Introduction to MongoDB

1. MongoDB Justin Smestad @jsmestad [email protected]

2. whoami Software Engineer (Ruby, Javascript, and Clojure) User Experience & Design on the side Passion for DevOps Chicagoland native

6. Background Java Engineer @ Orbitz Worldwide Brought Ruby and RSpec/Cucumber to replace Fitness Testing Application Developer @ Factory Design Labs Brand & Campaign sites for Audi, Oakley, and TNF Independent Contractor Development team for TechStars alumni

9. mongo machine hosted MongoDB wherever you need it

10. What’s mongo machine ?

11. mongo machine hosted MongoDB + data management http://mongomachine.com

12. mongo machine hosted MongoDB + data management Our Goals Educate and promote best practices Increase customer efﬁciency Promote transparency

13. Our Product

14. Hosted MongoDB Provide the best managed MongoDB experience, on any platform.

15. mongo machine hosted MongoDB + data management Managed MongoDB Infrastructure Our infrastructure on AWS or Rackspace Automated Deployments to your own infrastructure Management Console Instantly create new databases Track database trends Scale up & down on-demand

16. Management Console Analytics data about what your DB is doing.

17. Management Console Analytics data about what your DB is doing.

19. “NoSQL” hasn’t this been tried before? why should I care now?

20. So what is MongoDB? (10,000ft view)

21. MongoDB (from "humongous") is a scalable, high-performance, open source, schema-free, document-oriented database. -- mongodb.org

22. Who is using MongoDB?

23. Fortune 500 <=> Startups

24. Github Bug Tracking & Analytics

25. Foursquare Check-in System

26. New York Times Photo Submissions

27. The list is large and growing fast http://www.mongodb.org/display/DOCS/Production+Deployments

29. Philosophy

30. Philosophy “One size DOESN’T ﬁt”

31. Philosophy Non-relational (de-normalized) DBs are easier to scale, especially horizontally

32. Philosophy DBs should be an on-demand commodity (cloud-like)

33. Philosophy Focus on performance, ﬂexibility and scalability (CA)

34. Philosophy Not concerned with transactional stuff or relational semantics

35. Philosophy Mongo aims for the performance of key- value stores while maintaining functionality of traditional RDBMS

37. Features

38. Features Standard database stuff Indexing Traditional master-slave Database References (no concept of JOINS)

42. Features Speed in-memory dataset with fsync to disk

43. Features Durability solve with replication, or use journaling

44. Features Document-oriented database

45. Features: Document Storage Documents are stored in BSON (binary JSON)

46. Features: Document Storage BSON is a binary serialization of JSON-like objects

47. Features: Document Storage Large BSON documents are served in chunks (GridFS)

48. Features: Document Storage This is extremely powerful, b/c it means mongo understands JSON natively

49. Features: Document Storage Any valid JSON can be easily imported and queried

50. Features: Document Storage Documents can contain embedded documents (nested hashes) without losing any indexing capabilities.

51. Features Schema-less; very ﬂexible no more blocking ALTER TABLE or NULL debates

52. Features Replica Sets and Sharding make horizontal scaling easy.

53. Features: Replica Set Traditional Master-Slave, but automatic failover Each server holds all data (CA) One is elected master at a given time Arbitration process detects failover New election within seconds

58. Features Map/Reduce Map Reduce operations are written in Javascript.

59. Features: Querying Rich, javascript-based query syntax Allows us to do deep, nested queries

60. Features: Querying Rich, javascript-based query syntax Allows us to do deep, nested queries

61. Features: Querying Rich, javascript-based query syntax Allows us to do deep, nested queries db.order.find( { shipping: { carrier: "usps" } } );

62. Features: Querying Rich, javascript-based query syntax Allows us to do deep, nested queries db.order.find( { shipping: { carrier: "usps" } } ); shipping is an embedded document (object)

63. Features atomic operations upserts, $set, $inc, $push, $pull, $pop, $addToSet, ...

64. Features Ofﬁcial Drivers .NET, Java, Javascript, Ruby, Node.js, PHP, Haskell, C/C++, Perl

65. Features Community & Market Growth MongoDB works alongside your existing technologies

67. Concepts

68. Concepts: Document-oriented Think of “documents” as objects / database records

69. Concepts: Document-oriented Think of “documents” as objects / database records Documents are basically just JSON in binary

70. Concept: Document-oriented Think of “documents” as objects / database records Documents are basically just JSON in binary Ability to store information all together

71. Concept Mapping RDBMS (mysql, postgres) MongoDB Tables Collections

72. Concept Mapping RDBMS (mysql, postgres) MongoDB Tables Collections Records/rows Documents/objects

73. Concept Mapping RDBMS (mysql, postgres) MongoDB Tables Collections Records/rows Documents/objects Queries return record(s) Queries return a cursor

74. Concept Mapping RDBMS (mysql, postgres) MongoDB Tables Collections Records/rows Documents/objects Queries return record(s) Queries return a cursor ???

75. Concepts: Cursors Queries return “cursors” instead of collections

76. Concepts: Cursors Queries return “cursors” instead of collections A cursor allows you to iterate through the result set

77. Concepts: Cursors Queries return “cursors” instead of collections A cursor allows you to iterate through the result set A big reason for this is performance

78. Concepts: Cursors Queries return “cursors” instead of collections A cursor allows you to iterate through the result set A big reason for this is performance Much more efﬁcient than loading all objects into memory

79. Concepts: Cursors The ﬁnd() function returns a cursor object

80. Concepts: Cursors The ﬁnd() function returns a cursor object var cursor = db.logged_requests.find({ 'status_code' : 200 }) cursor.hasNext() // "true" cursor.forEach( function(item) { print(tojson(item)) } ); cursor.hasNext() // "false"

82. Cool Features

83. Cool Features Capped collections Fixed-sized, limited operation, auto-LRU age-out collections Fixed insertion order Extremely performant Ideal for logging and caching

89. Use Cases

90. Use Cases Data Warehouse Mongo understands JSON natively Very powerful map-reduce for analytics Nested hashes make roll-up (RRDtool) systems natural

94. Use Cases Audit Trails Nested documents allow you to store audit trails in context.

95. Use Cases Audit Trails Nested documents allow you to store audit trails in context. { ‘name’: ‘Justin Smestad’, ‘address’: ‘1441 Central St’, ‘history’: [ { ‘name’: ‘Justin Smestad’, ‘address’: ‘350 S Jackson St’ },....] }

97. Limitations

98. Limitations Transaction support Relational integrity (normalization) Partition balancing Map / Reduce is single threaded Data compaction

103. Why not `other db` ? CouchDB, Cassandra, Riak, Membase, Redis, ...

104. Why not `other db`? FLEXIBILITY MongoDB’s design choices empower developers and administrators with features that allow you to implement their own solutions. *

105. Questions? @jsmestad / @mongo_machine

Introduction to MongoDB

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