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* optimized ses and added des * added coefficient of variation * fix bug identified by @vlvkobal: use all available points when resampling is required and the timeframe is not enough for a single point
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| Original file line number | Diff line number | Diff line change |
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| # SPDX-License-Identifier: GPL-3.0-or-later | ||
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| AUTOMAKE_OPTIONS = subdir-objects | ||
| MAINTAINERCLEANFILES = $(srcdir)/Makefile.in | ||
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| dist_noinst_DATA = \ | ||
| README.md \ | ||
| $(NULL) |
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| # double exponential smoothing |
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| // SPDX-License-Identifier: GPL-3.0-or-later | ||
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| #include "des.h" | ||
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| // ---------------------------------------------------------------------------- | ||
| // single exponential smoothing | ||
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| struct grouping_des { | ||
| calculated_number alpha; | ||
| calculated_number alpha_other; | ||
| calculated_number beta; | ||
| calculated_number beta_other; | ||
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| calculated_number level; | ||
| calculated_number trend; | ||
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| size_t count; | ||
| }; | ||
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| #define MAX_WINDOW_SIZE 10 | ||
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| static inline void set_alpha(RRDR *r, struct grouping_des *g) { | ||
| // https://en.wikipedia.org/wiki/Moving_average#Exponential_moving_average | ||
| // A commonly used value for alpha is 2 / (N + 1) | ||
| calculated_number window = (r->group > MAX_WINDOW_SIZE) ? MAX_WINDOW_SIZE : r->group; | ||
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| g->alpha = 2.0 / ((calculated_number)window + 1.0); | ||
| g->alpha_other = 1.0 - g->alpha; | ||
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| //info("alpha for chart '%s' is " CALCULATED_NUMBER_FORMAT, r->st->name, g->alpha); | ||
| } | ||
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| static inline void set_beta(RRDR *r, struct grouping_des *g) { | ||
| // https://en.wikipedia.org/wiki/Moving_average#Exponential_moving_average | ||
| // A commonly used value for alpha is 2 / (N + 1) | ||
| calculated_number window = (r->group > MAX_WINDOW_SIZE) ? MAX_WINDOW_SIZE : r->group; | ||
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| g->beta = 2.0 / ((calculated_number)window + 1.0); | ||
| g->beta_other = 1.0 - g->beta; | ||
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| //info("beta for chart '%s' is " CALCULATED_NUMBER_FORMAT, r->st->name, g->beta); | ||
| } | ||
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| void *grouping_init_des(RRDR *r) { | ||
| struct grouping_des *g = (struct grouping_des *)malloc(sizeof(struct grouping_des)); | ||
| set_alpha(r, g); | ||
| set_beta(r, g); | ||
| g->level = 0.0; | ||
| g->trend = 0.0; | ||
| g->count = 0; | ||
| return g; | ||
| } | ||
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| // resets when switches dimensions | ||
| // so, clear everything to restart | ||
| void grouping_reset_des(RRDR *r) { | ||
| struct grouping_des *g = (struct grouping_des *)r->grouping_data; | ||
| g->level = 0.0; | ||
| g->trend = 0.0; | ||
| g->count = 0; | ||
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| // fprintf(stderr, "\nDES: "); | ||
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| } | ||
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| void grouping_free_des(RRDR *r) { | ||
| freez(r->grouping_data); | ||
| r->grouping_data = NULL; | ||
| } | ||
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| void grouping_add_des(RRDR *r, calculated_number value) { | ||
| struct grouping_des *g = (struct grouping_des *)r->grouping_data; | ||
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| if(isnormal(value)) { | ||
| if(likely(g->count > 0)) { | ||
| // we have at least a number so far | ||
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| if(unlikely(g->count == 1)) { | ||
| // the second value we got | ||
| g->trend = value - g->trend; | ||
| g->level = value; | ||
| } | ||
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| // for the values, except the first | ||
| calculated_number last_level = g->level; | ||
| g->level = (g->alpha * value) + (g->alpha_other * (g->level + g->trend)); | ||
| g->trend = (g->beta * (g->level - last_level)) + (g->beta_other * g->trend); | ||
| } | ||
| else { | ||
| // the first value we got | ||
| g->level = g->trend = value; | ||
| } | ||
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| g->count++; | ||
| } | ||
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| //fprintf(stderr, "value: " CALCULATED_NUMBER_FORMAT ", level: " CALCULATED_NUMBER_FORMAT ", trend: " CALCULATED_NUMBER_FORMAT "\n", value, g->level, g->trend); | ||
| } | ||
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| calculated_number grouping_flush_des(RRDR *r, RRDR_VALUE_FLAGS *rrdr_value_options_ptr) { | ||
| struct grouping_des *g = (struct grouping_des *)r->grouping_data; | ||
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| if(unlikely(!g->count || !isnormal(g->level))) { | ||
| *rrdr_value_options_ptr |= RRDR_VALUE_EMPTY; | ||
| return 0.0; | ||
| } | ||
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| //fprintf(stderr, " RESULT for %zu values = " CALCULATED_NUMBER_FORMAT " \n", g->count, g->level); | ||
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| return g->level; | ||
| } |
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| // SPDX-License-Identifier: GPL-3.0-or-later | ||
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| #ifndef NETDATA_API_QUERIES_DES_H | ||
| #define NETDATA_API_QUERIES_DES_H | ||
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| #include "../query.h" | ||
| #include "../rrdr.h" | ||
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| extern void *grouping_init_des(RRDR *r); | ||
| extern void grouping_reset_des(RRDR *r); | ||
| extern void grouping_free_des(RRDR *r); | ||
| extern void grouping_add_des(RRDR *r, calculated_number value); | ||
| extern calculated_number grouping_flush_des(RRDR *r, RRDR_VALUE_FLAGS *rrdr_value_options_ptr); | ||
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| #endif //NETDATA_API_QUERIES_DES_H |
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| Original file line number | Diff line number | Diff line change |
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| @@ -1 +1,45 @@ | ||
| # single exponential smoothing | ||
| # Single (or Simple) Exponential Smoothing (`ses`) | ||
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| > This query is also available as `ema` and `ewma`. | ||
| An exponential moving average (`ema`), also known as an exponentially weighted moving average (`ewma`) | ||
| is a first-order infinite impulse response filter that applies weighting factors which decrease | ||
| exponentially. The weighting for each older datum decreases exponentially, never reaching zero. | ||
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| In simple terms, this is like an average value, but more recent values are given more weight. | ||
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| Netdata automatically adjusts the weight based on the number of values processed, using the formula: | ||
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| ``` | ||
| alpha = 2 / (number_of_values + 1) | ||
| ``` | ||
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| ## how to use | ||
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| Use it in alarms like this: | ||
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| ``` | ||
| alarm: my_alarm | ||
| on: my_chart | ||
| lookup: ses -1m unaligned of my_dimension | ||
| warn: $this > 1000 | ||
| ``` | ||
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| `ses` does not change the units. For example, if the chart units is `requests/sec`, the exponential | ||
| moving average will be again expressed in the same units. | ||
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| It can also be used in APIs and badges as `&group=ses` in the URL. | ||
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| ## Examples | ||
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| Examining last 1 minute `successful` web server responses: | ||
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| -  | ||
| -  | ||
| -  | ||
| -  | ||
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| ## References | ||
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| - [https://en.wikipedia.org/wiki/Moving_average#exponential-moving-average](https://en.wikipedia.org/wiki/Moving_average#exponential-moving-average) | ||
| - [https://en.wikipedia.org/wiki/Exponential_smoothing](https://en.wikipedia.org/wiki/Exponential_smoothing). |
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