Schema Design - Kyle Banker, 10gen

MongoSF 2011

One of the challenges that comes with moving to MongoDB is figuring how to best model your data. While most developers have internalized the rules of thumb for designing schemas for RDBMSs, these rules don't always apply to MongoDB. The simple fact that documents can represent rich, schema-free data structures means that we have a lot of viable alternatives to the standard, normalized, relational model. Not only that, MongoDB has several unique features, such as atomic updates and indexed array keys, that greatly influence the kinds of schemas that make sense. Understandably, this begets good questions:

Are foreign keys permissible, or is it better to represent one-to-many relations withing a single document? Are join tables necessary, or is there another technique for building out many-to-many relationships? What level of denormalization is appropriate? How do my data modeling decisions affect the efficiency of updates and queries?

In this session, we'll answer these questions and more, provide a number of data modeling rules of thumb, and discuss the tradeoffs of various data modeling strategies.

Transcript

1. Kyle Banker MongoDB Schema Design Wednesday, May 25, 2011
2. kyle@10gen.com @hwaet Wednesday, May 25, 2011
3. http://manning.com/banker Wednesday, May 25, 2011
4. 4:30 - 5:15 Banking Hall The MongoDB Gamut Four Application Designs Wednesday, May 25, 2011
5. Topics Introduction • Working with documents • Evolving a schema • Queries and indexes • Rich documents Wednesday, May 25, 2011
6. Topics Introduction • Working with documents • Evolving a schema • Queries and indexes • Rich documents Common patterns • Single table inheritance • One-to-Many & Many-to-Many • Trees • Queues Wednesday, May 25, 2011
7. Ways to model data: http://www.flickr.com/photos/42304632@N00/493639870/ Wednesday, May 25, 2011
8. Normalized Wednesday, May 25, 2011
9. Denormalized Wednesday, May 25, 2011
10. Terminology RDBMS MongoDB Table Collection Row(s) JSON  Document Index Index Join Embedding  &  Linking Wednesday, May 25, 2011
11. Schema-design Criteria How can we manipulate this data? • Dynamic Queries • Secondary Indexes • Atomic Updates • Map Reduce Wednesday, May 25, 2011
12. Schema-design Criteria How can we manipulate this data? • Dynamic Queries • Secondary Indexes • Atomic Updates • Map Reduce Access Patterns? • Read / Write Ratio • Types of updates • Types of queries • Data life-cycle Wednesday, May 25, 2011
13. Schema-design Criteria How can we manipulate this data? • Dynamic Queries • Secondary Indexes • Atomic Updates • Map Reduce Considerations • No Joins • Document writes are atomic Access Patterns? • Read / Write Ratio • Types of updates • Types of queries • Data life-cycle Wednesday, May 25, 2011
14. Here’s an example with a book: Wednesday, May 25, 2011
15. A simple start: Map the documents to your application. post  =  {author:  “Hergé”,                date:  new  Date(),                text:  “Destination  Moon”,                tags:  [“comic”,  “adventure”]} >  db.post.save(post) Wednesday, May 25, 2011
16. >  db.posts.find()    {  _id:  ObjectId("4c4ba5c0672c685e5e8aabf3"),        author:  "Hergé",          date:  "Sat  Jul  24  2010  19:47:11  GMT-­‐0700  (PDT)",          text:  "Destination  Moon",          tags:  [  "comic",  "adventure"  ]    }     Notes: • _id must be unique, but can be anything you’d like • Default BSON ObjectId if one is not supplied Find the document Wednesday, May 25, 2011
17. Secondary index on “author”  >  db.posts.ensureIndex({author:  1})  >  db.posts.find({author:  'Hergé'})          {  _id:  ObjectId("4c4ba5c0672c685e5e8aabf3"),          date:  "Sat  Jul  24  2010  19:47:11  GMT-­‐0700  (PDT)",          author:  "Hergé",            ...  } Add an index, find via index Wednesday, May 25, 2011
18. Examine the query plan >  db.blogs.find({author:  'Hergé'}).explain() {   "cursor"  :  "BtreeCursor  author_1",   "nscanned"  :  1,   "nscannedObjects"  :  1,   "n"  :  1,   "millis"  :  5,   "indexBounds"  :  {     "author"  :  [       [         "Hergé",         "Hergé"       ]     ]   } } Wednesday, May 25, 2011
19. Multi-key indexes //  Build  an  index  on  the  ‘tags’  array >  db.posts.ensureIndex({tags:  1}) Wednesday, May 25, 2011
20. Multi-key indexes //  Build  an  index  on  the  ‘tags’  array >  db.posts.ensureIndex({tags:  1}) //  find  posts  with  a  specific  tag //  (This  will  use  an  index!) >  db.posts.find({tags:  ‘comic’}) Wednesday, May 25, 2011
21. Query operators Conditional operators: $ne, $in, $nin, $mod, $all, $size, $exists, $type, .. $lt, $lte, $gt, $gte, $ne Update operators: $set, $inc, $push, $pop, $pull, $pushAll, $pullAll Wednesday, May 25, 2011
22. Extending the Schema        new_comment  =  {author:  “Kyle”,                                  date:  new  Date(),                                text:  “great  book”,                                votes:  5}  >  db.posts.update(                      {text:  “Destination  Moon”  },                        {  ‘$push’:  {comments:  new_comment},                          ‘$inc’:    {comments_count:  1}}) Wednesday, May 25, 2011
23.      {  _id  :  ObjectId("4c4ba5c0672c685e5e8aabf3"),          author  :  "Hergé",        date  :  "Sat  Jul  24  2010  19:47:11  GMT-­‐0700  (PDT)",          text  :  "Destination  Moon",        tags  :  [  "comic",  "adventure"  ],                comments  :  [   {     author  :  "Kyle",     date  :  "Sat  Jul  24  2010  20:51:03  GMT-­‐0700  (PDT)",     text  :  "great  book",                  votes  :  5   }        ],        comments_count:  1    } Extending the Schema Wednesday, May 25, 2011
24. //  create  index  on  nested  documents: >  db.posts.ensureIndex({"comments.author":  1}) >  db.posts.find({comments.author:”Kyle”}) The ‘dot’ operator Wednesday, May 25, 2011
25. //  create  index  on  nested  documents: >  db.posts.ensureIndex({"comments.author":  1}) >  db.posts.find({comments.author:”Kyle”}) //  create  index  comment  votes: >  db.posts.ensureIndex({comments.votes:  1}) //  find  all  posts  with  any  comments  with  more  than //  50  votes >  db.posts.ensureIndex({comments.votes:  {$gt:  50}}) The ‘dot’ operator Wednesday, May 25, 2011
26. Rich Documents Wednesday, May 25, 2011
27. Rich Documents Wednesday, May 25, 2011
28. Wednesday, May 25, 2011
29. Rich Documents Wednesday, May 25, 2011
30. Rich Documents {      _id  :  ObjectId("4c4ba5c0672c685e5e8aabf3"),                  line_items  :  [  {  sku:  ‘tt-­‐123’,                                          name:  ‘Tintin  a  la  Lune’  },                                      {  ski:  ‘tt-­‐457’,                                          name:  ‘Coke  en  stock’  }  ],                address  :  {  name:  ‘Banker’,                                street:  ‘111  Main’,                                zip:  10010  },                  payment:  {  cc:  4567,                              exp:  Date(2011,  7,  7)  },        subtotal:  2355 } Wednesday, May 25, 2011
31. Inheritance Wednesday, May 25, 2011
32. Single Table Inheritance - RDBMS shapes table id type area radius d length width 1 circle 3.14 1 2 square 4 2 3 rect 10 5 2 Wednesday, May 25, 2011
33. Single Table Inheritance - MongoDB >  db.shapes.find()  {  _id:  "1",  type:  "circle",area:  3.14,  radius:  1}  {  _id:  "2",  type:  "square",area:  4,  d:  2}  {  _id:  "3",  type:  "rect",    area:  10,  length:  5,  width:  2} Wednesday, May 25, 2011
34. Single Table Inheritance - MongoDB >  db.shapes.find()  {  _id:  "1",  type:  "circle",area:  3.14,  radius:  1}  {  _id:  "2",  type:  "square",area:  4,  d:  2}  {  _id:  "3",  type:  "rect",    area:  10,  length:  5,  width:  2} //  find  shapes  where  radius  >  0   >  db.shapes.find({radius:  {$gt:  0}}) Wednesday, May 25, 2011
35. Single Table Inheritance - MongoDB >  db.shapes.find()  {  _id:  "1",  type:  "circle",area:  3.14,  radius:  1}  {  _id:  "2",  type:  "square",area:  4,  d:  2}  {  _id:  "3",  type:  "rect",    area:  10,  length:  5,  width:  2} //  find  shapes  where  radius  >  0   >  db.shapes.find({radius:  {$gt:  0}}) //  create  sparse  index >  db.shapes.ensureIndex({radius:  1},  {sparse:  true}) Wednesday, May 25, 2011
36. One to Many One to Many relationships can specify Wednesday, May 25, 2011
37. One to Many - Embedded Array / Array Keys - $slice operator to return subset of array - some queries hard e.g find latest comments across all documents Wednesday, May 25, 2011
38. One to Many - Embedded Array / Array Keys - $slice operator to return subset of array - some queries hard e.g find latest comments across all documents - Embedded tree - Single document - Natural - Hard to query Wednesday, May 25, 2011
39. One to Many - Embedded Array / Array Keys - $slice operator to return subset of array - some queries hard e.g find latest comments across all documents - Embedded tree - Single document - Natural - Hard to query - Normalized (2 collections) - most flexible - more queries Wednesday, May 25, 2011
40. One to Many - patterns - Embedded Array / Array Keys - Embedded Array / Array Keys - Embedded tree - Normalized Wednesday, May 25, 2011
41.      {  _id  :  ObjectId("4c4ba5c0672c685e5e8aabf3"),          author  :  "Hergé",        date  :  "Sat  Jul  24  2010  19:47:11  GMT-­‐0700  (PDT)",          text  :  "Destination  Moon",        tags  :  [  "comic",  "adventure"  ],                comments  :  [      {     author  :  "Kyle",     date  :  "Sat  Jul  24  2010  20:51:03  GMT-­‐0700  (PDT)",     text  :  "great  book",                  votes  :  5      }        ],        comments_count:  1    } Wednesday, May 25, 2011
42.      {  _id  :  ObjectId("4c4ba5c0672c685e5e8aabf3"),          author  :  "Hergé",        date  :  "Sat  Jul  24  2010  19:47:11  GMT-­‐0700  (PDT)",          text  :  "Destination  Moon",        tags  :  [  "comic",  "adventure"  ]    }        {   book_id:  ObjectId("4c4ba5c0672c685e5e8aabf3"),        author  :  "Kyle",   date  :  "Sat  Jul  24  2010  20:51:03  GMT-­‐0700  (PDT)",   text  :  "great  book",          votes  :  5    }     Wednesday, May 25, 2011
43. Referencing vs. Embedding - Embed when the ‘many’ objects always appear with their parent. - Reference when you need more flexibility. Wednesday, May 25, 2011
44. Many - Many Example: - Product can be in many categories - Category can have many products Wednesday, May 25, 2011
45. products:      {  _id:  ObjectId("4c4ca23933fb5941681b912e"),          name:  "Destination  Moon",          category_ids:  [  ObjectId("4c4ca25433fb5941681b912f"),                                          ObjectId("4c4ca25433fb5941681b92af”]}     Many - Many Wednesday, May 25, 2011
46. products:      {  _id:  ObjectId("4c4ca23933fb5941681b912e"),          name:  "Destination  Moon",          category_ids:  [  ObjectId("4c4ca25433fb5941681b912f"),                                          ObjectId("4c4ca25433fb5941681b92af”]}     categories:      {  _id:  ObjectId("4c4ca25433fb5941681b912f"),            name:  "adventure",            product_ids:  [  ObjectId("4c4ca23933fb5941681b912e"),                                        ObjectId("4c4ca30433fb5941681b9130"),                                        ObjectId("4c4ca30433fb5941681b913a"]} Many - Many Wednesday, May 25, 2011
47. products:      {  _id:  ObjectId("4c4ca23933fb5941681b912e"),          name:  "Destination  Moon",          category_ids:  [  ObjectId("4c4ca25433fb5941681b912f"),                                          ObjectId("4c4ca25433fb5941681b92af”]}     categories:      {  _id:  ObjectId("4c4ca25433fb5941681b912f"),            name:  "adventure",            product_ids:  [  ObjectId("4c4ca23933fb5941681b912e"),                                        ObjectId("4c4ca30433fb5941681b9130"),                                        ObjectId("4c4ca30433fb5941681b913a"]} //  Multi-­‐key  index  on  array  fields >  db.products.ensureIndex({category_ids:  1}); >  db.categories.ensureIndex({product_ids:  1}); Many - Many Wednesday, May 25, 2011
48. products:      {  _id:  ObjectId("4c4ca23933fb5941681b912e"),          name:  "Destination  Moon",          category_ids:  [  ObjectId("4c4ca25433fb5941681b912f"),                                          ObjectId("4c4ca25433fb5941681b92af”]}     categories:      {  _id:  ObjectId("4c4ca25433fb5941681b912f"),            name:  "adventure"} Better alternative Wednesday, May 25, 2011
49. products:      {  _id:  ObjectId("4c4ca23933fb5941681b912e"),          name:  "Destination  Moon",          category_ids:  [  ObjectId("4c4ca25433fb5941681b912f"),                                          ObjectId("4c4ca25433fb5941681b92af”]}     categories:      {  _id:  ObjectId("4c4ca25433fb5941681b912f"),            name:  "adventure"} //  All  products  for  a  given  category >  db.products.find({category_ids:  ObjectId ("4c4ca25433fb5941681b912f")})     Alternative Wednesday, May 25, 2011
50. products:      {  _id:  ObjectId("4c4ca23933fb5941681b912e"),          name:  "Destination  Moon",          category_ids:  [  ObjectId("4c4ca25433fb5941681b912f"),                                          ObjectId("4c4ca25433fb5941681b92af”]}     categories:      {  _id:  ObjectId("4c4ca25433fb5941681b912f"),            name:  "adventure"} //  All  products  for  a  given  category >  db.products.find({category_ids:          ObjectId("4c4ca25433fb5941681b912f")})   //  All  categories  for  a  given  product product    =  db.products.find(_id  :  some_id) >  db.categories.find({_id  :  {$in  :  product.category_ids}})   Alternative Wednesday, May 25, 2011
51. Trees Full Tree in Document {  comments:  [          {  author:  “Kyle”,  text:  “...”,                replies:  [                                            {author:  “Fred”,  text:  “...”,                                              replies:  []}                ]}    ] } Pros: Single Document, Performance, Intuitive Cons: Hard to search, Partial Results, 4MB limit     Wednesday, May 25, 2011
52. Trees Parent Links - Each node is stored as a document - Contains the id of the parent Child Links - Each node contains the id’s of the children - Can support graphs (multiple parents / child) Wednesday, May 25, 2011
53. Array of Ancestors - Store all Ancestors of a node    {  _id:  "a"  }    {  _id:  "b",  ancestors:  [  "a"  ],  parent:  "a"  }    {  _id:  "c",  ancestors:  [  "a",  "b"  ],  parent:  "b"  }    {  _id:  "d",  ancestors:  [  "a",  "b"  ],  parent:  "b"  }    {  _id:  "e",  ancestors:  [  "a"  ],  parent:  "a"  }    {  _id:  "f",  ancestors:  [  "a",  "e"  ],  parent:  "e"  } Wednesday, May 25, 2011
54. Array of Ancestors - Store all Ancestors of a node    {  _id:  "a"  }    {  _id:  "b",  ancestors:  [  "a"  ],  parent:  "a"  }    {  _id:  "c",  ancestors:  [  "a",  "b"  ],  parent:  "b"  }    {  _id:  "d",  ancestors:  [  "a",  "b"  ],  parent:  "b"  }    {  _id:  "e",  ancestors:  [  "a"  ],  parent:  "a"  }    {  _id:  "f",  ancestors:  [  "a",  "e"  ],  parent:  "e"  } //find  all  descendants  of  b: >  db.tree2.find({ancestors:  ‘b’}) //find  all  direct  descendants  of  b: >  db.tree2.find({parent:  ‘b’}) Wednesday, May 25, 2011
55. Array of Ancestors - Store all Ancestors of a node    {  _id:  "a"  }    {  _id:  "b",  ancestors:  [  "a"  ],  parent:  "a"  }    {  _id:  "c",  ancestors:  [  "a",  "b"  ],  parent:  "b"  }    {  _id:  "d",  ancestors:  [  "a",  "b"  ],  parent:  "b"  }    {  _id:  "e",  ancestors:  [  "a"  ],  parent:  "a"  }    {  _id:  "f",  ancestors:  [  "a",  "e"  ],  parent:  "e"  } //find  all  descendants  of  b: >  db.tree2.find({ancestors:  ‘b’}) //find  all  direct  descendants  of  b: >  db.tree2.find({parent:  ‘b’}) //find  all  ancestors  of  f: >  ancestors  =  db.tree2.findOne({_id:’f’}).ancestors >  db.tree2.find({_id:  {  $in  :  ancestors}) Wednesday, May 25, 2011
56. Queue Requirements • See jobs waiting, jobs in progress • Ensure that each job is started once and only once      {  inprogress:  false,          priority:  1,          message:  “Rich  documents  FTW!”      ...      } Wednesday, May 25, 2011
57. Queue Requirements • See jobs waiting, jobs in progress • Ensure that each job is started once and only once      {  inprogress:  false,          priority:  1,          message:  “Rich  documents  FTW!”      ...      } //  find  highest  priority  job  and  mark  as  in-­‐progress job  =  db.jobs.findAndModify({                              query:    {inprogress:  false},                              sort:      {priority:  -­‐1),                                update:  {$set:  {inprogress:  true,                                                                started:  new  Date()}}})     Wednesday, May 25, 2011
58. Summary Schema design is different in MongoDB Basic data design principals stay the same Focus on how the apps manipulates data Rapidly evolve schema to meet your requirements Enjoy your new freedom, use it wisely :-) Wednesday, May 25, 2011
59. @mongodb conferences,  appearances,  and  meetups http://www.10gen.com/events http://bit.ly/mongo>   Facebook                    |                  Twitter                  |                  LinkedIn http://linkd.in/joinmongo download at mongodb.org We’re Hiring ! info@10gen.com Wednesday, May 25, 2011