diff --git a/app/vlselect/vmui/asset-manifest.json b/app/vlselect/vmui/asset-manifest.json index 9f614ab639..589a689f1f 100644 --- a/app/vlselect/vmui/asset-manifest.json +++ b/app/vlselect/vmui/asset-manifest.json @@ -1,13 +1,13 @@ { "files": { - "main.css": "./static/css/main.bc07cc78.css", - "main.js": "./static/js/main.8e7757ef.js", + "main.css": "./static/css/main.1c2f4a93.css", + "main.js": "./static/js/main.c3285306.js", "static/js/685.bebe1265.chunk.js": "./static/js/685.bebe1265.chunk.js", - "static/media/MetricsQL.md": "./static/media/MetricsQL.da86c2db4f0b05e286b0.md", + "static/media/MetricsQL.md": "./static/media/MetricsQL.df7574389d8f8bbcf0c7.md", "index.html": "./index.html" }, "entrypoints": [ - "static/css/main.bc07cc78.css", - "static/js/main.8e7757ef.js" + "static/css/main.1c2f4a93.css", + "static/js/main.c3285306.js" ] } \ No newline at end of file diff --git a/app/vlselect/vmui/index.html b/app/vlselect/vmui/index.html index edbebda023..e62e7a1cc1 100644 --- a/app/vlselect/vmui/index.html +++ b/app/vlselect/vmui/index.html @@ -1 +1 @@ -VM UI
\ No newline at end of file +VM UI
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{0,3}(?:`{3,}(?=[^`\\n]*\\n)|~{3,})[^\\n]*\\n").replace("list"," {0,3}(?:[*+-]|1[.)]) ").replace("html",")|<(?:script|pre|style|textarea|!--)").replace("tag",Os._tag).getRegex(),Os.gfm.paragraph=ys(Os._paragraph).replace("hr",Os.hr).replace("heading"," {0,3}#{1,6} ").replace("|lheading","").replace("table",Os.gfm.table).replace("blockquote"," {0,3}>").replace("fences"," {0,3}(?:`{3,}(?=[^`\\n]*\\n)|~{3,})[^\\n]*\\n").replace("list"," {0,3}(?:[*+-]|1[.)]) ").replace("html",")|<(?:script|pre|style|textarea|!--)").replace("tag",Os._tag).getRegex(),Os.pedantic={...Os.normal,html:ys("^ *(?:comment *(?:\\n|\\s*$)|<(tag)[\\s\\S]+? *(?:\\n{2,}|\\s*$)|\\s]*)*?/?> *(?:\\n{2,}|\\s*$))").replace("comment",Os._comment).replace(/tag/g,"(?!(?:a|em|strong|small|s|cite|q|dfn|abbr|data|time|code|var|samp|kbd|sub|sup|i|b|u|mark|ruby|rt|rp|bdi|bdo|span|br|wbr|ins|del|img)\\b)\\w+(?!:|[^\\w\\s@]*@)\\b").getRegex(),def:/^ *\[([^\]]+)\]: *]+)>?(?: +(["(][^\n]+[")]))? *(?:\n+|$)/,heading:/^(#{1,6})(.*)(?:\n+|$)/,fences:Cs,lheading:/^(.+?)\n {0,3}(=+|-+) *(?:\n+|$)/,paragraph:ys(Os.normal._paragraph).replace("hr",Os.hr).replace("heading"," *#{1,6} *[^\n]").replace("lheading",Os.lheading).replace("blockquote"," {0,3}>").replace("|fences","").replace("|list","").replace("|html","").getRegex()};const Ps={escape:/^\\([!"#$%&'()*+,\-./:;<=>?@\[\]\\^_`{|}~])/,autolink:/^<(scheme:[^\s\x00-\x1f<>]*|email)>/,url:Cs,tag:"^comment|^|^<[a-zA-Z][\\w-]*(?:attribute)*?\\s*/?>|^<\\?[\\s\\S]*?\\?>|^|^",link:/^!?\[(label)\]\(\s*(href)(?:\s+(title))?\s*\)/,reflink:/^!?\[(label)\]\[(ref)\]/,nolink:/^!?\[(ref)\](?:\[\])?/,reflinkSearch:"reflink|nolink(?!\\()",emStrong:{lDelim:/^(?:\*+(?:((?!\*)[punct])|[^\s*]))|^_+(?:((?!_)[punct])|([^\s_]))/,rDelimAst:/^[^_*]*?__[^_*]*?\*[^_*]*?(?=__)|[^*]+(?=[^*])|(?!\*)[punct](\*+)(?=[\s]|$)|[^punct\s](\*+)(?!\*)(?=[punct\s]|$)|(?!\*)[punct\s](\*+)(?=[^punct\s])|[\s](\*+)(?!\*)(?=[punct])|(?!\*)[punct](\*+)(?!\*)(?=[punct])|[^punct\s](\*+)(?=[^punct\s])/,rDelimUnd:/^[^_*]*?\*\*[^_*]*?_[^_*]*?(?=\*\*)|[^_]+(?=[^_])|(?!_)[punct](_+)(?=[\s]|$)|[^punct\s](_+)(?!_)(?=[punct\s]|$)|(?!_)[punct\s](_+)(?=[^punct\s])|[\s](_+)(?!_)(?=[punct])|(?!_)[punct](_+)(?!_)(?=[punct])/},code:/^(`+)([^`]|[^`][\s\S]*?[^`])\1(?!`)/,br:/^( {2,}|\\)\n(?!\s*$)/,del:Cs,text:/^(`+|[^`])(?:(?= {2,}\n)|[\s\S]*?(?:(?=[\\.5&&(n="x"+n.toString(16)),r+="&#"+n+";";return r}Ps._punctuation="\\p{P}$+<=>`^|~",Ps.punctuation=ys(Ps.punctuation,"u").replace(/punctuation/g,Ps._punctuation).getRegex(),Ps.blockSkip=/\[[^[\]]*?\]\([^\(\)]*?\)|`[^`]*?`|<[^<>]*?>/g,Ps.anyPunctuation=/\\[punct]/g,Ps._escapes=/\\([punct])/g,Ps._comment=ys(Os._comment).replace("(?:--\x3e|$)","--\x3e").getRegex(),Ps.emStrong.lDelim=ys(Ps.emStrong.lDelim,"u").replace(/punct/g,Ps._punctuation).getRegex(),Ps.emStrong.rDelimAst=ys(Ps.emStrong.rDelimAst,"gu").replace(/punct/g,Ps._punctuation).getRegex(),Ps.emStrong.rDelimUnd=ys(Ps.emStrong.rDelimUnd,"gu").replace(/punct/g,Ps._punctuation).getRegex(),Ps.anyPunctuation=ys(Ps.anyPunctuation,"gu").replace(/punct/g,Ps._punctuation).getRegex(),Ps._escapes=ys(Ps._escapes,"gu").replace(/punct/g,Ps._punctuation).getRegex(),Ps._scheme=/[a-zA-Z][a-zA-Z0-9+.-]{1,31}/,Ps._email=/[a-zA-Z0-9.!#$%&'*+/=?^_`{|}~-]+(@)[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?(?:\.[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?)+(?![-_])/,Ps.autolink=ys(Ps.autolink).replace("scheme",Ps._scheme).replace("email",Ps._email).getRegex(),Ps._attribute=/\s+[a-zA-Z:_][\w.:-]*(?:\s*=\s*"[^"]*"|\s*=\s*'[^']*'|\s*=\s*[^\s"'=<>`]+)?/,Ps.tag=ys(Ps.tag).replace("comment",Ps._comment).replace("attribute",Ps._attribute).getRegex(),Ps._label=/(?:\[(?:\\.|[^\[\]\\])*\]|\\.|`[^`]*`|[^\[\]\\`])*?/,Ps._href=/<(?:\\.|[^\n<>\\])+>|[^\s\x00-\x1f]*/,Ps._title=/"(?:\\"?|[^"\\])*"|'(?:\\'?|[^'\\])*'|\((?:\\\)?|[^)\\])*\)/,Ps.link=ys(Ps.link).replace("label",Ps._label).replace("href",Ps._href).replace("title",Ps._title).getRegex(),Ps.reflink=ys(Ps.reflink).replace("label",Ps._label).replace("ref",Os._label).getRegex(),Ps.nolink=ys(Ps.nolink).replace("ref",Os._label).getRegex(),Ps.reflinkSearch=ys(Ps.reflinkSearch,"g").replace("reflink",Ps.reflink).replace("nolink",Ps.nolink).getRegex(),Ps.normal={...Ps},Ps.pedantic={...Ps.normal,strong:{start:/^__|\*\*/,middle:/^__(?=\S)([\s\S]*?\S)__(?!_)|^\*\*(?=\S)([\s\S]*?\S)\*\*(?!\*)/,endAst:/\*\*(?!\*)/g,endUnd:/__(?!_)/g},em:{start:/^_|\*/,middle:/^()\*(?=\S)([\s\S]*?\S)\*(?!\*)|^_(?=\S)([\s\S]*?\S)_(?!_)/,endAst:/\*(?!\*)/g,endUnd:/_(?!_)/g},link:ys(/^!?\[(label)\]\((.*?)\)/).replace("label",Ps._label).getRegex(),reflink:ys(/^!?\[(label)\]\s*\[([^\]]*)\]/).replace("label",Ps._label).getRegex()},Ps.gfm={...Ps.normal,escape:ys(Ps.escape).replace("])","~|])").getRegex(),_extended_email:/[A-Za-z0-9._+-]+(@)[a-zA-Z0-9-_]+(?:\.[a-zA-Z0-9-_]*[a-zA-Z0-9])+(?![-_])/,url:/^((?:ftp|https?):\/\/|www\.)(?:[a-zA-Z0-9\-]+\.?)+[^\s<]*|^email/,_backpedal:/(?:[^?!.,:;*_'"~()&]+|\([^)]*\)|&(?![a-zA-Z0-9]+;$)|[?!.,:;*_'"~)]+(?!$))+/,del:/^(~~?)(?=[^\s~])([\s\S]*?[^\s~])\1(?=[^~]|$)/,text:/^([`~]+|[^`~])(?:(?= {2,}\n)|(?=[a-zA-Z0-9.!#$%&'*+\/=?_`{\|}~-]+@)|[\s\S]*?(?:(?=[\\1&&void 0!==arguments[1]?arguments[1]:[];for(e=this.options.pedantic?e.replace(/\t/g," ").replace(/^ +$/gm,""):e.replace(/^( *)(\t+)/gm,((e,t,n)=>t+" ".repeat(n.length)));e;)if(!(this.options.extensions&&this.options.extensions.block&&this.options.extensions.block.some((n=>!!(t=n.call({lexer:this},e,i))&&(e=e.substring(t.raw.length),i.push(t),!0)))))if(t=this.tokenizer.space(e))e=e.substring(t.raw.length),1===t.raw.length&&i.length>0?i[i.length-1].raw+="\n":i.push(t);else if(t=this.tokenizer.code(e))e=e.substring(t.raw.length),n=i[i.length-1],!n||"paragraph"!==n.type&&"text"!==n.type?i.push(t):(n.raw+="\n"+t.raw,n.text+="\n"+t.text,this.inlineQueue[this.inlineQueue.length-1].src=n.text);else if(t=this.tokenizer.fences(e))e=e.substring(t.raw.length),i.push(t);else if(t=this.tokenizer.heading(e))e=e.substring(t.raw.length),i.push(t);else if(t=this.tokenizer.hr(e))e=e.substring(t.raw.length),i.push(t);else if(t=this.tokenizer.blockquote(e))e=e.substring(t.raw.length),i.push(t);else if(t=this.tokenizer.list(e))e=e.substring(t.raw.length),i.push(t);else if(t=this.tokenizer.html(e))e=e.substring(t.raw.length),i.push(t);else if(t=this.tokenizer.def(e))e=e.substring(t.raw.length),n=i[i.length-1],!n||"paragraph"!==n.type&&"text"!==n.type?this.tokens.links[t.tag]||(this.tokens.links[t.tag]={href:t.href,title:t.title}):(n.raw+="\n"+t.raw,n.text+="\n"+t.raw,this.inlineQueue[this.inlineQueue.length-1].src=n.text);else if(t=this.tokenizer.table(e))e=e.substring(t.raw.length),i.push(t);else if(t=this.tokenizer.lheading(e))e=e.substring(t.raw.length),i.push(t);else{if(r=e,this.options.extensions&&this.options.extensions.startBlock){let t=1/0;const n=e.slice(1);let o;this.options.extensions.startBlock.forEach((function(e){o=e.call({lexer:this},n),"number"===typeof 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e=Object.keys(this.tokens.links);if(e.length>0)for(;null!=(o=this.tokenizer.rules.inline.reflinkSearch.exec(s));)e.includes(o[0].slice(o[0].lastIndexOf("[")+1,-1))&&(s=s.slice(0,o.index)+"["+"a".repeat(o[0].length-2)+"]"+s.slice(this.tokenizer.rules.inline.reflinkSearch.lastIndex))}for(;null!=(o=this.tokenizer.rules.inline.blockSkip.exec(s));)s=s.slice(0,o.index)+"["+"a".repeat(o[0].length-2)+"]"+s.slice(this.tokenizer.rules.inline.blockSkip.lastIndex);for(;null!=(o=this.tokenizer.rules.inline.anyPunctuation.exec(s));)s=s.slice(0,o.index)+"++"+s.slice(this.tokenizer.rules.inline.anyPunctuation.lastIndex);for(;e;)if(i||(a=""),i=!1,!(this.options.extensions&&this.options.extensions.inline&&this.options.extensions.inline.some((n=>!!(t=n.call({lexer:this},e,l))&&(e=e.substring(t.raw.length),l.push(t),!0)))))if(t=this.tokenizer.escape(e))e=e.substring(t.raw.length),l.push(t);else 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o;this.options.extensions.startInline.forEach((function(e){o=e.call({lexer:this},n),"number"===typeof o&&o>=0&&(t=Math.min(t,o))})),t<1/0&&t>=0&&(r=e.substring(0,t+1))}if(t=this.tokenizer.inlineText(r,Ls))e=e.substring(t.raw.length),"_"!==t.raw.slice(-1)&&(a=t.raw.slice(-1)),i=!0,n=l[l.length-1],n&&"text"===n.type?(n.raw+=t.raw,n.text+=t.text):l.push(t);else if(e){const t="Infinite loop on byte: "+e.charCodeAt(0);if(this.options.silent){console.error(t);break}throw new Error(t)}}else e=e.substring(t.raw.length),l.push(t);return l}}class Ds{constructor(e){this.options=e||as}code(e,t,n){const r=(t||"").match(/\S*/)[0];if(this.options.highlight){const t=this.options.highlight(e,r);null!=t&&t!==e&&(n=!0,e=t)}return e=e.replace(/\n$/,"")+"\n",r?'
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\n":"
\n"}list(e,t,n){const r=t?"ol":"ul";return"<"+r+(t&&1!==n?' start="'+n+'"':"")+">\n"+e+"\n"}listitem(e){return"
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app/vlselect/vmui/static/media/MetricsQL.df7574389d8f8bbcf0c7.md index 7f3ccc498b..fec10e5dc0 100644 --- a/app/vlselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md +++ b/app/vlselect/vmui/static/media/MetricsQL.df7574389d8f8bbcf0c7.md @@ -79,6 +79,8 @@ The list of MetricsQL features on top of PromQL: * [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/#filtering-by-multiple-or-filters) for details. +* Support for matching against multiple numeric constants via `q == (C1, ..., CN)` and `q != (C1, ..., CN)` syntax. For example, `status_code == (300, 301, 304)` + returns `status_code` metrics with one of `300`, `301` or `304` values. * 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 @@ -152,9 +154,9 @@ MetricsQL provides the following functions: ### Rollup functions -**Rollup functions** (aka range functions or window functions) calculate rollups over **raw samples** +**Rollup functions** (aka range functions or window functions) calculate rollups over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. +For example, `avg_over_time(temperature[24h])` calculates the average temperature over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) for the last 24 hours. Additional details: @@ -184,7 +186,7 @@ The list of supported rollup functions: #### absent_over_time `absent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns 1 -if the given lookbehind window `d` doesn't contain raw samples. Otherwise, it returns an empty result. +if the given lookbehind window `d` doesn't contain [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples). Otherwise, it returns an empty result. This function is supported by PromQL. @@ -193,7 +195,7 @@ See also [present_over_time](#present_over_time). #### aggr_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`. +which calculates all the listed `rollup_func*` for [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -203,7 +205,7 @@ would calculate [min_over_time](#min_over_time), [max_over_time](#max_over_time) #### ascent_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 +ascent of [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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/#filtering). This function is useful for tracking height gains in GPS tracking. Metric names are stripped from the resulting rollups. @@ -215,7 +217,7 @@ See also [descent_over_time](#descent_over_time). #### avg_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 +over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -225,7 +227,7 @@ See also [median_over_time](#median_over_time). #### changes `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 +the [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) changed on the given lookbehind window `d` per each time series returned 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`. @@ -240,7 +242,7 @@ See also [changes_prometheus](#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 +the [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) changed on the given lookbehind window `d` per each time series returned 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. @@ -254,7 +256,7 @@ See also [changes](#changes). #### count_eq_over_time -`count_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-functions), which calculates the number of raw samples +`count_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-functions), which calculates the number of [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -264,7 +266,7 @@ See also [count_over_time](#count_over_time), [share_eq_over_time](#share_eq_ove #### count_gt_over_time -`count_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-functions), which calculates the number of raw samples +`count_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-functions), which calculates the number of [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -274,7 +276,7 @@ See also [count_over_time](#count_over_time) and [share_gt_over_time](#share_gt_ #### count_le_over_time -`count_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-functions), which calculates the number of raw samples +`count_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-functions), which calculates the number of [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -284,7 +286,7 @@ See also [count_over_time](#count_over_time) and [share_le_over_time](#share_le_ #### count_ne_over_time -`count_ne_over_time(series_selector[d], ne)` is a [rollup function](#rollup-functions), which calculates the number of raw samples +`count_ne_over_time(series_selector[d], ne)` is a [rollup function](#rollup-functions), which calculates the number of [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -294,7 +296,7 @@ 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 +`count_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -305,7 +307,7 @@ See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_ #### count_values_over_time -`count_values_over_time("label", series_selector[d])` is a [rollup function](#rollup-functions), which counts the number of raw samples +`count_values_over_time("label", series_selector[d])` is a [rollup function](#rollup-functions), which counts the number of [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -315,8 +317,8 @@ 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/#filtering). +`decreases_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +value decreases 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. @@ -324,8 +326,8 @@ 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/#filtering). +`default_rollup(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +value on the given lookbehind window `d` 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), @@ -375,7 +377,7 @@ See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv). #### deriv_fast `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 +using the first and the last [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -384,8 +386,8 @@ See also [deriv](#deriv) and [ideriv](#ideriv). #### descent_over_time -`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 +`descent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates descent of [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +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/#filtering). This function is useful for tracking height loss in GPS tracking. @@ -396,8 +398,8 @@ 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/#filtering). +`distinct_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the number of unique [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +values 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. @@ -416,15 +418,15 @@ 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/#filtering). +`first_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the first [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +value 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). #### geomean_over_time `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 +over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -432,8 +434,8 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k #### histogram_over_time `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/#filtering). +[VictoriaMetrics histogram](https://godoc.org/github.com/VictoriaMetrics/metrics#Histogram) over [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). The resulting histograms are useful to pass to [histogram_quantile](#histogram_quantile) for calculating quantiles over multiple [gauges](https://docs.victoriametrics.com/keyconcepts/#gauge). For example, the following query calculates median temperature by country over the last 24 hours: @@ -457,7 +459,7 @@ See also [hoeffding_bound_lower](#hoeffding_bound_lower). #### holt_winters `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 +(aka [double exponential smoothing](https://en.wikipedia.org/wiki/Exponential_smoothing#Double_exponential_smoothing)) for [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering) returns time series of [gauge type](https://docs.victoriametrics.com/keyconcepts/#gauge). @@ -468,7 +470,7 @@ 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 +`idelta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between the last two [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -479,7 +481,8 @@ See also [delta](#delta). #### ideriv -`ideriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the per-second derivative based on the last two raw samples +`ideriv(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the per-second derivative based +on the last two [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -522,8 +525,8 @@ 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/#filtering). +`increases_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number of [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +value increases 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. @@ -531,14 +534,15 @@ 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/#filtering). +`integrate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the integral over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +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. #### 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 +`irate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the "instant" per-second increase rate over +the last two [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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). @@ -560,8 +564,8 @@ 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/#filtering). +`last_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +value 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. @@ -579,13 +583,14 @@ 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/#filtering). +over [raw samples](https://docs.victoriametrics.com/keyconcepts/#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 +`max_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the maximum value over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -594,7 +599,7 @@ See also [tmax_over_time](#tmax_over_time). #### median_over_time -`median_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates median value over raw samples +`median_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates median value over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyconcepts/#filtering). @@ -602,7 +607,7 @@ 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 +`min_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the minimum value over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -612,15 +617,16 @@ See also [tmin_over_time](#tmin_over_time). #### mode_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/#filtering). It is expected that raw sample values are discrete. +for [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). It is expected that [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +values are discrete. #### outlier_iqr_over_time `outlier_iqr_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last sample on the given lookbehind window `d` if its value is either smaller than the `q25-1.5*iqr` or bigger than `q75+1.5*iqr` where: -- `iqr` is an [Interquartile range](https://en.wikipedia.org/wiki/Interquartile_range) over raw samples on the lookbehind window `d` -- `q25` and `q75` are 25th and 75th [percentiles](https://en.wikipedia.org/wiki/Percentile) over raw samples on the lookbehind window `d`. +- `iqr` is an [Interquartile range](https://en.wikipedia.org/wiki/Interquartile_range) over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) on the lookbehind window `d` +- `q25` and `q75` are 25th and 75th [percentiles](https://en.wikipedia.org/wiki/Percentile) over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) on the lookbehind window `d`. The `outlier_iqr_over_time()` is useful for detecting anomalies in gauge values based on the previous history of values. 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 hour. @@ -630,8 +636,8 @@ See also [outliers_iqr](#outliers_iqr). #### predict_linear `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/#filtering). +linear interpolation over [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). This function is supported by PromQL. @@ -639,7 +645,7 @@ See also [range_linear_regression](#range_linear_regression). #### present_over_time -`present_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns 1 if there is at least a single raw sample +`present_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns 1 if there is at least a single [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) on the given lookbehind window `d`. Otherwise, an empty result is returned. Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. @@ -648,7 +654,7 @@ 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 +`quantile_over_time(phi, series_selector[d])` is a [rollup function](#rollup-functions), which calculates `phi`-quantile over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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]`. @@ -659,7 +665,7 @@ See also [quantiles_over_time](#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 +over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) on the given lookbehind window `d` per each time series returned 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]`. @@ -667,7 +673,7 @@ 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 +`range_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates value range over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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])`. @@ -692,7 +698,7 @@ See also [irate](#irate) and [rollup_rate](#rollup_rate). #### rate_over_sum -`rate_over_sum(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second rate over the sum of raw samples +`rate_over_sum(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second rate over the sum of [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -711,7 +717,7 @@ This function is supported by PromQL. #### rollup -`rollup(series_selector[d])` is a [rollup function](#rollup-functions), which calculates `min`, `max` and `avg` values for raw samples +`rollup(series_selector[d])` is a [rollup function](#rollup-functions), which calculates `min`, `max` and `avg` values for [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -721,7 +727,8 @@ See also [label_match](#label_match). #### rollup_candlestick `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. +over [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). This function is useful for financial applications. @@ -730,7 +737,7 @@ See also [label_match](#label_match). #### rollup_delta -`rollup_delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates differences between adjacent raw samples +`rollup_delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates differences between adjacent [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -745,8 +752,8 @@ See also [rollup_increase](#rollup_increase). #### rollup_deriv `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. +for adjacent [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label. @@ -756,7 +763,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k #### rollup_increase -`rollup_increase(series_selector[d])` is a [rollup function](#rollup-functions), which calculates increases for adjacent raw samples +`rollup_increase(series_selector[d])` is a [rollup function](#rollup-functions), which calculates increases for adjacent [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -768,7 +775,8 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k #### rollup_rate -`rollup_rate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second change rates for adjacent raw samples +`rollup_rate(series_selector[d])` is a [rollup function](#rollup-functions), which calculates per-second change rates +for adjacent [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) on the given lookbehind window `d` and returns `min`, `max` and `avg` values for the calculated per-second change rates and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup="avg"` additional labels. @@ -785,7 +793,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k #### rollup_scrape_interval `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 +adjacent [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -796,7 +804,8 @@ 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 +`scrape_interval(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the average interval in seconds +between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -805,7 +814,8 @@ See also [rollup_scrape_interval](#rollup_scrape_interval). #### share_gt_over_time -`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 +`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](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -817,7 +827,8 @@ See also [share_le_over_time](#share_le_over_time) and [count_gt_over_time](#cou #### share_le_over_time -`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 +`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](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -830,7 +841,8 @@ See also [share_gt_over_time](#share_gt_over_time) and [count_le_over_time](#cou #### share_eq_over_time -`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 +`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](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). @@ -848,7 +860,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k #### stddev_over_time -`stddev_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard deviation over raw samples +`stddev_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard deviation over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -859,7 +871,7 @@ 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 +`stdvar_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates standard variance over [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -870,8 +882,8 @@ 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/#filtering). +`sum_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-function), which calculates the sum of [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +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/#filtering). Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. @@ -879,8 +891,8 @@ 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/#filtering). +`sum_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-function), which calculates the sum of [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +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/#filtering). Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. @@ -888,8 +900,8 @@ 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/#filtering). +`sum_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-function), which calculates the sum of [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +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/#filtering). Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. @@ -897,7 +909,7 @@ 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 +`sum_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the sum of [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) values 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. @@ -906,14 +918,15 @@ 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/#filtering). +`sum2_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the sum of squares for [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) +values 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 +`timestamp(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision +for the last [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -924,7 +937,8 @@ 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 +`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](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -933,7 +947,8 @@ 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 +`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](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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. @@ -957,7 +972,8 @@ See also [tlast_change_over_time](#tlast_change_over_time). #### tmax_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 +`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](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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/#filtering). @@ -967,7 +983,8 @@ See also [max_over_time](#max_over_time). #### tmin_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 +`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](https://docs.victoriametrics.com/keyconcepts/#raw-samples) 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/#filtering). @@ -978,7 +995,7 @@ See also [min_over_time](#min_over_time). #### zscore_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 +for [raw samples](https://docs.victoriametrics.com/keyconcepts/#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/#filtering). Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. @@ -2212,6 +2229,7 @@ Any [rollup function](#rollup-functions) for something other than [series select 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). +This behavior can be disabled or logged via cmd-line flags `-search.disableImplicitConversion` and `-search.logImplicitConversion` since v1.101.0. VictoriaMetrics performs subqueries in the following way: @@ -2244,4 +2262,5 @@ VictoriaMetrics performs the following implicit conversions for incoming queries 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/#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])`. + For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up)))[1i:1i])`. + This behavior can be disabled or logged via cmd-line flags `-search.disableImplicitConversion` and `-search.logImplicitConversion` since v1.101.0.