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Think You Know MongoDB? PHP User Group Munich

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Think You Know MongoDB? PHP User Group Munich

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Getting Started

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$ brew install mongodb-atlas-cli $ atlas setup

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Yes, it’s FREE!

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MongoDB Atlas

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MongoDB Atlas Free clusters • M0 shared clusters are free • Allows quick testing without stability guarantees • Limitations apply • Don’t run production on it! • Really, don’t!

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MongoDB Atlas Dedicated Clusters • Support production usage • More storage and automatic scaling • Automatic cluster tier scaling • Supports backups and point-in-time restore • Includes Enterprise features

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MongoDB Atlas Serverless tier • Minimal con fi guration • Production-ready for variable workloads • Great for startups

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You can still host MongoDB yourself

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On-premise deployments You’re in charge • Deploy MongoDB on your own hardware • Decide which cluster con fi guration to run • Manage upgrades and backups yourself • Community Edition is free • Enterprise Edition for advanced features

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The Database

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The Database Document model { "name": "alcaeus", "email": [ { "type": "work", "address": "" }, { "type": "private", "address": "" } ], "phone": [ { "type": "mobile", "number": "" }, { "type": "home", "number": "" } ] }

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The Database Replication

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The Database Scaling via replication

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The Database Sharding

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Global Clusters MongoDB Atlas makes it easy

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The Driver(s)

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Drivers Choose your fi ghter

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Drivers Your connection to MongoDB • Connect your application to a MongoDB deployment • Monitor deployment and route commands • Provide a rich database API

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Drivers Putting the “No” in NoSQL • Driver API is common across programming languages • Client object to interact with a deployment • Database object to interact with a database • Collection object to interact with a collection • Driver speci fi cation is public

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PHP Driver Collection API interface Collection { public function insertMany(array $documents, array $options = []); public function insertOne($document, array $options = []); public function find($filter = [], array $options = []); public function findOne($filter = [], array $options = []); public function updateMany($filter, $update, array $options = []); public function updateOne($filter, $update, array $options = []); public function deleteMany($filter, array $options = []); public function deleteOne($filter, array $options = []); }

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PHP Driver Getting started $client = new MongoDB\Client('mongodb+srv://[...].mongodb.net'); $client->db->coll->insertOne(['name' => 'alcaeus']); $client->db->coll->findOne(['name' => 'alcaeus']);

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PHP Driver Collection API (2) interface Collection { public function aggregate(array $pipeline, array $options = []); public function findOneAndUpdate($filter, $update, array $options = []); public function findOneAndDelete($filter, array $options = []); public function watch(array $pipeline = [], array $options = []); }

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The Queries

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Queries Atomic array operations $collection->updateOne( ['_id' => 1], [ '$currentDate' => ['updated_at' => true], '$pull' => ['vegetables' => 'tomato'], '$push' => ['fruits' => 'tomato'], ] );

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Queries Atomic update errors $collection->updateOne( ['_id' => 1], [ '$pull' => ['fruits' => 'strawberry'], '$push' => ['fruits' => 'tomato'], ] ); // Exception: Updating the path 'fruits' would create a conflict at 'fruits'

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Queries Separate updates for multiple fi elds $collection->updateOne( ['_id' => 1], ['$pull' => ['fruits' => 'strawberry']] ); $collection->updateOne( ['_id' => 1], ['$push' => ['fruits' => 'tomato']] );

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Queries Use transactions use function MongoDB\with_transaction; $session = $client->startSession(); with_transaction($session, function (Session $session) use ($collection) { $collection->updateOne( ['_id' => 1], ['$pull' => ['fruits' => 'strawberry']], ['session' => $session] ); $collection->updateOne( ['_id' => 1], ['$push' => ['fruits' => 'tomato']], ['session' => $session] ); });

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The Schema

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Document Model Topic data { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "num_posts": 1, "created_at": { "$date": { "$numberLong": "1687158294045" } }, "posts": [ { "_id": { "$oid": "648ffe160a8daeb5e50506a4" }, "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "body": "I love it, what about you?", "created_at": { "$date": { "$numberLong": "1687158294045" } } } ] }

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Document Model Identi fi ers { "title": "What do you think about MongoDB?", "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "num_posts": 1, "created_at": { "$date": { "$numberLong": "1687158294045" } }, "posts": [ { "_id": { "$oid": "648ffe160a8daeb5e50506a4" }, "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "body": "I love it, what about you?", "created_at": { "$date": { "$numberLong": "1687158294045" } } } ] } "_id": { "$oid": "648ffe160a8daeb5e50506a3" },

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Document Model ObjectIds contain timestamps { "_id": { "$oid": " 0a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "num_posts": 1, "created_at": { "$date": { "$numberLong": "1687158294045" } }, "posts": [ { "_id": { "$oid": "648ffe160a8daeb5e50506a4" }, "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "body": "I love it, what about you?", "created_at": { "$date": { "$numberLong": "1687158294045" } } } ] } 648ffe16

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Document Model ObjectIds contain timestamps { "_id": { "$oid": " 0a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "num_posts": 1, "created_at": { "$date": { "$numberLong": " 045" } }, "posts": [ { "_id": { "$oid": "648ffe160a8daeb5e50506a4" }, "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "body": "I love it, what about you?", "created_at": { "$date": { "$numberLong": "1687158294045" } } } ] } 648ffe16 1687158294

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Document Model No more created_at { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "num_posts": 1, "posts": [ { "_id": { "$oid": "648ffe160a8daeb5e50506a4" }, "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "body": "I love it, what about you?" } ] }

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Document Model Embed data { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "author": { "_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "name": "alcaeus", "image": "..." }, "num_posts": 1, "posts": [ { "_id": { "$oid": "648ffe160a8daeb5e50506a4" }, "author": { ... }, "body": "I love it, what about you?" } ] }

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Document Model Don’t be afraid to duplicate data $collection->updateMany( ['author._id' => $author['_id']], ['$set' => ['author.name' => $author['name']]] ); $collection->updateMany( [], ['$set' => ['posts.$[post].author.name' => $author['name']]], ['arrayFilters' => [['post.author._id' => $author['_id']]]] );

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Document Model Atomic updates $collection->updateOne( ['_id' => $topic['_id']], [ '$push' => [ 'posts' => [ '_id' => new MongoDB\BSON\ObjectId(), 'author' => $author, 'body' => $body, ], ], '$inc' => ['numPosts' => 1], ] );

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Document Model It gets BIG { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "author": { "_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "name": "alcaeus", "image": "..." }, "num_posts": 14290, "posts": [ ... ] }

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Document Limits Just because you can… • Documents have a maximum size of 16 MB • Documents support 255 levels of nesting • Embedding same data multiple times is an anti-pattern • Ever-growing arrays are problematic

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Document Model Don’t embed everything { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "num_replies": 14289 } "post": { "author": { "_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "name": "alcaeus", "image": "..." }, "body": "I love it, what about you?" },

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Document Model Embed relevant data { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "post": { ... }, "num_replies": 14289, } "last_reply": { "_id": { "$oid": "648ffe160a8daeb5e50506ce" }, "author": { "_id": { "$oid": "648ffe160a8daeb5e50506a5" }, "name": "youdontknowme", "image": "..." }, "body": "I have a lot to learn about it!" }

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Document Model The other side: posts { "_id": { "$oid": "648ffe160a8daeb5e50506ce" }, "author": { "_id": { "$oid": "648ffe160a8daeb5e50506a5" }, "name": "youdontknowme", "image": "..." }, "body": "I still have a lot to learn about it!", "topic": { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?" } }

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Flexible Schema Let’s add polls { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "post": { ... }, "num_replies": 14289, "last_reply": { ... } } "poll": { "question": "Have you used MongoDB?", "options": [ { "title": "Yes" }, { "title": "No" } ] },

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Schema Updates Add tables and columns CREATE TABLE polls (...); ALTER TABLE topics ADD COLUMN poll_id INTEGER DEFAULT NULL;

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Schema Update MongoDB makes it easy

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MongoDB is not schemaless

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Schema Validation Supports JSON schema { "required": ["_id", "author", "title", "post", "num_replies"], "properties": { "_id": { "bsonType": "objectId" }, "author": { "bsonType": "object", "required": ["_id", "name"], "properties": { "_id": { "bsonType": "objectId" }, "name": { "bsonType": "string" }, "image": { "bsonType": "string" } } }, "title": { "bsonType": "string"}, ... } }

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Schema Validation Supports JSON schema db.createCollection( "topics", { validator: { $jsonSchema: mySchema }, validationLevel: "moderate", } );

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Aggregation Pipeline

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Aggregation Pipeline Raw GPS data { "document": { "_id": { "$oid": "6490311fd97a12c964c25030" }, "time": { "$numberDouble": "1685866107.024" }, "latitude": { "$numberDouble": "44.8859" }, "longitude": { "$numberDouble": "13.873914" }, "altitude": { "$numberDouble": "35.092" }, "speed": { "$numberDouble": "0.663" } } }

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Aggregation Pipeline Modify data [ { '$addFields': { 'time': { '$toDate': { '$multiply': [ '$time', 1000 ] } }, 'position': { 'type': 'point', 'coordinates': [ '$longitude', '$latitude' ] } } } ]

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Aggregation Pipeline Complex operations [ { '$setWindowFields': { 'sortBy': { 'time': 1 }, 'output': { 'previousPosition': { '$shift': { 'by': -1, 'default': null, 'output': { 'time': '$time', 'latitude': '$latitude', 'longitude': '$longitude' } } } } }}, { '$addFields': { 'bearing': { '$radiansToDegrees': { '$atan2': [ { '$multiply': [ { '$cos': '$latitude' }, { '$sin': { '$subtract': [ '$longitude', '$previousPosition.longitude' ] } } ]}, { '$subtract': [ { '$multiply': [ { '$cos': '$previousPosition.latitude' }, { '$sin': '$latitude' } ]}, { '$multiply': [ { '$sin': '$previousPosition.latitude' }, { '$cos': '$latitude' }, { '$cos': { '$subtract': ['$longitude', '$previousPosition.longitude'] } } ]} ]} ] } } }} ]

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Aggregation Pipeline Use for views db.createView( "telemetry", // View name "gpsdata", // Source collection [ { '$addFields': { 'time': { '$toDate': { '$multiply': [ '$time', 1000 ] } }, 'position': { 'type': 'point', 'coordinates': [ '$longitude', '$latitude' ] } } }, // ... more stages ] );

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Aggregation Pipeline On-demand materialised views { '$merge': { 'into': 'telemetry', 'on': '_id', 'whenMatched': 'replace', 'whenNotMatched': 'insert' } }

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MongoDB Atlas

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Charts

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MongoDB Atlas Data Federation • Query and move data from various sources • Atlas Clusters • Atlas Data Lake • AWS S3 buckets • HTTPS endpoints

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Data API Request $ curl --location --request POST 'https://.../v1/action/findOne' \ --header 'Content-Type: application/json' \ --header 'Access-Control-Request-Headers: *' \ --header 'api-key: 0fUMoHadYlL2QiI5vxQ7HyWIxNZ6jwHdFAyrb4zUB2ZZlGozFdXX5aiLNDYQu3K1' \ --header 'Accept: application/ejson' \ --data-raw '{ "collection":"gpsdata", "database":"karting", "dataSource":"Cluster95038" }'

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Data API Response { "document": { "_id": { "$oid": "6490311fd97a12c964c25030" }, "time": { "$numberDouble": "1685866107.024" }, "latitude": { "$numberDouble": "44.8859" }, "longitude": { "$numberDouble": "13.873914" }, "altitude": { "$numberDouble": "35.092" }, "speed": { "$numberDouble": "0.663" } } }

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MongoDB Atlas Atlas Search • Full-text search embedded in MongoDB Atlas • Built on Apache Lucene • Search data directly without duplicating it

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MongoDB Atlas Other features • Atlas Data Lake • Triggers • Encryption at Rest • Self-managed X.509 Authentication • App Services • In-Use Encryption

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Don’t Trust Anyone

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Don’t Trust Anyone Encrypt your data • MongoDB supports Client-Side Field Level Encryption • You have the key, we don’t • Data is encrypted in the driver • Schema to de fi ne encrypted fi elds and keys • Equality queries on deterministically encrypted fi elds only

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Don’t Trust Anyone Queryable Encryption • Searchable encryption scheme • In public preview, stay tuned • Equality queries on randomised encrypted data • More query types coming soon

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Your data is protected

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What’s next?

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What’s Next MongoDB 7.0 • Will be announced Thursday • Atlas Search Index management • Delete Time Series data • And more…

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What’s Next PHP Driver • Aggregation Pipeline builder • Laravel Integration • Native BSON classes • Lazy BSON deserialisation for more performance

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Things I didn’t mention There isn’t enough time for everything • Mirrored and hedged reads • Time Series collections • Clustered collections • Wildcard Indexes • Cloud Manager • Kubernetes Operator • Compass

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Join me at WSC! • Learn schema design patterns • JSONb, composite types in PostgreSQL • Migrate existing schema to MongoDB • Leverage aggregation pipeline for complex workloads Want to learn more?

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Thanks! @alcaeus github.com/alcaeus symfony-devs: @alcaeus