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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2018-11-07 12:19:29 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2018-11-07 12:20:17 +0000 |
commit | a64a253794ac64cb40befee54db53bde17dd0d49 (patch) | |
tree | c1024acc5f6e508814b944d99f112259bb28b1be /web/api/queries/des/README.md | |
parent | New upstream version 1.10.0+dfsg (diff) | |
download | netdata-2dec20452b290c484d509f7ac9a29b38cf690223.tar.xz netdata-2dec20452b290c484d509f7ac9a29b38cf690223.zip |
New upstream version 1.11.0+dfsgupstream/1.11.0+dfsg
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 | 66 |
1 files changed, 66 insertions, 0 deletions
diff --git a/web/api/queries/des/README.md b/web/api/queries/des/README.md new file mode 100644 index 000000000..fa546a338 --- /dev/null +++ b/web/api/queries/des/README.md @@ -0,0 +1,66 @@ +# 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). |