From d3635aae7f32106fe8a2c9bdaf2b5f0112203caa Mon Sep 17 00:00:00 2001 From: Aliaksandr Valialkin Date: Thu, 18 Apr 2024 17:33:03 +0200 Subject: [PATCH] app/{vlselect,vmselect}: run `make vmui-update vmui-logs-update` --- app/vlselect/vmui/asset-manifest.json | 6 +- app/vlselect/vmui/index.html | 2 +- app/vlselect/vmui/static/js/main.034044a7.js | 2 - app/vlselect/vmui/static/js/main.8e7757ef.js | 2 + ...CENSE.txt => main.8e7757ef.js.LICENSE.txt} | 0 .../media/MetricsQL.da86c2db4f0b05e286b0.md} | 208 +++++++++--------- app/vmselect/vmui/asset-manifest.json | 10 +- app/vmselect/vmui/dashboards/README.md | 2 +- app/vmselect/vmui/index.html | 2 +- .../vmui/static/css/main.4ebf2874.css | 1 + .../vmui/static/css/main.a2ad4674.css | 1 - app/vmselect/vmui/static/js/main.202937c2.js | 2 + ...CENSE.txt => main.202937c2.js.LICENSE.txt} | 0 app/vmselect/vmui/static/js/main.f9cc1e6c.js | 2 - .../media/MetricsQL.da86c2db4f0b05e286b0.md} | 208 +++++++++--------- .../packages/vmui/src/assets/MetricsQL.md | 208 +++++++++--------- 16 files changed, 328 insertions(+), 328 deletions(-) delete mode 100644 app/vlselect/vmui/static/js/main.034044a7.js create mode 100644 app/vlselect/vmui/static/js/main.8e7757ef.js rename app/vlselect/vmui/static/js/{main.034044a7.js.LICENSE.txt => main.8e7757ef.js.LICENSE.txt} (100%) rename app/{vmselect/vmui/static/media/MetricsQL.10add6e7bdf0f1d98cf7.md => vlselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md} (95%) create mode 100644 app/vmselect/vmui/static/css/main.4ebf2874.css delete mode 100644 app/vmselect/vmui/static/css/main.a2ad4674.css create mode 100644 app/vmselect/vmui/static/js/main.202937c2.js rename app/vmselect/vmui/static/js/{main.f9cc1e6c.js.LICENSE.txt => main.202937c2.js.LICENSE.txt} (100%) delete mode 100644 app/vmselect/vmui/static/js/main.f9cc1e6c.js rename app/{vlselect/vmui/static/media/MetricsQL.10add6e7bdf0f1d98cf7.md => vmselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md} (95%) diff --git a/app/vlselect/vmui/asset-manifest.json b/app/vlselect/vmui/asset-manifest.json index 1a7695c03..9f614ab63 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.034044a7.js", + "main.js": "./static/js/main.8e7757ef.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.bc07cc78.css", - "static/js/main.034044a7.js" + "static/js/main.8e7757ef.js" ] } \ No newline at end of file diff --git a/app/vlselect/vmui/index.html b/app/vlselect/vmui/index.html index a72d8f239..edbebda02 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
\ No newline at end of file diff --git a/app/vlselect/vmui/static/js/main.034044a7.js b/app/vlselect/vmui/static/js/main.034044a7.js deleted file mode 100644 index 0abbe89f9..000000000 --- a/app/vlselect/vmui/static/js/main.034044a7.js +++ /dev/null @@ -1,2 +0,0 @@ -/*! 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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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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:/^([`~]+|[^`~])(?:(?= 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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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pt("div",{className:Yn()({"vm-header-controls":!0,"vm-header-controls_mobile":t}),children:[pt(yu,{}),pt(nu,{})]})},bu=(Boolean(We("DISABLED_DEFAULT_TIMEZONE")),()=>{const{serverUrl:e}=vt(),[n,r]=(Qt(),(0,t.useState)(!1)),[o,i]=(0,t.useState)(""),a=async()=>{};return(0,t.useEffect)((()=>{a()}),[e]),{isLoading:n,error:o}}),wu=()=>{const e=je(),{isMobile:n}=dr(),{pathname:r}=te();bu();return(0,t.useEffect)((()=>{var e;const t="vmui for VictoriaLogs",n=null===(e=cc[uc.logs])||void 0===e?void 0:e.title;document.title=n?"".concat(n," - ").concat(t):t}),[r]),pt("section",{className:"vm-container",children:[pt(jc,{controlsComponent:_u}),pt("div",{className:Yn()({"vm-container-body":!0,"vm-container-body_mobile":n,"vm-container-body_app":e}),children:pt(ye,{})}),!e&&pt(Vc,{})]})},ku=()=>{const[e,n]=(0,t.useState)(!1);return pt(ht.FK,{children:pt(Ne,{children:pt(yr,{children:pt(ht.FK,{children:[pt(xr,{onLoaded:n}),e&&pt(we,{children:pt(_e,{path:"/",element:pt(wu,{}),children:pt(_e,{path:"/",element:pt(oc,{})})})})]})})})})},xu=e=>{e&&n.e(685).then(n.bind(n,685)).then((t=>{let{getCLS:n,getFID:r,getFCP:o,getLCP:i,getTTFB:a}=t;n(e),r(e),o(e),i(e),a(e)}))},Su=document.getElementById("root");Su&&(0,t.render)(pt(ku,{}),Su),xu()})()})(); \ No newline at end of file diff --git a/app/vlselect/vmui/static/js/main.034044a7.js.LICENSE.txt b/app/vlselect/vmui/static/js/main.8e7757ef.js.LICENSE.txt similarity index 100% rename from app/vlselect/vmui/static/js/main.034044a7.js.LICENSE.txt rename to app/vlselect/vmui/static/js/main.8e7757ef.js.LICENSE.txt diff --git a/app/vmselect/vmui/static/media/MetricsQL.10add6e7bdf0f1d98cf7.md b/app/vlselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md similarity index 95% rename from app/vmselect/vmui/static/media/MetricsQL.10add6e7bdf0f1d98cf7.md rename to app/vlselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md index 3dfe43dca..7f3ccc498 100644 --- a/app/vmselect/vmui/static/media/MetricsQL.10add6e7bdf0f1d98cf7.md +++ b/app/vlselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md @@ -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])`. diff --git a/app/vmselect/vmui/asset-manifest.json b/app/vmselect/vmui/asset-manifest.json index 4a664d374..6db50dda7 100644 --- a/app/vmselect/vmui/asset-manifest.json +++ b/app/vmselect/vmui/asset-manifest.json @@ -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" ] } \ No newline at end of file diff --git a/app/vmselect/vmui/dashboards/README.md b/app/vmselect/vmui/dashboards/README.md index 1fab50792..1208e19c5 100644 --- a/app/vmselect/vmui/dashboards/README.md +++ b/app/vmselect/vmui/dashboards/README.md @@ -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) diff --git a/app/vmselect/vmui/index.html b/app/vmselect/vmui/index.html index b3671904a..0697bf80b 100644 --- a/app/vmselect/vmui/index.html +++ b/app/vmselect/vmui/index.html @@ -1 +1 @@ -VM UI
    \ No newline at end of file +VM UI
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    \n This table returns a list of the labels with the highest number of series.\n

    \n

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    \n

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    \n This table returns a list of unique label values per selected label.\n

    \n

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    ",labelValueCountByLabelName:"\n

    \n This table returns a list of labels with the highest number of the unique values.\n

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    \n This table returns a list of the label values pairs with the highest number of series.\n

    \n

    \n Use this table to identify unique label values pairs. This helps to identify same labels \n is applied to count timeseries in your system, since every unique combination of key-value label pairs \n creates a new time series and therefore can dramatically increase the number of time series in your system\n

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b/app/vmselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md similarity index 95% rename from app/vlselect/vmui/static/media/MetricsQL.10add6e7bdf0f1d98cf7.md rename to app/vmselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md index 3dfe43dca..7f3ccc498 100644 --- a/app/vlselect/vmui/static/media/MetricsQL.10add6e7bdf0f1d98cf7.md +++ b/app/vmselect/vmui/static/media/MetricsQL.da86c2db4f0b05e286b0.md @@ -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])`. diff --git a/app/vmui/packages/vmui/src/assets/MetricsQL.md b/app/vmui/packages/vmui/src/assets/MetricsQL.md index 3dfe43dca..7f3ccc498 100644 --- a/app/vmui/packages/vmui/src/assets/MetricsQL.md +++ b/app/vmui/packages/vmui/src/assets/MetricsQL.md @@ -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])`.