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Building your First MEAN App

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Building your First MEAN App

  1. 1. Evening with MongoDB Building your first MEAN app Solution Architect, MongoDB, Inc. dbaev@mongodb.com Dmitry Baev
  2. 2. Agenda • Designing your schema in MongoDB • How to be MEAN • Visualizing your MongoDB data in a MEANingful way! • Scalability &Availability • DeploymentArchitectures & Operations
  3. 3. The Document Model
  4. 4. Terminology MongoDB RDBMS Collection Table Document Row Index Index Embedded Document Join Reference Foreign Key
  5. 5. Focus on data storage Focus on data use
  6. 6. What answers do I have? What questions do I have?
  7. 7. 7 Document Data Model Relational MongoDB { first_name: „Paul‟, surname: „Miller‟, city: „London‟, location: [45.123,47.232], cars: [ { model: „Bentley‟, year: 1973, value: 100000, … }, { model: „Rolls Royce‟, year: 1965, value: 330000, … } } }
  8. 8. 8 Documents are Rich Data Structures { first_name: „Paul‟, surname: „Miller‟, cell: „+447557505611‟ city: „London‟, location: [45.123,47.232], Profession: [banking, finance, trader], cars: [ { model: „Bentley‟, year: 1973, value: 100000, … }, { model: „Rolls Royce‟, year: 1965, value: 330000, … } } } Fields can contain an array of sub-documents Fields Typed field values Fields can contain arrays
  9. 9. 9 Document Model Benefits • Agility and flexibility – Data model supports business change – Rapidly iterate to meet new requirements • Intuitive, natural data representation – Eliminates ORM layer – Developers are more productive • Reduces the need for joins, disk seeks – Programming is more simple – Performance delivered at scale
  10. 10. 10 Developers are more productive
  11. 11. 11 Developers are more productive
  12. 12. 12 Better Data Locality Performance In-Memory Caching In-Place Updates
  13. 13. 14 Do More With Your Data MongoDB Rich Queries • Find Paul’s cars • Find everybody in London with a car built between 1970 and 1980 Geospatial • Find all of the car owners within 5km of Trafalgar Sq. Text Search • Find all the cars described as having leather seats Aggregation • Calculate the average value of Paul’s car collection Map Reduce • What is the ownership pattern of colors by geography over time? (is purple trending up in China?) { first_name: „Paul‟, surname: „Miller‟, city: „London‟, location: [45.123,47.232], cars: [ { model: „Bentley‟, year: 1973, value: 100000, … }, { model: „Rolls Royce‟, year: 1965, value: 330000, … } } }
  14. 14. 15 Drivers & Ecosystem Drivers Support for the most popular languages and frameworks Frameworks Morphia MEAN Stack Java Python Perl Ruby
  15. 15. Modeling Data with MongoDB
  16. 16. Contact Address Business Card
  17. 17. Referencing Addresses { _id : , street : , city : , state : ”, zip_code : , country : } Contacts { _id : , name : , title : , company : ”, phone : , address_id : }
  18. 18. Embedding Contacts { _id : , name : , title : , company : , address : { street : , city : , state : , zip_code : , country : }, phone : }
  19. 19. Schema Flexibility { name : , title : , company : , address : { street : , city : , state : , zip_code : }, phone : } { name : , url : , title : , company : , email : , address : { street : , city : , state : , zip_code : } phone : , fax }
  20. 20. { “_id”: , “name”: , “title”: , “company”: , “address”: [ { “street”: , “city”: , “state”: , “zip_code”: , “country”: }, { “street”: , “city”: , “state”: } ], “phone”: } Schema Flexibility { _id : , name : , title : , company : , address : { street : , city : , state : , zip_code : , country : }, phone : }
  21. 21. Let’s get MEAN
  22. 22. MEAN Stack Database Server Client Angularjs-nvd3 ----------------------------------------------------------------------------------------------- -----------------------------------------------------------------------------------------------
  23. 23. How to be MEAN! ServerClient ------------------------------------------------------ View Controller Service Route Controller Model REST API call
  24. 24. Node.js MongoDB Driver • Install using npm • Basic CRUD • Mongos • Aggregation • Replica Set • Sharding • Read preferences
  25. 25. Mongoose • Provides “elegant MongoDB object modeling for Node.js” using Schemas and Models • Each schema maps to a MongoDB collection • Models can be instantiated based on a schema • Instances of models represent documents in MongoDB • Support for CRUD, aggregation, validation, pseudo-joins, rich query builder + lots more! • Install using npm
  26. 26. Mongoose (getting started) • Require Node module • Connect to MongoDB • Define your schema in JSON • Create the model object
  27. 27. Mongoose (example) • Create/ Update – #model.save() • Read – #model.findOne() – #model.find() • Update – #model.update() • Delete – #model.remove() • Aggregate – #model.aggregate()
  28. 28. Visualizing data • D3.js – JavaScript library for manipulating documents based on data – bring your data to life • NVD3.js – reusable charts for d3.js • Angularjs-nvd3-directives – Angular‟s way of extending HTML to create new elements and functionality
  29. 29. D3.js NVD3.js Visualizing data Angularjs -nvd3- directives
  30. 30. Real-time streaming charts • Socket.IO (Node.js module) – “aims to make realtime apps possible in every browser and mobile device” • MongoDB Tailable Cursors – requires a capped collection • NVD3.js Event Listeners – charts can be refreshed continuouslyas data is inserted/update in MongoDB collection
  31. 31. Demo: Visualizing your MongoDB data in a MEANingful way!
  32. 32. City of Toronto – Open Data • Data source: REST ServiceAPI – To retrieve a list of service requestbetween Feb 1, 2012 to Feb 7, 2012 https://secure.toronto.ca/webwizard/ws/requests.json?start_date=2012-02- 01T00:00:00Z&end_date=2012-02-07T00:00:00Z&jurisdiction_id=toronto.ca • Output format: JSON • Refresh rate: continuously - real time refresh
  33. 33. Getting started with MEAN • MEAN.io – ready to use MEAN stack boilerplate • Yeoman – scaffolding tool for building modern web apps – CommunityMEAN stack generators: • https://github.com/wlepinski/generator-meanstack • https://github.com/jrcryer/generator-mean • https://github.com/chrisenytc/generator-meanis
  34. 34. Scalability & Availability
  35. 35. 36 Scalability Auto-Sharding • Increase capacity as you go • Commodity and cloud architectures • Improved operational simplicity and cost visibility
  36. 36. 37 High Availability • Automated replication and failover • Multi-data center support • Improved operational simplicity (e.g., HW swaps) • Data durability and consistency
  37. 37. 38 MongoDB Architecture
  38. 38. Deployment Architectures & Operations
  39. 39. 40 Single Data Center • Automated failover • Tolerates server failures • Tolerates rack failures • Number of replicas defines failure tolerance Primary – A Primary – B Primary – C Secondary – A Secondary – ASecondary – B Secondary – BSecondary – CSecondary – C
  40. 40. 41 Active/Active Data Center • Tolerates server, rack, data center failures, network partitions Data Center - West Primary – A Primary – B Primary – C Secondary – A Secondary – BSecondary – C Data Center - East Secondary – A Secondary – B Secondary – C Secondary – B Secondary – C Secondary – A Data Center - Central Arbiter – A Arbiter – B Arbiter – C
  41. 41. 42 Read Global/Write Local Primary:NYC Secondary:NYC Primary:LON Primary:SYD Secondary:LON Secondary:NYC Secondary:SYD Secondary:LON Secondary:SYD
  42. 42. References • MEAN.io - http://www.mean.io • MongoDB - http://mongodb.com • Express - http://expressjs.com • Angular - http://angularjs.org • Node - http://nodejs.org • Socket.IO- http://http://socket.io • Angularjs-nvd3-directives - http://cmaurer.github.io/angularjs-nvd3- directives
  43. 43. mongodb.org/downloads
  44. 44. Online Training at MongoDB University
  45. 45. For More Information Resource Location MongoDB Downloads mongodb.org/downloads Free Online Training education.mongodb.com Webinars and Events mongodb.com/events White Papers mongodb.com/white-papers Case Studies mongodb.com/customers Presentations mongodb.com/presentations Documentation docs.mongodb.org Additional Info info@mongodb.com Resource Location
  46. 46. Thank You Solution Architect, MongoDB, Inc. dbaev@mongodb.com Dmitry Baev

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