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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-05-06 01:22:31 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-05-06 01:22:31 +0000 |
commit | 8d4f58e49b9dc7d3545651023a36729de773ad86 (patch) | |
tree | 7bc7be4a8e9e298daa1349348400aa2a653866f2 /web/api/queries/des/README.md | |
parent | Initial commit. (diff) | |
download | netdata-8d4f58e49b9dc7d3545651023a36729de773ad86.tar.xz netdata-8d4f58e49b9dc7d3545651023a36729de773ad86.zip |
Adding upstream version 1.12.0.upstream/1.12.0upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'web/api/queries/des/README.md')
-rw-r--r-- | web/api/queries/des/README.md | 68 |
1 files changed, 68 insertions, 0 deletions
diff --git a/web/api/queries/des/README.md b/web/api/queries/des/README.md new file mode 100644 index 0000000..486221c --- /dev/null +++ b/web/api/queries/des/README.md @@ -0,0 +1,68 @@ +# double exponential smoothing + +Exponential smoothing is one of many window functions commonly applied to smooth data in signal +processing, acting as low-pass filters to remove high frequency noise. + +Simple exponential smoothing does not do well when there is a trend in the data. +In such situations, several methods were devised under the name "double exponential smoothing" +or "second-order exponential smoothing.", which is the recursive application of an exponential +filter twice, thus being termed "double exponential smoothing". + +In simple terms, this is like an average value, but more recent values are given more weight +and the trend of the values influences significantly the result. + +> **IMPORTANT** +> +> It is common for `des` to provide "average" values that far beyond the minimum or the maximum +> values found in the time-series. +> `des` estimates these values because of it takes into account the trend. + +This module implements the "Holt-Winters double exponential smoothing". + +Netdata automatically adjusts the weight (`alpha`) and the trend (`beta`) based on the number +of values processed, using the formula: + +``` +window = max(number of values, 15) +alpha = 2 / (window + 1) +beta = 2 / (window + 1) +``` + +You can change the fixed value `15` by setting in `netdata.conf`: + +``` +[web] + des max window = 15 +``` + +## how to use + +Use it in alarms like this: + +``` + alarm: my_alarm + on: my_chart +lookup: des -1m unaligned of my_dimension + warn: $this > 1000 +``` + +`des` does not change the units. For example, if the chart units is `requests/sec`, the result +will be again expressed in the same units. + +It can also be used in APIs and badges as `&group=des` in the URL. + +## Examples + +Examining last 1 minute `successful` web server responses: + +- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=min&after=-60&label=min) +- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=average&after=-60&label=average&value_color=yellow) +- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=ses&after=-60&label=single+exponential+smoothing&value_color=yellow) +- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=des&after=-60&label=double+exponential+smoothing&value_color=orange) +- ![](https://registry.my-netdata.io/api/v1/badge.svg?chart=web_log_nginx.response_statuses&options=unaligned&dimensions=success&group=max&after=-60&label=max) + +## References + +- [https://en.wikipedia.org/wiki/Exponential_smoothing](https://en.wikipedia.org/wiki/Exponential_smoothing). + +[![analytics](https://www.google-analytics.com/collect?v=1&aip=1&t=pageview&_s=1&ds=github&dr=https%3A%2F%2Fgithub.com%2Fnetdata%2Fnetdata&dl=https%3A%2F%2Fmy-netdata.io%2Fgithub%2Fweb%2Fapi%2Fqueries%2Fdes%2FREADME&_u=MAC~&cid=5792dfd7-8dc4-476b-af31-da2fdb9f93d2&tid=UA-64295674-3)]() |