---------------------+-----------------------------+
| ---------           | ---------                   |
| 2019-04-17 17:30:00 | 0                           |
| 2019-04-17 17:31:00 | 0                           |
...
| 2019-04-17 17:44:00 | 0                           |
| 2019-04-17 17:45:00 | 1                           |
| 2019-04-17 17:46:00 | 1                           |
| 2019-04-17 17:47:00 | 1                           |
| 2019-04-17 17:48:00 | 1                           |
| 2019-04-17 17:49:00 | 1                           |
| 2019-04-17 17:50:00 | 1                           |
| 2019-04-17 17:51:00 | 0                           |
| 2019-04-17 17:52:00 | 0                           |
...
+---------------------+-----------------------------+

Exclude Null

Function	Description	Example
`exclude_null()`	Remove N/A groups from your graph or top list.	`exclude_null(avg:system.load.1{*} by {host})`

Rolling Average

Function	Description	Example
`rollingavg_5()`	Compute the rolling average over a span of 5.	`rollingavg_5(system.load.1{*})`
`rollingavg_13()`	Compute the rolling average over a span of 13.	`rollingavg_13(system.load.1{*})`
`rollingavg_21()`	Compute the rolling average over a span of 21.	`rollingavg_21(system.load.1{*})`
`rollingavg_29()`	Compute the rolling average over a span of 29.	`rollingavg_29(system.load.1{*})`