Think you know MongoDB?

Talk about MongoDB at the Munich PHP User Group.

Transcript

1. Think You Know MongoDB? PHP User Group Munich
2. Think You Know MongoDB? PHP User Group Munich
4. Getting Started
5. $ brew install mongodb-atlas-cli $ atlas setup
6. Yes, it’s FREE!
7. MongoDB Atlas
9. 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!
10. 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
11. MongoDB Atlas Serverless tier • Minimal con fi guration • Production-ready for variable workloads • Great for startups
12. You can still host MongoDB yourself
13. 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
14. The Database
15. The Database Document model { "name": "alcaeus", "email": [ { "type": "work", "address": "<redacted>" }, { "type": "private", "address": "<redacted>" } ], "phone": [ { "type": "mobile", "number": "<redacted>" }, { "type": "home", "number": "<redacted>" } ] }
16. The Database Replication
17. The Database Scaling via replication
18. The Database Sharding
19. Global Clusters MongoDB Atlas makes it easy
20. The Driver(s)
21. Drivers Choose your fi ghter
22. Drivers Your connection to MongoDB • Connect your application to a MongoDB deployment • Monitor deployment and route commands • Provide a rich database API
23. 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
24. 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 = []); }
25. PHP Driver Getting started $client = new MongoDB\Client('mongodb+srv://[...].mongodb.net'); $client->db->coll->insertOne(['name' => 'alcaeus']); $client->db->coll->findOne(['name' => 'alcaeus']);
26. 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 = []); }
27. The Queries
28. Queries Atomic array operations $collection->updateOne( ['_id' => 1], [ '$currentDate' => ['updated_at' => true], '$pull' => ['vegetables' => 'tomato'], '$push' => ['fruits' => 'tomato'], ] );
29. 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'
30. Queries Separate updates for multiple fi elds $collection->updateOne( ['_id' => 1], ['$pull' => ['fruits' => 'strawberry']] ); $collection->updateOne( ['_id' => 1], ['$push' => ['fruits' => 'tomato']] );
31. 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' => $session] ); });
32. The Schema
34. Document Model Topic data { "_id": { "$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": { "$numberLong": "1687158294045" } } } ] }
35. Document Model Identi fi ers { "title": "What do you think about MongoDB?", "author_id": { "$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": { "$oid": "648ffe160a8daeb5e50506a3" },
36. Document Model ObjectIds contain timestamps { "_id": { "$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": { "$numberLong": "1687158294045" } } } ] } 648ffe16
37. Document Model ObjectIds contain timestamps { "_id": { "$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": { "$numberLong": "1687158294045" } } } ] } 648ffe16 1687158294
38. Document Model No more created_at { "_id": { "$oid": "648ffe160a8daeb5e50506a3" }, "title": "What do you think about MongoDB?", "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "num_posts": 1, "posts": [ { "_id": { "$oid": "648ffe160a8daeb5e50506a4" }, "author_id": { "$oid": "648ffe160a8daeb5e50506a2" }, "body": "I love it, what about you?" } ] }
39. Document Model Embed data { "_id": { "$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?" } ] }
40. 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']]]] );
41. Document Model Atomic updates $collection->updateOne( ['_id' => $topic['_id']], [ '$push' => [ 'posts' => [ '_id' => new MongoDB\BSON\ObjectId(), 'author' => $author, 'body' => $body, ], ], '$inc' => ['numPosts' => 1], ] );
42. 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": [ ... ] }
43. 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
44. 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?" },
45. 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": { "$oid": "648ffe160a8daeb5e50506a5" }, "name": "youdontknowme", "image": "..." }, "body": "I have a lot to learn about it!" }
46. Document Model The other side: posts { "_id": { "$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?" } }
48. 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" } ] },
49. Schema Updates Add tables and columns CREATE TABLE polls (...); ALTER TABLE topics ADD COLUMN poll_id INTEGER DEFAULT NULL;
50. Schema Update MongoDB makes it easy
51. MongoDB is not schemaless
52. 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"}, ... } }
53. Schema Validation Supports JSON schema db.createCollection( "topics", { validator: { $jsonSchema: mySchema }, validationLevel: "moderate", } );
54. Aggregation Pipeline
55. Aggregation Pipeline Raw GPS data { "document": { "_id": { "$oid": "6490311fd97a12c964c25030" }, "time": { "$numberDouble": "1685866107.024" }, "latitude": { "$numberDouble": "44.8859" }, "longitude": { "$numberDouble": "13.873914" }, "altitude": { "$numberDouble": "35.092" }, "speed": { "$numberDouble": "0.663" } } }
56. Aggregation Pipeline Modify data [ { '$addFields': { 'time': { '$toDate': { '$multiply': [ '$time', 1000 ] } }, 'position': { 'type': 'point', 'coordinates': [ '$longitude', '$latitude' ] } } } ]
57. Aggregation Pipeline Complex operations [ { '$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', '$previousPosition.longitude'] } } ]} ]} ] } } }} ]
58. Aggregation Pipeline Use for views db.createView( "telemetry", // View name "gpsdata", // Source collection [ { '$addFields': { 'time': { '$toDate': { '$multiply': [ '$time', 1000 ] } }, 'position': { 'type': 'point', 'coordinates': [ '$longitude', '$latitude' ] } } }, // ... more stages ] );
59. Aggregation Pipeline On-demand materialised views { '$merge': { 'into': 'telemetry', 'on': '_id', 'whenMatched': 'replace', 'whenNotMatched': 'insert' } }
60. MongoDB Atlas
61. Charts
64. MongoDB Atlas Data Federation • Query and move data from various sources • Atlas Clusters • Atlas Data Lake • AWS S3 buckets • HTTPS endpoints
66. 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" }'
67. 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" } } }
68. MongoDB Atlas Atlas Search • Full-text search embedded in MongoDB Atlas • Built on Apache Lucene • Search data directly without duplicating it
69. MongoDB Atlas Other features • Atlas Data Lake • Triggers • Encryption at Rest • Self-managed X.509 Authentication • App Services • In-Use Encryption
70. Don’t Trust Anyone
71. 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
72. 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
73. Your data is protected
74. What’s next?
75. What’s Next MongoDB 7.0 • Will be announced Thursday • Atlas Search Index management • Delete Time Series data • And more…
76. What’s Next PHP Driver • Aggregation Pipeline builder • Laravel Integration • Native BSON classes • Lazy BSON deserialisation for more performance
77. 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
78. 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?
80. Thanks! @alcaeus github.com/alcaeus symfony-devs: @alcaeus