You can apply functions to the result of each query, below was taken from our docs.
Functions
You can apply functions to the result of each query. Examples
| Function | Description |
|---|---|
| cumsum() | cumulative sum over visible time window |
| dt() | time delta between points |
| diff() | value delta between points |
| derivative() | 1st order derivative, diff / dt |
| rate() | 1st order derivate that skips non-monotonically increasing values |
| derived() | synonym for derivative |
| per_second() | synonym for rate |
| per_minute() | 60 * rate |
| per_hour() | 3600 * rate |
| ewma_3() | Exponentially Weighted Moving Average with a span of 3 |
| ewma_5() | EWMA with a span of 5 |
| ewma_10() | EWMA with a span of 10 |
| ewma_20() | EWMA with a span of 20 |
| median_3() | Median filter, useful for reducing noise, with a span of 3 |
| median_5() | Median with a span of 5 |
| median_7() | Median with a span of 7 |
| median_9() | Median with a span of 9 |
| abs() | Absolute value |
| log10() | Base-10 logarithm |
| log2() | Base-2 logarithm |
| hour_before() | Metric values from one hour ago |
| day_before() | Metric values from one day ago |
| week_before() | Metric values from one week ago |
| month_before() | Metric values from one month ago |
| top() | Select the top series responsive to a given query, according to some ranking method. Takes four parameters:
|
| top_offset() | Similar to top(), except with an additional offset parameter, which controls where in the ordered sequence of series the graphing starts. For example, an offset of 2 would start graphing at the number 3 ranked series, according to the chosen ranking metric. |
The top() method also has the following convenience functions, all of which take a single series list as input:
- top5, top10, top15, top20
- Retrieves top-valued [5, 10, 15, 20] series using the 'mean' metric.
- top5_max, top10_max, top15_max, top20_max
- Retrieves top-valued [5, 10, 15, 20] series using the 'max' metric.
- top5_min, top10_min, top15_min, top20_min
- Retrieves top-valued [5, 10, 15, 20] series using the 'min' metric.
- top5_last, top10_last, top15_last, top20_last
- Retrieves top-valued [5, 10, 15, 20] series using the 'last' metric.
- top5_area, top10_area, top15_area, top20_area
- Retrieves top-valued [5, 10, 15, 20] series using the 'area' metric.
- top5_l2norm, top10_l2norm, top15_l2norm, top20_l2norm
- Retrieves top-valued [5, 10, 15, 20] series using the 'l2norm' metric.
- bottom5, bottom10, bottom15, bottom20
- Retrieves lowest-valued [5, 10, 15, 20] series using the 'mean' metric.
- bottom5_max, bottom10_max, bottom15_max, bottom20_max
- Retrieves lowest-valued [5, 10, 15, 20] series using the 'max' metric.
- bottom5_min, bottom10_min, bottom15_min, bottom20_min
- Retrieves lowest-valued [5, 10, 15, 20] series using the 'min' metric.
- bottom5_last, bottom10_last, bottom15_last, bottom20_last
- Retrieves lowest-valued [5, 10, 15, 20] series using the 'last' metric.
- bottom5_area, bottom10_area, bottom15_area, bottom20_area
- Retrieves lowest-valued [5, 10, 15, 20] series using the 'area' metric.
- bottom5_l2norm, bottom10_l2norm, bottom15_l2norm, bottom20_l2norm
- Retrieves lowest-valued [5, 10, 15, 20] series using the 'l2norm' metric.
There are also a few functions you can append to a query which we recommend for expert users only.
One of these is .rollup(). Appending this function allows you to control the number of points rolled up into a single point. This function takes two parameters, method and time, like so: .rollup(method,time). The method can be sum/min/max/count/avg and time is in seconds. You can use either one individually, or both combined like .rollup(sum,120). There are some checks on this, though, because for a given time range we do not return more than 350 points. Thus if you're requesting .rollup(20) where 20 is in seconds, and ask for a month of data, we will be returning the points at a rollup of far greater than 20 seconds.
.as_count() and .as_rate() are two other expert-only functions, which are only intended for metrics submitted in a certain way (for metadata types where that is acceptable). At present, for metrics submitted as rates or counters via statsd, appending.as_count() or .as_rate() will function correctly. For other metrics, including gauges submitted by statsd, .as_count() and.as_rate() will have no effect.
We strongly recommend not using .rollup() and .as_count() within the same query. We will also be building these functions fully into the graph editor in the near future. For more on .as_count() please see our blog post here.
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