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We use a ",(0,a.kt)("inlineCode",{parentName:"li"},"pipeline")," to get just ",(0,a.kt)("inlineCode",{parentName:"li"},"authors")," ",(0,a.kt)("inlineCode",{parentName:"li"},"name")," and ",(0,a.kt)("inlineCode",{parentName:"li"},"bio"),".")),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-js"},'db.books.aggregate([\n // as a book can have many authors, we get one doc per book\'s author\n {$unwind: "$authors"},\n // convert it to an objectId\n {"$set":{"authorId":{"$toObjectId":"$authors._id"}}},\n {$lookup: {\n from: "authors",\n localField: "authorId",\n foreignField: "_id",\n pipeline: [\n {$project: {name: 1, bio: 1}},\n ],\n as: "bookAuthorDetails"\n } \n },\n // remove some noisy fields\n {$project: {attributes: 0, reviews: 0}}\n])\n')))}c.isMDXComponent=!0}}]); \ No newline at end of file diff --git a/assets/js/05b5f383.73023389.js b/assets/js/05b5f383.73023389.js new file mode 100644 index 0000000..3595cfe --- /dev/null +++ b/assets/js/05b5f383.73023389.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkaggregation_pipeline_workshop=self.webpackChunkaggregation_pipeline_workshop||[]).push([[426],{1530:(e,o,n)=>{n.r(o),n.d(o,{assets:()=>d,contentTitle:()=>r,default:()=>h,frontMatter:()=>s,metadata:()=>i,toc:()=>c});var t=n(5893),a=n(1151);const s={},r="\ud83e\uddb8\u200d\u2642\ufe0f Advanced lookups",i={id:"lookups/advanced-lookups",title:"\ud83e\uddb8\u200d\u2642\ufe0f Advanced lookups",description:"Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab",source:"@site/docs/60-lookups/2-advanced-lookups.mdx",sourceDirName:"60-lookups",slug:"/lookups/advanced-lookups",permalink:"/aggregation-pipeline-lab/docs/lookups/advanced-lookups",draft:!1,unlisted:!1,editUrl:"https://github.com/mongodb-developer/aggregation-pipeline-lab/blob/main/docs/60-lookups/2-advanced-lookups.mdx",tags:[],version:"current",sidebarPosition:2,frontMatter:{},sidebar:"tutorialSidebar",previous:{title:"Lookupups AKA Left Outer Join",permalink:"/aggregation-pipeline-lab/docs/lookups/lookups"},next:{title:"Grouping results",permalink:"/aggregation-pipeline-lab/docs/category/grouping-results"}},d={},c=[];function l(e){const o={admonition:"admonition",code:"code",h1:"h1",li:"li",p:"p",pre:"pre",ul:"ul",...(0,a.a)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(o.h1,{id:"\ufe0f-advanced-lookups",children:"\ud83e\uddb8\u200d\u2642\ufe0f Advanced lookups"}),"\n",(0,t.jsx)(o.admonition,{type:"info",children:(0,t.jsx)(o.p,{children:"Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab"})}),"\n",(0,t.jsxs)(o.p,{children:["We get this request: Write a ",(0,t.jsx)(o.code,{children:"$lookup"})," to get ",(0,t.jsx)(o.code,{children:"name"})," and ",(0,t.jsx)(o.code,{children:"bio"})," from author's information inside each book document. 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r=this._stack[n],o=[],a=0;a<e.length;a++){var i=r(e[a],a,e);if(null!=i&&""!==i)if(Array.isArray(i))for(var l=0;l<i.length;l++)o.push(i[l]);else o.push(i)}e=o}return e},R.Pipeline.prototype.runString=function(e,t){var n=new R.Token(e,t);return this.run([n]).map((function(e){return e.toString()}))},R.Pipeline.prototype.reset=function(){this._stack=[]},R.Pipeline.prototype.toJSON=function(){return this._stack.map((function(e){return R.Pipeline.warnIfFunctionNotRegistered(e),e.label}))},R.Vector=function(e){this._magnitude=0,this.elements=e||[]},R.Vector.prototype.positionForIndex=function(e){if(0==this.elements.length)return 0;for(var t=0,n=this.elements.length/2,r=n-t,o=Math.floor(r/2),a=this.elements[2*o];r>1&&(a<e&&(t=o),a>e&&(n=o),a!=e);)r=n-t,o=t+Math.floor(r/2),a=this.elements[2*o];return a==e||a>e?2*o:a<e?2*(o+1):void 0},R.Vector.prototype.insert=function(e,t){this.upsert(e,t,(function(){throw"duplicate index"}))},R.Vector.prototype.upsert=function(e,t,n){this._magnitude=0;var r=this.positionForIndex(e);this.elements[r]==e?this.elements[r+1]=n(this.elements[r+1],t):this.elements.splice(r,0,e,t)},R.Vector.prototype.magnitude=function(){if(this._magnitude)return this._magnitude;for(var e=0,t=this.elements.length,n=1;n<t;n+=2){var r=this.elements[n];e+=r*r}return this._magnitude=Math.sqrt(e)},R.Vector.prototype.dot=function(e){for(var t=0,n=this.elements,r=e.elements,o=n.length,a=r.length,i=0,l=0,s=0,u=0;s<o&&u<a;)(i=n[s])<(l=r[u])?s+=2:i>l?u+=2:i==l&&(t+=n[s+1]*r[u+1],s+=2,u+=2);return t},R.Vector.prototype.similarity=function(e){return this.dot(e)/this.magnitude()||0},R.Vector.prototype.toArray=function(){for(var e=new Array(this.elements.length/2),t=1,n=0;t<this.elements.length;t+=2,n++)e[n]=this.elements[t];return e},R.Vector.prototype.toJSON=function(){return this.elements},R.stemmer=(i={ational:"ate",tional:"tion",enci:"ence",anci:"ance",izer:"ize",bli:"ble",alli:"al",entli:"ent",eli:"e",ousli:"ous",ization:"ize",ation:"ate",ator:"ate",alism:"al",iveness:"ive",fulness:"ful",ousness:"ous",aliti:"al",iviti:"ive",biliti:"ble",logi:"log"},l={icate:"ic",ative:"",alize:"al",iciti:"ic",ical:"ic",ful:"",ness:""},d="^("+(u="[^aeiou][^aeiouy]*")+")?"+(c=(s="[aeiouy]")+"[aeiou]*")+u+"("+c+")?$",f="^("+u+")?"+c+u+c+u,p="^("+u+")?"+s,m=new RegExp("^("+u+")?"+c+u),g=new RegExp(f),h=new RegExp(d),b=new RegExp(p),y=/^(.+?)(ss|i)es$/,v=/^(.+?)([^s])s$/,w=/^(.+?)eed$/,S=/^(.+?)(ed|ing)$/,E=/.$/,k=/(at|bl|iz)$/,_=new RegExp("([^aeiouylsz])\\1$"),x=new RegExp("^"+u+s+"[^aeiouwxy]$"),O=/^(.+?[^aeiou])y$/,P=/^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/,C=/^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/,T=/^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/,I=/^(.+?)(s|t)(ion)$/,A=/^(.+?)e$/,N=/ll$/,L=new RegExp("^"+u+s+"[^aeiouwxy]$"),j=function(e){var t,n,r,o,a,s,u;if(e.length<3)return e;if("y"==(r=e.substr(0,1))&&(e=r.toUpperCase()+e.substr(1)),a=v,(o=y).test(e)?e=e.replace(o,"$1$2"):a.test(e)&&(e=e.replace(a,"$1$2")),a=S,(o=w).test(e)){var c=o.exec(e);(o=m).test(c[1])&&(o=E,e=e.replace(o,""))}else a.test(e)&&(t=(c=a.exec(e))[1],(a=b).test(t)&&(s=_,u=x,(a=k).test(e=t)?e+="e":s.test(e)?(o=E,e=e.replace(o,"")):u.test(e)&&(e+="e")));return(o=O).test(e)&&(e=(t=(c=o.exec(e))[1])+"i"),(o=P).test(e)&&(t=(c=o.exec(e))[1],n=c[2],(o=m).test(t)&&(e=t+i[n])),(o=C).test(e)&&(t=(c=o.exec(e))[1],n=c[2],(o=m).test(t)&&(e=t+l[n])),a=I,(o=T).test(e)?(t=(c=o.exec(e))[1],(o=g).test(t)&&(e=t)):a.test(e)&&(t=(c=a.exec(e))[1]+c[2],(a=g).test(t)&&(e=t)),(o=A).test(e)&&(t=(c=o.exec(e))[1],a=h,s=L,((o=g).test(t)||a.test(t)&&!s.test(t))&&(e=t)),a=g,(o=N).test(e)&&a.test(e)&&(o=E,e=e.replace(o,"")),"y"==r&&(e=r.toLowerCase()+e.substr(1)),e},function(e){return e.update(j)}),R.Pipeline.registerFunction(R.stemmer,"stemmer"),R.generateStopWordFilter=function(e){var t=e.reduce((function(e,t){return e[t]=t,e}),{});return function(e){if(e&&t[e.toString()]!==e.toString())return e}},R.stopWordFilter=R.generateStopWordFilter(["a","able","about","across","after","all","almost","also","am","among","an","and","any","are","as","at","be","because","been","but","by","can","cannot","could","dear","did","do","does","either","else","ever","every","for","from","get","got","had","has","have","he","her","hers","him","his","how","however","i","if","in","into","is","it","its","just","least","let","like","likely","may","me","might","most","must","my","neither","no","nor","not","of","off","often","on","only","or","other","our","own","rather","said","say","says","she","should","since","so","some","than","that","the","their","them","then","there","these","they","this","tis","to","too","twas","us","wants","was","we","were","what","when","where","which","while","who","whom","why","will","with","would","yet","you","your"]),R.Pipeline.registerFunction(R.stopWordFilter,"stopWordFilter"),R.trimmer=function(e){return e.update((function(e){return e.replace(/^\W+/,"").replace(/\W+$/,"")}))},R.Pipeline.registerFunction(R.trimmer,"trimmer"),R.TokenSet=function(){this.final=!1,this.edges={},this.id=R.TokenSet._nextId,R.TokenSet._nextId+=1},R.TokenSet._nextId=1,R.TokenSet.fromArray=function(e){for(var t=new R.TokenSet.Builder,n=0,r=e.length;n<r;n++)t.insert(e[n]);return t.finish(),t.root},R.TokenSet.fromClause=function(e){return"editDistance"in e?R.TokenSet.fromFuzzyString(e.term,e.editDistance):R.TokenSet.fromString(e.term)},R.TokenSet.fromFuzzyString=function(e,t){for(var n=new R.TokenSet,r=[{node:n,editsRemaining:t,str:e}];r.length;){var o=r.pop();if(o.str.length>0){var a,i=o.str.charAt(0);i in o.node.edges?a=o.node.edges[i]:(a=new R.TokenSet,o.node.edges[i]=a),1==o.str.length&&(a.final=!0),r.push({node:a,editsRemaining:o.editsRemaining,str:o.str.slice(1)})}if(0!=o.editsRemaining){if("*"in o.node.edges)var l=o.node.edges["*"];else{l=new R.TokenSet;o.node.edges["*"]=l}if(0==o.str.length&&(l.final=!0),r.push({node:l,editsRemaining:o.editsRemaining-1,str:o.str}),o.str.length>1&&r.push({node:o.node,editsRemaining:o.editsRemaining-1,str:o.str.slice(1)}),1==o.str.length&&(o.node.final=!0),o.str.length>=1){if("*"in o.node.edges)var s=o.node.edges["*"];else{s=new R.TokenSet;o.node.edges["*"]=s}1==o.str.length&&(s.final=!0),r.push({node:s,editsRemaining:o.editsRemaining-1,str:o.str.slice(1)})}if(o.str.length>1){var u,c=o.str.charAt(0),d=o.str.charAt(1);d in o.node.edges?u=o.node.edges[d]:(u=new R.TokenSet,o.node.edges[d]=u),1==o.str.length&&(u.final=!0),r.push({node:u,editsRemaining:o.editsRemaining-1,str:c+o.str.slice(2)})}}}return n},R.TokenSet.fromString=function(e){for(var t=new R.TokenSet,n=t,r=0,o=e.length;r<o;r++){var a=e[r],i=r==o-1;if("*"==a)t.edges[a]=t,t.final=i;else{var l=new R.TokenSet;l.final=i,t.edges[a]=l,t=l}}return n},R.TokenSet.prototype.toArray=function(){for(var e=[],t=[{prefix:"",node:this}];t.length;){var n=t.pop(),r=Object.keys(n.node.edges),o=r.length;n.node.final&&(n.prefix.charAt(0),e.push(n.prefix));for(var a=0;a<o;a++){var i=r[a];t.push({prefix:n.prefix.concat(i),node:n.node.edges[i]})}}return e},R.TokenSet.prototype.toString=function(){if(this._str)return this._str;for(var e=this.final?"1":"0",t=Object.keys(this.edges).sort(),n=t.length,r=0;r<n;r++){var o=t[r];e=e+o+this.edges[o].id}return e},R.TokenSet.prototype.intersect=function(e){for(var t=new R.TokenSet,n=void 0,r=[{qNode:e,output:t,node:this}];r.length;){n=r.pop();for(var o=Object.keys(n.qNode.edges),a=o.length,i=Object.keys(n.node.edges),l=i.length,s=0;s<a;s++)for(var u=o[s],c=0;c<l;c++){var d=i[c];if(d==u||"*"==u){var f=n.node.edges[d],p=n.qNode.edges[u],m=f.final&&p.final,g=void 0;d in n.output.edges?(g=n.output.edges[d]).final=g.final||m:((g=new R.TokenSet).final=m,n.output.edges[d]=g),r.push({qNode:p,output:g,node:f})}}}return t},R.TokenSet.Builder=function(){this.previousWord="",this.root=new R.TokenSet,this.uncheckedNodes=[],this.minimizedNodes={}},R.TokenSet.Builder.prototype.insert=function(e){var t,n=0;if(e<this.previousWord)throw new Error("Out of order word insertion");for(var r=0;r<e.length&&r<this.previousWord.length&&e[r]==this.previousWord[r];r++)n++;this.minimize(n),t=0==this.uncheckedNodes.length?this.root:this.uncheckedNodes[this.uncheckedNodes.length-1].child;for(r=n;r<e.length;r++){var o=new R.TokenSet,a=e[r];t.edges[a]=o,this.uncheckedNodes.push({parent:t,char:a,child:o}),t=o}t.final=!0,this.previousWord=e},R.TokenSet.Builder.prototype.finish=function(){this.minimize(0)},R.TokenSet.Builder.prototype.minimize=function(e){for(var t=this.uncheckedNodes.length-1;t>=e;t--){var n=this.uncheckedNodes[t],r=n.child.toString();r in this.minimizedNodes?n.parent.edges[n.char]=this.minimizedNodes[r]:(n.child._str=r,this.minimizedNodes[r]=n.child),this.uncheckedNodes.pop()}},R.Index=function(e){this.invertedIndex=e.invertedIndex,this.fieldVectors=e.fieldVectors,this.tokenSet=e.tokenSet,this.fields=e.fields,this.pipeline=e.pipeline},R.Index.prototype.search=function(e){return this.query((function(t){new R.QueryParser(e,t).parse()}))},R.Index.prototype.query=function(e){for(var t=new R.Query(this.fields),n=Object.create(null),r=Object.create(null),o=Object.create(null),a=Object.create(null),i=Object.create(null),l=0;l<this.fields.length;l++)r[this.fields[l]]=new R.Vector;e.call(t,t);for(l=0;l<t.clauses.length;l++){var s=t.clauses[l],u=null,c=R.Set.empty;u=s.usePipeline?this.pipeline.runString(s.term,{fields:s.fields}):[s.term];for(var d=0;d<u.length;d++){var f=u[d];s.term=f;var p=R.TokenSet.fromClause(s),m=this.tokenSet.intersect(p).toArray();if(0===m.length&&s.presence===R.Query.presence.REQUIRED){for(var g=0;g<s.fields.length;g++){a[A=s.fields[g]]=R.Set.empty}break}for(var h=0;h<m.length;h++){var b=m[h],y=this.invertedIndex[b],v=y._index;for(g=0;g<s.fields.length;g++){var w=y[A=s.fields[g]],S=Object.keys(w),E=b+"/"+A,k=new R.Set(S);if(s.presence==R.Query.presence.REQUIRED&&(c=c.union(k),void 0===a[A]&&(a[A]=R.Set.complete)),s.presence!=R.Query.presence.PROHIBITED){if(r[A].upsert(v,s.boost,(function(e,t){return e+t})),!o[E]){for(var _=0;_<S.length;_++){var x,O=S[_],P=new R.FieldRef(O,A),C=w[O];void 0===(x=n[P])?n[P]=new R.MatchData(b,A,C):x.add(b,A,C)}o[E]=!0}}else void 0===i[A]&&(i[A]=R.Set.empty),i[A]=i[A].union(k)}}}if(s.presence===R.Query.presence.REQUIRED)for(g=0;g<s.fields.length;g++){a[A=s.fields[g]]=a[A].intersect(c)}}var T=R.Set.complete,I=R.Set.empty;for(l=0;l<this.fields.length;l++){var A;a[A=this.fields[l]]&&(T=T.intersect(a[A])),i[A]&&(I=I.union(i[A]))}var N=Object.keys(n),L=[],j=Object.create(null);if(t.isNegated()){N=Object.keys(this.fieldVectors);for(l=0;l<N.length;l++){P=N[l];var D=R.FieldRef.fromString(P);n[P]=new R.MatchData}}for(l=0;l<N.length;l++){var M=(D=R.FieldRef.fromString(N[l])).docRef;if(T.contains(M)&&!I.contains(M)){var F,B=this.fieldVectors[D],U=r[D.fieldName].similarity(B);if(void 0!==(F=j[M]))F.score+=U,F.matchData.combine(n[D]);else{var $={ref:M,score:U,matchData:n[D]};j[M]=$,L.push($)}}}return L.sort((function(e,t){return t.score-e.score}))},R.Index.prototype.toJSON=function(){var e=Object.keys(this.invertedIndex).sort().map((function(e){return[e,this.invertedIndex[e]]}),this),t=Object.keys(this.fieldVectors).map((function(e){return[e,this.fieldVectors[e].toJSON()]}),this);return{version:R.version,fields:this.fields,fieldVectors:t,invertedIndex:e,pipeline:this.pipeline.toJSON()}},R.Index.load=function(e){var t={},n={},r=e.fieldVectors,o=Object.create(null),a=e.invertedIndex,i=new R.TokenSet.Builder,l=R.Pipeline.load(e.pipeline);e.version!=R.version&&R.utils.warn("Version mismatch when loading serialised index. Current version of lunr '"+R.version+"' does not match serialized index '"+e.version+"'");for(var s=0;s<r.length;s++){var u=(d=r[s])[0],c=d[1];n[u]=new R.Vector(c)}for(s=0;s<a.length;s++){var d,f=(d=a[s])[0],p=d[1];i.insert(f),o[f]=p}return i.finish(),t.fields=e.fields,t.fieldVectors=n,t.invertedIndex=o,t.tokenSet=i.root,t.pipeline=l,new R.Index(t)},R.Builder=function(){this._ref="id",this._fields=Object.create(null),this._documents=Object.create(null),this.invertedIndex=Object.create(null),this.fieldTermFrequencies={},this.fieldLengths={},this.tokenizer=R.tokenizer,this.pipeline=new R.Pipeline,this.searchPipeline=new R.Pipeline,this.documentCount=0,this._b=.75,this._k1=1.2,this.termIndex=0,this.metadataWhitelist=[]},R.Builder.prototype.ref=function(e){this._ref=e},R.Builder.prototype.field=function(e,t){if(/\//.test(e))throw new RangeError("Field '"+e+"' contains illegal character '/'");this._fields[e]=t||{}},R.Builder.prototype.b=function(e){this._b=e<0?0:e>1?1:e},R.Builder.prototype.k1=function(e){this._k1=e},R.Builder.prototype.add=function(e,t){var n=e[this._ref],r=Object.keys(this._fields);this._documents[n]=t||{},this.documentCount+=1;for(var o=0;o<r.length;o++){var a=r[o],i=this._fields[a].extractor,l=this._fields[a].isLiteral??!1,s=i?i(e):e[a],u=l?[s]:this.tokenizer(s,{fields:[a]}),c=l?u:this.pipeline.run(u),d=new R.FieldRef(n,a),f=Object.create(null);this.fieldTermFrequencies[d]=f,this.fieldLengths[d]=0,this.fieldLengths[d]+=c.length;for(var p=0;p<c.length;p++){var m=c[p];if(null==f[m]&&(f[m]=0),f[m]+=1,null==this.invertedIndex[m]){var g=Object.create(null);g._index=this.termIndex,this.termIndex+=1;for(var h=0;h<r.length;h++)g[r[h]]=Object.create(null);this.invertedIndex[m]=g}null==this.invertedIndex[m][a][n]&&(this.invertedIndex[m][a][n]=Object.create(null));for(var b=0;b<this.metadataWhitelist.length;b++){var y=this.metadataWhitelist[b],v=m.metadata[y];null==this.invertedIndex[m][a][n][y]&&(this.invertedIndex[m][a][n][y]=[]),this.invertedIndex[m][a][n][y].push(v)}}}},R.Builder.prototype.calculateAverageFieldLengths=function(){for(var e=Object.keys(this.fieldLengths),t=e.length,n={},r={},o=0;o<t;o++){var a=R.FieldRef.fromString(e[o]),i=a.fieldName;r[i]||(r[i]=0),r[i]+=1,n[i]||(n[i]=0),n[i]+=this.fieldLengths[a]}var l=Object.keys(this._fields);for(o=0;o<l.length;o++){var s=l[o];n[s]=n[s]/r[s]}this.averageFieldLength=n},R.Builder.prototype.createFieldVectors=function(){for(var e={},t=Object.keys(this.fieldTermFrequencies),n=t.length,r=Object.create(null),o=0;o<n;o++){for(var a=R.FieldRef.fromString(t[o]),i=a.fieldName,l=this.fieldLengths[a],s=new R.Vector,u=this.fieldTermFrequencies[a],c=Object.keys(u),d=c.length,f=this._fields[i].boost||1,p=this._documents[a.docRef].boost||1,m=0;m<d;m++){var g,h,b,y=c[m],v=u[y],w=this.invertedIndex[y]._index;void 0===r[y]?(g=R.idf(this.invertedIndex[y],this.documentCount),r[y]=g):g=r[y],h=g*((this._k1+1)*v)/(this._k1*(1-this._b+this._b*(l/this.averageFieldLength[i]))+v),h*=f,h*=p,b=Math.round(1e3*h)/1e3,s.insert(w,b)}e[a]=s}this.fieldVectors=e},R.Builder.prototype.createTokenSet=function(){this.tokenSet=R.TokenSet.fromArray(Object.keys(this.invertedIndex).sort())},R.Builder.prototype.build=function(){return this.calculateAverageFieldLengths(),this.createFieldVectors(),this.createTokenSet(),new R.Index({invertedIndex:this.invertedIndex,fieldVectors:this.fieldVectors,tokenSet:this.tokenSet,fields:Object.keys(this._fields),pipeline:this.searchPipeline})},R.Builder.prototype.use=function(e){var t=Array.prototype.slice.call(arguments,1);t.unshift(this),e.apply(this,t)},R.MatchData=function(e,t,n){for(var r=Object.create(null),o=Object.keys(n||{}),a=0;a<o.length;a++){var i=o[a];r[i]=n[i].slice()}this.metadata=Object.create(null),void 0!==e&&(this.metadata[e]=Object.create(null),this.metadata[e][t]=r)},R.MatchData.prototype.combine=function(e){for(var t=Object.keys(e.metadata),n=0;n<t.length;n++){var r=t[n],o=Object.keys(e.metadata[r]);null==this.metadata[r]&&(this.metadata[r]=Object.create(null));for(var a=0;a<o.length;a++){var i=o[a],l=Object.keys(e.metadata[r][i]);null==this.metadata[r][i]&&(this.metadata[r][i]=Object.create(null));for(var s=0;s<l.length;s++){var u=l[s];null==this.metadata[r][i][u]?this.metadata[r][i][u]=e.metadata[r][i][u]:this.metadata[r][i][u]=this.metadata[r][i][u].concat(e.metadata[r][i][u])}}}},R.MatchData.prototype.add=function(e,t,n){if(!(e in this.metadata))return this.metadata[e]=Object.create(null),void(this.metadata[e][t]=n);if(t in this.metadata[e])for(var r=Object.keys(n),o=0;o<r.length;o++){var a=r[o];a in this.metadata[e][t]?this.metadata[e][t][a]=this.metadata[e][t][a].concat(n[a]):this.metadata[e][t][a]=n[a]}else 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R.QueryLexer(e),this.query=t,this.currentClause={},this.lexemeIdx=0},R.QueryParser.prototype.parse=function(){this.lexer.run(),this.lexemes=this.lexer.lexemes;for(var e=R.QueryParser.parseClause;e;)e=e(this);return this.query},R.QueryParser.prototype.peekLexeme=function(){return this.lexemes[this.lexemeIdx]},R.QueryParser.prototype.consumeLexeme=function(){var e=this.peekLexeme();return this.lexemeIdx+=1,e},R.QueryParser.prototype.nextClause=function(){var e=this.currentClause;this.query.clause(e),this.currentClause={}},R.QueryParser.parseClause=function(e){var t=e.peekLexeme();if(null!=t)switch(t.type){case R.QueryLexer.PRESENCE:return R.QueryParser.parsePresence;case R.QueryLexer.FIELD:return R.QueryParser.parseField;case R.QueryLexer.TERM:return R.QueryParser.parseTerm;default:var n="expected either a field or a term, found "+t.type;throw t.str.length>=1&&(n+=" with value '"+t.str+"'"),new R.QueryParseError(n,t.start,t.end)}},R.QueryParser.parsePresence=function(e){var t=e.consumeLexeme();if(null!=t){switch(t.str){case"-":e.currentClause.presence=R.Query.presence.PROHIBITED;break;case"+":e.currentClause.presence=R.Query.presence.REQUIRED;break;default:var n="unrecognised presence operator'"+t.str+"'";throw new R.QueryParseError(n,t.start,t.end)}var r=e.peekLexeme();if(null==r){n="expecting term or field, found nothing";throw new R.QueryParseError(n,t.start,t.end)}switch(r.type){case R.QueryLexer.FIELD:return R.QueryParser.parseField;case R.QueryLexer.TERM:return R.QueryParser.parseTerm;default:n="expecting term or field, found '"+r.type+"'";throw new R.QueryParseError(n,r.start,r.end)}}},R.QueryParser.parseField=function(e){var t=e.consumeLexeme();if(null!=t){if(-1==e.query.allFields.indexOf(t.str)){var n=e.query.allFields.map((function(e){return"'"+e+"'"})).join(", "),r="unrecognised field '"+t.str+"', possible fields: "+n;throw new R.QueryParseError(r,t.start,t.end)}e.currentClause.fields=[t.str];var o=e.peekLexeme();if(null==o){r="expecting term, 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this.minimizedNodes?n.parent.edges[n.char]=this.minimizedNodes[r]:(n.child._str=r,this.minimizedNodes[r]=n.child),this.uncheckedNodes.pop()}},R.Index=function(e){this.invertedIndex=e.invertedIndex,this.fieldVectors=e.fieldVectors,this.tokenSet=e.tokenSet,this.fields=e.fields,this.pipeline=e.pipeline},R.Index.prototype.search=function(e){return this.query((function(t){new R.QueryParser(e,t).parse()}))},R.Index.prototype.query=function(e){for(var t=new R.Query(this.fields),n=Object.create(null),r=Object.create(null),o=Object.create(null),a=Object.create(null),i=Object.create(null),l=0;l<this.fields.length;l++)r[this.fields[l]]=new R.Vector;e.call(t,t);for(l=0;l<t.clauses.length;l++){var s=t.clauses[l],u=null,c=R.Set.empty;u=s.usePipeline?this.pipeline.runString(s.term,{fields:s.fields}):[s.term];for(var d=0;d<u.length;d++){var p=u[d];s.term=p;var f=R.TokenSet.fromClause(s),g=this.tokenSet.intersect(f).toArray();if(0===g.length&&s.presence===R.Query.presence.REQUIRED){for(var m=0;m<s.fields.length;m++){a[I=s.fields[m]]=R.Set.empty}break}for(var h=0;h<g.length;h++){var y=g[h],b=this.invertedIndex[y],v=b._index;for(m=0;m<s.fields.length;m++){var w=b[I=s.fields[m]],S=Object.keys(w),k=y+"/"+I,x=new R.Set(S);if(s.presence==R.Query.presence.REQUIRED&&(c=c.union(x),void 0===a[I]&&(a[I]=R.Set.complete)),s.presence!=R.Query.presence.PROHIBITED){if(r[I].upsert(v,s.boost,(function(e,t){return e+t})),!o[k]){for(var _=0;_<S.length;_++){var E,O=S[_],j=new R.FieldRef(O,I),C=w[O];void 0===(E=n[j])?n[j]=new R.MatchData(y,I,C):E.add(y,I,C)}o[k]=!0}}else void 0===i[I]&&(i[I]=R.Set.empty),i[I]=i[I].union(x)}}}if(s.presence===R.Query.presence.REQUIRED)for(m=0;m<s.fields.length;m++){a[I=s.fields[m]]=a[I].intersect(c)}}var P=R.Set.complete,T=R.Set.empty;for(l=0;l<this.fields.length;l++){var I;a[I=this.fields[l]]&&(P=P.intersect(a[I])),i[I]&&(T=T.union(i[I]))}var A=Object.keys(n),N=[],L=Object.create(null);if(t.isNegated()){A=Object.keys(this.fieldVectors);for(l=0;l<A.length;l++){j=A[l];var D=R.FieldRef.fromString(j);n[j]=new R.MatchData}}for(l=0;l<A.length;l++){var F=(D=R.FieldRef.fromString(A[l])).docRef;if(P.contains(F)&&!T.contains(F)){var M,B=this.fieldVectors[D],z=r[D.fieldName].similarity(B);if(void 0!==(M=L[F]))M.score+=z,M.matchData.combine(n[D]);else{var $={ref:F,score:z,matchData:n[D]};L[F]=$,N.push($)}}}return N.sort((function(e,t){return t.score-e.score}))},R.Index.prototype.toJSON=function(){var e=Object.keys(this.invertedIndex).sort().map((function(e){return[e,this.invertedIndex[e]]}),this),t=Object.keys(this.fieldVectors).map((function(e){return[e,this.fieldVectors[e].toJSON()]}),this);return{version:R.version,fields:this.fields,fieldVectors:t,invertedIndex:e,pipeline:this.pipeline.toJSON()}},R.Index.load=function(e){var t={},n={},r=e.fieldVectors,o=Object.create(null),a=e.invertedIndex,i=new R.TokenSet.Builder,l=R.Pipeline.load(e.pipeline);e.version!=R.version&&R.utils.warn("Version mismatch when loading serialised index. Current version of lunr '"+R.version+"' does not match serialized index '"+e.version+"'");for(var s=0;s<r.length;s++){var u=(d=r[s])[0],c=d[1];n[u]=new R.Vector(c)}for(s=0;s<a.length;s++){var d,p=(d=a[s])[0],f=d[1];i.insert(p),o[p]=f}return i.finish(),t.fields=e.fields,t.fieldVectors=n,t.invertedIndex=o,t.tokenSet=i.root,t.pipeline=l,new R.Index(t)},R.Builder=function(){this._ref="id",this._fields=Object.create(null),this._documents=Object.create(null),this.invertedIndex=Object.create(null),this.fieldTermFrequencies={},this.fieldLengths={},this.tokenizer=R.tokenizer,this.pipeline=new R.Pipeline,this.searchPipeline=new R.Pipeline,this.documentCount=0,this._b=.75,this._k1=1.2,this.termIndex=0,this.metadataWhitelist=[]},R.Builder.prototype.ref=function(e){this._ref=e},R.Builder.prototype.field=function(e,t){if(/\//.test(e))throw new RangeError("Field '"+e+"' contains illegal character '/'");this._fields[e]=t||{}},R.Builder.prototype.b=function(e){this._b=e<0?0:e>1?1:e},R.Builder.prototype.k1=function(e){this._k1=e},R.Builder.prototype.add=function(e,t){var n=e[this._ref],r=Object.keys(this._fields);this._documents[n]=t||{},this.documentCount+=1;for(var o=0;o<r.length;o++){var a=r[o],i=this._fields[a].extractor,l=this._fields[a].isLiteral??!1,s=i?i(e):e[a],u=l?[s]:this.tokenizer(s,{fields:[a]}),c=l?u:this.pipeline.run(u),d=new R.FieldRef(n,a),p=Object.create(null);this.fieldTermFrequencies[d]=p,this.fieldLengths[d]=0,this.fieldLengths[d]+=c.length;for(var f=0;f<c.length;f++){var g=c[f];if(null==p[g]&&(p[g]=0),p[g]+=1,null==this.invertedIndex[g]){var m=Object.create(null);m._index=this.termIndex,this.termIndex+=1;for(var h=0;h<r.length;h++)m[r[h]]=Object.create(null);this.invertedIndex[g]=m}null==this.invertedIndex[g][a][n]&&(this.invertedIndex[g][a][n]=Object.create(null));for(var y=0;y<this.metadataWhitelist.length;y++){var b=this.metadataWhitelist[y],v=g.metadata[b];null==this.invertedIndex[g][a][n][b]&&(this.invertedIndex[g][a][n][b]=[]),this.invertedIndex[g][a][n][b].push(v)}}}},R.Builder.prototype.calculateAverageFieldLengths=function(){for(var e=Object.keys(this.fieldLengths),t=e.length,n={},r={},o=0;o<t;o++){var a=R.FieldRef.fromString(e[o]),i=a.fieldName;r[i]||(r[i]=0),r[i]+=1,n[i]||(n[i]=0),n[i]+=this.fieldLengths[a]}var l=Object.keys(this._fields);for(o=0;o<l.length;o++){var s=l[o];n[s]=n[s]/r[s]}this.averageFieldLength=n},R.Builder.prototype.createFieldVectors=function(){for(var e={},t=Object.keys(this.fieldTermFrequencies),n=t.length,r=Object.create(null),o=0;o<n;o++){for(var a=R.FieldRef.fromString(t[o]),i=a.fieldName,l=this.fieldLengths[a],s=new R.Vector,u=this.fieldTermFrequencies[a],c=Object.keys(u),d=c.length,p=this._fields[i].boost||1,f=this._documents[a.docRef].boost||1,g=0;g<d;g++){var m,h,y,b=c[g],v=u[b],w=this.invertedIndex[b]._index;void 0===r[b]?(m=R.idf(this.invertedIndex[b],this.documentCount),r[b]=m):m=r[b],h=m*((this._k1+1)*v)/(this._k1*(1-this._b+this._b*(l/this.averageFieldLength[i]))+v),h*=p,h*=f,y=Math.round(1e3*h)/1e3,s.insert(w,y)}e[a]=s}this.fieldVectors=e},R.Builder.prototype.createTokenSet=function(){this.tokenSet=R.TokenSet.fromArray(Object.keys(this.invertedIndex).sort())},R.Builder.prototype.build=function(){return this.calculateAverageFieldLengths(),this.createFieldVectors(),this.createTokenSet(),new R.Index({invertedIndex:this.invertedIndex,fieldVectors:this.fieldVectors,tokenSet:this.tokenSet,fields:Object.keys(this._fields),pipeline:this.searchPipeline})},R.Builder.prototype.use=function(e){var t=Array.prototype.slice.call(arguments,1);t.unshift(this),e.apply(this,t)},R.MatchData=function(e,t,n){for(var r=Object.create(null),o=Object.keys(n||{}),a=0;a<o.length;a++){var i=o[a];r[i]=n[i].slice()}this.metadata=Object.create(null),void 0!==e&&(this.metadata[e]=Object.create(null),this.metadata[e][t]=r)},R.MatchData.prototype.combine=function(e){for(var t=Object.keys(e.metadata),n=0;n<t.length;n++){var r=t[n],o=Object.keys(e.metadata[r]);null==this.metadata[r]&&(this.metadata[r]=Object.create(null));for(var a=0;a<o.length;a++){var i=o[a],l=Object.keys(e.metadata[r][i]);null==this.metadata[r][i]&&(this.metadata[r][i]=Object.create(null));for(var s=0;s<l.length;s++){var u=l[s];null==this.metadata[r][i][u]?this.metadata[r][i][u]=e.metadata[r][i][u]:this.metadata[r][i][u]=this.metadata[r][i][u].concat(e.metadata[r][i][u])}}}},R.MatchData.prototype.add=function(e,t,n){if(!(e in this.metadata))return this.metadata[e]=Object.create(null),void(this.metadata[e][t]=n);if(t in this.metadata[e])for(var r=Object.keys(n),o=0;o<r.length;o++){var a=r[o];a in this.metadata[e][t]?this.metadata[e][t][a]=this.metadata[e][t][a].concat(n[a]):this.metadata[e][t][a]=n[a]}else this.metadata[e][t]=n},R.Query=function(e){this.clauses=[],this.allFields=e},R.Query.wildcard=new String("*"),R.Query.wildcard.NONE=0,R.Query.wildcard.LEADING=1,R.Query.wildcard.TRAILING=2,R.Query.presence={OPTIONAL:1,REQUIRED:2,PROHIBITED:3},R.Query.prototype.clause=function(e){return"fields"in e||(e.fields=this.allFields),"boost"in e||(e.boost=1),"usePipeline"in e||(e.usePipeline=!0),"wildcard"in e||(e.wildcard=R.Query.wildcard.NONE),e.wildcard&R.Query.wildcard.LEADING&&e.term.charAt(0)!=R.Query.wildcard&&(e.term="*"+e.term),e.wildcard&R.Query.wildcard.TRAILING&&e.term.slice(-1)!=R.Query.wildcard&&(e.term=e.term+"*"),"presence"in e||(e.presence=R.Query.presence.OPTIONAL),this.clauses.push(e),this},R.Query.prototype.isNegated=function(){for(var e=0;e<this.clauses.length;e++)if(this.clauses[e].presence!=R.Query.presence.PROHIBITED)return!1;return!0},R.Query.prototype.term=function(e,t){if(Array.isArray(e))return e.forEach((function(e){this.term(e,R.utils.clone(t))}),this),this;var n=t||{};return n.term=e.toString(),this.clause(n),this},R.QueryParseError=function(e,t,n){this.name="QueryParseError",this.message=e,this.start=t,this.end=n},R.QueryParseError.prototype=new Error,R.QueryLexer=function(e){this.lexemes=[],this.str=e,this.length=e.length,this.pos=0,this.start=0,this.escapeCharPositions=[]},R.QueryLexer.prototype.run=function(){for(var e=R.QueryLexer.lexText;e;)e=e(this)},R.QueryLexer.prototype.sliceString=function(){for(var e=[],t=this.start,n=this.pos,r=0;r<this.escapeCharPositions.length;r++)n=this.escapeCharPositions[r],e.push(this.str.slice(t,n)),t=n+1;return e.push(this.str.slice(t,this.pos)),this.escapeCharPositions.length=0,e.join("")},R.QueryLexer.prototype.emit=function(e){this.lexemes.push({type:e,str:this.sliceString(),start:this.start,end:this.pos}),this.start=this.pos},R.QueryLexer.prototype.escapeCharacter=function(){this.escapeCharPositions.push(this.pos-1),this.pos+=1},R.QueryLexer.prototype.next=function(){if(this.pos>=this.length)return R.QueryLexer.EOS;var e=this.str.charAt(this.pos);return this.pos+=1,e},R.QueryLexer.prototype.width=function(){return this.pos-this.start},R.QueryLexer.prototype.ignore=function(){this.start==this.pos&&(this.pos+=1),this.start=this.pos},R.QueryLexer.prototype.backup=function(){this.pos-=1},R.QueryLexer.prototype.acceptDigitRun=function(){var e,t;do{t=(e=this.next()).charCodeAt(0)}while(t>47&&t<58);e!=R.QueryLexer.EOS&&this.backup()},R.QueryLexer.prototype.more=function(){return this.pos<this.length},R.QueryLexer.EOS="EOS",R.QueryLexer.FIELD="FIELD",R.QueryLexer.TERM="TERM",R.QueryLexer.EDIT_DISTANCE="EDIT_DISTANCE",R.QueryLexer.BOOST="BOOST",R.QueryLexer.PRESENCE="PRESENCE",R.QueryLexer.lexField=function(e){return e.backup(),e.emit(R.QueryLexer.FIELD),e.ignore(),R.QueryLexer.lexText},R.QueryLexer.lexTerm=function(e){if(e.width()>1&&(e.backup(),e.emit(R.QueryLexer.TERM)),e.ignore(),e.more())return R.QueryLexer.lexText},R.QueryLexer.lexEditDistance=function(e){return e.ignore(),e.acceptDigitRun(),e.emit(R.QueryLexer.EDIT_DISTANCE),R.QueryLexer.lexText},R.QueryLexer.lexBoost=function(e){return e.ignore(),e.acceptDigitRun(),e.emit(R.QueryLexer.BOOST),R.QueryLexer.lexText},R.QueryLexer.lexEOS=function(e){e.width()>0&&e.emit(R.QueryLexer.TERM)},R.QueryLexer.termSeparator=R.tokenizer.separator,R.QueryLexer.lexText=function(e){for(;;){var t=e.next();if(t==R.QueryLexer.EOS)return R.QueryLexer.lexEOS;if(92!=t.charCodeAt(0)){if(":"==t)return R.QueryLexer.lexField;if("~"==t)return e.backup(),e.width()>0&&e.emit(R.QueryLexer.TERM),R.QueryLexer.lexEditDistance;if("^"==t)return e.backup(),e.width()>0&&e.emit(R.QueryLexer.TERM),R.QueryLexer.lexBoost;if("+"==t&&1===e.width())return e.emit(R.QueryLexer.PRESENCE),R.QueryLexer.lexText;if("-"==t&&1===e.width())return e.emit(R.QueryLexer.PRESENCE),R.QueryLexer.lexText;if(t.match(R.QueryLexer.termSeparator))return R.QueryLexer.lexTerm}else e.escapeCharacter()}},R.QueryParser=function(e,t){this.lexer=new R.QueryLexer(e),this.query=t,this.currentClause={},this.lexemeIdx=0},R.QueryParser.prototype.parse=function(){this.lexer.run(),this.lexemes=this.lexer.lexemes;for(var e=R.QueryParser.parseClause;e;)e=e(this);return this.query},R.QueryParser.prototype.peekLexeme=function(){return this.lexemes[this.lexemeIdx]},R.QueryParser.prototype.consumeLexeme=function(){var e=this.peekLexeme();return this.lexemeIdx+=1,e},R.QueryParser.prototype.nextClause=function(){var e=this.currentClause;this.query.clause(e),this.currentClause={}},R.QueryParser.parseClause=function(e){var t=e.peekLexeme();if(null!=t)switch(t.type){case R.QueryLexer.PRESENCE:return R.QueryParser.parsePresence;case R.QueryLexer.FIELD:return R.QueryParser.parseField;case R.QueryLexer.TERM:return R.QueryParser.parseTerm;default:var n="expected either a field or a term, found "+t.type;throw t.str.length>=1&&(n+=" with value '"+t.str+"'"),new R.QueryParseError(n,t.start,t.end)}},R.QueryParser.parsePresence=function(e){var t=e.consumeLexeme();if(null!=t){switch(t.str){case"-":e.currentClause.presence=R.Query.presence.PROHIBITED;break;case"+":e.currentClause.presence=R.Query.presence.REQUIRED;break;default:var n="unrecognised presence operator'"+t.str+"'";throw new R.QueryParseError(n,t.start,t.end)}var r=e.peekLexeme();if(null==r){n="expecting term or field, found nothing";throw new R.QueryParseError(n,t.start,t.end)}switch(r.type){case R.QueryLexer.FIELD:return R.QueryParser.parseField;case R.QueryLexer.TERM:return R.QueryParser.parseTerm;default:n="expecting term or field, found '"+r.type+"'";throw new R.QueryParseError(n,r.start,r.end)}}},R.QueryParser.parseField=function(e){var t=e.consumeLexeme();if(null!=t){if(-1==e.query.allFields.indexOf(t.str)){var n=e.query.allFields.map((function(e){return"'"+e+"'"})).join(", "),r="unrecognised field '"+t.str+"', possible fields: "+n;throw new R.QueryParseError(r,t.start,t.end)}e.currentClause.fields=[t.str];var o=e.peekLexeme();if(null==o){r="expecting term, found nothing";throw new R.QueryParseError(r,t.start,t.end)}if(o.type===R.QueryLexer.TERM)return R.QueryParser.parseTerm;r="expecting term, found '"+o.type+"'";throw new R.QueryParseError(r,o.start,o.end)}},R.QueryParser.parseTerm=function(e){var t=e.consumeLexeme();if(null!=t){e.currentClause.term=t.str.toLowerCase(),-1!=t.str.indexOf("*")&&(e.currentClause.usePipeline=!1);var n=e.peekLexeme();if(null!=n)switch(n.type){case R.QueryLexer.TERM:return e.nextClause(),R.QueryParser.parseTerm;case R.QueryLexer.FIELD:return e.nextClause(),R.QueryParser.parseField;case R.QueryLexer.EDIT_DISTANCE:return R.QueryParser.parseEditDistance;case R.QueryLexer.BOOST:return R.QueryParser.parseBoost;case R.QueryLexer.PRESENCE:return e.nextClause(),R.QueryParser.parsePresence;default:var r="Unexpected lexeme type '"+n.type+"'";throw new R.QueryParseError(r,n.start,n.end)}else e.nextClause()}},R.QueryParser.parseEditDistance=function(e){var t=e.consumeLexeme();if(null!=t){var n=parseInt(t.str,10);if(isNaN(n)){var r="edit distance must be numeric";throw new R.QueryParseError(r,t.start,t.end)}e.currentClause.editDistance=n;var o=e.peekLexeme();if(null!=o)switch(o.type){case R.QueryLexer.TERM:return e.nextClause(),R.QueryParser.parseTerm;case R.QueryLexer.FIELD:return e.nextClause(),R.QueryParser.parseField;case R.QueryLexer.EDIT_DISTANCE:return R.QueryParser.parseEditDistance;case R.QueryLexer.BOOST:return R.QueryParser.parseBoost;case R.QueryLexer.PRESENCE:return e.nextClause(),R.QueryParser.parsePresence;default:r="Unexpected lexeme type '"+o.type+"'";throw new R.QueryParseError(r,o.start,o.end)}else e.nextClause()}},R.QueryParser.parseBoost=function(e){var t=e.consumeLexeme();if(null!=t){var n=parseInt(t.str,10);if(isNaN(n)){var r="boost must be numeric";throw new R.QueryParseError(r,t.start,t.end)}e.currentClause.boost=n;var o=e.peekLexeme();if(null!=o)switch(o.type){case R.QueryLexer.TERM:return e.nextClause(),R.QueryParser.parseTerm;case 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e.split("").forEach((function(o){n.every((function(n){if(-1!==n.indexOf(o)){if(r.indexOf(n)>-1)return!1;e=e.replace(new RegExp("["+n+"]","gm"+t),"["+n+"]"),r.push(n)}return!0}))})),e}},{key:"createMergedBlanksRegExp",value:function(e){return e.replace(/[\s]+/gim,"[\\s]+")}},{key:"createAccuracyRegExp",value:function(e){var t=this,n="!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~\xa1\xbf",r=this.opt.accuracy,o="string"==typeof r?r:r.value,a="string"==typeof r?[]:r.limiters,i="";switch(a.forEach((function(e){i+="|"+t.escapeStr(e)})),o){case"partially":default:return"()("+e+")";case"complementary":return"()([^"+(i="\\s"+(i||this.escapeStr(n)))+"]*"+e+"[^"+i+"]*)";case"exactly":return"(^|\\s"+i+")("+e+")(?=$|\\s"+i+")"}}},{key:"getSeparatedKeywords",value:function(e){var t=this,n=[];return e.forEach((function(e){t.opt.separateWordSearch?e.split(" ").forEach((function(e){e.trim()&&-1===n.indexOf(e)&&n.push(e)})):e.trim()&&-1===n.indexOf(e)&&n.push(e)})),{keywords:n.sort((function(e,t){return t.length-e.length})),length:n.length}}},{key:"isNumeric",value:function(e){return Number(parseFloat(e))==e}},{key:"checkRanges",value:function(e){var t=this;if(!Array.isArray(e)||"[object Object]"!==Object.prototype.toString.call(e[0]))return this.log("markRanges() will only accept an array of objects"),this.opt.noMatch(e),[];var n=[],r=0;return e.sort((function(e,t){return e.start-t.start})).forEach((function(e){var o=t.callNoMatchOnInvalidRanges(e,r),a=o.start,i=o.end;o.valid&&(e.start=a,e.length=i-a,n.push(e),r=i)})),n}},{key:"callNoMatchOnInvalidRanges",value:function(e,t){var n=void 0,r=void 0,o=!1;return e&&void 0!==e.start?(r=(n=parseInt(e.start,10))+parseInt(e.length,10),this.isNumeric(e.start)&&this.isNumeric(e.length)&&r-t>0&&r-n>0?o=!0:(this.log("Ignoring invalid or overlapping range: "+JSON.stringify(e)),this.opt.noMatch(e))):(this.log("Ignoring invalid range: 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o.matches(e,this.opt.exclude.concat(["script","style","title","head","html"]))}},{key:"wrapRangeInTextNode",value:function(e,t,n){var r=this.opt.element?this.opt.element:"mark",o=e.splitText(t),a=o.splitText(n-t),i=document.createElement(r);return i.setAttribute("data-markjs","true"),this.opt.className&&i.setAttribute("class",this.opt.className),i.textContent=o.textContent,o.parentNode.replaceChild(i,o),a}},{key:"wrapRangeInMappedTextNode",value:function(e,t,n,r,o){var a=this;e.nodes.every((function(i,l){var s=e.nodes[l+1];if(void 0===s||s.start>t){if(!r(i.node))return!1;var u=t-i.start,c=(n>i.end?i.end:n)-i.start,d=e.value.substr(0,i.start),p=e.value.substr(c+i.start);if(i.node=a.wrapRangeInTextNode(i.node,u,c),e.value=d+p,e.nodes.forEach((function(t,n){n>=l&&(e.nodes[n].start>0&&n!==l&&(e.nodes[n].start-=c),e.nodes[n].end-=c)})),n-=c,o(i.node.previousSibling,i.start),!(n>i.end))return!1;t=i.end}return!0}))}},{key:"wrapMatches",value:function(e,t,n,r,o){var 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t=e.stateNode;t.pendingContext?Ro(0,t.pendingContext,t.pendingContext!==t.context):t.context&&Ro(0,t.context,!1),oi(e,t.containerInfo)}function Il(e,t,n,r,o){return ga(),ma(o),t.flags|=256,Sl(e,t,n,r),t.child}var Al,Nl,Ll,Rl,Dl={dehydrated:null,treeContext:null,retryLane:0};function Fl(e){return{baseLanes:e,cachePool:null,transitions:null}}function Ml(e,t,n){var r,o=t.pendingProps,i=si.current,l=!1,s=0!=(128&t.flags);if((r=s)||(r=(null===e||null!==e.memoizedState)&&0!=(2&i)),r?(l=!0,t.flags&=-129):null!==e&&null===e.memoizedState||(i|=1),jo(si,1&i),null===e)return 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a/docs/category/counting-and-sorting.html +++ b/docs/category/counting-and-sorting.html @@ -1,19 +1,16 @@ <!doctype html> -<html lang="en" dir="ltr" class="docs-wrapper docs-doc-page docs-version-current plugin-docs plugin-id-default" data-has-hydrated="false"> +<html lang="en" dir="ltr" class="docs-wrapper plugin-docs plugin-id-default docs-version-current docs-doc-page" data-has-hydrated="false"> <head> <meta charset="UTF-8"> -<meta name="generator" content="Docusaurus v2.4.3"> -<title data-rh="true">Counting and Sorting | Aggregation Pipeline Lab + +Counting and Sorting | Aggregation Pipeline Lab - - - + + + -
-

Counting and Sorting

Count and Sort our documents.

- - +

Counting and Sorting

Count and Sort our documents.

\ No newline at end of file diff --git a/docs/category/exporting-data.html b/docs/category/exporting-data.html index 2cd06cc..e3076a4 100644 --- a/docs/category/exporting-data.html +++ b/docs/category/exporting-data.html @@ -1,19 +1,16 @@ - + - -Exporting Data | Aggregation Pipeline Lab + +Exporting Data | Aggregation Pipeline Lab - - - + + + -
-

Exporting Data

Exporting data.

- - +

Exporting Data

Exporting data.

\ No newline at end of file diff --git a/docs/category/grouping-results.html b/docs/category/grouping-results.html index 9bf4389..34e6617 100644 --- a/docs/category/grouping-results.html +++ b/docs/category/grouping-results.html @@ -1,19 +1,16 @@ - + - -Grouping results | Aggregation Pipeline Lab + +Grouping results | Aggregation Pipeline Lab - - - + + + -
-

Grouping results

Grouping.

- - +

Grouping results

Grouping.

\ No newline at end of file diff --git a/docs/category/lookups--joins.html b/docs/category/lookups--joins.html index 89af875..7517828 100644 --- a/docs/category/lookups--joins.html +++ b/docs/category/lookups--joins.html @@ -1,19 +1,16 @@ - + - -Lookups / Joins | Aggregation Pipeline Lab + +Lookups / Joins | Aggregation Pipeline Lab - - - + + + -
-

Lookups / Joins

Learn how to make Joins.

- - +

Lookups / Joins

Learn how to make Joins.

\ No newline at end of file diff --git a/docs/category/modifying-results.html b/docs/category/modifying-results.html index fdc31ca..4cb7022 100644 --- a/docs/category/modifying-results.html +++ b/docs/category/modifying-results.html @@ -1,19 +1,16 @@ - + - -Modifying results | Aggregation Pipeline Lab + +Modifying results | Aggregation Pipeline Lab - - - + + + -
-

Modifying results

Changing the output of our pipelines.

- - +

Modifying results

Changing the output of our pipelines.

\ No newline at end of file diff --git a/docs/category/prerequisites.html b/docs/category/prerequisites.html index e7443bf..a151629 100644 --- a/docs/category/prerequisites.html +++ b/docs/category/prerequisites.html @@ -1,19 +1,16 @@ - + - -Prerequisites | Aggregation Pipeline Lab + +Prerequisites | Aggregation Pipeline Lab - - - + + + -
-

Prerequisites

In this section, you will get up and running, creating your Atlas account and spinning up your first database.

- - +

Prerequisites

In this section, you will get up and running, creating your Atlas account and spinning up your first database.

\ No newline at end of file diff --git a/docs/category/simple-queries.html b/docs/category/simple-queries.html index 4281841..32dfb44 100644 --- a/docs/category/simple-queries.html +++ b/docs/category/simple-queries.html @@ -1,19 +1,16 @@ - + - -Simple queries | Aggregation Pipeline Lab + +Simple queries | Aggregation Pipeline Lab - - - + + + -
-

Simple queries

Let's start with the basics.

- - +

Simple queries

Let's start with the basics.

\ No newline at end of file diff --git a/docs/category/the-aggregation-pipeline.html b/docs/category/the-aggregation-pipeline.html index 0767fbd..68e15a9 100644 --- a/docs/category/the-aggregation-pipeline.html +++ b/docs/category/the-aggregation-pipeline.html @@ -1,19 +1,16 @@ - + - -The Aggregation Pipeline | Aggregation Pipeline Lab + +The Aggregation Pipeline | Aggregation Pipeline Lab - - - + + + -
-

The Aggregation Pipeline

Learn the basics of the Aggregation Pipeline and how it compares to SQL.

- - +

The Aggregation Pipeline

Learn the basics of the Aggregation Pipeline and how it compares to SQL.

\ No newline at end of file diff --git a/docs/category/using-arrays.html b/docs/category/using-arrays.html index 5d2ef9d..30ed19d 100644 --- a/docs/category/using-arrays.html +++ b/docs/category/using-arrays.html @@ -1,19 +1,16 @@ - + - -Using Arrays | Aggregation Pipeline Lab + +Using Arrays | Aggregation Pipeline Lab - - - + + + -
-

Using Arrays

Using arrays inside our documents.

- - +

Using Arrays

Using arrays inside our documents.

\ No newline at end of file diff --git a/docs/counting-sorting/counting-documents.html b/docs/counting-sorting/counting-documents.html index 6ba8d56..326d92c 100644 --- a/docs/counting-sorting/counting-documents.html +++ b/docs/counting-sorting/counting-documents.html @@ -1,19 +1,27 @@ - + - -$count | Aggregation Pipeline Lab + +$count | Aggregation Pipeline Lab - - - + + + -
-

$count

How can we be sure that this pipeline is returning exactly 2 books?

let moreThan150pages =  {pages: {$gte: 150}}
let booksFrom1985WithMoreThan150pages = {$match: {$and: [{year: 1985}, moreThan150pages]}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};

db.books.aggregate([
    booksFrom1985WithMoreThan150pages,
    showOnlyTheseFields,
    getJust15books,
]);

Counting the books! Let's add a new stage to the pipeline to count those books:

let moreThan150pages =  {pages: {$gte: 150}}
let booksFrom1985WithMoreThan150pages = {$match: {$and: [{year: 1985}, moreThan150pages]}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};
let count = {$count: "totalBooks"}

db.books.aggregate([
    booksFrom1985WithMoreThan150pages,
    showOnlyTheseFields,
    getJust15books,
    count,
]);

Here, $count will count the resulting docs and will return a document with just one field: totalBooks

{
  totalBooks: 2
}

💻 How many authors do we have in our authors collection?

Answer
db.authors.aggregate([{$count: "authorCount"}])

The order of stages is important​

If we count after the $match stage, the document we're passing to the next steps contains only the totalBooks field. So the $project stage will return an empty document.

let moreThan150pages =  {pages: {$gte: 150}}
let booksFrom1985WithMoreThan150pages = {$match: {$and: [{year: 1985}, moreThan150pages]}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};
let count = {$count: "totalBooks"}

db.books.aggregate([
    booksFrom1985WithMoreThan150pages,
    count,
    showOnlyTheseFields,
    getJust15books,
]);
- - +

$count

+

How can we be sure that this pipeline is returning exactly 2 books?

+
let moreThan150pages =  {pages: {$gte: 150}}
let booksFrom1985WithMoreThan150pages = {$match: {$and: [{year: 1985}, moreThan150pages]}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};

db.books.aggregate([
    booksFrom1985WithMoreThan150pages,
    showOnlyTheseFields,
    getJust15books,
]);
+

Counting the books! Let's add a new stage to the pipeline to count those books:

+
let moreThan150pages =  {pages: {$gte: 150}}
let booksFrom1985WithMoreThan150pages = {$match: {$and: [{year: 1985}, moreThan150pages]}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};
let count = {$count: "totalBooks"}

db.books.aggregate([
    booksFrom1985WithMoreThan150pages,
    showOnlyTheseFields,
    getJust15books,
    count,
]);
+

Here, $count will count the resulting docs and will return a document with just one field: totalBooks

+
{
  totalBooks: 2
}
+

💻 How many authors do we have in our authors collection?

+
Answer
db.authors.aggregate([{$count: "authorCount"}])
+

The order of stages is important​

+

If we count after the $match stage, the document we're passing to the next steps contains only the totalBooks field. So the $project stage will return an empty document.

+
let moreThan150pages =  {pages: {$gte: 150}}
let booksFrom1985WithMoreThan150pages = {$match: {$and: [{year: 1985}, moreThan150pages]}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};
let count = {$count: "totalBooks"}

db.books.aggregate([
    booksFrom1985WithMoreThan150pages,
    count,
    showOnlyTheseFields,
    getJust15books,
]);
\ No newline at end of file diff --git a/docs/counting-sorting/sorting.html b/docs/counting-sorting/sorting.html index 3135805..6095621 100644 --- a/docs/counting-sorting/sorting.html +++ b/docs/counting-sorting/sorting.html @@ -1,19 +1,24 @@ - + - -Sorting | Aggregation Pipeline Lab + +Sorting | Aggregation Pipeline Lab - - - + + + -
-

Sorting

We can sort our results using the $sort stage. We need to sort on a field, being 1 ascending and -1 descending order.

💻 Let's get all books from 1984, sorted by number of pages. We'll only show the title, pages and authors.

let booksFrom1984 = {$match: {year: 1984}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, pages: 1, authors: 1}};
let slimmerBooksFirst = {$sort: {"pages": 1}}

db.books.aggregate([
    booksFrom1984,
    showOnlyTheseFields,
    slimmerBooksFirst,
]);

As we can see, books with no pages info appear first. These documents don't have that information, hence pages is null and gets sorted as less than any number.

💻 We can sort the other way around:

let booksFrom1984 = {$match: {year: 1984}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, pages: 1, authors: 1}};
let thickerBooksFirst = {$sort: {"pages": -1}}

db.books.aggregate([
    booksFrom1984,
    showOnlyTheseFields,
    thickerBooksFirst,
]);

💻 How can we get the thickest book from 1984?

Answer
let booksFrom1984 = {$match: {year: 1984}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, pages: 1, authors: 1}};
let thickerBooksFirst = {$sort: {"pages": -1}}
let justOne = {$limit: 1}

db.books.aggregate([
    booksFrom1984,
    showOnlyTheseFields,
    thickerBooksFirst,
    justOne
]);
- - +

Sorting

+

We can sort our results using the $sort stage. We need to sort on a field, being 1 ascending and -1 descending order.

+

💻 Let's get all books from 1984, sorted by number of pages. We'll only show the title, pages and authors.

+
let booksFrom1984 = {$match: {year: 1984}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, pages: 1, authors: 1}};
let slimmerBooksFirst = {$sort: {"pages": 1}}

db.books.aggregate([
    booksFrom1984,
    showOnlyTheseFields,
    slimmerBooksFirst,
]);
+

As we can see, books with no pages info appear first. These documents don't have that information, hence pages is null and gets sorted as less than any number.

+

💻 We can sort the other way around:

+
let booksFrom1984 = {$match: {year: 1984}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, pages: 1, authors: 1}};
let thickerBooksFirst = {$sort: {"pages": -1}}

db.books.aggregate([
    booksFrom1984,
    showOnlyTheseFields,
    thickerBooksFirst,
]);
+

💻 How can we get the thickest book from 1984?

+
Answer
let booksFrom1984 = {$match: {year: 1984}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, pages: 1, authors: 1}};
let thickerBooksFirst = {$sort: {"pages": -1}}
let justOne = {$limit: 1}

db.books.aggregate([
    booksFrom1984,
    showOnlyTheseFields,
    thickerBooksFirst,
    justOne
]);
\ No newline at end of file diff --git a/docs/exporting-data/saving-to-collection.html b/docs/exporting-data/saving-to-collection.html index 371f9e5..05c99a3 100644 --- a/docs/exporting-data/saving-to-collection.html +++ b/docs/exporting-data/saving-to-collection.html @@ -1,19 +1,22 @@ - + - -Saving to a collection | Aggregation Pipeline Lab + +Saving to a collection | Aggregation Pipeline Lab - - - + + + -
-

Saving to a collection

You can export the result of an aggregation pipeline to a different DB / Collection. To do that just add a last aggregation stage to your pipeline:

{ $out: { db: "<output-db>", coll: "<output-collection>" } }

You can omit the db attribute, in which case the new collection is created in the current DB.

{ $out: "<output-collection>" }

💻 Create a copy of the books with exactly 100 pages and output as a new collection named `OneHundredPagesBooks.

Answer
let oneHundredPagesBooks = {$match: {pages: 100}};
let saveToNewCollection = {$out: "OneHundredPagesBooks"}

db.books.aggregate([
    oneHundredPagesBooks,
    saveToNewCollection
]);

After running this, we should see a new collection with:

show collections
- - +

Saving to a collection

+

You can export the result of an aggregation pipeline to a different DB / Collection. To do that just add a last aggregation stage to your pipeline:

+
{ $out: { db: "<output-db>", coll: "<output-collection>" } }
+

You can omit the db attribute, in which case the new collection is created in the current DB.

+
{ $out: "<output-collection>" }
+

💻 Create a copy of the books with exactly 100 pages and output as a new collection named `OneHundredPagesBooks.

+
Answer
let oneHundredPagesBooks = {$match: {pages: 100}};
let saveToNewCollection = {$out: "OneHundredPagesBooks"}

db.books.aggregate([
    oneHundredPagesBooks,
    saveToNewCollection
]);

After running this, we should see a new collection with:

show collections
\ No newline at end of file diff --git a/docs/grouping/group.html b/docs/grouping/group.html index 76b9018..efd44c3 100644 --- a/docs/grouping/group.html +++ b/docs/grouping/group.html @@ -1,19 +1,25 @@ - + - -Group | Aggregation Pipeline Lab + +Group | Aggregation Pipeline Lab - - - + + + -
-

Group

We can sum all the pages for all books in each year:

db.books.aggregate([
    {$group:{
        _id: "$year",
        totalPages: {$sum: "$pages"}
    }}
])

Here, we group by book's year (the _id of the grouping), and then we create a new field called totalPages that's the sum of all pages.

💻 Can you get the results ordered ascending by year?

Answer
db.books.aggregate([
    {$group:{
        _id: "$year",
        totalPages: {$sum: "$pages"}
    }},
    {$sort: {_id: 1}}
])

💻 Can you get the average pages per year (hint: use $avg)?

Answer
db.books.aggregate([
    {$group:{
        _id: "$year",
        totalPages: {$avg: "$pages"}
    }},
    {$sort: {_id: 1}}
])

💻 Which year had the most printed out pages?

Answer
db.books.aggregate([
    {$group:{
        _id: "$year",
        totalPages: {$sum: "$pages"}
    }},
    {$sort: {totalPages: -1}},
    {$limit: 1}
])
- - +

Group

+

We can sum all the pages for all books in each year:

+
db.books.aggregate([
    {$group:{
        _id: "$year",
        totalPages: {$sum: "$pages"}
    }}
])
+

Here, we group by book's year (the _id of the grouping), and then we create a new field called totalPages that's the sum of all pages.

+

💻 Can you get the results ordered ascending by year?

+
Answer
db.books.aggregate([
    {$group:{
        _id: "$year",
        totalPages: {$sum: "$pages"}
    }},
    {$sort: {_id: 1}}
])
+

💻 Can you get the average pages per year (hint: use $avg)?

+
Answer
db.books.aggregate([
    {$group:{
        _id: "$year",
        totalPages: {$avg: "$pages"}
    }},
    {$sort: {_id: 1}}
])
+

💻 Which year had the most printed out pages?

+
Answer
db.books.aggregate([
    {$group:{
        _id: "$year",
        totalPages: {$sum: "$pages"}
    }},
    {$sort: {totalPages: -1}},
    {$limit: 1}
])
\ No newline at end of file diff --git a/docs/intro.html b/docs/intro.html index 9a4549d..ec063cb 100644 --- a/docs/intro.html +++ b/docs/intro.html @@ -1,19 +1,21 @@ - + - -Intro | Aggregation Pipeline Lab + +Intro | Aggregation Pipeline Lab - - - + + + -
-

Intro

Lab goalsLearn about Aggregation Pipelines writing Aggregation Pipelines
PrerequisitesA MongoDB database an sample data, you can create a free forever cluster following these instructions
What you'll learnWhat an Aggregation Pipeline is
QueriesYou'll learn how to query and manipulate data using the Aggregation Pipeline
Time to complete90 mins

In the navigation bar and in some pages, you will notice some icons. Here is their meaning:

IconMeaning
📘Lecture material - If you're following along in an instructor lead session, they probably have covered this already.
💻Hands-on content - Get ready to get some work done. You should follow these steps.
💬Discussion - Item to discuss during the Lab
🦸Advanced content - This content isn't covered during the lab, but if you're interested in learning more, you can check it out.
- - +

Intro

+ + +
Lab goalsLearn about Aggregation Pipelines writing Aggregation Pipelines
PrerequisitesA MongoDB database an sample data, you can create a free forever cluster following these instructions
What you'll learnWhat an Aggregation Pipeline is
QueriesYou'll learn how to query and manipulate data using the Aggregation Pipeline
Time to complete90 mins
+

In the navigation bar and in some pages, you will notice some icons. Here is their meaning:

+
IconMeaning
📘Lecture material - If you're following along in an instructor lead session, they probably have covered this already.
💻Hands-on content - Get ready to get some work done. You should follow these steps.
💬Discussion - Item to discuss during the Lab
🦸Advanced content - This content isn't covered during the lab, but if you're interested in learning more, you can check it out.
\ No newline at end of file diff --git a/docs/lecture-material.html b/docs/lecture-material.html index 6832a1e..5e86344 100644 --- a/docs/lecture-material.html +++ b/docs/lecture-material.html @@ -1,19 +1,21 @@ - + - -📘 Lecture material | Aggregation Pipeline Lab + +📘 Lecture material | Aggregation Pipeline Lab - - - + + + -
-
- - +
\ No newline at end of file diff --git a/docs/lookups/advanced-lookups.html b/docs/lookups/advanced-lookups.html index 935a86b..4368641 100644 --- a/docs/lookups/advanced-lookups.html +++ b/docs/lookups/advanced-lookups.html @@ -1,19 +1,34 @@ - + - -🦸‍♂️ Advanced lookups | Aggregation Pipeline Lab + +🦸‍♂️ Advanced lookups | Aggregation Pipeline Lab - - - + + + -
-

🦸‍♂️ Advanced lookups

info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

We get this request: Write a $lookup to get name and bio from author's information inside each book document. To get this done, we need to review several things:

  • each book can have several authors. This many to many relationship (as an author can also write many books) is modelled using two different arrays: a books array in the authors collection and an authors array in the books collection.
  • so we'll need to get a separate document for each book that has more than one author. If a book has three authors we'll use $unwind to get three documents with the same data except for the author, that will be each of the three authors.

You can try this with this Aggregation Pipeline:

db.books.aggregate([
    // as a book can have many authors, we get one doc per book's author
    {$unwind: "$authors"},
    // remove some noisy fields
    {$project: {attributes: 0, reviews: 0}}
])
  • now, we need to get the authors'information. For that, we'll use $lookup, linking the _id in the authors collection with the _id we have in each book's authors array. But as we can see here, these have a different type: the ones inside our array are Strings, while the author collection _id are ObjectId.
  authors: {
    _id: '64cc2db4830ba29148da64a2',
    name: 'Timothy Findley'
  },

So we need to convert from String into ObjectId. We can do that using $toObjectId. This will add a new field authorId converting it into ObjectId:

db.books.aggregate([
    // as a book can have many authors, we get one doc per book's author
    {$unwind: "$authors"},
    // convert it to an objectId
    {"$set":{"authorId":{"$toObjectId":"$authors._id"}}},
    // remove some noisy fields
    {$project: {attributes: 0, reviews: 0}}
])
  • now we're ready to do the $lookup: we want all documents from authors that have the same _id as the authorId we just created. We use a pipeline to get just authors name and bio.
db.books.aggregate([
    // as a book can have many authors, we get one doc per book's author
    {$unwind: "$authors"},
    // convert it to an objectId
    {"$set":{"authorId":{"$toObjectId":"$authors._id"}}},
    {$lookup: {
       from: "authors",
       localField: "authorId",
       foreignField: "_id",
       pipeline: [
            {$project: {name: 1, bio: 1}},
       ],
       as: "bookAuthorDetails"
     } 
    },
    // remove some noisy fields
    {$project: {attributes: 0, reviews: 0}}
])
- - +

🦸‍♂️ Advanced lookups

+
info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

+

We get this request: Write a $lookup to get name and bio from author's information inside each book document. To get this done, we need to review several things:

+
    +
  • each book can have several authors. This many to many relationship (as an author can also write many books) is modelled using two different arrays: a books array in the authors collection and an authors array in the books collection.
    • +
  • so we'll need to get a separate document for each book that has more than one author. If a book has three authors we'll use $unwind to get three documents with the same data except for the author, that will be each of the three authors.
    • +
+

You can try this with this Aggregation Pipeline:

+
db.books.aggregate([
    // as a book can have many authors, we get one doc per book's author
    {$unwind: "$authors"},
    // remove some noisy fields
    {$project: {attributes: 0, reviews: 0}}
])
+
    +
  • now, we need to get the authors'information. For that, we'll use $lookup, linking the _id in the authors collection with the _id we have in each book's authors array. But as we can see here, these have a different type: the ones inside our array are Strings, while the author collection _id are ObjectId.
    • +
+
  authors: {
    _id: '64cc2db4830ba29148da64a2',
    name: 'Timothy Findley'
  },
+

So we need to convert from String into ObjectId. We can do that using $toObjectId. This will add a new field authorId converting it into ObjectId:

+
db.books.aggregate([
    // as a book can have many authors, we get one doc per book's author
    {$unwind: "$authors"},
    // convert it to an objectId
    {"$set":{"authorId":{"$toObjectId":"$authors._id"}}},
    // remove some noisy fields
    {$project: {attributes: 0, reviews: 0}}
])
+
    +
  • now we're ready to do the $lookup: we want all documents from authors that have the same _id as the authorId we just created. We use a pipeline to get just authors name and bio.
    • +
+
db.books.aggregate([
    // as a book can have many authors, we get one doc per book's author
    {$unwind: "$authors"},
    // convert it to an objectId
    {"$set":{"authorId":{"$toObjectId":"$authors._id"}}},
    {$lookup: {
       from: "authors",
       localField: "authorId",
       foreignField: "_id",
       pipeline: [
            {$project: {name: 1, bio: 1}},
       ],
       as: "bookAuthorDetails"
     } 
    },
    // remove some noisy fields
    {$project: {attributes: 0, reviews: 0}}
])
\ No newline at end of file diff --git a/docs/lookups/lookups.html b/docs/lookups/lookups.html index 49a9c17..a213f61 100644 --- a/docs/lookups/lookups.html +++ b/docs/lookups/lookups.html @@ -1,19 +1,28 @@ - + - -Lookupups AKA Left Outer Join | Aggregation Pipeline Lab + +Lookupups AKA Left Outer Join | Aggregation Pipeline Lab - - - + + + -
-

Lookupups AKA Left Outer Join

Using Documents we usually model 1:1, 1:many relationships embedding documents inside other documents, even using arrays for that. For instance an Author can have many aliases, and they live inside an array in the authors collection.

But other times we need to use references to those documents instead of embedding them. For instance an author has an array of the books she has written, but instead of moving the book documents inside an array inside author (which will be tricky for books with multiple authors) we embed the books _id instead.

So how can we get the authors and all the books she has written, embedded in the array? Using $lookup, that will do a Left Outer Join and return author docs containing book docs inside.

💻 Run this aggregation and look at the results:

db.authors.aggregate([
    {$lookup: {
       from: "books",
       localField: "books",
       foreignField: "_id",
       as: "booksWritten"
     } 
    },
    {$project: {_id: 0}}
])

The syntax for this version of $lookup is:

{
   $lookup:
     {
       from: <collection to join>,
       localField: <field from the input documents>,
       foreignField: <field from the documents of the "from" collection>,
       as: <output array field>
     }
}

Lookups from a previous stage​

We can do a $lookup on the result of another pipeline, not only joining with a collection. For instance, we want to remove some noise from the books before joining, so we use $project to exclude a couple arrays.

db.authors.aggregate([
    {$lookup: {
       from: "books",
       localField: "books",
       foreignField: "_id",
       pipeline: [
         {$project: {title: 1, synopsis: 1}}
       ],
       as: "booksWritten"
     } 
    }
])

The nice part is that we can extract that pipeline and test it / tweak it.

let justShowTitleSynopsis = [
    {$project: {title: 1, synopsis: 1}},
]

db.authors.aggregate([
    {$lookup: {
       from: "books",
       localField: "books",
       foreignField: "_id",
       pipeline:
          justShowTitleSynopsis,
       as: "booksWritten"
     } 
    }
])
- - +

Lookupups AKA Left Outer Join

+

Using Documents we usually model 1:1, 1:many relationships embedding documents inside other documents, even using arrays for that. For instance an Author can have many aliases, and they live inside an array in the authors collection.

+

But other times we need to use references to those documents instead of embedding them. For instance an author has an array of the books she has written, but instead of moving the book documents inside an array inside author (which will be tricky for books with multiple authors) we embed the books _id instead.

+

So how can we get the authors and all the books she has written, embedded in the array? Using $lookup, that will do a Left Outer Join and return author docs containing book docs inside.

+

💻 Run this aggregation and look at the results:

+
db.authors.aggregate([
    {$lookup: {
       from: "books",
       localField: "books",
       foreignField: "_id",
       as: "booksWritten"
     } 
    },
    {$project: {_id: 0}}
])
+

The syntax for this version of $lookup is:

+
{
   $lookup:
     {
       from: <collection to join>,
       localField: <field from the input documents>,
       foreignField: <field from the documents of the "from" collection>,
       as: <output array field>
     }
}
+

Lookups from a previous stage​

+

We can do a $lookup on the result of another pipeline, not only joining with a collection. For instance, we want to remove some noise from the books before joining, so we use $project to exclude a couple arrays.

+
db.authors.aggregate([
    {$lookup: {
       from: "books",
       localField: "books",
       foreignField: "_id",
       pipeline: [
         {$project: {title: 1, synopsis: 1}}
       ],
       as: "booksWritten"
     } 
    }
])
+

The nice part is that we can extract that pipeline and test it / tweak it.

+
let justShowTitleSynopsis = [
    {$project: {title: 1, synopsis: 1}},
]

db.authors.aggregate([
    {$lookup: {
       from: "books",
       localField: "books",
       foreignField: "_id",
       pipeline:
          justShowTitleSynopsis,
       as: "booksWritten"
     } 
    }
])
\ No newline at end of file diff --git a/docs/modifying-results/adding-fields.html b/docs/modifying-results/adding-fields.html index 5e9b7b9..0fdf1b2 100644 --- a/docs/modifying-results/adding-fields.html +++ b/docs/modifying-results/adding-fields.html @@ -1,19 +1,21 @@ - + - -Adding new fields to results | Aggregation Pipeline Lab + +Adding new fields to results | Aggregation Pipeline Lab - - - + + + -
-

Adding new fields to results

$addFields​

We want to estimate the reading time for a book. But we don't have that field stored in our data. We can use $addFields for this. If the field exists, it'll get updated, if not, it's added.

db.books.aggregate([
    {$project: {
        title: 1,
        pages: 1,
        }
    },
    {$addFields: {readingTimeHours: {$divide: [{$multiply: ["$pages", 2]}, 60]}}},
])

💻 Add a new field notes that contains the text PLACEHOLDER for all documents.

Answer
db.books.aggregate([
    {$project: {
        title: 1,
        pages: 1,
        
    }
    
    },

    {$addFields: {notes: "PLACEHOLDER"}}
])
- - +

Adding new fields to results

+

$addFields​

+

We want to estimate the reading time for a book. But we don't have that field stored in our data. We can use $addFields for this. If the field exists, it'll get updated, if not, it's added.

+
db.books.aggregate([
    {$project: {
        title: 1,
        pages: 1,
        }
    },
    {$addFields: {readingTimeHours: {$divide: [{$multiply: ["$pages", 2]}, 60]}}},
])
+

💻 Add a new field notes that contains the text PLACEHOLDER for all documents.

+
Answer
db.books.aggregate([
    {$project: {
        title: 1,
        pages: 1,
        
    }
    
    },

    {$addFields: {notes: "PLACEHOLDER"}}
])
\ No newline at end of file diff --git a/docs/modifying-results/missing-data.html b/docs/modifying-results/missing-data.html index b435f76..ff08650 100644 --- a/docs/modifying-results/missing-data.html +++ b/docs/modifying-results/missing-data.html @@ -1,19 +1,18 @@ - + - -Missing Data | Aggregation Pipeline Lab + +Missing Data | Aggregation Pipeline Lab - - - + + + -
-

Missing Data

Sometimes we're missing a field we're looking for (it's not there, as documents in a collection can be polymorphic, so this field is null). For these cases we can check if something is there using $ifNull and add a default value in that case.

let getAuthorsWithBooks = {
    $project: {
        name: 1,
        books: { $ifNull: ["$books", []]},
    }
}

db.authors.aggregate([
    getAuthorsWithBooks,
])
- - +

Missing Data

+

Sometimes we're missing a field we're looking for (it's not there, as documents in a collection can be polymorphic, so this field is null). For these cases we can check if something is there using $ifNull and add a default value in that case.

+
let getAuthorsWithBooks = {
    $project: {
        name: 1,
        books: { $ifNull: ["$books", []]},
    }
}

db.authors.aggregate([
    getAuthorsWithBooks,
])
\ No newline at end of file diff --git a/docs/mongodb-atlas/prerequisites.html b/docs/mongodb-atlas/prerequisites.html index 1001422..266a72d 100644 --- a/docs/mongodb-atlas/prerequisites.html +++ b/docs/mongodb-atlas/prerequisites.html @@ -1,19 +1,22 @@ - + - -Set up Lab | Aggregation Pipeline Lab + +Set up Lab | Aggregation Pipeline Lab - - - + + + -
-

Set up Lab

To follow along you'll need:

  • a MongoDB Atlas account
  • some test data, in this case this is Books, Authors and Reviews data for a Library management system.

💻 To get both, open the Intro Lab and follow it (only takes 10-15 mins) to get your database ready. Return here when finished!

- - +

Set up Lab

+

To follow along you'll need:

+
    +
  • a MongoDB Atlas account
    • +
  • some test data, in this case this is Books, Authors and Reviews data for a Library management system.
    • +
+

💻 To get both, open the Intro Lab and follow it (only takes 10-15 mins) to get your database ready. Return here when finished!

\ No newline at end of file diff --git a/docs/simple-queries/aggregation-options.html b/docs/simple-queries/aggregation-options.html index 1ce9135..2f2ffc2 100644 --- a/docs/simple-queries/aggregation-options.html +++ b/docs/simple-queries/aggregation-options.html @@ -1,19 +1,22 @@ - + - -🦸‍♂️ Aggregation options | Aggregation Pipeline Lab + +🦸‍♂️ Aggregation options | Aggregation Pipeline Lab - - - + + + -
-

🦸‍♂️ Aggregation options

info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

We can pass a document to aggregate with some options

let options = {
    maxTimeMS: 100
};

db.authors.aggregate([], options);

💻 Have a look at the different options you can pass to the aggregate method.

💻 Try to launch an itcount (a long operation) to iterate through the whole books cursor with a time limt of 10 ms: you should see the operation timing out and failing.

let options = {
    maxTimeMS: 10
};

db.authors.aggregate([], options).itcount();

> MongoServerError: operation exceeded time limit
- - +

🦸‍♂️ Aggregation options

+
info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

+

We can pass a document to aggregate with some options

+
let options = {
    maxTimeMS: 100
};

db.authors.aggregate([], options);
+

💻 Have a look at the different options you can pass to the aggregate method.

+

💻 Try to launch an itcount (a long operation) to iterate through the whole books cursor with a time limt of 10 ms: you should see the operation timing out and failing.

+
let options = {
    maxTimeMS: 10
};

db.authors.aggregate([], options).itcount();

> MongoServerError: operation exceeded time limit
\ No newline at end of file diff --git a/docs/simple-queries/combining-them-all.html b/docs/simple-queries/combining-them-all.html index 07dbdb2..53153f4 100644 --- a/docs/simple-queries/combining-them-all.html +++ b/docs/simple-queries/combining-them-all.html @@ -1,19 +1,21 @@ - + - -Combining stages | Aggregation Pipeline Lab + +Combining stages | Aggregation Pipeline Lab - - - + + + -
-

Combining stages

Up until now, we've just been using one stage in the pipeline. But the power of the aggregation pipeline is that we can use many stages, and the output of one will be the input of the next. Think of it as UNIX pipes or using functional programming with map, filter, reduce, flatmap, etc.

Get 10 books from 2001 with 200 pages. Show only the title and authors.

db.books.aggregate([
    {$match: {year: 2001, pages: 200}}, {$project: {_id: 0, title: 1, authors: 1}}, {$limit: 10}
])

💻 Get 15 books from 1985 with 150 pages. Show only the title, year, totalInventory and available books. (If you don't remember which fields we have, the sample doc is here)

Answer
db.books.aggregate([
    {$match: {year: 1985, pages: 150}}, {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}}, {$limit: 15}
])
- - +

Combining stages

+

Up until now, we've just been using one stage in the pipeline. But the power of the aggregation pipeline is that we can use many stages, and the output of one will be the input of the next. Think of it as UNIX pipes or using functional programming with map, filter, reduce, flatmap, etc.

+

Get 10 books from 2001 with 200 pages. Show only the title and authors.

+
db.books.aggregate([
    {$match: {year: 2001, pages: 200}}, {$project: {_id: 0, title: 1, authors: 1}}, {$limit: 10}
])
+

💻 Get 15 books from 1985 with 150 pages. Show only the title, year, totalInventory and available books. (If you don't remember which fields we have, the sample doc is here)

+
Answer
db.books.aggregate([
    {$match: {year: 1985, pages: 150}}, {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}}, {$limit: 15}
])
\ No newline at end of file diff --git a/docs/simple-queries/empty-aggregation.html b/docs/simple-queries/empty-aggregation.html index 3ac3631..edf4466 100644 --- a/docs/simple-queries/empty-aggregation.html +++ b/docs/simple-queries/empty-aggregation.html @@ -1,19 +1,32 @@ - + - -Empty aggregation pipeline | Aggregation Pipeline Lab + +Empty aggregation pipeline | Aggregation Pipeline Lab - - - + + + -
-

Empty aggregation pipeline

An empty aggregation​

This code is the equivalent to a SELECT * FROM AUTHORS. Returns a cursor with all documents in the authors collection:

db.authors.aggregate([])

We can iterate over this cursor and get more documents typing it.

💻 Return all the documents in the books collection and iterate to get the next page of books.

Answer
db.books.aggregate([])
it

🦸‍♂️ Cursor methods​

info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

A cursor has several useful methods, for instance we can check the size of the returned cursor with itcount

cursor.itcount()

💻 In our previous example with the empty aggregation, to check the size of the returned cursor, what should we type in?

Answer
// as db.books.aggregate([]) returns a cursor we can just call itcount() on it
db.books.aggregate([]).itcount()
- - +

Empty aggregation pipeline

+

An empty aggregation​

+

This code is the equivalent to a SELECT * FROM AUTHORS. Returns a cursor with all documents in the authors collection:

+
db.authors.aggregate([])
+

We can iterate over this cursor and get more documents typing it.

+

💻 Return all the documents in the books collection and iterate to get the next page of books.

+
Answer
db.books.aggregate([])
it
+

🦸‍♂️ Cursor methods​

+
info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

+

A cursor has several useful methods, for instance we can check the size of the returned cursor with itcount

+
cursor.itcount()
+

💻 In our previous example with the empty aggregation, to check the size of the returned cursor, what should we type in?

+
Answer
// as db.books.aggregate([]) returns a cursor we can just call itcount() on it
db.books.aggregate([]).itcount()
\ No newline at end of file diff --git a/docs/simple-queries/limiting-results.html b/docs/simple-queries/limiting-results.html index 348e23c..476b0da 100644 --- a/docs/simple-queries/limiting-results.html +++ b/docs/simple-queries/limiting-results.html @@ -1,19 +1,21 @@ - + - -$limit | Aggregation Pipeline Lab + +$limit | Aggregation Pipeline Lab - - - + + + -
-

$limit

If we return too many documents, but we're interested just in a few, we can limit the number of documents returned using $limit

db.books.aggregate([{$limit: 1}])

This returns just one document.

💻 Return just 7 books.

Answer
db.books.aggregate([{$limit: 7}])
- - +

$limit

+

If we return too many documents, but we're interested just in a few, we can limit the number of documents returned using $limit

+
db.books.aggregate([{$limit: 1}])
+

This returns just one document.

+

💻 Return just 7 books.

+
Answer
db.books.aggregate([{$limit: 7}])
\ No newline at end of file diff --git a/docs/simple-queries/match.html b/docs/simple-queries/match.html index 6fc9b7c..babdd5e 100644 --- a/docs/simple-queries/match.html +++ b/docs/simple-queries/match.html @@ -1,19 +1,36 @@ - + - -$match | Aggregation Pipeline Lab + +$match | Aggregation Pipeline Lab - - - + + + -
-

$match

This is the simplest one, similar to the WHERE SQL clause.

Say we want all the books from 2010. We'll write:

db.books.aggregate([{$match: {year: 2010}}])

💻 Return all the books that have exactly 100 pages.

Answer
db.books.aggregate([{$match: {pages: 100}}])

AND​

If we need to add more conditions using AND, we can do it using the $and operator.

If we want all the books with 100 pages with exactly totalInventory 2 we can use an $and operator. This takes and array of documents with all the conditions that should be true for the AND to succeed:

db.books.aggregate([{$match: {$and: [{pages: 100}, {totalInventory: 2}]}}])

The pseudo-code for this would be something like:

IF pages == 100 AND totalInventory == 2 {
    return matching docs
}

💻 Return all the books from 2015 that have exactly 100 pages.

Answer
db.books.aggregate([{$match: {$and: [{pages: 100}, {year: 2015}]}}])

💻 How many are they? (hint: use itcount()).

Answer
db.books.aggregate([{$match: {$and: [{pages: 100}, {year: 2015}]}}]).itcount()

Shorthand AND​

We can do an implicit AND just passing a document with all the conditions (instead of an array of documents):

db.books.aggregate([{$match: {pages: 100, totalInventory: 2}}])

💻 Return all the books from 2015 that have exactly 100 pages, using the simple $and notation

Answer
db.books.aggregate([{$match: {pages: 100, year: 2015}}])
- - +

$match

+

This is the simplest one, similar to the WHERE SQL clause.

+

Say we want all the books from 2010. We'll write:

+
db.books.aggregate([{$match: {year: 2010}}])
+

💻 Return all the books that have exactly 100 pages.

+
Answer
db.books.aggregate([{$match: {pages: 100}}])
+

AND​

+

If we need to add more conditions using AND, we can do it using the $and operator.

+

If we want all the books with 100 pages with exactly totalInventory 2 we can use an $and operator. This takes and array of documents with all the conditions that should be true for the AND to succeed:

+
db.books.aggregate([{$match: {$and: [{pages: 100}, {totalInventory: 2}]}}])
+

The pseudo-code for this would be something like:

+
IF pages == 100 AND totalInventory == 2 {
    return matching docs
}
+

💻 Return all the books from 2015 that have exactly 100 pages.

+
Answer
db.books.aggregate([{$match: {$and: [{pages: 100}, {year: 2015}]}}])
+

💻 How many are they? (hint: use itcount()).

+
Answer
db.books.aggregate([{$match: {$and: [{pages: 100}, {year: 2015}]}}]).itcount()
+

Shorthand AND​

+

We can do an implicit AND just passing a document with all the conditions (instead of an array of documents):

+
db.books.aggregate([{$match: {pages: 100, totalInventory: 2}}])
+

💻 Return all the books from 2015 that have exactly 100 pages, using the simple $and notation

+
Answer
db.books.aggregate([{$match: {pages: 100, year: 2015}}])
\ No newline at end of file diff --git a/docs/simple-queries/project.html b/docs/simple-queries/project.html index fce1bdf..6da304b 100644 --- a/docs/simple-queries/project.html +++ b/docs/simple-queries/project.html @@ -1,19 +1,39 @@ - + - -$project | Aggregation Pipeline Lab + +$project | Aggregation Pipeline Lab - - - + + + -
-

$project

Including fields in a projection​

A document from the books collection looks like:

{
  _id: '0395623650',
  title: 'Platero y yo / Platero and I (Spanish-English Bilingual Edition) (English and Spanish Edition)',
  authors: [
    {
      _id: '64cc2db4830ba29148db5180',
      name: 'Juan Ramón Jiménez'
    }
  ],
  pages: 64,
  year: 1994,
  synopsis: 'Selections from a classic of world literature present a picture of life in the town of Moguer, in Andalusia, Spain.\n' +
    '\n' +
    '\n' +
    '                        Presents a picture of life in the town of Moguer, in Andalusia, Spain, as seen through the eyes of a wandering poet and his faithful donkey.\n',
  cover: 'https://images.isbndb.com/covers/36/57/9780395623657.jpg',
  attributes: [
    {
      key: 'edition',
      value: 'F First Edition Thus'
    },
    {
      key: 'dimensions',
      value: 'Height: 10.499979 Inches, Length: 6.999986 Inches, Weight: 2.0502990366 Pounds, Width: 0.12499975 Inches'
    },
    {
      key: 'isbn13',
      value: '9780395623657'
    },
    {
      key: 'msrp',
      value: 1.99
    },
    {
      key: 'isbn',
      value: '0395623650'
    },
    {
      key: 'isbn10',
      value: '0395623650'
    }
  ],
  totalInventory: 1,
  available: 1,
  binding: 'Hardcover',
  language: 'en',
  longTitle: 'Platero y yo / Platero and I (Spanish-English Bilingual Edition) (English and Spanish Edition)',
  publisher: 'Clarion Books'
}

If we're interested just in the titles, we can use $project to select just the fields we're interested in. As an example, to get just the book's title and year we'll write:

db.books.aggregate([{$project: {title: 1, year: 1}}])
  • 1 means "show that field"
  • 0 means "hide that field"
  • the primary key _id field is shown by default

So we can exclude fields and show all fields except attributes using:

db.books.aggregate([{$project: {attributes: 0}}])

💻 Show only title and cover.

Answer
db.books.aggregate([{$project: {title:1, cover: 1}}])

Excluding fields​

💻 Exclude the cover, attributes and _id fields from the result.

Answer
db.books.aggregate([{$project: {_id :0, attributes: 0, cover: 0}}])

Including and excluding fields​

danger

You can't include and exclude fields in the same projection: if you start including, you must keep including and vice versa.

For instance, this will fail:

db.books.aggregate([{$project: {title:1, attributes: 0}}])

MongoServerError: Invalid $project :: caused by :: Cannot do exclusion on field attributes in inclusion projection
info

The only exception to this rule is the _id field, which we can exclude in an inclusion projection

db.books.aggregate([{$project: {title:1, _id: 0}}])
- - +

$project

+

Including fields in a projection​

+

A document from the books collection looks like:

+
{
  _id: '0395623650',
  title: 'Platero y yo / Platero and I (Spanish-English Bilingual Edition) (English and Spanish Edition)',
  authors: [
    {
      _id: '64cc2db4830ba29148db5180',
      name: 'Juan Ramón Jiménez'
    }
  ],
  pages: 64,
  year: 1994,
  synopsis: 'Selections from a classic of world literature present a picture of life in the town of Moguer, in Andalusia, Spain.\n' +
    '\n' +
    '\n' +
    '                        Presents a picture of life in the town of Moguer, in Andalusia, Spain, as seen through the eyes of a wandering poet and his faithful donkey.\n',
  cover: 'https://images.isbndb.com/covers/36/57/9780395623657.jpg',
  attributes: [
    {
      key: 'edition',
      value: 'F First Edition Thus'
    },
    {
      key: 'dimensions',
      value: 'Height: 10.499979 Inches, Length: 6.999986 Inches, Weight: 2.0502990366 Pounds, Width: 0.12499975 Inches'
    },
    {
      key: 'isbn13',
      value: '9780395623657'
    },
    {
      key: 'msrp',
      value: 1.99
    },
    {
      key: 'isbn',
      value: '0395623650'
    },
    {
      key: 'isbn10',
      value: '0395623650'
    }
  ],
  totalInventory: 1,
  available: 1,
  binding: 'Hardcover',
  language: 'en',
  longTitle: 'Platero y yo / Platero and I (Spanish-English Bilingual Edition) (English and Spanish Edition)',
  publisher: 'Clarion Books'
}
+

If we're interested just in the titles, we can use $project to select just the fields we're interested in. As an example, to get just the book's title and year we'll write:

+
db.books.aggregate([{$project: {title: 1, year: 1}}])
+
    +
  • 1 means "show that field"
    • +
  • 0 means "hide that field"
    • +
  • the primary key _id field is shown by default
    • +
+

So we can exclude fields and show all fields except attributes using:

+
db.books.aggregate([{$project: {attributes: 0}}])
+

💻 Show only title and cover.

+
Answer
db.books.aggregate([{$project: {title:1, cover: 1}}])
+

Excluding fields​

+

💻 Exclude the cover, attributes and _id fields from the result.

+
Answer
db.books.aggregate([{$project: {_id :0, attributes: 0, cover: 0}}])
+

Including and excluding fields​

+
danger

You can't include and exclude fields in the same projection: if you start including, you must keep including and vice versa.

+

For instance, this will fail:

+
db.books.aggregate([{$project: {title:1, attributes: 0}}])

MongoServerError: Invalid $project :: caused by :: Cannot do exclusion on field attributes in inclusion projection
+
info

The only exception to this rule is the _id field, which we can exclude in an inclusion projection

+
db.books.aggregate([{$project: {title:1, _id: 0}}])
\ No newline at end of file diff --git a/docs/simple-queries/repeating-stages.html b/docs/simple-queries/repeating-stages.html index 26b0c67..13cb455 100644 --- a/docs/simple-queries/repeating-stages.html +++ b/docs/simple-queries/repeating-stages.html @@ -1,19 +1,25 @@ - + - -🦸‍♂️ Repeating stages | Aggregation Pipeline Lab + +🦸‍♂️ Repeating stages | Aggregation Pipeline Lab - - - + + + -
-

🦸‍♂️ Repeating stages

info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

From the Aggregation Pipelines manual.

All stages except the $out, $merge, $geoNear, $changeStream, and $changeStreamSplitLargeEvent stages can appear multiple times in a pipeline.

So we can repeat most stages, and do something like this to get all books from 1985 with more than 100 pages (although it can make sense or not)

db.books.aggregate([{$match: {pages: {$gte: 100}}}, {$match: {year: 1985}}])

💻 Add several $limt stages at the end of the above aggregation, limiting to 1 book and see what happens

Answer
db.books.aggregate([
    {$match: {pages: {$gte: 100}}}, 
    {$match: {year: 2011}},
    {$limit: 1},
    {$limit: 1},
])
- - +

🦸‍♂️ Repeating stages

+
info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

+

From the Aggregation Pipelines manual.

+
+

All stages except the $out, $merge, $geoNear, $changeStream, and $changeStreamSplitLargeEvent stages can appear multiple times in a pipeline.

+
+

So we can repeat most stages, and do something like this to get all books from 1985 with more than 100 pages (although it can make sense or not)

+
db.books.aggregate([{$match: {pages: {$gte: 100}}}, {$match: {year: 1985}}])
+

💻 Add several $limt stages at the end of the above aggregation, limiting to 1 book and see what happens

+
Answer
db.books.aggregate([
    {$match: {pages: {$gte: 100}}}, 
    {$match: {year: 2011}},
    {$limit: 1},
    {$limit: 1},
])
\ No newline at end of file diff --git a/docs/simple-queries/using-library-database.html b/docs/simple-queries/using-library-database.html index 64d1bfa..8237948 100644 --- a/docs/simple-queries/using-library-database.html +++ b/docs/simple-queries/using-library-database.html @@ -1,19 +1,27 @@ - + - -Using the library database | Aggregation Pipeline Lab + +Using the library database | Aggregation Pipeline Lab - - - + + + -
-

Using the library database

Select the library database​

💻 We'll use the library database. To do that, in a MongoDB shell type in:

use library

You can show all collections with

show collections

🦸‍♂️ 💻 How would you switch to a database called orders?

info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

Answer
use orders

Even if this database does not yet exists, MongoDB can change to it. If we create a collection, users, etc. then this DB will get created.

Remember to get back to the library database by using:

use library

🦸‍♂️ Showing all Databases​

info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

You can also list other databases in your MongoDB instance with

show databases
- - +

Using the library database

+

Select the library database​

+

💻 We'll use the library database. To do that, in a MongoDB shell type in:

+
use library

You can show all collections with

show collections
+
+

🦸‍♂️ 💻 How would you switch to a database called orders?

+
info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

+
Answer
use orders

Even if this database does not yet exists, MongoDB can change to it. If we create a collection, users, etc. then this DB will get created.

Remember to get back to the library database by using:

use library
+

🦸‍♂️ Showing all Databases​

+
info

Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab

+

You can also list other databases in your MongoDB instance with

+
show databases
\ No newline at end of file diff --git a/docs/simple-queries/writing-long-pipelines.html b/docs/simple-queries/writing-long-pipelines.html index 6f8528d..f5214ad 100644 --- a/docs/simple-queries/writing-long-pipelines.html +++ b/docs/simple-queries/writing-long-pipelines.html @@ -1,19 +1,29 @@ - + - -Writing long pipelines | Aggregation Pipeline Lab + +Writing long pipelines | Aggregation Pipeline Lab - - - + + + -
-

Writing long pipelines

Aggregation pipelines can get very long, depending on how many stages we need to run. Writing a pipeline is writing code, as you will write it using one of the many MongoDB drivers in your own language. Here we're presenting the examples using JavaScript suitable for the MongoDB Shell mongosh, but if you are writing a microservice in Rust, you'll definitely write your pipelines in Rust.

This is why we should rewrite our last pipeline like this:

Get 15 books from 1985 with 150 pages. Show only the title, year, totalInventory and available books. (Sample doc here)

db.books.aggregate([
    {$match: {year: 1985, pages: 150}}, {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}}, {$limit: 15}
])

Will be changed into:

let booksFrom1985With150pages = {$match: {year: 1985, pages: 150}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};

db.books.aggregate([
    booksFrom1985With150pages,
    showOnlyTheseFields,
    getJust15books,
]);

Easier to read, and reason about, right?

💻 Try to run the above pipeline and compare your results: should be the same as before

tip

Write your aggregation pipelines like you'll compose functions in your programming language. Aggregations are code that runs on the server. In the client you just express what you want to be done, not how to do it.

tip

As this is code, we can even add comments (starting with //) to our pipelines

💻 We can also use $gte to get the books with 150 pages or more. Check $gte syntax in the docucumentation and write an aggregation pipeline to return 15 books from 1985 with more than 150 pages. Show only the title, year, totalInventory and available books. (Sample doc here)

Hint: we'll need to use $and as maybe this is a bit more complex.

Answer
let moreThan150pages =  {pages: {$gte: 150}}
let booksFrom1985WithMoreThan150pages = {$match: {$and: [{year: 1985}, moreThan150pages]}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};

db.books.aggregate([
    booksFrom1985With150pages,
    showOnlyTheseFields,
    getJust15books,
]);
- - +

Writing long pipelines

+

Aggregation pipelines can get very long, depending on how many stages we need to run. Writing a pipeline is writing code, as you will write it using one of the many MongoDB drivers in your own language. Here we're presenting the examples using JavaScript suitable for the MongoDB Shell mongosh, but if you are writing a microservice in Rust, you'll definitely write your pipelines in Rust.

+

This is why we should rewrite our last pipeline like this:

+

Get 15 books from 1985 with 150 pages. Show only the title, year, totalInventory and available books. (Sample doc here)

+
db.books.aggregate([
    {$match: {year: 1985, pages: 150}}, {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}}, {$limit: 15}
])
+

Will be changed into:

+
let booksFrom1985With150pages = {$match: {year: 1985, pages: 150}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};

db.books.aggregate([
    booksFrom1985With150pages,
    showOnlyTheseFields,
    getJust15books,
]);
+

Easier to read, and reason about, right?

+

💻 Try to run the above pipeline and compare your results: should be the same as before

+
tip

Write your aggregation pipelines like you'll compose functions in your programming language. Aggregations are code that runs on the server. In the client you just express what you want to be done, not how to do it.

+
tip

As this is code, we can even add comments (starting with //) to our pipelines

+

💻 We can also use $gte to get the books with 150 pages or more. Check $gte syntax in the docucumentation and write an aggregation pipeline to return 15 books from 1985 with more than 150 pages. Show only the title, year, totalInventory and available books. (Sample doc here)

+

_Hint: _ we'll need to use $and as maybe this is a bit more complex.

+
Answer
let moreThan150pages =  {pages: {$gte: 150}}
let booksFrom1985WithMoreThan150pages = {$match: {$and: [{year: 1985}, moreThan150pages]}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1}};
let getJust15books =  {$limit: 15};

db.books.aggregate([
    booksFrom1985With150pages,
    showOnlyTheseFields,
    getJust15books,
]);
\ No newline at end of file diff --git a/docs/summary.html b/docs/summary.html index ac992c8..bf549c6 100644 --- a/docs/summary.html +++ b/docs/summary.html @@ -1,19 +1,25 @@ - + - -🎯 Summary | Aggregation Pipeline Lab + +🎯 Summary | Aggregation Pipeline Lab - - - + + + -
-

🎯 Summary

Congratulations! Following this tutorial, you have successfully:

  • installed Node and Npx,
  • cloned a docusaurus repo,
  • learned the structure of a docusaurus site,
  • saw how Markdown and JSX can be used in your docs,
  • and run your docusaurus site.

Visit the MongoDB Developer Center for more useful information and tutorials.

- - +

🎯 Summary

+

Congratulations! Following this tutorial, you have successfully:

+
    +
  • installed Node and Npx,
    • +
  • cloned a docusaurus repo,
    • +
  • learned the structure of a docusaurus site,
    • +
  • saw how Markdown and JSX can be used in your docs,
    • +
  • and run your docusaurus site.
    • +
+

Visit the MongoDB Developer Center for more useful information and tutorials.

\ No newline at end of file diff --git a/docs/using-arrays/search-inside-objects-in-arrays.html b/docs/using-arrays/search-inside-objects-in-arrays.html index 6a22953..c1c7633 100644 --- a/docs/using-arrays/search-inside-objects-in-arrays.html +++ b/docs/using-arrays/search-inside-objects-in-arrays.html @@ -1,19 +1,26 @@ - + - -Searching inside Objects in arrays | Aggregation Pipeline Lab + +Searching inside Objects in arrays | Aggregation Pipeline Lab - - - + + + -
-

Searching inside Objects in arrays

In our books we're using the Attribute Pattern to have different attributes in our documents. As we can see in the sample doc we have an attributes array, containing several objects, each with the same structure:

attributes: [
    {
      key: 'edition',
      value: '1st'
    },
    {
      key: 'dimensions',
      value: 'Height: 1.111 Inches, Length: 1.111 Inches, Weight: 0.2 Pounds, Width: 1.111 Inches'
    },
    {
      key: 'isbn13',
      value: '9780765342508'
    },
    {
      key: 'msrp',
      value: 6.99
    },
    {
      key: 'isbn',
      value: '0765342502'
    },
    {
      key: 'isbn10',
      value: '0765342502'
    }
  ],

How do we search for all the books that have an msrp of 9.99? We want books that, inside attributes has an object with key msrp and value 9.99. We can think this works:

let nineNinetyNine = {$match: {"attributes.key": "msrp", "attributes.value": 9.99}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1, "attributes": 1}};

db.books.aggregate([
    nineNinetyNine,
    showOnlyTheseFields,
]);

But it doesn't. This one works:

db.books.aggregate([
    { $unwind : "$attributes" },
    {$match: {"attributes.key": "msrp", "attributes.value": 9.99} },
   {$project: {title: 1, attributes: 1}}
]);

Here we're getting a copy of each book for each object inside the $attributes array. This "flattens" the array and returns many copies of the same documents, one for each different attribute that we have which will be different for each of these generated docs.

To better understand $unwind, run this aggregation

db.books.aggregate([
  { $match: {_id: "0395623650"} },
  { $unwind : "$attributes" },
]);

You should get one document per attribute of the original book.

- - +

Searching inside Objects in arrays

+

In our books we're using the Attribute Pattern to have different attributes in our documents. As we can see in the sample doc we have an attributes array, containing several objects, each with the same structure:

+
attributes: [
    {
      key: 'edition',
      value: '1st'
    },
    {
      key: 'dimensions',
      value: 'Height: 1.111 Inches, Length: 1.111 Inches, Weight: 0.2 Pounds, Width: 1.111 Inches'
    },
    {
      key: 'isbn13',
      value: '9780765342508'
    },
    {
      key: 'msrp',
      value: 6.99
    },
    {
      key: 'isbn',
      value: '0765342502'
    },
    {
      key: 'isbn10',
      value: '0765342502'
    }
  ],
+

How do we search for all the books that have an msrp of 9.99? We want books that, inside attributes has an object with key msrp and value 9.99. We can think this works:

+
let nineNinetyNine = {$match: {"attributes.key": "msrp", "attributes.value": 9.99}};
let showOnlyTheseFields = {$project: {_id: 0, title: 1, year: 1, totalInventory: 1, available: 1, "attributes": 1}};

db.books.aggregate([
    nineNinetyNine,
    showOnlyTheseFields,
]);
+

But it doesn't. This one works:

+
db.books.aggregate([
    { $unwind : "$attributes" },
    {$match: {"attributes.key": "msrp", "attributes.value": 9.99} },
   {$project: {title: 1, attributes: 1}}
]);
+

Here we're getting a copy of each book for each object inside the $attributes array. This "flattens" the array and returns many copies of the same documents, one for each different attribute that we have which will be different for each of these generated docs.

+

To better understand $unwind, run this aggregation

+
db.books.aggregate([
  { $match: {_id: "0395623650"} },
  { $unwind : "$attributes" },
]);
+

You should get one document per attribute of the original book.

\ No newline at end of file diff --git a/docs/using-arrays/simple-match-array.html b/docs/using-arrays/simple-match-array.html index 12c5960..18bb67d 100644 --- a/docs/using-arrays/simple-match-array.html +++ b/docs/using-arrays/simple-match-array.html @@ -1,19 +1,31 @@ - + - -Simple Array queries | Aggregation Pipeline Lab + +Simple Array queries | Aggregation Pipeline Lab - - - + + + -
-

Simple Array queries

Find data in arrays​

A JSON Array can contain scalar values or objects. In our data, authors have an array of the books they've authored (their ISBNs). Let's get one author:

db.authors.aggregate([{$limit: 1}])

💻 Run this aggregation to get one author

I got this one (can change depending on the data source you imported)

{
  _id: ObjectId("64cc2db4830ba29148da4c3b"),
  name: 'Richard Bruce Wright',
  sanitizedName: 'richardbrucewright',
  books: [
    '0002005018'
  ],
  aliases: [
    'Wright, Richard Bruce'
  ]
}

Can I get all authors for book 0002005018? For that, I want all authors that have 0002005018 inside the books array. Turns out it's quite simple:

db.authors.aggregate([
    {$match: {books: "0002005018"}}
])

💻 Get book's author name for ISBN 0395623650:

Answer
db.authors.aggregate([{$match: {books: "0395623650"}}])

>   name: 'Juan Ramón Jiménez',

Size of an array​

What if we want to know how many aliases an Author has? To do that we can use $size, adding the array field that we're interested in:

db.authors.aggregate([
{$project: {
    name: 1,
    bookCount: {$size: "$books"}
 }
},
])

💻 Who wrote the most books? (we can sort using { $sort: {"bookCount": -1}})

Answer
let addNumberBooks = {
    $project: {
        name: 1,
        bookCount: {$size: "$books"}
    }
}

let orderByNumberOfBooksDesc = { $sort: {"bookCount": -1}}

let getOne = {$limit: 1}

db.authors.aggregate([
    addNumberBooks,
    orderByNumberOfBooksDesc,
    getOne,
])
- - +

Simple Array queries

+

Find data in arrays​

+

A JSON Array can contain scalar values or objects. In our data, authors have an array of the books they've authored (their ISBNs). Let's get one author:

+
db.authors.aggregate([{$limit: 1}])
+

💻 Run this aggregation to get one author

+

I got this one (can change depending on the data source you imported)

+
{
  _id: ObjectId("64cc2db4830ba29148da4c3b"),
  name: 'Richard Bruce Wright',
  sanitizedName: 'richardbrucewright',
  books: [
    '0002005018'
  ],
  aliases: [
    'Wright, Richard Bruce'
  ]
}
+

Can I get all authors for book 0002005018? For that, I want all authors that have 0002005018 inside the books array. Turns out it's quite simple:

+
db.authors.aggregate([
    {$match: {books: "0002005018"}}
])
+

💻 Get book's author name for ISBN 0395623650:

+
Answer
db.authors.aggregate([{$match: {books: "0395623650"}}])

>   name: 'Juan Ramón Jiménez',
+

Size of an array​

+

What if we want to know how many aliases an Author has? To do that we can use $size, adding the array field that we're interested in:

+
db.authors.aggregate([
{$project: {
    name: 1,
    bookCount: {$size: "$books"}
 }
},
])
+

💻 Who wrote the most books? (we can sort using { $sort: {"bookCount": -1}})

+
Answer
let addNumberBooks = {
    $project: {
        name: 1,
        bookCount: {$size: "$books"}
    }
}

let orderByNumberOfBooksDesc = { $sort: {"bookCount": -1}}

let getOne = {$limit: 1}

db.authors.aggregate([
    addNumberBooks,
    orderByNumberOfBooksDesc,
    getOne,
])
\ No newline at end of file diff --git a/docs/what-is-aggregation/sql-vs-aggregation.html b/docs/what-is-aggregation/sql-vs-aggregation.html index 6b62e63..279e006 100644 --- a/docs/what-is-aggregation/sql-vs-aggregation.html +++ b/docs/what-is-aggregation/sql-vs-aggregation.html @@ -1,19 +1,24 @@ - + - -SQL vs Aggregations | Aggregation Pipeline Lab + +SQL vs Aggregations | Aggregation Pipeline Lab - - - + + + -
-

SQL vs Aggregations

SQL​

A SQL query statement usually starts with a SELECT where we put a list of the fields we need, then a FROM clause to state the table/s (or as in this case the subquery) that will return the rows. We can filter out using WHERE and group data using GROUP.

We read this from the inside. If there's too much nesting is not easy to follow.

SELECT
    city,
    SUM(annual_spend) Total_Spend,
    AVG(annual_spend) Average_Spend,
    MAX(annual_spend) Max_Spend,
    COUNT(annual_spend) customers
FROM (
    SELECT t1.city, customer.annual_spend
    FROM customer 
    LEFT JOIN (
        SELECT address.address_id, city.city,
               address.customer_id, address.location
        FROM address LEFT JOIN city
        ON address.city_id = city.city_id
        ) AS t1
    ON
    (customer.customer_id = t1.customer_id AND
              t1.location = "home")
) AS t2
GROUP BY city;

Equivalent MongoDB Aggregation Pipeline​

Here we pass three stages, one to return one document per element in the address array, then we filter out to get only the documents that have a home address location and finally we do the grouping. As we'll see, this can be split and tested separately, and resembles our code. 

db.customers.aggregate([
    {
        $unwind: "$address",
    },
    {
        $match: {"address.location": "home"}
    },
    {
         $group: {
            _id: "$address.city",
            totalSpend: {$sum: "$annualSpend"},
            averageSpend: {$avg: "$annualSpend"},
            maximumSpend: {$max: "$annualSpend"},
            customers: {$sum: 1}
        }
    }
])
info

See also SQL to Aggregation Mapping Chart

- - +

SQL vs Aggregations

+

SQL​

+

A SQL query statement usually starts with a SELECT where we put a list of the fields we need, then a FROM clause to state the table/s (or as in this case the subquery) that will return the rows. We can filter out using WHERE and group data using GROUP.

+

We read this from the inside. If there's too much nesting is not easy to follow.

+
SELECT
    city,
    SUM(annual_spend) Total_Spend,
    AVG(annual_spend) Average_Spend,
    MAX(annual_spend) Max_Spend,
    COUNT(annual_spend) customers
FROM (
    SELECT t1.city, customer.annual_spend
    FROM customer 
    LEFT JOIN (
        SELECT address.address_id, city.city,
               address.customer_id, address.location
        FROM address LEFT JOIN city
        ON address.city_id = city.city_id
        ) AS t1
    ON
    (customer.customer_id = t1.customer_id AND
              t1.location = "home")
) AS t2
GROUP BY city;
+

Equivalent MongoDB Aggregation Pipeline​

+

Here we pass three stages, one to return one document per element in the address array, then we filter out to get only the documents that have a home address location and finally we do the grouping. As we'll see, this can be split and tested separately, and resembles our code.

+
db.customers.aggregate([
	{
		$unwind: "$address",
	},
	{
		$match: {"address.location": "home"}
	},
	{
		 $group: {
			_id: "$address.city",
			totalSpend: {$sum: "$annualSpend"},
			averageSpend: {$avg: "$annualSpend"},
			maximumSpend: {$max: "$annualSpend"},
			customers: {$sum: 1}
		}
	}
])
+
info

See also SQL to Aggregation Mapping Chart

\ No newline at end of file diff --git a/docs/what-is-aggregation/structure-aggregation.html b/docs/what-is-aggregation/structure-aggregation.html index 9f62655..091f6dd 100644 --- a/docs/what-is-aggregation/structure-aggregation.html +++ b/docs/what-is-aggregation/structure-aggregation.html @@ -1,19 +1,23 @@ - + - -Structure of an aggregation pipeline | Aggregation Pipeline Lab + +Structure of an aggregation pipeline | Aggregation Pipeline Lab - - - + + + -
-

Structure of an aggregation pipeline

To interact with a relational database we typically use SQL, a 4th Generation language to access our data. With MongoDB we instead get data and transform it in incremental steps.

An aggregation pipeline is composed of stages.

We pass an array of stages to the aggregate method like so:

db.mycollection.aggregate([
    stage1,
    stage2,
    stage3
])

Example​

An Aggregation Pipeline that does the same than above SQL statement could be:

db.mycollection.aggregate([
  {
    $sort:
      /**
       * Provide any number of field/order pairs.
       */
      {
        num_mflix_comments: -1,
      },
  },
  {
    $limit:
      /**
       * Provide the number of documents to limit.
       */
      1,
  },
  {
    $unwind:
      /**
       * path: Path to the array field.
       * includeArrayIndex: Optional name for index.
       * preserveNullAndEmptyArrays: Optional
       *   toggle to unwind null and empty values.
       */
      {
        path: "$cast",
      },
  },
  {
    $project:
      /**
       * Specifications: The fields to
       *   include or exclude.
       */
      {
        cast: 1,
      },
  },
])
- - +

Structure of an aggregation pipeline

+

To interact with a relational database we typically use SQL, a 4th Generation language to access our data. With MongoDB we instead get data and transform it in incremental steps.

+

An aggregation pipeline is composed of stages.

+

We pass an array of stages to the aggregate method like so:

+
db.mycollection.aggregate([
    stage1,
    stage2,
    stage3
])
+

Example​

+

An Aggregation Pipeline that does the same than above SQL statement could be:

+
db.mycollection.aggregate([
  {
    $sort:
      /**
       * Provide any number of field/order pairs.
       */
      {
        num_mflix_comments: -1,
      },
  },
  {
    $limit:
      /**
       * Provide the number of documents to limit.
       */
      1,
  },
  {
    $unwind:
      /**
       * path: Path to the array field.
       * includeArrayIndex: Optional name for index.
       * preserveNullAndEmptyArrays: Optional
       *   toggle to unwind null and empty values.
       */
      {
        path: "$cast",
      },
  },
  {
    $project:
      /**
       * Specifications: The fields to
       *   include or exclude.
       */
      {
        cast: 1,
      },
  },
])
\ No newline at end of file diff --git a/docs/what-is-aggregation/what-is-aggregation.html b/docs/what-is-aggregation/what-is-aggregation.html index 2829073..9d0ddca 100644 --- a/docs/what-is-aggregation/what-is-aggregation.html +++ b/docs/what-is-aggregation/what-is-aggregation.html @@ -1,20 +1,23 @@ - + - -What is an Aggregation Pipeline | Aggregation Pipeline Lab + +What is an Aggregation Pipeline | Aggregation Pipeline Lab - - - + + + -
-

What is an Aggregation Pipeline

An Aggregation Pipeline is similar to unix commands connected using pipes. -We can Construct modular, composable processing pipelines.

An aggregation pipeline consists of one or more stages that processes documents:

Each stage performs an operation on the input documents. For example, a stage can filter documents, group documents, and calculate values.

The documents that are the output of a stage are passed as the input to the next stage.

An aggregation pipeline can return results for groups of documents. For example, return the total, average, maximum, and minimum values, etc.

- - +

What is an Aggregation Pipeline

+

+

An Aggregation Pipeline is similar to unix commands connected using pipes. +We can Construct modular, composable processing pipelines.

+

An aggregation pipeline consists of one or more stages that processes documents:

+

Each stage performs an operation on the input documents. For example, a stage can filter documents, group documents, and calculate values.

+

The documents that are the output of a stage are passed as the input to the next stage.

+

An aggregation pipeline can return results for groups of documents. For example, return the total, average, maximum, and minimum values, etc.

\ No newline at end of file diff --git a/helloWorld.html b/helloWorld.html index 416cbd4..0a480a7 100644 --- a/helloWorld.html +++ b/helloWorld.html @@ -2,18 +2,15 @@ - -Hello | Aggregation Pipeline Lab + +Hello | Aggregation Pipeline Lab - - - + + + -
-

Edit pages/helloWorld.js and save to reload.

- - +

Edit pages/helloWorld.js and save to reload.

\ No newline at end of file diff --git a/index.html b/index.html index 82dab77..6ab227e 100644 --- a/index.html +++ b/index.html @@ -2,24 +2,21 @@ - -Aggregation Pipeline Lab | Aggregation Pipeline Lab + +Aggregation Pipeline Lab | Aggregation Pipeline Lab - - - + + + -
-

Aggregation Pipeline Lab

Write Aggregation Pipelines in no time!

Start Lab

Learn to write Aggregation Pipelines!

+

Aggregation Pipeline Lab

Write Aggregation Pipelines in no time!

Start Lab

Learn to write Aggregation Pipelines!

Writing Aggregation Pipelines!

Compose pipeline stages

Unleash the power of the Aggregation pipeline!

Get hands-on experience and sample code

Learn by doing and build your Apps faster!

- - \ No newline at end of file diff --git a/search-index-docs-default-current.json b/search-index-docs-default-current.json index 9af34be..1184331 100644 --- a/search-index-docs-default-current.json +++ b/search-index-docs-default-current.json @@ -1 +1 @@ -{"documents":[{"id":1,"pageTitle":"","sectionTitle":"📄️ $count","sectionRoute":"/aggregation-pipeline-lab/docs/category/counting-and-sorting","type":"docs"},{"id":2,"pageTitle":"","sectionTitle":"📄️ Sorting","sectionRoute":"/aggregation-pipeline-lab/docs/category/counting-and-sorting","type":"docs"},{"id":3,"pageTitle":"","sectionTitle":"📄️ Saving to a collection","sectionRoute":"/aggregation-pipeline-lab/docs/category/exporting-data","type":"docs"},{"id":4,"pageTitle":"","sectionTitle":"📄️ Group","sectionRoute":"/aggregation-pipeline-lab/docs/category/grouping-results","type":"docs"},{"id":5,"pageTitle":"","sectionTitle":"📄️ Lookupups AKA Left Outer Join","sectionRoute":"/aggregation-pipeline-lab/docs/category/lookups--joins","type":"docs"},{"id":6,"pageTitle":"","sectionTitle":"📄️ 🦸‍♂️ Advanced lookups","sectionRoute":"/aggregation-pipeline-lab/docs/category/lookups--joins","type":"docs"},{"id":7,"pageTitle":"","sectionTitle":"📄️ Adding new fields to results","sectionRoute":"/aggregation-pipeline-lab/docs/category/modifying-results","type":"docs"},{"id":8,"pageTitle":"","sectionTitle":"📄️ Missing Data","sectionRoute":"/aggregation-pipeline-lab/docs/category/modifying-results","type":"docs"},{"id":9,"pageTitle":"","sectionTitle":"📄️ Set up Lab","sectionRoute":"/aggregation-pipeline-lab/docs/category/prerequisites","type":"docs"},{"id":10,"pageTitle":"","sectionTitle":"📄️ Using the library database","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":11,"pageTitle":"","sectionTitle":"📄️ Empty aggregation pipeline","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":12,"pageTitle":"","sectionTitle":"📄️ $match","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":13,"pageTitle":"","sectionTitle":"📄️ $project","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":14,"pageTitle":"","sectionTitle":"📄️ $limit","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":15,"pageTitle":"","sectionTitle":"📄️ Combining stages","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":16,"pageTitle":"","sectionTitle":"📄️ Writing long pipelines","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":17,"pageTitle":"","sectionTitle":"📄️ 🦸‍♂️ Repeating stages","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":18,"pageTitle":"","sectionTitle":"📄️ 🦸‍♂️ Aggregation options","sectionRoute":"/aggregation-pipeline-lab/docs/category/simple-queries","type":"docs"},{"id":19,"pageTitle":"","sectionTitle":"📄️ What is an Aggregation Pipeline","sectionRoute":"/aggregation-pipeline-lab/docs/category/the-aggregation-pipeline","type":"docs"},{"id":20,"pageTitle":"","sectionTitle":"📄️ SQL vs Aggregations","sectionRoute":"/aggregation-pipeline-lab/docs/category/the-aggregation-pipeline","type":"docs"},{"id":21,"pageTitle":"","sectionTitle":"📄️ Structure of an aggregation pipeline","sectionRoute":"/aggregation-pipeline-lab/docs/category/the-aggregation-pipeline","type":"docs"},{"id":22,"pageTitle":"","sectionTitle":"📄️ Simple Array queries","sectionRoute":"/aggregation-pipeline-lab/docs/category/using-arrays","type":"docs"},{"id":23,"pageTitle":"","sectionTitle":"📄️ Searching inside Objects in arrays","sectionRoute":"/aggregation-pipeline-lab/docs/category/using-arrays","type":"docs"},{"id":24,"pageTitle":"$count","sectionTitle":"$count","sectionRoute":"/aggregation-pipeline-lab/docs/counting-sorting/counting-documents","type":"docs"},{"id":25,"pageTitle":"$count","sectionTitle":"The order of stages is important","sectionRoute":"/aggregation-pipeline-lab/docs/counting-sorting/counting-documents#the-order-of-stages-is-important","type":"docs"},{"id":26,"pageTitle":"Sorting","sectionTitle":"Sorting","sectionRoute":"/aggregation-pipeline-lab/docs/counting-sorting/sorting","type":"docs"},{"id":27,"pageTitle":"Saving to a collection","sectionTitle":"Saving to a collection","sectionRoute":"/aggregation-pipeline-lab/docs/exporting-data/saving-to-collection","type":"docs"},{"id":28,"pageTitle":"Group","sectionTitle":"Group","sectionRoute":"/aggregation-pipeline-lab/docs/grouping/group","type":"docs"},{"id":29,"pageTitle":"Intro","sectionTitle":"Intro","sectionRoute":"/aggregation-pipeline-lab/docs/intro","type":"docs"},{"id":30,"pageTitle":"📘 Lecture material","sectionTitle":"📘 Lecture material","sectionRoute":"/aggregation-pipeline-lab/docs/lecture-material","type":"docs"},{"id":31,"pageTitle":"📘 Lecture material","sectionTitle":"Aggregation Pipeline Cheatsheet","sectionRoute":"/aggregation-pipeline-lab/docs/lecture-material#aggregation-pipeline-cheatsheet","type":"docs"},{"id":32,"pageTitle":"🦸‍♂️ Advanced lookups","sectionTitle":"🦸‍♂️ Advanced lookups","sectionRoute":"/aggregation-pipeline-lab/docs/lookups/advanced-lookups","type":"docs"},{"id":33,"pageTitle":"Lookupups AKA Left Outer Join","sectionTitle":"Lookupups AKA Left Outer 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