mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
synced 2024-11-21 14:44:00 +00:00
app/vmui: fix non-working Disable cache checkbox at JSON and Table views
This commit is contained in:
Aliaksandr Valialkin
parent
7b7ad44e84
commit
28f0610e14
9 changed files with 70 additions and 19 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.b863450b.css",
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"main.js": "./static/js/main.ed7b3eaf.js",
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"main.js": "./static/js/main.19e7f129.js",
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"static/js/522.da77e7b3.chunk.js": "./static/js/522.da77e7b3.chunk.js",
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"static/media/MetricsQL.md": "./static/media/MetricsQL.a7f5a575814b6da6b0b2.md",
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"static/media/MetricsQL.md": "./static/media/MetricsQL.8644fd7c964802dd34a9.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.b863450b.css",
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"static/js/main.ed7b3eaf.js"
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"static/js/main.19e7f129.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.ed7b3eaf.js"></script><link href="./static/css/main.b863450b.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.19e7f129.js"></script><link href="./static/css/main.b863450b.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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File diff suppressed because one or more lines are too long
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@ -532,7 +532,7 @@ See also [duration_over_time](#duration_over_time) and [lag](#lag).
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`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)
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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).
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See also [mad](#mad) and [range_mad](#range_mad).
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See also [mad](#mad), [range_mad](#range_mad) and [outlier_iqr_over_time](#outlier_iqr_over_time).
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#### max_over_time
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@ -562,6 +562,18 @@ This function is supported by PromQL. See also [tmin_over_time](#tmin_over_time)
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for raw samples on the given lookbehind window `d`. It is calculated individually per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). It is expected that raw sample values are discrete.
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#### outlier_iqr_over_time
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`outlier_iqr_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last sample on the given lookbehind window `d`
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if its value is either smaller than the `q25-1.5*iqr` or bigger than `q75+1.5*iqr` where:
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- `iqr` is an [Interquartile range](https://en.wikipedia.org/wiki/Interquartile_range) over raw samples on the lookbehind window `d`
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- `q25` and `q75` are 25th and 75th [percentiles](https://en.wikipedia.org/wiki/Percentile) over raw samples on the lookbehind window `d`.
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The `outlier_iqr_over_time()` is useful for detecting anomalies in gauge values based on the previous history of values.
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For example, `outlier_iqr_over_time(memory_usage_bytes[1h])` triggers when `memory_usage_bytes` suddenly goes outside the usual value range for the last 24 hours.
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See also [outliers_iqr](#outliers_iqr).
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#### predict_linear
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`predict_linear(series_selector[d], t)` is a [rollup function](#rollup-functions), which calculates the value `t` seconds in the future using
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@ -866,7 +878,7 @@ from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.ht
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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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See also [zscore](#zscore) and [range_trim_zscore](#range_trim_zscore).
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See also [zscore](#zscore), [range_trim_zscore](#range_trim_zscore) and [outlier_iqr_over_time](#outlier_iqr_over_time).
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### Transform functions
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@ -1858,20 +1870,33 @@ This function is supported by PromQL.
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`mode(q) by (group_labels)` is [aggregate function](#aggregate-functions), which returns [mode](https://en.wikipedia.org/wiki/Mode_(statistics))
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per each `group_labels` for all the time series returned by `q`. The aggregate is calculated individually per each group of points with the same timestamp.
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#### outliers_iqr
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`outliers_iqr(q)` is [aggregate function](#aggregate-functions), which returns time series from `q` with at least a single point
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outside e.g. [Interquartile range outlier bounds](https://en.wikipedia.org/wiki/Interquartile_range) `[q25-1.5*iqr .. q75+1.5*iqr]`
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comparing to other time series at the given point, where:
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- `iqr` is an [Interquartile range](https://en.wikipedia.org/wiki/Interquartile_range) calculated independently per each point on the graph across `q` series.
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- `q25` and `q75` are 25th and 75th [percentiles](https://en.wikipedia.org/wiki/Percentile) calculated independently per each point on the graph across `q` series.
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The `outliers_iqr()` is useful for detecting anomalous series in the group of series. For example, `outliers_iqr(temperature) by (country)` returns
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per-country series with anomalous outlier values comparing to the rest of per-country series.
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See also [outliers_mad](#outliers_mad), [outliersk](#outliersk) and [outlier_iqr_over_time](#outlier_iqr_over_time).
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#### outliers_mad
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`outliers_mad(tolerance, q)` is [aggregate function](#aggregate-functions), which returns time series from `q` with at least
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a single point outside [Median absolute deviation](https://en.wikipedia.org/wiki/Median_absolute_deviation) (aka MAD) multiplied by `tolerance`.
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E.g. it returns time series with at least a single point below `median(q) - mad(q)` or a single point above `median(q) + mad(q)`.
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See also [outliersk](#outliersk) and [mad](#mad).
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See also [outliers_iqr](#outliers_iqr), [outliersk](#outliersk) and [mad](#mad).
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#### outliersk
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`outliersk(k, q)` is [aggregate function](#aggregate-functions), which returns up to `k` time series with the biggest standard deviation (aka outliers)
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out of time series returned by `q`.
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See also [outliers_mad](#outliers_mad).
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See also [outliers_iqr](#outliers_iqr) and [outliers_mad](#outliers_mad).
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#### quantile
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@ -1991,7 +2016,7 @@ See also [bottomk_min](#bottomk_min).
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per each `group_labels` for all the time series returned by `q`. The aggregate is calculated individually per each group of points with the same timestamp.
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This function is useful for detecting anomalies in the group of related time series.
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See also [zscore_over_time](#zscore_over_time) and [range_trim_zscore](#range_trim_zscore).
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See also [zscore_over_time](#zscore_over_time), [range_trim_zscore](#range_trim_zscore) and [outliers_iqr](#outliers_iqr).
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## Subqueries
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@ -3,5 +3,5 @@ import { TimeParams } from "../types";
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export const getQueryRangeUrl = (server: string, query: string, period: TimeParams, nocache: boolean, queryTracing: boolean): string =>
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`${server}/api/v1/query_range?query=${encodeURIComponent(query)}&start=${period.start}&end=${period.end}&step=${period.step}${nocache ? "&nocache=1" : ""}${queryTracing ? "&trace=1" : ""}`;
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export const getQueryUrl = (server: string, query: string, period: TimeParams, queryTracing: boolean): string =>
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`${server}/api/v1/query?query=${encodeURIComponent(query)}&time=${period.end}${queryTracing ? "&trace=1" : ""}`;
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export const getQueryUrl = (server: string, query: string, period: TimeParams, nocache: boolean, queryTracing: boolean): string =>
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`${server}/api/v1/query?query=${encodeURIComponent(query)}&time=${period.end}${nocache ? "&nocache=1" : ""}${queryTracing ? "&trace=1" : ""}`;
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@ -532,7 +532,7 @@ See also [duration_over_time](#duration_over_time) and [lag](#lag).
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`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)
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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).
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See also [mad](#mad) and [range_mad](#range_mad).
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See also [mad](#mad), [range_mad](#range_mad) and [outlier_iqr_over_time](#outlier_iqr_over_time).
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#### max_over_time
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@ -562,6 +562,18 @@ This function is supported by PromQL. See also [tmin_over_time](#tmin_over_time)
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for raw samples on the given lookbehind window `d`. It is calculated individually per each time series returned
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from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). It is expected that raw sample values are discrete.
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#### outlier_iqr_over_time
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`outlier_iqr_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last sample on the given lookbehind window `d`
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if its value is either smaller than the `q25-1.5*iqr` or bigger than `q75+1.5*iqr` where:
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- `iqr` is an [Interquartile range](https://en.wikipedia.org/wiki/Interquartile_range) over raw samples on the lookbehind window `d`
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- `q25` and `q75` are 25th and 75th [percentiles](https://en.wikipedia.org/wiki/Percentile) over raw samples on the lookbehind window `d`.
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The `outlier_iqr_over_time()` is useful for detecting anomalies in gauge values based on the previous history of values.
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For example, `outlier_iqr_over_time(memory_usage_bytes[1h])` triggers when `memory_usage_bytes` suddenly goes outside the usual value range for the last 24 hours.
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See also [outliers_iqr](#outliers_iqr).
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#### predict_linear
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`predict_linear(series_selector[d], t)` is a [rollup function](#rollup-functions), which calculates the value `t` seconds in the future using
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@ -866,7 +878,7 @@ from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.ht
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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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See also [zscore](#zscore) and [range_trim_zscore](#range_trim_zscore).
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See also [zscore](#zscore), [range_trim_zscore](#range_trim_zscore) and [outlier_iqr_over_time](#outlier_iqr_over_time).
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### Transform functions
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@ -1858,20 +1870,33 @@ This function is supported by PromQL.
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`mode(q) by (group_labels)` is [aggregate function](#aggregate-functions), which returns [mode](https://en.wikipedia.org/wiki/Mode_(statistics))
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per each `group_labels` for all the time series returned by `q`. The aggregate is calculated individually per each group of points with the same timestamp.
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#### outliers_iqr
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`outliers_iqr(q)` is [aggregate function](#aggregate-functions), which returns time series from `q` with at least a single point
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outside e.g. [Interquartile range outlier bounds](https://en.wikipedia.org/wiki/Interquartile_range) `[q25-1.5*iqr .. q75+1.5*iqr]`
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comparing to other time series at the given point, where:
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- `iqr` is an [Interquartile range](https://en.wikipedia.org/wiki/Interquartile_range) calculated independently per each point on the graph across `q` series.
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- `q25` and `q75` are 25th and 75th [percentiles](https://en.wikipedia.org/wiki/Percentile) calculated independently per each point on the graph across `q` series.
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The `outliers_iqr()` is useful for detecting anomalous series in the group of series. For example, `outliers_iqr(temperature) by (country)` returns
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per-country series with anomalous outlier values comparing to the rest of per-country series.
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See also [outliers_mad](#outliers_mad), [outliersk](#outliersk) and [outlier_iqr_over_time](#outlier_iqr_over_time).
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#### outliers_mad
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`outliers_mad(tolerance, q)` is [aggregate function](#aggregate-functions), which returns time series from `q` with at least
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a single point outside [Median absolute deviation](https://en.wikipedia.org/wiki/Median_absolute_deviation) (aka MAD) multiplied by `tolerance`.
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E.g. it returns time series with at least a single point below `median(q) - mad(q)` or a single point above `median(q) + mad(q)`.
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See also [outliersk](#outliersk) and [mad](#mad).
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See also [outliers_iqr](#outliers_iqr), [outliersk](#outliersk) and [mad](#mad).
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#### outliersk
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`outliersk(k, q)` is [aggregate function](#aggregate-functions), which returns up to `k` time series with the biggest standard deviation (aka outliers)
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out of time series returned by `q`.
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See also [outliers_mad](#outliers_mad).
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See also [outliers_iqr](#outliers_iqr) and [outliers_mad](#outliers_mad).
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#### quantile
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@ -1991,7 +2016,7 @@ See also [bottomk_min](#bottomk_min).
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per each `group_labels` for all the time series returned by `q`. The aggregate is calculated individually per each group of points with the same timestamp.
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This function is useful for detecting anomalies in the group of related time series.
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See also [zscore_over_time](#zscore_over_time) and [range_trim_zscore](#range_trim_zscore).
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See also [zscore_over_time](#zscore_over_time), [range_trim_zscore](#range_trim_zscore) and [outliers_iqr](#outliers_iqr).
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## Subqueries
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@ -172,7 +172,7 @@ export const useFetchQuery = ({
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updatedPeriod.step = customStep;
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return expr.map(q => displayChart
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? getQueryRangeUrl(serverUrl, q, updatedPeriod, nocache, isTracingEnabled)
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: getQueryUrl(serverUrl, q, updatedPeriod, isTracingEnabled));
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: getQueryUrl(serverUrl, q, updatedPeriod, nocache, isTracingEnabled));
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} else {
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setError(ErrorTypes.validServer);
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}
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@ -88,6 +88,7 @@ The sandbox cluster installation is running under the constant load generated by
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* BUGFIX: [vmagent](https://docs.victoriametrics.com/vmagent.html): do not print redundant error logs when failed to scrape consul or nomad target. See [this pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5239).
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* BUGFIX: [vmstorage](https://docs.victoriametrics.com/Cluster-VictoriaMetrics.html): prevent deleted series to be searchable via `/api/v1/series` API if they were re-ingested with staleness markers. This situation could happen if user deletes the series from the target and from VM, and then vmagent sends stale markers for absent series. Thanks to @ilyatrefilov for the [issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5069) and [pull request](https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5174).
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* BUGFIX: [vmstorage](https://docs.victoriametrics.com/Cluster-VictoriaMetrics.html): log warning about switching to ReadOnly mode only on state change. Before, vmstorage would log this warning every 1s. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5159) for details.
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* BUGFIX: [vmui](https://docs.victoriametrics.com/#vmui): fix the `Disable cache` toggle at `JSON` and `Table` views. Previously response caching was always enabled and couldn't be disabled at these views.
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## [v1.94.0](https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.94.0)
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