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Building your First MongoDB Application Rick Copeland @rick446 http://arborian.com Saturday, June 9, 12

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Who am I? • Now a consultant, but formerly... • Software engineer at SourceForge • Author of Essential SQLAlchemy • Primarily code Python Saturday, June 9, 12

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What will you learn here? Saturday, June 9, 12

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What will you learn here? • Data Modeling Saturday, June 9, 12

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What will you learn here? • Data Modeling • Queries Saturday, June 9, 12

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What will you learn here? • Data Modeling • Queries • Geospatial indexing Saturday, June 9, 12

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What will you learn here? • Data Modeling • Queries • Geospatial indexing • Updates Saturday, June 9, 12

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What will you learn here? • Data Modeling • Queries • Geospatial indexing • Updates • Map/Reduce Saturday, June 9, 12

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What will you learn here? • Data Modeling • Queries • Geospatial indexing • Updates • Map/Reduce • Deployment and Scaling Concerns Saturday, June 9, 12

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What will you learn here? • Data Modeling • Queries • Geospatial indexing • Updates • Map/Reduce • Deployment and Scaling Concerns • Why MongoDB? Saturday, June 9, 12

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Our Application • Users can create different locations • Users can “check in” to these locations • Users can see who else is checked in • Let’s call it ThreeTriangles (3tri) Saturday, June 9, 12

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3tri Operations Places Checkins User-generated content Find nearby places Record checkins Checkin Stats Saturday, June 9, 12

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MongoDB Terminology Relational MongoDB Database Database Table Collection Index Index Row Document Column Field Saturday, June 9, 12

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Documents? doc1 = {! _id: ObjectId('4b97e62bf1d8c7152c9ccb74'), key1: value1,! key2: value2, key3: {..., ..., ...}, key4: [..., ..., ] } Saturday, June 9, 12

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Collections • No schema enforcement • Per-collection... • Querying • Indexing • Updating • Sharding doc1,doc2,... doc5,doc6,... doc8,doc9,... Places Users Checkins Saturday, June 9, 12

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Places v1 place1 = {! name: "Blake Hotel",! address: "555 South McDowell Street", city: "Charlotte", zip: "28204"} db.places.find({zip:"28204"}).limit(10) Saturday, June 9, 12

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Places v2 place2 = { name: "Blake Hotel",! address: "555 South McDowell Street", city: "Charlotte", zip: "28204", tags: ["hotel", "recommended"]} db.places.find({ zip: "28204", tags: "hotel"}).limit(10) Saturday, June 9, 12

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Places v3 place3 = { name: "Blake Hotel",! address: "555 South McDowell Street", city: "Charlotte", zip: "28204", tags: ["hotel", "recommended"], latlon: [ 35.21, 80.83 ] } db.places.ensureIndex({latlong:"2d"}) db.places.find({latlong:{$near:[35,80]}}) Saturday, June 9, 12

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Places v4 place4 = { name: "Blake Hotel",! address: "555 South McDowell Street", city: "Charlotte", zip: "28204", tags: ["hotel", "recommended"], latlon: [ 35.21, 80.83 ], tips: [ { user: "rick", time: ISODateTime(...), tip: "Come learn about #self2012"}, { ... }, { ... } ] } Saturday, June 9, 12

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Some Queries /* First, some indexes */ db.places.ensureIndex({tags:1}) db.places.ensureIndex({name:1}) db.places.ensureIndex({latlong:"2d"}) /* Find places */ db.places.find({latlong:{$near:[40,70]}}) /* Regex searching */ db.places.find({name: /^typeaheadstring/) /* Searching arrays */ db.places.find({tags: "business"}) Saturday, June 9, 12

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Inserting and updating /* Initial data load */ db.places.insert([place1, place2, ...]) /* Update-in-place */ db.places.update( { name:"Blake Hotel" }, { $push : { tips: { user: "rick", time: ISODateTime(...), tip: "Come learn about #self2012" } } } ) Saturday, June 9, 12

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3tri Operations Places Checkins User-generated content Find nearby places Record checkins Checkin Stats Saturday, June 9, 12

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Users user1 = { name: "rick", email: "[email protected]", ... checkins: [ ObjectId('4b97e62bf1d8c7152c9ccb74'), ... ] } /* checkins [] = references checkin collection _id field */ Saturday, June 9, 12

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Checkins db.checkins.ensureIndex({place:1, ts:1}) db.checkins.ensureIndex({ts:1}) checkin1 = { place: { id: ObjectId(...), name: "Blake Hotel" }, ts: ISODateTime(...), user: { id: ObjectId(...), name: "rick" } } Saturday, June 9, 12

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Atomic Updates • $set • $unset • $rename • $push • $pushAll • $pop • $pull • $pullAll • $addToSet • $inc • $bit Saturday, June 9, 12

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3tri Operations Places Checkins User-generated content Find nearby places Record checkins Checkin Stats Saturday, June 9, 12

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Simple Statistics /* All checkins */ db.checkins.find({"place.name": "Blake Hotel"}) /* Last 10 checkins */ db.checkins.find({"place.name": "Blake Hotel"}) .sort({ts:-1}).limit(10) /* Number of checkins today */ db.checkins.find( { "place.name": "Blake Hotel", ts: { $gt: ISODateTime(...)} }) .count() Saturday, June 9, 12

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MapReduce mapFunc = function() { emit(this.place.name, 1); } reduceFunc = function(key, values) { return Array.sum(values); } res = db.checkins.mapReduce( mapFunc, reduceFunc, ! { query: { ts: { $gt: nowminus3hrs } } out: {inline: 1} }) res.results = [ {_id:"Blake Hotel", value: 17}, ...] Saturday, June 9, 12

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Deployment and Scaling Options Saturday, June 9, 12

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Single Master Deployment Primary Secondary Secondary Read / Write Read Read Saturday, June 9, 12

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Auto-Sharding Shard 1 (0..10) Primary Secondary Secondary Shard 2 (10..20) Primary Secondary Secondary Shard 3 (20..30) Primary Secondary Secondary Config Saturday, June 9, 12

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Use Cases • Replace RDBMS for high-traffic web applications • CMS-style applications • Social and mobile applications • Real-time analytics, high-speed logging • Maybe not double-entry bookkeeping Saturday, June 9, 12

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What do you give up? • No multi-document atomic operations (i.e. transactions) • No server-side JOINs • No referential integrity constraints between documents • Data model is typically tied to query patterns (less flexible than relational DBs) Saturday, June 9, 12

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Questions? Please rate this talk at http://svy.mk/L3jM7f Interested in training? http://Arborian.com/training MongoDB Info & Downloads: http://mongodb.org Rick Copeland @rick446 http://arborian.com Saturday, June 9, 12