mirror of
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app/{vlselect,vmselect}: run make vmui-update vmui-logs-update
This commit is contained in:
Aliaksandr Valialkin
parent
453988e244
commit
d3635aae7f
16 changed files with 328 additions and 328 deletions
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@ -1,13 +1,13 @@
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{
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"files": {
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"main.css": "./static/css/main.bc07cc78.css",
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"main.js": "./static/js/main.034044a7.js",
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"main.js": "./static/js/main.8e7757ef.js",
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"static/js/685.bebe1265.chunk.js": "./static/js/685.bebe1265.chunk.js",
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"static/media/MetricsQL.md": "./static/media/MetricsQL.10add6e7bdf0f1d98cf7.md",
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"static/media/MetricsQL.md": "./static/media/MetricsQL.da86c2db4f0b05e286b0.md",
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"index.html": "./index.html"
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},
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"entrypoints": [
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"static/css/main.bc07cc78.css",
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"static/js/main.034044a7.js"
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"static/js/main.8e7757ef.js"
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]
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}
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@ -1 +1 @@
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<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.034044a7.js"></script><link href="./static/css/main.bc07cc78.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
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<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.8e7757ef.js"></script><link href="./static/css/main.bc07cc78.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
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2
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app/vlselect/vmui/static/js/main.8e7757ef.js
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@ -22,7 +22,7 @@ However, there are some [intentional differences](https://medium.com/@romanhavro
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[Standalone MetricsQL package](https://godoc.org/github.com/VictoriaMetrics/metricsql) can be used for parsing MetricsQL in external apps.
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If you are unfamiliar with PromQL, then it is suggested reading [this tutorial for beginners](https://medium.com/@valyala/promql-tutorial-for-beginners-9ab455142085)
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and introduction into [basic querying via MetricsQL](https://docs.victoriametrics.com/keyConcepts.html#metricsql).
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and introduction into [basic querying via MetricsQL](https://docs.victoriametrics.com/keyconcepts/#metricsql).
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The following functionality is implemented differently in MetricsQL compared to PromQL. This improves user experience:
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@ -70,15 +70,15 @@ The list of MetricsQL features on top of PromQL:
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VictoriaMetrics can be used as Graphite datasource in Grafana. See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
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See also [label_graphite_group](#label_graphite_group) function, which can be used for extracting the given groups from Graphite metric name.
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* Lookbehind window in square brackets for [rollup functions](#rollup-functions) may be omitted. VictoriaMetrics automatically selects the lookbehind window
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depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)
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depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query)
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and the real interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) (aka `scrape_interval`).
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For instance, the following query is valid in VictoriaMetrics: `rate(node_network_receive_bytes_total)`.
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It is roughly equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
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The difference is documented in [rate() docs](#rate).
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* Numeric values can contain `_` delimiters for better readability. For example, `1_234_567_890` can be used in queries instead of `1234567890`.
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* [Series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
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* [Series selectors](https://docs.victoriametrics.com/keyconcepts/#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
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selects series with `{env="prod",job="a"}` or `{env="dev",job="b"}` labels.
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See [these docs](https://docs.victoriametrics.com/keyConcepts.html#filtering-by-multiple-or-filters) for details.
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See [these docs](https://docs.victoriametrics.com/keyconcepts/#filtering-by-multiple-or-filters) for details.
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* Support for `group_left(*)` and `group_right(*)` for copying all the labels from time series on the `one` side
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of [many-to-one operations](https://prometheus.io/docs/prometheus/latest/querying/operators/#many-to-one-and-one-to-many-vector-matches).
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The copied label names may clash with the existing label names, so MetricsQL provides an ability to add prefix to the copied metric names
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@ -153,26 +153,26 @@ MetricsQL provides the following functions:
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### Rollup functions
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**Rollup functions** (aka range functions or window functions) calculate rollups over **raw samples**
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on the given lookbehind window for the [selected time series](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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on the given lookbehind window for the [selected time series](https://docs.victoriametrics.com/keyconcepts/#filtering).
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For example, `avg_over_time(temperature[24h])` calculates the average temperature over raw samples for the last 24 hours.
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Additional details:
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* If rollup functions are used for building graphs in Grafana, then the rollup is calculated independently per each point on the graph.
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For example, every point for `avg_over_time(temperature[24h])` graph shows the average temperature for the last 24 hours ending at this point.
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The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
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* If the given [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) returns multiple time series,
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The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
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* If the given [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) returns multiple time series,
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then rollups are calculated individually per each returned series.
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* If lookbehind window in square brackets is missing, then it is automatically set to the following value:
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- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
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- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
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for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
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For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
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- To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
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for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
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* Every [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) in MetricsQL must be wrapped into a rollup function.
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* Every [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) in MetricsQL must be wrapped into a rollup function.
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Otherwise, it is automatically wrapped into [default_rollup](#default_rollup). For example, `foo{bar="baz"}`
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is automatically converted to `default_rollup(foo{bar="baz"})` before performing the calculations.
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* If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) is passed to rollup function,
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* If something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) is passed to rollup function,
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then the inner arg is automatically converted to a [subquery](#subqueries).
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* All the rollup functions accept optional `keep_metric_names` modifier. If it is set, then the function keeps metric names in results.
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See [these docs](#keep_metric_names).
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@ -195,7 +195,7 @@ See also [present_over_time](#present_over_time).
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`aggr_over_time(("rollup_func1", "rollup_func2", ...), series_selector[d])` is a [rollup function](#rollup-functions),
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which calculates all the listed `rollup_func*` for raw samples on the given lookbehind window `d`.
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The calculations are performed individually per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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`rollup_func*` can contain any rollup function. For instance, `aggr_over_time(("min_over_time", "max_over_time", "rate"), m[d])`
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would calculate [min_over_time](#min_over_time), [max_over_time](#max_over_time) and [rate](#rate) for `m[d]`.
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@ -204,7 +204,7 @@ would calculate [min_over_time](#min_over_time), [max_over_time](#max_over_time)
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`ascent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates
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ascent of raw sample values on the given lookbehind window `d`. The calculations are performed individually
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per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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This function is useful for tracking height gains in GPS tracking. Metric names are stripped from the resulting rollups.
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@ -216,7 +216,7 @@ See also [descent_over_time](#descent_over_time).
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`avg_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average value
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over raw samples on the given lookbehind window `d` per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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This function is supported by PromQL.
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@ -226,7 +226,7 @@ See also [median_over_time](#median_over_time).
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`changes(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of times
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the raw samples changed on the given lookbehind window `d` per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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Unlike `changes()` in Prometheus it takes into account the change from the last sample before the given lookbehind window `d`.
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See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
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@ -241,7 +241,7 @@ See also [changes_prometheus](#changes_prometheus).
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`changes_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of times
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the raw samples changed on the given lookbehind window `d` per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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It doesn't take into account the change from the last sample before the given lookbehind window `d` in the same way as Prometheus does.
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See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
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@ -256,7 +256,7 @@ See also [changes](#changes).
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`count_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
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on the given lookbehind window `d`, which are equal to `eq`. It is calculated independently per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
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@ -266,7 +266,7 @@ See also [count_over_time](#count_over_time), [share_eq_over_time](#share_eq_ove
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`count_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
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on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
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@ -276,7 +276,7 @@ See also [count_over_time](#count_over_time) and [share_gt_over_time](#share_gt_
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`count_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
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on the given lookbehind window `d`, which don't exceed `le`. It is calculated independently per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
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@ -286,7 +286,7 @@ See also [count_over_time](#count_over_time) and [share_le_over_time](#share_le_
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`count_ne_over_time(series_selector[d], ne)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
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on the given lookbehind window `d`, which aren't equal to `ne`. It is calculated independently per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
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@ -295,7 +295,7 @@ See also [count_over_time](#count_over_time).
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#### count_over_time
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`count_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw samples
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on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
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@ -307,7 +307,7 @@ See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_
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`count_values_over_time("label", series_selector[d])` is a [rollup function](#rollup-functions), which counts the number of raw samples
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with the same value over the given lookbehind window and stores the counts in a time series with an additional `label`, which contains each initial value.
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The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
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@ -316,7 +316,7 @@ See also [count_eq_over_time](#count_eq_over_time), [count_values](#count_values
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#### decreases_over_time
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`decreases_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw sample value decreases
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over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
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@ -325,7 +325,7 @@ See also [increases_over_time](#increases_over_time).
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#### default_rollup
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`default_rollup(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
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per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
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passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
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@ -336,7 +336,7 @@ This allows avoiding unexpected gaps on the graph when `step` is smaller than th
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`delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
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the last sample before the given lookbehind window `d` and the last sample at the given lookbehind window `d`
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per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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The behaviour of `delta()` function in MetricsQL is slightly different to the behaviour of `delta()` function in Prometheus.
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See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
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@ -351,7 +351,7 @@ See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
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`delta_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
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the first and the last samples at the given lookbehind window `d` per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
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The behaviour of `delta_prometheus()` is close to the behaviour of `delta()` function in Prometheus.
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See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
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@ -363,7 +363,7 @@ See also [delta](#delta).
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#### deriv
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`deriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivative over the given lookbehind window `d`
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per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
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per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The derivative is calculated using linear regression.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
|
@ -376,7 +376,7 @@ See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
|
|||
|
||||
`deriv_fast(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivative
|
||||
using the first and the last raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -386,7 +386,7 @@ See also [deriv](#deriv) and [ideriv](#ideriv).
|
|||
|
||||
`descent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates descent of raw sample values
|
||||
on the given lookbehind window `d`. The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for tracking height loss in GPS tracking.
|
||||
|
||||
|
|
@ -397,7 +397,7 @@ See also [ascent_over_time](#ascent_over_time).
|
|||
#### distinct_over_time
|
||||
|
||||
`distinct_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the number of distinct raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -406,7 +406,7 @@ See also [count_values_over_time](#count_values_over_time).
|
|||
#### duration_over_time
|
||||
|
||||
`duration_over_time(series_selector[d], max_interval)` is a [rollup function](#rollup-functions), which returns the duration in seconds
|
||||
when time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) were present
|
||||
when time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering) were present
|
||||
over the given lookbehind window `d`. It is expected that intervals between adjacent samples per each series don't exceed the `max_interval`.
|
||||
Otherwise, such intervals are considered as gaps and aren't counted.
|
||||
|
||||
|
|
@ -417,7 +417,7 @@ See also [lifetime](#lifetime) and [lag](#lag).
|
|||
#### first_over_time
|
||||
|
||||
`first_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the first raw sample value
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [last_over_time](#last_over_time) and [tfirst_over_time](#tfirst_over_time).
|
||||
|
||||
|
|
@ -425,7 +425,7 @@ See also [last_over_time](#last_over_time) and [tfirst_over_time](#tfirst_over_t
|
|||
|
||||
`geomean_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [geometric mean](https://en.wikipedia.org/wiki/Geometric_mean)
|
||||
over raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -433,9 +433,9 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
|
||||
`histogram_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates
|
||||
[VictoriaMetrics histogram](https://godoc.org/github.com/VictoriaMetrics/metrics#Histogram) over raw samples on the given lookbehind window `d`.
|
||||
It is calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The resulting histograms are useful to pass to [histogram_quantile](#histogram_quantile) for calculating quantiles
|
||||
over multiple [gauges](https://docs.victoriametrics.com/keyConcepts.html#gauge).
|
||||
over multiple [gauges](https://docs.victoriametrics.com/keyconcepts/#gauge).
|
||||
For example, the following query calculates median temperature by country over the last 24 hours:
|
||||
|
||||
`histogram_quantile(0.5, sum(histogram_over_time(temperature[24h])) by (vmrange,country))`.
|
||||
|
|
@ -459,8 +459,8 @@ See also [hoeffding_bound_lower](#hoeffding_bound_lower).
|
|||
`holt_winters(series_selector[d], sf, tf)` is a [rollup function](#rollup-functions), which calculates Holt-Winters value
|
||||
(aka [double exponential smoothing](https://en.wikipedia.org/wiki/Exponential_smoothing#Double_exponential_smoothing)) for raw samples
|
||||
over the given lookbehind window `d` using the given smoothing factor `sf` and the given trend factor `tf`.
|
||||
Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
|
||||
returns time series of [gauge type](https://docs.victoriametrics.com/keyConcepts.html#gauge).
|
||||
Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering)
|
||||
returns time series of [gauge type](https://docs.victoriametrics.com/keyconcepts/#gauge).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -469,7 +469,7 @@ See also [range_linear_regression](#range_linear_regression).
|
|||
#### idelta
|
||||
|
||||
`idelta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between the last two raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -481,7 +481,7 @@ See also [delta](#delta).
|
|||
|
||||
`ideriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the per-second derivative based on the last two raw samples
|
||||
over the given lookbehind window `d`. The derivative is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -490,8 +490,8 @@ See also [deriv](#deriv).
|
|||
#### increase
|
||||
|
||||
`increase(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the increase over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Unlike Prometheus, it takes into account the last sample before the given lookbehind window `d` when calculating the result.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -505,8 +505,8 @@ See also [increase_pure](#increase_pure), [increase_prometheus](#increase_promet
|
|||
#### increase_prometheus
|
||||
|
||||
`increase_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the increase
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
It doesn't take into account the last sample before the given lookbehind window `d` when calculating the result in the same way as Prometheus does.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
||||
|
|
@ -517,13 +517,13 @@ See also [increase_pure](#increase_pure) and [increase](#increase).
|
|||
#### increase_pure
|
||||
|
||||
`increase_pure(series_selector[d])` is a [rollup function](#rollup-functions), which works the same as [increase](#increase) except
|
||||
of the following corner case - it assumes that [counters](https://docs.victoriametrics.com/keyConcepts.html#counter) always start from 0,
|
||||
of the following corner case - it assumes that [counters](https://docs.victoriametrics.com/keyconcepts/#counter) always start from 0,
|
||||
while [increase](#increase) ignores the first value in a series if it is too big.
|
||||
|
||||
#### increases_over_time
|
||||
|
||||
`increases_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw sample value increases
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -532,15 +532,15 @@ See also [decreases_over_time](#decreases_over_time).
|
|||
#### integrate
|
||||
|
||||
`integrate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the integral over raw samples on the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### irate
|
||||
|
||||
`irate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the "instant" per-second increase rate over the last two raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -552,7 +552,7 @@ See also [rate](#rate) and [rollup_rate](#rollup_rate).
|
|||
|
||||
`lag(series_selector[d])` is a [rollup function](#rollup-functions), which returns the duration in seconds between the last sample
|
||||
on the given lookbehind window `d` and the timestamp of the current point. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -561,7 +561,7 @@ See also [lifetime](#lifetime) and [duration_over_time](#duration_over_time).
|
|||
#### last_over_time
|
||||
|
||||
`last_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -570,7 +570,7 @@ See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_t
|
|||
#### lifetime
|
||||
|
||||
`lifetime(series_selector[d])` is a [rollup function](#rollup-functions), which returns the duration in seconds between the last and the first sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -579,14 +579,14 @@ See also [duration_over_time](#duration_over_time) and [lag](#lag).
|
|||
#### mad_over_time
|
||||
|
||||
`mad_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [median absolute deviation](https://en.wikipedia.org/wiki/Median_absolute_deviation)
|
||||
over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [mad](#mad), [range_mad](#range_mad) and [outlier_iqr_over_time](#outlier_iqr_over_time).
|
||||
|
||||
#### max_over_time
|
||||
|
||||
`max_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the maximum value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -596,14 +596,14 @@ See also [tmax_over_time](#tmax_over_time).
|
|||
|
||||
`median_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates median value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [avg_over_time](#avg_over_time).
|
||||
|
||||
#### min_over_time
|
||||
|
||||
`min_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the minimum value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -613,7 +613,7 @@ See also [tmin_over_time](#tmin_over_time).
|
|||
|
||||
`mode_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [mode](https://en.wikipedia.org/wiki/Mode_(statistics))
|
||||
for raw samples on the given lookbehind window `d`. It is calculated individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). It is expected that raw sample values are discrete.
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering). It is expected that raw sample values are discrete.
|
||||
|
||||
#### outlier_iqr_over_time
|
||||
|
||||
|
|
@ -631,7 +631,7 @@ See also [outliers_iqr](#outliers_iqr).
|
|||
|
||||
`predict_linear(series_selector[d], t)` is a [rollup function](#rollup-functions), which calculates the value `t` seconds in the future using
|
||||
linear interpolation over raw samples on the given lookbehind window `d`. The predicted value is calculated individually per each time series
|
||||
returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -649,7 +649,7 @@ This function is supported by PromQL.
|
|||
#### quantile_over_time
|
||||
|
||||
`quantile_over_time(phi, series_selector[d])` is a [rollup function](#rollup-functions), which calculates `phi`-quantile over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The `phi` value must be in the range `[0...1]`.
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
|
@ -660,7 +660,7 @@ See also [quantiles_over_time](#quantiles_over_time).
|
|||
|
||||
`quantiles_over_time("phiLabel", phi1, ..., phiN, series_selector[d])` is a [rollup function](#rollup-functions), which calculates `phi*`-quantiles
|
||||
over raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The function returns individual series per each `phi*` with `{phiLabel="phi*"}` label. `phi*` values must be in the range `[0...1]`.
|
||||
|
||||
See also [quantile_over_time](#quantile_over_time).
|
||||
|
|
@ -668,7 +668,7 @@ See also [quantile_over_time](#quantile_over_time).
|
|||
#### range_over_time
|
||||
|
||||
`range_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates value range over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
E.g. it calculates `max_over_time(series_selector[d]) - min_over_time(series_selector[d])`.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
|
@ -676,8 +676,8 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
#### rate
|
||||
|
||||
`rate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average per-second increase rate
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
|
||||
passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
|
||||
|
|
@ -694,16 +694,16 @@ See also [irate](#irate) and [rollup_rate](#rollup_rate).
|
|||
|
||||
`rate_over_sum(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second rate over the sum of raw samples
|
||||
on the given lookbehind window `d`. The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### resets
|
||||
|
||||
`resets(series_selector[d])` is a [rollup function](#rollup-functions), which returns the number
|
||||
of [counter](https://docs.victoriametrics.com/keyConcepts.html#counter) resets over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
of [counter](https://docs.victoriametrics.com/keyconcepts/#counter) resets over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -713,7 +713,7 @@ This function is supported by PromQL.
|
|||
|
||||
`rollup(series_selector[d])` is a [rollup function](#rollup-functions), which calculates `min`, `max` and `avg` values for raw samples
|
||||
on the given lookbehind window `d` and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -723,7 +723,7 @@ See also [label_match](#label_match).
|
|||
`rollup_candlestick(series_selector[d])` is a [rollup function](#rollup-functions), which calculates `open`, `high`, `low` and `close` values (aka OHLC)
|
||||
over raw samples on the given lookbehind window `d` and returns them in time series with `rollup="open"`, `rollup="high"`, `rollup="low"` and `rollup="close"` additional labels.
|
||||
The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). This function is useful for financial applications.
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering). This function is useful for financial applications.
|
||||
|
||||
Optional 2nd argument `"open"`, `"high"` or `"low"` or `"close"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -733,7 +733,7 @@ See also [label_match](#label_match).
|
|||
`rollup_delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates differences between adjacent raw samples
|
||||
on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated differences
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -747,7 +747,7 @@ See also [rollup_increase](#rollup_increase).
|
|||
`rollup_deriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivatives
|
||||
for adjacent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated per-second derivatives
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -759,7 +759,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
`rollup_increase(series_selector[d])` is a [rollup function](#rollup-functions), which calculates increases for adjacent raw samples
|
||||
on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated increases
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -778,7 +778,7 @@ when to use `rollup_rate()`.
|
|||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -787,7 +787,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
`rollup_scrape_interval(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the interval in seconds between
|
||||
adjacent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated interval
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -797,7 +797,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
#### scrape_interval
|
||||
|
||||
`scrape_interval(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average interval in seconds between raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -807,7 +807,7 @@ See also [rollup_scrape_interval](#rollup_scrape_interval).
|
|||
|
||||
`share_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for calculating SLI and SLO. Example: `share_gt_over_time(up[24h], 0)` - returns service availability for the last 24 hours.
|
||||
|
||||
|
|
@ -819,7 +819,7 @@ See also [share_le_over_time](#share_le_over_time) and [count_gt_over_time](#cou
|
|||
|
||||
`share_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are smaller or equal to `le`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for calculating SLI and SLO. Example: `share_le_over_time(memory_usage_bytes[24h], 100*1024*1024)` returns
|
||||
the share of time series values for the last 24 hours when memory usage was below or equal to 100MB.
|
||||
|
|
@ -832,7 +832,7 @@ See also [share_gt_over_time](#share_gt_over_time) and [count_le_over_time](#cou
|
|||
|
||||
`share_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are equal to `eq`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -841,15 +841,15 @@ See also [count_eq_over_time](#count_eq_over_time).
|
|||
#### stale_samples_over_time
|
||||
|
||||
`stale_samples_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number
|
||||
of [staleness markers](https://docs.victoriametrics.com/vmagent.html#prometheus-staleness-markers) on the given lookbehind window `d`
|
||||
per each time series matching the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
of [staleness markers](https://docs.victoriametrics.com/vmagent/#prometheus-staleness-markers) on the given lookbehind window `d`
|
||||
per each time series matching the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### stddev_over_time
|
||||
|
||||
`stddev_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard deviation over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -860,7 +860,7 @@ See also [stdvar_over_time](#stdvar_over_time).
|
|||
#### stdvar_over_time
|
||||
|
||||
`stdvar_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard variance over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -871,7 +871,7 @@ See also [stddev_over_time](#stddev_over_time).
|
|||
#### sum_eq_over_time
|
||||
|
||||
`sum_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values equal to `eq`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -880,7 +880,7 @@ See also [sum_over_time](#sum_over_time) and [count_eq_over_time](#count_eq_over
|
|||
#### sum_gt_over_time
|
||||
|
||||
`sum_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values bigger than `gt`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -889,7 +889,7 @@ See also [sum_over_time](#sum_over_time) and [count_gt_over_time](#count_gt_over
|
|||
#### sum_le_over_time
|
||||
|
||||
`sum_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values smaller or equal to `le`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -898,7 +898,7 @@ See also [sum_over_time](#sum_over_time) and [count_le_over_time](#count_le_over
|
|||
#### sum_over_time
|
||||
|
||||
`sum_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the sum of raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -907,14 +907,14 @@ This function is supported by PromQL.
|
|||
#### sum2_over_time
|
||||
|
||||
`sum2_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the sum of squares for raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### timestamp
|
||||
|
||||
`timestamp(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -925,7 +925,7 @@ See also [time](#time) and [now](#now).
|
|||
#### timestamp_with_name
|
||||
|
||||
`timestamp_with_name(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are preserved in the resulting rollups.
|
||||
|
||||
|
|
@ -934,7 +934,7 @@ See also [timestamp](#timestamp) and [keep_metric_names](#keep_metric_names) mod
|
|||
#### tfirst_over_time
|
||||
|
||||
`tfirst_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the first raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -943,7 +943,7 @@ See also [first_over_time](#first_over_time).
|
|||
#### tlast_change_over_time
|
||||
|
||||
`tlast_change_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last change
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) on the given lookbehind window `d`.
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering) on the given lookbehind window `d`.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -959,7 +959,7 @@ See also [tlast_change_over_time](#tlast_change_over_time).
|
|||
|
||||
`tmax_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the raw sample
|
||||
with the maximum value on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -969,7 +969,7 @@ See also [max_over_time](#max_over_time).
|
|||
|
||||
`tmin_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the raw sample
|
||||
with the minimum value on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -979,7 +979,7 @@ See also [min_over_time](#min_over_time).
|
|||
|
||||
`zscore_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns [z-score](https://en.wikipedia.org/wiki/Standard_score)
|
||||
for raw samples on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -994,7 +994,7 @@ returned from the rollup `delta(temperature[24h])`.
|
|||
|
||||
Additional details:
|
||||
|
||||
* If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before calculating the transformations.
|
||||
For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature))`.
|
||||
* All the transform functions accept optional `keep_metric_names` modifier. If it is set,
|
||||
|
|
@ -1230,7 +1230,7 @@ by replacing all the values bigger or equal to 30 with 40.
|
|||
#### end
|
||||
|
||||
`end()` is a [transform function](#transform-functions), which returns the unix timestamp in seconds for the last point.
|
||||
It is known as `end` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `end` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [start](#start), [time](#time) and [now](#now).
|
||||
|
||||
|
|
@ -1653,14 +1653,14 @@ This function is supported by PromQL.
|
|||
|
||||
`start()` is a [transform function](#transform-functions), which returns unix timestamp in seconds for the first point.
|
||||
|
||||
It is known as `start` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `start` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [end](#end), [time](#time) and [now](#now).
|
||||
|
||||
#### step
|
||||
|
||||
`step()` is a [transform function](#transform-functions), which returns the step in seconds (aka interval) between the returned points.
|
||||
It is known as `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [start](#start) and [end](#end).
|
||||
|
||||
|
|
@ -1717,7 +1717,7 @@ This function is supported by PromQL.
|
|||
|
||||
Additional details:
|
||||
|
||||
* If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before performing the label transformation.
|
||||
For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature), "foo")`.
|
||||
|
||||
|
|
@ -1894,7 +1894,7 @@ Additional details:
|
|||
and calculate the [count](#count) aggregate function independently per each group, while `count(up) without (instance)`
|
||||
would group [rollup results](#rollup-functions) by all the labels except `instance` before calculating [count](#count) aggregate function independently per each group.
|
||||
Multiple labels can be put in `by` and `without` modifiers.
|
||||
* If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before calculating the aggregate.
|
||||
For example, `count(up)` is implicitly transformed to `count(default_rollup(up))`.
|
||||
* Aggregate functions accept arbitrary number of args. For example, `avg(q1, q2, q3)` would return the average values for every point
|
||||
|
|
@ -2104,7 +2104,7 @@ See also [quantile](#quantile).
|
|||
`share(q) by (group_labels)` is [aggregate function](#aggregate-functions), which returns shares in the range `[0..1]`
|
||||
for every non-negative points returned by `q` per each timestamp, so the sum of shares per each `group_labels` equals 1.
|
||||
|
||||
This function is useful for normalizing [histogram bucket](https://docs.victoriametrics.com/keyConcepts.html#histogram) shares
|
||||
This function is useful for normalizing [histogram bucket](https://docs.victoriametrics.com/keyconcepts/#histogram) shares
|
||||
into `[0..1]` range:
|
||||
|
||||
```metricsql
|
||||
|
|
@ -2208,7 +2208,7 @@ See also [zscore_over_time](#zscore_over_time), [range_trim_zscore](#range_trim_
|
|||
## Subqueries
|
||||
|
||||
MetricsQL supports and extends PromQL subqueries. See [this article](https://valyala.medium.com/prometheus-subqueries-in-victoriametrics-9b1492b720b3) for details.
|
||||
Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) form a subquery.
|
||||
Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) form a subquery.
|
||||
Nested rollup functions can be implicit thanks to the [implicit query conversions](#implicit-query-conversions).
|
||||
For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m))[1i:1i])`, so it becomes a subquery,
|
||||
since it contains [default_rollup](#default_rollup) nested into [delta](#delta).
|
||||
|
|
@ -2219,19 +2219,19 @@ VictoriaMetrics performs subqueries in the following way:
|
|||
For example, for expression `max_over_time(rate(http_requests_total[5m])[1h:30s])` the inner function `rate(http_requests_total[5m])`
|
||||
is calculated with `step=30s`. The resulting data points are aligned by the `step`.
|
||||
* It calculates the outer rollup function over the results of the inner rollup function using the `step` value
|
||||
passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
## Implicit query conversions
|
||||
|
||||
VictoriaMetrics performs the following implicit conversions for incoming queries before starting the calculations:
|
||||
|
||||
* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions), then it is automatically set to the following value:
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
|
||||
For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
|
||||
- To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
|
||||
for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
|
||||
* All the [series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* All the [series selectors](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
which aren't wrapped into [rollup functions](#rollup-functions), are automatically wrapped into [default_rollup](#default_rollup) function.
|
||||
Examples:
|
||||
* `foo` is transformed to `default_rollup(foo)`
|
||||
|
|
@ -2242,6 +2242,6 @@ VictoriaMetrics performs the following implicit conversions for incoming queries
|
|||
it is [transform function](#transform-functions)
|
||||
* If `step` in square brackets is missing inside [subquery](#subqueries), then `1i` step is automatically added there.
|
||||
For example, `avg_over_time(rate(http_requests_total[5m])[1h])` is automatically converted to `avg_over_time(rate(http_requests_total[5m])[1h:1i])`.
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering)
|
||||
is passed to [rollup function](#rollup-functions), then a [subquery](#subqueries) with `1i` lookbehind window and `1i` step is automatically formed.
|
||||
For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up)))[1i:1i])`.
|
||||
|
|
@ -1,13 +1,13 @@
|
|||
{
|
||||
"files": {
|
||||
"main.css": "./static/css/main.a2ad4674.css",
|
||||
"main.js": "./static/js/main.f9cc1e6c.js",
|
||||
"main.css": "./static/css/main.4ebf2874.css",
|
||||
"main.js": "./static/js/main.202937c2.js",
|
||||
"static/js/685.bebe1265.chunk.js": "./static/js/685.bebe1265.chunk.js",
|
||||
"static/media/MetricsQL.md": "./static/media/MetricsQL.10add6e7bdf0f1d98cf7.md",
|
||||
"static/media/MetricsQL.md": "./static/media/MetricsQL.da86c2db4f0b05e286b0.md",
|
||||
"index.html": "./index.html"
|
||||
},
|
||||
"entrypoints": [
|
||||
"static/css/main.a2ad4674.css",
|
||||
"static/js/main.f9cc1e6c.js"
|
||||
"static/css/main.4ebf2874.css",
|
||||
"static/js/main.202937c2.js"
|
||||
]
|
||||
}
|
||||
|
|
@ -1,3 +1,3 @@
|
|||
## Predefined dashboards
|
||||
|
||||
See [this docs](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/master/app/vmui#predefined-dashboards)
|
||||
See [this doc](https://github.com/VictoriaMetrics/VictoriaMetrics/tree/master/app/vmui#predefined-dashboards)
|
||||
|
|
|
|||
|
|
@ -1 +1 @@
|
|||
<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.f9cc1e6c.js"></script><link href="./static/css/main.a2ad4674.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
|
||||
<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.202937c2.js"></script><link href="./static/css/main.4ebf2874.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
|
||||
1
app/vmselect/vmui/static/css/main.4ebf2874.css
Normal file
1
app/vmselect/vmui/static/css/main.4ebf2874.css
Normal file
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
2
app/vmselect/vmui/static/js/main.202937c2.js
Normal file
2
app/vmselect/vmui/static/js/main.202937c2.js
Normal file
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
|
|
@ -22,7 +22,7 @@ However, there are some [intentional differences](https://medium.com/@romanhavro
|
|||
[Standalone MetricsQL package](https://godoc.org/github.com/VictoriaMetrics/metricsql) can be used for parsing MetricsQL in external apps.
|
||||
|
||||
If you are unfamiliar with PromQL, then it is suggested reading [this tutorial for beginners](https://medium.com/@valyala/promql-tutorial-for-beginners-9ab455142085)
|
||||
and introduction into [basic querying via MetricsQL](https://docs.victoriametrics.com/keyConcepts.html#metricsql).
|
||||
and introduction into [basic querying via MetricsQL](https://docs.victoriametrics.com/keyconcepts/#metricsql).
|
||||
|
||||
The following functionality is implemented differently in MetricsQL compared to PromQL. This improves user experience:
|
||||
|
||||
|
|
@ -70,15 +70,15 @@ The list of MetricsQL features on top of PromQL:
|
|||
VictoriaMetrics can be used as Graphite datasource in Grafana. See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
|
||||
See also [label_graphite_group](#label_graphite_group) function, which can be used for extracting the given groups from Graphite metric name.
|
||||
* Lookbehind window in square brackets for [rollup functions](#rollup-functions) may be omitted. VictoriaMetrics automatically selects the lookbehind window
|
||||
depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)
|
||||
depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query)
|
||||
and the real interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) (aka `scrape_interval`).
|
||||
For instance, the following query is valid in VictoriaMetrics: `rate(node_network_receive_bytes_total)`.
|
||||
It is roughly equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
|
||||
The difference is documented in [rate() docs](#rate).
|
||||
* Numeric values can contain `_` delimiters for better readability. For example, `1_234_567_890` can be used in queries instead of `1234567890`.
|
||||
* [Series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
|
||||
* [Series selectors](https://docs.victoriametrics.com/keyconcepts/#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
|
||||
selects series with `{env="prod",job="a"}` or `{env="dev",job="b"}` labels.
|
||||
See [these docs](https://docs.victoriametrics.com/keyConcepts.html#filtering-by-multiple-or-filters) for details.
|
||||
See [these docs](https://docs.victoriametrics.com/keyconcepts/#filtering-by-multiple-or-filters) for details.
|
||||
* Support for `group_left(*)` and `group_right(*)` for copying all the labels from time series on the `one` side
|
||||
of [many-to-one operations](https://prometheus.io/docs/prometheus/latest/querying/operators/#many-to-one-and-one-to-many-vector-matches).
|
||||
The copied label names may clash with the existing label names, so MetricsQL provides an ability to add prefix to the copied metric names
|
||||
|
|
@ -153,26 +153,26 @@ MetricsQL provides the following functions:
|
|||
### Rollup functions
|
||||
|
||||
**Rollup functions** (aka range functions or window functions) calculate rollups over **raw samples**
|
||||
on the given lookbehind window for the [selected time series](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window for the [selected time series](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
For example, `avg_over_time(temperature[24h])` calculates the average temperature over raw samples for the last 24 hours.
|
||||
|
||||
Additional details:
|
||||
|
||||
* If rollup functions are used for building graphs in Grafana, then the rollup is calculated independently per each point on the graph.
|
||||
For example, every point for `avg_over_time(temperature[24h])` graph shows the average temperature for the last 24 hours ending at this point.
|
||||
The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
* If the given [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) returns multiple time series,
|
||||
The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
* If the given [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) returns multiple time series,
|
||||
then rollups are calculated individually per each returned series.
|
||||
* If lookbehind window in square brackets is missing, then it is automatically set to the following value:
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
|
||||
For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
|
||||
- To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
|
||||
for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
|
||||
* Every [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) in MetricsQL must be wrapped into a rollup function.
|
||||
* Every [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) in MetricsQL must be wrapped into a rollup function.
|
||||
Otherwise, it is automatically wrapped into [default_rollup](#default_rollup). For example, `foo{bar="baz"}`
|
||||
is automatically converted to `default_rollup(foo{bar="baz"})` before performing the calculations.
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) is passed to rollup function,
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) is passed to rollup function,
|
||||
then the inner arg is automatically converted to a [subquery](#subqueries).
|
||||
* All the rollup functions accept optional `keep_metric_names` modifier. If it is set, then the function keeps metric names in results.
|
||||
See [these docs](#keep_metric_names).
|
||||
|
|
@ -195,7 +195,7 @@ See also [present_over_time](#present_over_time).
|
|||
`aggr_over_time(("rollup_func1", "rollup_func2", ...), series_selector[d])` is a [rollup function](#rollup-functions),
|
||||
which calculates all the listed `rollup_func*` for raw samples on the given lookbehind window `d`.
|
||||
The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
`rollup_func*` can contain any rollup function. For instance, `aggr_over_time(("min_over_time", "max_over_time", "rate"), m[d])`
|
||||
would calculate [min_over_time](#min_over_time), [max_over_time](#max_over_time) and [rate](#rate) for `m[d]`.
|
||||
|
|
@ -204,7 +204,7 @@ would calculate [min_over_time](#min_over_time), [max_over_time](#max_over_time)
|
|||
|
||||
`ascent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates
|
||||
ascent of raw sample values on the given lookbehind window `d`. The calculations are performed individually
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for tracking height gains in GPS tracking. Metric names are stripped from the resulting rollups.
|
||||
|
||||
|
|
@ -216,7 +216,7 @@ See also [descent_over_time](#descent_over_time).
|
|||
|
||||
`avg_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average value
|
||||
over raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -226,7 +226,7 @@ See also [median_over_time](#median_over_time).
|
|||
|
||||
`changes(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of times
|
||||
the raw samples changed on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Unlike `changes()` in Prometheus it takes into account the change from the last sample before the given lookbehind window `d`.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -241,7 +241,7 @@ See also [changes_prometheus](#changes_prometheus).
|
|||
|
||||
`changes_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of times
|
||||
the raw samples changed on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
It doesn't take into account the change from the last sample before the given lookbehind window `d` in the same way as Prometheus does.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -256,7 +256,7 @@ See also [changes](#changes).
|
|||
|
||||
`count_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d`, which are equal to `eq`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -266,7 +266,7 @@ See also [count_over_time](#count_over_time), [share_eq_over_time](#share_eq_ove
|
|||
|
||||
`count_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -276,7 +276,7 @@ See also [count_over_time](#count_over_time) and [share_gt_over_time](#share_gt_
|
|||
|
||||
`count_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d`, which don't exceed `le`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -286,7 +286,7 @@ See also [count_over_time](#count_over_time) and [share_le_over_time](#share_le_
|
|||
|
||||
`count_ne_over_time(series_selector[d], ne)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d`, which aren't equal to `ne`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -295,7 +295,7 @@ See also [count_over_time](#count_over_time).
|
|||
#### count_over_time
|
||||
|
||||
`count_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -307,7 +307,7 @@ See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_
|
|||
|
||||
`count_values_over_time("label", series_selector[d])` is a [rollup function](#rollup-functions), which counts the number of raw samples
|
||||
with the same value over the given lookbehind window and stores the counts in a time series with an additional `label`, which contains each initial value.
|
||||
The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -316,7 +316,7 @@ See also [count_eq_over_time](#count_eq_over_time), [count_values](#count_values
|
|||
#### decreases_over_time
|
||||
|
||||
`decreases_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw sample value decreases
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -325,7 +325,7 @@ See also [increases_over_time](#increases_over_time).
|
|||
#### default_rollup
|
||||
|
||||
`default_rollup(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
|
||||
passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
|
||||
|
|
@ -336,7 +336,7 @@ This allows avoiding unexpected gaps on the graph when `step` is smaller than th
|
|||
|
||||
`delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
|
||||
the last sample before the given lookbehind window `d` and the last sample at the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
The behaviour of `delta()` function in MetricsQL is slightly different to the behaviour of `delta()` function in Prometheus.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -351,7 +351,7 @@ See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
|
|||
|
||||
`delta_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
|
||||
the first and the last samples at the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
The behaviour of `delta_prometheus()` is close to the behaviour of `delta()` function in Prometheus.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -363,7 +363,7 @@ See also [delta](#delta).
|
|||
#### deriv
|
||||
|
||||
`deriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivative over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The derivative is calculated using linear regression.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
|
@ -376,7 +376,7 @@ See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
|
|||
|
||||
`deriv_fast(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivative
|
||||
using the first and the last raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -386,7 +386,7 @@ See also [deriv](#deriv) and [ideriv](#ideriv).
|
|||
|
||||
`descent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates descent of raw sample values
|
||||
on the given lookbehind window `d`. The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for tracking height loss in GPS tracking.
|
||||
|
||||
|
|
@ -397,7 +397,7 @@ See also [ascent_over_time](#ascent_over_time).
|
|||
#### distinct_over_time
|
||||
|
||||
`distinct_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the number of distinct raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -406,7 +406,7 @@ See also [count_values_over_time](#count_values_over_time).
|
|||
#### duration_over_time
|
||||
|
||||
`duration_over_time(series_selector[d], max_interval)` is a [rollup function](#rollup-functions), which returns the duration in seconds
|
||||
when time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) were present
|
||||
when time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering) were present
|
||||
over the given lookbehind window `d`. It is expected that intervals between adjacent samples per each series don't exceed the `max_interval`.
|
||||
Otherwise, such intervals are considered as gaps and aren't counted.
|
||||
|
||||
|
|
@ -417,7 +417,7 @@ See also [lifetime](#lifetime) and [lag](#lag).
|
|||
#### first_over_time
|
||||
|
||||
`first_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the first raw sample value
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [last_over_time](#last_over_time) and [tfirst_over_time](#tfirst_over_time).
|
||||
|
||||
|
|
@ -425,7 +425,7 @@ See also [last_over_time](#last_over_time) and [tfirst_over_time](#tfirst_over_t
|
|||
|
||||
`geomean_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [geometric mean](https://en.wikipedia.org/wiki/Geometric_mean)
|
||||
over raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -433,9 +433,9 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
|
||||
`histogram_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates
|
||||
[VictoriaMetrics histogram](https://godoc.org/github.com/VictoriaMetrics/metrics#Histogram) over raw samples on the given lookbehind window `d`.
|
||||
It is calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The resulting histograms are useful to pass to [histogram_quantile](#histogram_quantile) for calculating quantiles
|
||||
over multiple [gauges](https://docs.victoriametrics.com/keyConcepts.html#gauge).
|
||||
over multiple [gauges](https://docs.victoriametrics.com/keyconcepts/#gauge).
|
||||
For example, the following query calculates median temperature by country over the last 24 hours:
|
||||
|
||||
`histogram_quantile(0.5, sum(histogram_over_time(temperature[24h])) by (vmrange,country))`.
|
||||
|
|
@ -459,8 +459,8 @@ See also [hoeffding_bound_lower](#hoeffding_bound_lower).
|
|||
`holt_winters(series_selector[d], sf, tf)` is a [rollup function](#rollup-functions), which calculates Holt-Winters value
|
||||
(aka [double exponential smoothing](https://en.wikipedia.org/wiki/Exponential_smoothing#Double_exponential_smoothing)) for raw samples
|
||||
over the given lookbehind window `d` using the given smoothing factor `sf` and the given trend factor `tf`.
|
||||
Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
|
||||
returns time series of [gauge type](https://docs.victoriametrics.com/keyConcepts.html#gauge).
|
||||
Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering)
|
||||
returns time series of [gauge type](https://docs.victoriametrics.com/keyconcepts/#gauge).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -469,7 +469,7 @@ See also [range_linear_regression](#range_linear_regression).
|
|||
#### idelta
|
||||
|
||||
`idelta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between the last two raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -481,7 +481,7 @@ See also [delta](#delta).
|
|||
|
||||
`ideriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the per-second derivative based on the last two raw samples
|
||||
over the given lookbehind window `d`. The derivative is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -490,8 +490,8 @@ See also [deriv](#deriv).
|
|||
#### increase
|
||||
|
||||
`increase(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the increase over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Unlike Prometheus, it takes into account the last sample before the given lookbehind window `d` when calculating the result.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -505,8 +505,8 @@ See also [increase_pure](#increase_pure), [increase_prometheus](#increase_promet
|
|||
#### increase_prometheus
|
||||
|
||||
`increase_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the increase
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
It doesn't take into account the last sample before the given lookbehind window `d` when calculating the result in the same way as Prometheus does.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
||||
|
|
@ -517,13 +517,13 @@ See also [increase_pure](#increase_pure) and [increase](#increase).
|
|||
#### increase_pure
|
||||
|
||||
`increase_pure(series_selector[d])` is a [rollup function](#rollup-functions), which works the same as [increase](#increase) except
|
||||
of the following corner case - it assumes that [counters](https://docs.victoriametrics.com/keyConcepts.html#counter) always start from 0,
|
||||
of the following corner case - it assumes that [counters](https://docs.victoriametrics.com/keyconcepts/#counter) always start from 0,
|
||||
while [increase](#increase) ignores the first value in a series if it is too big.
|
||||
|
||||
#### increases_over_time
|
||||
|
||||
`increases_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw sample value increases
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -532,15 +532,15 @@ See also [decreases_over_time](#decreases_over_time).
|
|||
#### integrate
|
||||
|
||||
`integrate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the integral over raw samples on the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### irate
|
||||
|
||||
`irate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the "instant" per-second increase rate over the last two raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -552,7 +552,7 @@ See also [rate](#rate) and [rollup_rate](#rollup_rate).
|
|||
|
||||
`lag(series_selector[d])` is a [rollup function](#rollup-functions), which returns the duration in seconds between the last sample
|
||||
on the given lookbehind window `d` and the timestamp of the current point. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -561,7 +561,7 @@ See also [lifetime](#lifetime) and [duration_over_time](#duration_over_time).
|
|||
#### last_over_time
|
||||
|
||||
`last_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -570,7 +570,7 @@ See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_t
|
|||
#### lifetime
|
||||
|
||||
`lifetime(series_selector[d])` is a [rollup function](#rollup-functions), which returns the duration in seconds between the last and the first sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -579,14 +579,14 @@ See also [duration_over_time](#duration_over_time) and [lag](#lag).
|
|||
#### mad_over_time
|
||||
|
||||
`mad_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [median absolute deviation](https://en.wikipedia.org/wiki/Median_absolute_deviation)
|
||||
over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [mad](#mad), [range_mad](#range_mad) and [outlier_iqr_over_time](#outlier_iqr_over_time).
|
||||
|
||||
#### max_over_time
|
||||
|
||||
`max_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the maximum value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -596,14 +596,14 @@ See also [tmax_over_time](#tmax_over_time).
|
|||
|
||||
`median_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates median value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [avg_over_time](#avg_over_time).
|
||||
|
||||
#### min_over_time
|
||||
|
||||
`min_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the minimum value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -613,7 +613,7 @@ See also [tmin_over_time](#tmin_over_time).
|
|||
|
||||
`mode_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [mode](https://en.wikipedia.org/wiki/Mode_(statistics))
|
||||
for raw samples on the given lookbehind window `d`. It is calculated individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). It is expected that raw sample values are discrete.
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering). It is expected that raw sample values are discrete.
|
||||
|
||||
#### outlier_iqr_over_time
|
||||
|
||||
|
|
@ -631,7 +631,7 @@ See also [outliers_iqr](#outliers_iqr).
|
|||
|
||||
`predict_linear(series_selector[d], t)` is a [rollup function](#rollup-functions), which calculates the value `t` seconds in the future using
|
||||
linear interpolation over raw samples on the given lookbehind window `d`. The predicted value is calculated individually per each time series
|
||||
returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -649,7 +649,7 @@ This function is supported by PromQL.
|
|||
#### quantile_over_time
|
||||
|
||||
`quantile_over_time(phi, series_selector[d])` is a [rollup function](#rollup-functions), which calculates `phi`-quantile over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The `phi` value must be in the range `[0...1]`.
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
|
@ -660,7 +660,7 @@ See also [quantiles_over_time](#quantiles_over_time).
|
|||
|
||||
`quantiles_over_time("phiLabel", phi1, ..., phiN, series_selector[d])` is a [rollup function](#rollup-functions), which calculates `phi*`-quantiles
|
||||
over raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The function returns individual series per each `phi*` with `{phiLabel="phi*"}` label. `phi*` values must be in the range `[0...1]`.
|
||||
|
||||
See also [quantile_over_time](#quantile_over_time).
|
||||
|
|
@ -668,7 +668,7 @@ See also [quantile_over_time](#quantile_over_time).
|
|||
#### range_over_time
|
||||
|
||||
`range_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates value range over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
E.g. it calculates `max_over_time(series_selector[d]) - min_over_time(series_selector[d])`.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
|
@ -676,8 +676,8 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
#### rate
|
||||
|
||||
`rate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average per-second increase rate
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
|
||||
passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
|
||||
|
|
@ -694,16 +694,16 @@ See also [irate](#irate) and [rollup_rate](#rollup_rate).
|
|||
|
||||
`rate_over_sum(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second rate over the sum of raw samples
|
||||
on the given lookbehind window `d`. The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### resets
|
||||
|
||||
`resets(series_selector[d])` is a [rollup function](#rollup-functions), which returns the number
|
||||
of [counter](https://docs.victoriametrics.com/keyConcepts.html#counter) resets over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
of [counter](https://docs.victoriametrics.com/keyconcepts/#counter) resets over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -713,7 +713,7 @@ This function is supported by PromQL.
|
|||
|
||||
`rollup(series_selector[d])` is a [rollup function](#rollup-functions), which calculates `min`, `max` and `avg` values for raw samples
|
||||
on the given lookbehind window `d` and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -723,7 +723,7 @@ See also [label_match](#label_match).
|
|||
`rollup_candlestick(series_selector[d])` is a [rollup function](#rollup-functions), which calculates `open`, `high`, `low` and `close` values (aka OHLC)
|
||||
over raw samples on the given lookbehind window `d` and returns them in time series with `rollup="open"`, `rollup="high"`, `rollup="low"` and `rollup="close"` additional labels.
|
||||
The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). This function is useful for financial applications.
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering). This function is useful for financial applications.
|
||||
|
||||
Optional 2nd argument `"open"`, `"high"` or `"low"` or `"close"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -733,7 +733,7 @@ See also [label_match](#label_match).
|
|||
`rollup_delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates differences between adjacent raw samples
|
||||
on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated differences
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -747,7 +747,7 @@ See also [rollup_increase](#rollup_increase).
|
|||
`rollup_deriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivatives
|
||||
for adjacent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated per-second derivatives
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -759,7 +759,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
`rollup_increase(series_selector[d])` is a [rollup function](#rollup-functions), which calculates increases for adjacent raw samples
|
||||
on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated increases
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -778,7 +778,7 @@ when to use `rollup_rate()`.
|
|||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -787,7 +787,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
`rollup_scrape_interval(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the interval in seconds between
|
||||
adjacent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated interval
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -797,7 +797,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
#### scrape_interval
|
||||
|
||||
`scrape_interval(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average interval in seconds between raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -807,7 +807,7 @@ See also [rollup_scrape_interval](#rollup_scrape_interval).
|
|||
|
||||
`share_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for calculating SLI and SLO. Example: `share_gt_over_time(up[24h], 0)` - returns service availability for the last 24 hours.
|
||||
|
||||
|
|
@ -819,7 +819,7 @@ See also [share_le_over_time](#share_le_over_time) and [count_gt_over_time](#cou
|
|||
|
||||
`share_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are smaller or equal to `le`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for calculating SLI and SLO. Example: `share_le_over_time(memory_usage_bytes[24h], 100*1024*1024)` returns
|
||||
the share of time series values for the last 24 hours when memory usage was below or equal to 100MB.
|
||||
|
|
@ -832,7 +832,7 @@ See also [share_gt_over_time](#share_gt_over_time) and [count_le_over_time](#cou
|
|||
|
||||
`share_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are equal to `eq`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -841,15 +841,15 @@ See also [count_eq_over_time](#count_eq_over_time).
|
|||
#### stale_samples_over_time
|
||||
|
||||
`stale_samples_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number
|
||||
of [staleness markers](https://docs.victoriametrics.com/vmagent.html#prometheus-staleness-markers) on the given lookbehind window `d`
|
||||
per each time series matching the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
of [staleness markers](https://docs.victoriametrics.com/vmagent/#prometheus-staleness-markers) on the given lookbehind window `d`
|
||||
per each time series matching the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### stddev_over_time
|
||||
|
||||
`stddev_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard deviation over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -860,7 +860,7 @@ See also [stdvar_over_time](#stdvar_over_time).
|
|||
#### stdvar_over_time
|
||||
|
||||
`stdvar_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard variance over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -871,7 +871,7 @@ See also [stddev_over_time](#stddev_over_time).
|
|||
#### sum_eq_over_time
|
||||
|
||||
`sum_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values equal to `eq`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -880,7 +880,7 @@ See also [sum_over_time](#sum_over_time) and [count_eq_over_time](#count_eq_over
|
|||
#### sum_gt_over_time
|
||||
|
||||
`sum_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values bigger than `gt`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -889,7 +889,7 @@ See also [sum_over_time](#sum_over_time) and [count_gt_over_time](#count_gt_over
|
|||
#### sum_le_over_time
|
||||
|
||||
`sum_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values smaller or equal to `le`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -898,7 +898,7 @@ See also [sum_over_time](#sum_over_time) and [count_le_over_time](#count_le_over
|
|||
#### sum_over_time
|
||||
|
||||
`sum_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the sum of raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -907,14 +907,14 @@ This function is supported by PromQL.
|
|||
#### sum2_over_time
|
||||
|
||||
`sum2_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the sum of squares for raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### timestamp
|
||||
|
||||
`timestamp(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -925,7 +925,7 @@ See also [time](#time) and [now](#now).
|
|||
#### timestamp_with_name
|
||||
|
||||
`timestamp_with_name(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are preserved in the resulting rollups.
|
||||
|
||||
|
|
@ -934,7 +934,7 @@ See also [timestamp](#timestamp) and [keep_metric_names](#keep_metric_names) mod
|
|||
#### tfirst_over_time
|
||||
|
||||
`tfirst_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the first raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -943,7 +943,7 @@ See also [first_over_time](#first_over_time).
|
|||
#### tlast_change_over_time
|
||||
|
||||
`tlast_change_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last change
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) on the given lookbehind window `d`.
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering) on the given lookbehind window `d`.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -959,7 +959,7 @@ See also [tlast_change_over_time](#tlast_change_over_time).
|
|||
|
||||
`tmax_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the raw sample
|
||||
with the maximum value on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -969,7 +969,7 @@ See also [max_over_time](#max_over_time).
|
|||
|
||||
`tmin_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the raw sample
|
||||
with the minimum value on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -979,7 +979,7 @@ See also [min_over_time](#min_over_time).
|
|||
|
||||
`zscore_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns [z-score](https://en.wikipedia.org/wiki/Standard_score)
|
||||
for raw samples on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -994,7 +994,7 @@ returned from the rollup `delta(temperature[24h])`.
|
|||
|
||||
Additional details:
|
||||
|
||||
* If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before calculating the transformations.
|
||||
For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature))`.
|
||||
* All the transform functions accept optional `keep_metric_names` modifier. If it is set,
|
||||
|
|
@ -1230,7 +1230,7 @@ by replacing all the values bigger or equal to 30 with 40.
|
|||
#### end
|
||||
|
||||
`end()` is a [transform function](#transform-functions), which returns the unix timestamp in seconds for the last point.
|
||||
It is known as `end` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `end` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [start](#start), [time](#time) and [now](#now).
|
||||
|
||||
|
|
@ -1653,14 +1653,14 @@ This function is supported by PromQL.
|
|||
|
||||
`start()` is a [transform function](#transform-functions), which returns unix timestamp in seconds for the first point.
|
||||
|
||||
It is known as `start` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `start` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [end](#end), [time](#time) and [now](#now).
|
||||
|
||||
#### step
|
||||
|
||||
`step()` is a [transform function](#transform-functions), which returns the step in seconds (aka interval) between the returned points.
|
||||
It is known as `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [start](#start) and [end](#end).
|
||||
|
||||
|
|
@ -1717,7 +1717,7 @@ This function is supported by PromQL.
|
|||
|
||||
Additional details:
|
||||
|
||||
* If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before performing the label transformation.
|
||||
For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature), "foo")`.
|
||||
|
||||
|
|
@ -1894,7 +1894,7 @@ Additional details:
|
|||
and calculate the [count](#count) aggregate function independently per each group, while `count(up) without (instance)`
|
||||
would group [rollup results](#rollup-functions) by all the labels except `instance` before calculating [count](#count) aggregate function independently per each group.
|
||||
Multiple labels can be put in `by` and `without` modifiers.
|
||||
* If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before calculating the aggregate.
|
||||
For example, `count(up)` is implicitly transformed to `count(default_rollup(up))`.
|
||||
* Aggregate functions accept arbitrary number of args. For example, `avg(q1, q2, q3)` would return the average values for every point
|
||||
|
|
@ -2104,7 +2104,7 @@ See also [quantile](#quantile).
|
|||
`share(q) by (group_labels)` is [aggregate function](#aggregate-functions), which returns shares in the range `[0..1]`
|
||||
for every non-negative points returned by `q` per each timestamp, so the sum of shares per each `group_labels` equals 1.
|
||||
|
||||
This function is useful for normalizing [histogram bucket](https://docs.victoriametrics.com/keyConcepts.html#histogram) shares
|
||||
This function is useful for normalizing [histogram bucket](https://docs.victoriametrics.com/keyconcepts/#histogram) shares
|
||||
into `[0..1]` range:
|
||||
|
||||
```metricsql
|
||||
|
|
@ -2208,7 +2208,7 @@ See also [zscore_over_time](#zscore_over_time), [range_trim_zscore](#range_trim_
|
|||
## Subqueries
|
||||
|
||||
MetricsQL supports and extends PromQL subqueries. See [this article](https://valyala.medium.com/prometheus-subqueries-in-victoriametrics-9b1492b720b3) for details.
|
||||
Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) form a subquery.
|
||||
Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) form a subquery.
|
||||
Nested rollup functions can be implicit thanks to the [implicit query conversions](#implicit-query-conversions).
|
||||
For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m))[1i:1i])`, so it becomes a subquery,
|
||||
since it contains [default_rollup](#default_rollup) nested into [delta](#delta).
|
||||
|
|
@ -2219,19 +2219,19 @@ VictoriaMetrics performs subqueries in the following way:
|
|||
For example, for expression `max_over_time(rate(http_requests_total[5m])[1h:30s])` the inner function `rate(http_requests_total[5m])`
|
||||
is calculated with `step=30s`. The resulting data points are aligned by the `step`.
|
||||
* It calculates the outer rollup function over the results of the inner rollup function using the `step` value
|
||||
passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
## Implicit query conversions
|
||||
|
||||
VictoriaMetrics performs the following implicit conversions for incoming queries before starting the calculations:
|
||||
|
||||
* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions), then it is automatically set to the following value:
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
|
||||
For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
|
||||
- To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
|
||||
for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
|
||||
* All the [series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* All the [series selectors](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
which aren't wrapped into [rollup functions](#rollup-functions), are automatically wrapped into [default_rollup](#default_rollup) function.
|
||||
Examples:
|
||||
* `foo` is transformed to `default_rollup(foo)`
|
||||
|
|
@ -2242,6 +2242,6 @@ VictoriaMetrics performs the following implicit conversions for incoming queries
|
|||
it is [transform function](#transform-functions)
|
||||
* If `step` in square brackets is missing inside [subquery](#subqueries), then `1i` step is automatically added there.
|
||||
For example, `avg_over_time(rate(http_requests_total[5m])[1h])` is automatically converted to `avg_over_time(rate(http_requests_total[5m])[1h:1i])`.
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering)
|
||||
is passed to [rollup function](#rollup-functions), then a [subquery](#subqueries) with `1i` lookbehind window and `1i` step is automatically formed.
|
||||
For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up)))[1i:1i])`.
|
||||
|
|
@ -22,7 +22,7 @@ However, there are some [intentional differences](https://medium.com/@romanhavro
|
|||
[Standalone MetricsQL package](https://godoc.org/github.com/VictoriaMetrics/metricsql) can be used for parsing MetricsQL in external apps.
|
||||
|
||||
If you are unfamiliar with PromQL, then it is suggested reading [this tutorial for beginners](https://medium.com/@valyala/promql-tutorial-for-beginners-9ab455142085)
|
||||
and introduction into [basic querying via MetricsQL](https://docs.victoriametrics.com/keyConcepts.html#metricsql).
|
||||
and introduction into [basic querying via MetricsQL](https://docs.victoriametrics.com/keyconcepts/#metricsql).
|
||||
|
||||
The following functionality is implemented differently in MetricsQL compared to PromQL. This improves user experience:
|
||||
|
||||
|
|
@ -70,15 +70,15 @@ The list of MetricsQL features on top of PromQL:
|
|||
VictoriaMetrics can be used as Graphite datasource in Grafana. See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
|
||||
See also [label_graphite_group](#label_graphite_group) function, which can be used for extracting the given groups from Graphite metric name.
|
||||
* Lookbehind window in square brackets for [rollup functions](#rollup-functions) may be omitted. VictoriaMetrics automatically selects the lookbehind window
|
||||
depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)
|
||||
depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query)
|
||||
and the real interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) (aka `scrape_interval`).
|
||||
For instance, the following query is valid in VictoriaMetrics: `rate(node_network_receive_bytes_total)`.
|
||||
It is roughly equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
|
||||
The difference is documented in [rate() docs](#rate).
|
||||
* Numeric values can contain `_` delimiters for better readability. For example, `1_234_567_890` can be used in queries instead of `1234567890`.
|
||||
* [Series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
|
||||
* [Series selectors](https://docs.victoriametrics.com/keyconcepts/#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
|
||||
selects series with `{env="prod",job="a"}` or `{env="dev",job="b"}` labels.
|
||||
See [these docs](https://docs.victoriametrics.com/keyConcepts.html#filtering-by-multiple-or-filters) for details.
|
||||
See [these docs](https://docs.victoriametrics.com/keyconcepts/#filtering-by-multiple-or-filters) for details.
|
||||
* Support for `group_left(*)` and `group_right(*)` for copying all the labels from time series on the `one` side
|
||||
of [many-to-one operations](https://prometheus.io/docs/prometheus/latest/querying/operators/#many-to-one-and-one-to-many-vector-matches).
|
||||
The copied label names may clash with the existing label names, so MetricsQL provides an ability to add prefix to the copied metric names
|
||||
|
|
@ -153,26 +153,26 @@ MetricsQL provides the following functions:
|
|||
### Rollup functions
|
||||
|
||||
**Rollup functions** (aka range functions or window functions) calculate rollups over **raw samples**
|
||||
on the given lookbehind window for the [selected time series](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window for the [selected time series](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
For example, `avg_over_time(temperature[24h])` calculates the average temperature over raw samples for the last 24 hours.
|
||||
|
||||
Additional details:
|
||||
|
||||
* If rollup functions are used for building graphs in Grafana, then the rollup is calculated independently per each point on the graph.
|
||||
For example, every point for `avg_over_time(temperature[24h])` graph shows the average temperature for the last 24 hours ending at this point.
|
||||
The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
* If the given [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) returns multiple time series,
|
||||
The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
* If the given [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) returns multiple time series,
|
||||
then rollups are calculated individually per each returned series.
|
||||
* If lookbehind window in square brackets is missing, then it is automatically set to the following value:
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
|
||||
For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
|
||||
- To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
|
||||
for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
|
||||
* Every [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) in MetricsQL must be wrapped into a rollup function.
|
||||
* Every [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) in MetricsQL must be wrapped into a rollup function.
|
||||
Otherwise, it is automatically wrapped into [default_rollup](#default_rollup). For example, `foo{bar="baz"}`
|
||||
is automatically converted to `default_rollup(foo{bar="baz"})` before performing the calculations.
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) is passed to rollup function,
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) is passed to rollup function,
|
||||
then the inner arg is automatically converted to a [subquery](#subqueries).
|
||||
* All the rollup functions accept optional `keep_metric_names` modifier. If it is set, then the function keeps metric names in results.
|
||||
See [these docs](#keep_metric_names).
|
||||
|
|
@ -195,7 +195,7 @@ See also [present_over_time](#present_over_time).
|
|||
`aggr_over_time(("rollup_func1", "rollup_func2", ...), series_selector[d])` is a [rollup function](#rollup-functions),
|
||||
which calculates all the listed `rollup_func*` for raw samples on the given lookbehind window `d`.
|
||||
The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
`rollup_func*` can contain any rollup function. For instance, `aggr_over_time(("min_over_time", "max_over_time", "rate"), m[d])`
|
||||
would calculate [min_over_time](#min_over_time), [max_over_time](#max_over_time) and [rate](#rate) for `m[d]`.
|
||||
|
|
@ -204,7 +204,7 @@ would calculate [min_over_time](#min_over_time), [max_over_time](#max_over_time)
|
|||
|
||||
`ascent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates
|
||||
ascent of raw sample values on the given lookbehind window `d`. The calculations are performed individually
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for tracking height gains in GPS tracking. Metric names are stripped from the resulting rollups.
|
||||
|
||||
|
|
@ -216,7 +216,7 @@ See also [descent_over_time](#descent_over_time).
|
|||
|
||||
`avg_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average value
|
||||
over raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -226,7 +226,7 @@ See also [median_over_time](#median_over_time).
|
|||
|
||||
`changes(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of times
|
||||
the raw samples changed on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Unlike `changes()` in Prometheus it takes into account the change from the last sample before the given lookbehind window `d`.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -241,7 +241,7 @@ See also [changes_prometheus](#changes_prometheus).
|
|||
|
||||
`changes_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of times
|
||||
the raw samples changed on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
It doesn't take into account the change from the last sample before the given lookbehind window `d` in the same way as Prometheus does.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -256,7 +256,7 @@ See also [changes](#changes).
|
|||
|
||||
`count_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d`, which are equal to `eq`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -266,7 +266,7 @@ See also [count_over_time](#count_over_time), [share_eq_over_time](#share_eq_ove
|
|||
|
||||
`count_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -276,7 +276,7 @@ See also [count_over_time](#count_over_time) and [share_gt_over_time](#share_gt_
|
|||
|
||||
`count_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d`, which don't exceed `le`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -286,7 +286,7 @@ See also [count_over_time](#count_over_time) and [share_le_over_time](#share_le_
|
|||
|
||||
`count_ne_over_time(series_selector[d], ne)` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d`, which aren't equal to `ne`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -295,7 +295,7 @@ See also [count_over_time](#count_over_time).
|
|||
#### count_over_time
|
||||
|
||||
`count_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -307,7 +307,7 @@ See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_
|
|||
|
||||
`count_values_over_time("label", series_selector[d])` is a [rollup function](#rollup-functions), which counts the number of raw samples
|
||||
with the same value over the given lookbehind window and stores the counts in a time series with an additional `label`, which contains each initial value.
|
||||
The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -316,7 +316,7 @@ See also [count_eq_over_time](#count_eq_over_time), [count_values](#count_values
|
|||
#### decreases_over_time
|
||||
|
||||
`decreases_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw sample value decreases
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -325,7 +325,7 @@ See also [increases_over_time](#increases_over_time).
|
|||
#### default_rollup
|
||||
|
||||
`default_rollup(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
|
||||
passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
|
||||
|
|
@ -336,7 +336,7 @@ This allows avoiding unexpected gaps on the graph when `step` is smaller than th
|
|||
|
||||
`delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
|
||||
the last sample before the given lookbehind window `d` and the last sample at the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
The behaviour of `delta()` function in MetricsQL is slightly different to the behaviour of `delta()` function in Prometheus.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -351,7 +351,7 @@ See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
|
|||
|
||||
`delta_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
|
||||
the first and the last samples at the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
The behaviour of `delta_prometheus()` is close to the behaviour of `delta()` function in Prometheus.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -363,7 +363,7 @@ See also [delta](#delta).
|
|||
#### deriv
|
||||
|
||||
`deriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivative over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The derivative is calculated using linear regression.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
|
@ -376,7 +376,7 @@ See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
|
|||
|
||||
`deriv_fast(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivative
|
||||
using the first and the last raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -386,7 +386,7 @@ See also [deriv](#deriv) and [ideriv](#ideriv).
|
|||
|
||||
`descent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates descent of raw sample values
|
||||
on the given lookbehind window `d`. The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for tracking height loss in GPS tracking.
|
||||
|
||||
|
|
@ -397,7 +397,7 @@ See also [ascent_over_time](#ascent_over_time).
|
|||
#### distinct_over_time
|
||||
|
||||
`distinct_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the number of distinct raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -406,7 +406,7 @@ See also [count_values_over_time](#count_values_over_time).
|
|||
#### duration_over_time
|
||||
|
||||
`duration_over_time(series_selector[d], max_interval)` is a [rollup function](#rollup-functions), which returns the duration in seconds
|
||||
when time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) were present
|
||||
when time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering) were present
|
||||
over the given lookbehind window `d`. It is expected that intervals between adjacent samples per each series don't exceed the `max_interval`.
|
||||
Otherwise, such intervals are considered as gaps and aren't counted.
|
||||
|
||||
|
|
@ -417,7 +417,7 @@ See also [lifetime](#lifetime) and [lag](#lag).
|
|||
#### first_over_time
|
||||
|
||||
`first_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the first raw sample value
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [last_over_time](#last_over_time) and [tfirst_over_time](#tfirst_over_time).
|
||||
|
||||
|
|
@ -425,7 +425,7 @@ See also [last_over_time](#last_over_time) and [tfirst_over_time](#tfirst_over_t
|
|||
|
||||
`geomean_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [geometric mean](https://en.wikipedia.org/wiki/Geometric_mean)
|
||||
over raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -433,9 +433,9 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
|
||||
`histogram_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates
|
||||
[VictoriaMetrics histogram](https://godoc.org/github.com/VictoriaMetrics/metrics#Histogram) over raw samples on the given lookbehind window `d`.
|
||||
It is calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The resulting histograms are useful to pass to [histogram_quantile](#histogram_quantile) for calculating quantiles
|
||||
over multiple [gauges](https://docs.victoriametrics.com/keyConcepts.html#gauge).
|
||||
over multiple [gauges](https://docs.victoriametrics.com/keyconcepts/#gauge).
|
||||
For example, the following query calculates median temperature by country over the last 24 hours:
|
||||
|
||||
`histogram_quantile(0.5, sum(histogram_over_time(temperature[24h])) by (vmrange,country))`.
|
||||
|
|
@ -459,8 +459,8 @@ See also [hoeffding_bound_lower](#hoeffding_bound_lower).
|
|||
`holt_winters(series_selector[d], sf, tf)` is a [rollup function](#rollup-functions), which calculates Holt-Winters value
|
||||
(aka [double exponential smoothing](https://en.wikipedia.org/wiki/Exponential_smoothing#Double_exponential_smoothing)) for raw samples
|
||||
over the given lookbehind window `d` using the given smoothing factor `sf` and the given trend factor `tf`.
|
||||
Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
|
||||
returns time series of [gauge type](https://docs.victoriametrics.com/keyConcepts.html#gauge).
|
||||
Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering)
|
||||
returns time series of [gauge type](https://docs.victoriametrics.com/keyconcepts/#gauge).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -469,7 +469,7 @@ See also [range_linear_regression](#range_linear_regression).
|
|||
#### idelta
|
||||
|
||||
`idelta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between the last two raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -481,7 +481,7 @@ See also [delta](#delta).
|
|||
|
||||
`ideriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the per-second derivative based on the last two raw samples
|
||||
over the given lookbehind window `d`. The derivative is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -490,8 +490,8 @@ See also [deriv](#deriv).
|
|||
#### increase
|
||||
|
||||
`increase(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the increase over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Unlike Prometheus, it takes into account the last sample before the given lookbehind window `d` when calculating the result.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
|
@ -505,8 +505,8 @@ See also [increase_pure](#increase_pure), [increase_prometheus](#increase_promet
|
|||
#### increase_prometheus
|
||||
|
||||
`increase_prometheus(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the increase
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
It doesn't take into account the last sample before the given lookbehind window `d` when calculating the result in the same way as Prometheus does.
|
||||
See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e) for details.
|
||||
|
||||
|
|
@ -517,13 +517,13 @@ See also [increase_pure](#increase_pure) and [increase](#increase).
|
|||
#### increase_pure
|
||||
|
||||
`increase_pure(series_selector[d])` is a [rollup function](#rollup-functions), which works the same as [increase](#increase) except
|
||||
of the following corner case - it assumes that [counters](https://docs.victoriametrics.com/keyConcepts.html#counter) always start from 0,
|
||||
of the following corner case - it assumes that [counters](https://docs.victoriametrics.com/keyconcepts/#counter) always start from 0,
|
||||
while [increase](#increase) ignores the first value in a series if it is too big.
|
||||
|
||||
#### increases_over_time
|
||||
|
||||
`increases_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of raw sample value increases
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -532,15 +532,15 @@ See also [decreases_over_time](#decreases_over_time).
|
|||
#### integrate
|
||||
|
||||
`integrate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the integral over raw samples on the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### irate
|
||||
|
||||
`irate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the "instant" per-second increase rate over the last two raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -552,7 +552,7 @@ See also [rate](#rate) and [rollup_rate](#rollup_rate).
|
|||
|
||||
`lag(series_selector[d])` is a [rollup function](#rollup-functions), which returns the duration in seconds between the last sample
|
||||
on the given lookbehind window `d` and the timestamp of the current point. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -561,7 +561,7 @@ See also [lifetime](#lifetime) and [duration_over_time](#duration_over_time).
|
|||
#### last_over_time
|
||||
|
||||
`last_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -570,7 +570,7 @@ See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_t
|
|||
#### lifetime
|
||||
|
||||
`lifetime(series_selector[d])` is a [rollup function](#rollup-functions), which returns the duration in seconds between the last and the first sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -579,14 +579,14 @@ See also [duration_over_time](#duration_over_time) and [lag](#lag).
|
|||
#### mad_over_time
|
||||
|
||||
`mad_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [median absolute deviation](https://en.wikipedia.org/wiki/Median_absolute_deviation)
|
||||
over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
over raw samples on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [mad](#mad), [range_mad](#range_mad) and [outlier_iqr_over_time](#outlier_iqr_over_time).
|
||||
|
||||
#### max_over_time
|
||||
|
||||
`max_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the maximum value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -596,14 +596,14 @@ See also [tmax_over_time](#tmax_over_time).
|
|||
|
||||
`median_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates median value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
See also [avg_over_time](#avg_over_time).
|
||||
|
||||
#### min_over_time
|
||||
|
||||
`min_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the minimum value over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -613,7 +613,7 @@ See also [tmin_over_time](#tmin_over_time).
|
|||
|
||||
`mode_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates [mode](https://en.wikipedia.org/wiki/Mode_(statistics))
|
||||
for raw samples on the given lookbehind window `d`. It is calculated individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). It is expected that raw sample values are discrete.
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering). It is expected that raw sample values are discrete.
|
||||
|
||||
#### outlier_iqr_over_time
|
||||
|
||||
|
|
@ -631,7 +631,7 @@ See also [outliers_iqr](#outliers_iqr).
|
|||
|
||||
`predict_linear(series_selector[d], t)` is a [rollup function](#rollup-functions), which calculates the value `t` seconds in the future using
|
||||
linear interpolation over raw samples on the given lookbehind window `d`. The predicted value is calculated individually per each time series
|
||||
returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
||||
|
|
@ -649,7 +649,7 @@ This function is supported by PromQL.
|
|||
#### quantile_over_time
|
||||
|
||||
`quantile_over_time(phi, series_selector[d])` is a [rollup function](#rollup-functions), which calculates `phi`-quantile over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The `phi` value must be in the range `[0...1]`.
|
||||
|
||||
This function is supported by PromQL.
|
||||
|
|
@ -660,7 +660,7 @@ See also [quantiles_over_time](#quantiles_over_time).
|
|||
|
||||
`quantiles_over_time("phiLabel", phi1, ..., phiN, series_selector[d])` is a [rollup function](#rollup-functions), which calculates `phi*`-quantiles
|
||||
over raw samples on the given lookbehind window `d` per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
The function returns individual series per each `phi*` with `{phiLabel="phi*"}` label. `phi*` values must be in the range `[0...1]`.
|
||||
|
||||
See also [quantile_over_time](#quantile_over_time).
|
||||
|
|
@ -668,7 +668,7 @@ See also [quantile_over_time](#quantile_over_time).
|
|||
#### range_over_time
|
||||
|
||||
`range_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates value range over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
E.g. it calculates `max_over_time(series_selector[d]) - min_over_time(series_selector[d])`.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
|
@ -676,8 +676,8 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
#### rate
|
||||
|
||||
`rate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average per-second increase rate
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
|
||||
passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
|
||||
|
|
@ -694,16 +694,16 @@ See also [irate](#irate) and [rollup_rate](#rollup_rate).
|
|||
|
||||
`rate_over_sum(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second rate over the sum of raw samples
|
||||
on the given lookbehind window `d`. The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### resets
|
||||
|
||||
`resets(series_selector[d])` is a [rollup function](#rollup-functions), which returns the number
|
||||
of [counter](https://docs.victoriametrics.com/keyConcepts.html#counter) resets over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
|
||||
of [counter](https://docs.victoriametrics.com/keyconcepts/#counter) resets over the given lookbehind window `d`
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyconcepts/#counter).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -713,7 +713,7 @@ This function is supported by PromQL.
|
|||
|
||||
`rollup(series_selector[d])` is a [rollup function](#rollup-functions), which calculates `min`, `max` and `avg` values for raw samples
|
||||
on the given lookbehind window `d` and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -723,7 +723,7 @@ See also [label_match](#label_match).
|
|||
`rollup_candlestick(series_selector[d])` is a [rollup function](#rollup-functions), which calculates `open`, `high`, `low` and `close` values (aka OHLC)
|
||||
over raw samples on the given lookbehind window `d` and returns them in time series with `rollup="open"`, `rollup="high"`, `rollup="low"` and `rollup="close"` additional labels.
|
||||
The calculations are performed individually per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). This function is useful for financial applications.
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering). This function is useful for financial applications.
|
||||
|
||||
Optional 2nd argument `"open"`, `"high"` or `"low"` or `"close"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -733,7 +733,7 @@ See also [label_match](#label_match).
|
|||
`rollup_delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates differences between adjacent raw samples
|
||||
on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated differences
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -747,7 +747,7 @@ See also [rollup_increase](#rollup_increase).
|
|||
`rollup_deriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second derivatives
|
||||
for adjacent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated per-second derivatives
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -759,7 +759,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
`rollup_increase(series_selector[d])` is a [rollup function](#rollup-functions), which calculates increases for adjacent raw samples
|
||||
on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated increases
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -778,7 +778,7 @@ when to use `rollup_rate()`.
|
|||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -787,7 +787,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
`rollup_scrape_interval(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the interval in seconds between
|
||||
adjacent raw samples on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated interval
|
||||
and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels.
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
|
||||
See also [label_match](#label_match).
|
||||
|
|
@ -797,7 +797,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
|
|||
#### scrape_interval
|
||||
|
||||
`scrape_interval(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average interval in seconds between raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -807,7 +807,7 @@ See also [rollup_scrape_interval](#rollup_scrape_interval).
|
|||
|
||||
`share_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are bigger than `gt`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for calculating SLI and SLO. Example: `share_gt_over_time(up[24h], 0)` - returns service availability for the last 24 hours.
|
||||
|
||||
|
|
@ -819,7 +819,7 @@ See also [share_le_over_time](#share_le_over_time) and [count_gt_over_time](#cou
|
|||
|
||||
`share_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are smaller or equal to `le`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
This function is useful for calculating SLI and SLO. Example: `share_le_over_time(memory_usage_bytes[24h], 100*1024*1024)` returns
|
||||
the share of time series values for the last 24 hours when memory usage was below or equal to 100MB.
|
||||
|
|
@ -832,7 +832,7 @@ See also [share_gt_over_time](#share_gt_over_time) and [count_le_over_time](#cou
|
|||
|
||||
`share_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-functions), which returns share (in the range `[0...1]`) of raw samples
|
||||
on the given lookbehind window `d`, which are equal to `eq`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -841,15 +841,15 @@ See also [count_eq_over_time](#count_eq_over_time).
|
|||
#### stale_samples_over_time
|
||||
|
||||
`stale_samples_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number
|
||||
of [staleness markers](https://docs.victoriametrics.com/vmagent.html#prometheus-staleness-markers) on the given lookbehind window `d`
|
||||
per each time series matching the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
of [staleness markers](https://docs.victoriametrics.com/vmagent/#prometheus-staleness-markers) on the given lookbehind window `d`
|
||||
per each time series matching the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### stddev_over_time
|
||||
|
||||
`stddev_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard deviation over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -860,7 +860,7 @@ See also [stdvar_over_time](#stdvar_over_time).
|
|||
#### stdvar_over_time
|
||||
|
||||
`stdvar_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard variance over raw samples
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -871,7 +871,7 @@ See also [stddev_over_time](#stddev_over_time).
|
|||
#### sum_eq_over_time
|
||||
|
||||
`sum_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values equal to `eq`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -880,7 +880,7 @@ See also [sum_over_time](#sum_over_time) and [count_eq_over_time](#count_eq_over
|
|||
#### sum_gt_over_time
|
||||
|
||||
`sum_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values bigger than `gt`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -889,7 +889,7 @@ See also [sum_over_time](#sum_over_time) and [count_gt_over_time](#count_gt_over
|
|||
#### sum_le_over_time
|
||||
|
||||
`sum_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values smaller or equal to `le`
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -898,7 +898,7 @@ See also [sum_over_time](#sum_over_time) and [count_le_over_time](#count_le_over
|
|||
#### sum_over_time
|
||||
|
||||
`sum_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the sum of raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -907,14 +907,14 @@ This function is supported by PromQL.
|
|||
#### sum2_over_time
|
||||
|
||||
`sum2_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the sum of squares for raw sample values
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
#### timestamp
|
||||
|
||||
`timestamp(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -925,7 +925,7 @@ See also [time](#time) and [now](#now).
|
|||
#### timestamp_with_name
|
||||
|
||||
`timestamp_with_name(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are preserved in the resulting rollups.
|
||||
|
||||
|
|
@ -934,7 +934,7 @@ See also [timestamp](#timestamp) and [keep_metric_names](#keep_metric_names) mod
|
|||
#### tfirst_over_time
|
||||
|
||||
`tfirst_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the first raw sample
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -943,7 +943,7 @@ See also [first_over_time](#first_over_time).
|
|||
#### tlast_change_over_time
|
||||
|
||||
`tlast_change_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last change
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) on the given lookbehind window `d`.
|
||||
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering) on the given lookbehind window `d`.
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -959,7 +959,7 @@ See also [tlast_change_over_time](#tlast_change_over_time).
|
|||
|
||||
`tmax_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the raw sample
|
||||
with the maximum value on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -969,7 +969,7 @@ See also [max_over_time](#max_over_time).
|
|||
|
||||
`tmin_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the raw sample
|
||||
with the minimum value on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -979,7 +979,7 @@ See also [min_over_time](#min_over_time).
|
|||
|
||||
`zscore_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns [z-score](https://en.wikipedia.org/wiki/Standard_score)
|
||||
for raw samples on the given lookbehind window `d`. It is calculated independently per each time series returned
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
|
||||
from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering).
|
||||
|
||||
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
|
||||
|
||||
|
|
@ -994,7 +994,7 @@ returned from the rollup `delta(temperature[24h])`.
|
|||
|
||||
Additional details:
|
||||
|
||||
* If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before calculating the transformations.
|
||||
For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature))`.
|
||||
* All the transform functions accept optional `keep_metric_names` modifier. If it is set,
|
||||
|
|
@ -1230,7 +1230,7 @@ by replacing all the values bigger or equal to 30 with 40.
|
|||
#### end
|
||||
|
||||
`end()` is a [transform function](#transform-functions), which returns the unix timestamp in seconds for the last point.
|
||||
It is known as `end` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `end` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [start](#start), [time](#time) and [now](#now).
|
||||
|
||||
|
|
@ -1653,14 +1653,14 @@ This function is supported by PromQL.
|
|||
|
||||
`start()` is a [transform function](#transform-functions), which returns unix timestamp in seconds for the first point.
|
||||
|
||||
It is known as `start` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `start` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [end](#end), [time](#time) and [now](#now).
|
||||
|
||||
#### step
|
||||
|
||||
`step()` is a [transform function](#transform-functions), which returns the step in seconds (aka interval) between the returned points.
|
||||
It is known as `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
It is known as `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
See also [start](#start) and [end](#end).
|
||||
|
||||
|
|
@ -1717,7 +1717,7 @@ This function is supported by PromQL.
|
|||
|
||||
Additional details:
|
||||
|
||||
* If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before performing the label transformation.
|
||||
For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature), "foo")`.
|
||||
|
||||
|
|
@ -1894,7 +1894,7 @@ Additional details:
|
|||
and calculate the [count](#count) aggregate function independently per each group, while `count(up) without (instance)`
|
||||
would group [rollup results](#rollup-functions) by all the labels except `instance` before calculating [count](#count) aggregate function independently per each group.
|
||||
Multiple labels can be put in `by` and `without` modifiers.
|
||||
* If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
then the [default_rollup()](#default_rollup) function is automatically applied before calculating the aggregate.
|
||||
For example, `count(up)` is implicitly transformed to `count(default_rollup(up))`.
|
||||
* Aggregate functions accept arbitrary number of args. For example, `avg(q1, q2, q3)` would return the average values for every point
|
||||
|
|
@ -2104,7 +2104,7 @@ See also [quantile](#quantile).
|
|||
`share(q) by (group_labels)` is [aggregate function](#aggregate-functions), which returns shares in the range `[0..1]`
|
||||
for every non-negative points returned by `q` per each timestamp, so the sum of shares per each `group_labels` equals 1.
|
||||
|
||||
This function is useful for normalizing [histogram bucket](https://docs.victoriametrics.com/keyConcepts.html#histogram) shares
|
||||
This function is useful for normalizing [histogram bucket](https://docs.victoriametrics.com/keyconcepts/#histogram) shares
|
||||
into `[0..1]` range:
|
||||
|
||||
```metricsql
|
||||
|
|
@ -2208,7 +2208,7 @@ See also [zscore_over_time](#zscore_over_time), [range_trim_zscore](#range_trim_
|
|||
## Subqueries
|
||||
|
||||
MetricsQL supports and extends PromQL subqueries. See [this article](https://valyala.medium.com/prometheus-subqueries-in-victoriametrics-9b1492b720b3) for details.
|
||||
Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) form a subquery.
|
||||
Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering) form a subquery.
|
||||
Nested rollup functions can be implicit thanks to the [implicit query conversions](#implicit-query-conversions).
|
||||
For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m))[1i:1i])`, so it becomes a subquery,
|
||||
since it contains [default_rollup](#default_rollup) nested into [delta](#delta).
|
||||
|
|
@ -2219,19 +2219,19 @@ VictoriaMetrics performs subqueries in the following way:
|
|||
For example, for expression `max_over_time(rate(http_requests_total[5m])[1h:30s])` the inner function `rate(http_requests_total[5m])`
|
||||
is calculated with `step=30s`. The resulting data points are aligned by the `step`.
|
||||
* It calculates the outer rollup function over the results of the inner rollup function using the `step` value
|
||||
passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
|
||||
passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
|
||||
|
||||
## Implicit query conversions
|
||||
|
||||
VictoriaMetrics performs the following implicit conversions for incoming queries before starting the calculations:
|
||||
|
||||
* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions), then it is automatically set to the following value:
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
- To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
|
||||
for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
|
||||
For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
|
||||
- To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
|
||||
for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
|
||||
* All the [series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering),
|
||||
* All the [series selectors](https://docs.victoriametrics.com/keyconcepts/#filtering),
|
||||
which aren't wrapped into [rollup functions](#rollup-functions), are automatically wrapped into [default_rollup](#default_rollup) function.
|
||||
Examples:
|
||||
* `foo` is transformed to `default_rollup(foo)`
|
||||
|
|
@ -2242,6 +2242,6 @@ VictoriaMetrics performs the following implicit conversions for incoming queries
|
|||
it is [transform function](#transform-functions)
|
||||
* If `step` in square brackets is missing inside [subquery](#subqueries), then `1i` step is automatically added there.
|
||||
For example, `avg_over_time(rate(http_requests_total[5m])[1h])` is automatically converted to `avg_over_time(rate(http_requests_total[5m])[1h:1i])`.
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
|
||||
* If something other than [series selector](https://docs.victoriametrics.com/keyconcepts/#filtering)
|
||||
is passed to [rollup function](#rollup-functions), then a [subquery](#subqueries) with `1i` lookbehind window and `1i` step is automatically formed.
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For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up)))[1i:1i])`.
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Reference in a new issue