Entity Relationships in a Document Database at CouchConf Boston

Transcript

1. Entity Relationships in a Document Database MapReduce Views for SQL

   Users

2. Entity: An object de ned by its identity and a

   thread of continuity[1] 1. "Entity" Domain-driven Design Community <http://domaindrivendesign.org/node/109>.

3. Entity Relationship Model

4. Join vs. Collation

5. SELECT `publisher`.`id`, `publisher`.`name`, `book`.`title` FROM `publisher` FULL OUTER JOIN `book`

   ON `publisher`.`id` = `book`.`publisher_id` ORDER BY `publisher`.`id`, `book`.`title`; SQL Query Joining Publishers and Books

6. Joined Result Set publisher.id publisher.name book.title oreilly O'Reilly Media Building

   iPhone Apps with HTML, CSS, and JavaScript oreilly O'Reilly Media CouchDB: The Definitive Guide oreilly O'Reilly Media DocBook: The Definitive Guide oreilly O'Reilly Media RESTful Web Services

7. Joined Result Set publisher.id publisher.name book.title oreilly O'Reilly Media Building

   iPhone Apps with HTML, CSS, and JavaScript oreilly O'Reilly Media CouchDB: The Definitive Guide oreilly O'Reilly Media DocBook: The Definitive Guide oreilly O'Reilly Media RESTful Web Services Publisher (“left”)

8. Joined Result Set publisher.id publisher.name book.title oreilly O'Reilly Media Building

   iPhone Apps with HTML, CSS, and JavaScript oreilly O'Reilly Media CouchDB: The Definitive Guide oreilly O'Reilly Media DocBook: The Definitive Guide oreilly O'Reilly Media RESTful Web Services Publisher (“left”) Book “right”

9. Collated Result Set key id value ["oreilly",0] "oreilly" "O'Reilly Media"

   ["oreilly",1] "oreilly" "Building iPhone Apps with HTML, CSS, and JavaScript" ["oreilly",1] "oreilly" "CouchDB: The Definitive Guide" ["oreilly",1] "oreilly" "DocBook: The Definitive Guide" ["oreilly",1] "oreilly" "RESTful Web Services"

10. Collated Result Set key id value ["oreilly",0] "oreilly" "O'Reilly Media"

    ["oreilly",1] "oreilly" "Building iPhone Apps with HTML, CSS, and JavaScript" ["oreilly",1] "oreilly" "CouchDB: The Definitive Guide" ["oreilly",1] "oreilly" "DocBook: The Definitive Guide" ["oreilly",1] "oreilly" "RESTful Web Services" Publisher

11. Collated Result Set key id value ["oreilly",0] "oreilly" "O'Reilly Media"

    ["oreilly",1] "oreilly" "Building iPhone Apps with HTML, CSS, and JavaScript" ["oreilly",1] "oreilly" "CouchDB: The Definitive Guide" ["oreilly",1] "oreilly" "DocBook: The Definitive Guide" ["oreilly",1] "oreilly" "RESTful Web Services" Publisher Books

12. View Result Sets Made up of columns and rows Every

    row has the same three columns: • key • id • value Columns can contain a mixture of logical data types

13. One to Many Relationships

14. Embedded Entities: Nest related entities within a document

15. A single document represents the “one” entity Nested entities (JSON

    Array) represents the “many” entities Simplest way to create a one to many relationship Embedded Entities

16. Example: Publisher with Nested Books { "_id":"oreilly", "collection":"publisher", "name":"O'Reilly Media",

    "books":[ { "title":"CouchDB: The Definitive Guide" }, { "title":"RESTful Web Services" }, { "title":"DocBook: The Definitive Guide" }, { "title":"Building iPhone Apps with HTML, CSS, and JavaScript" } ] }

17. function(doc) { if ("publisher" == doc.collection) { emit([doc._id, 0], doc.name);

    for (var i in doc.books) { emit([doc._id, 1], doc.books[i].title); } } } Map Function

18. Result Set key id value ["oreilly",0] "oreilly" "O'Reilly Media" ["oreilly",1]

    "oreilly" "Building iPhone Apps with HTML, CSS, and JavaScript" ["oreilly",1] "oreilly" "CouchDB: The Definitive Guide" ["oreilly",1] "oreilly" "DocBook: The Definitive Guide" ["oreilly",1] "oreilly" "RESTful Web Services"

19. Only works if there aren’t a large number of related

    entities: • Too many nested entities can result in very large documents • Slow to transfer between client and server • Unwieldy to modify • Time-consuming to index Limitations

20. Related Documents: Reference an entity by its identi er

21. A document representing the “one” entity Separate documents for each

    “many” entity Each “many” entity references its related “one” entity by the “one” entity’s document identi er Makes for smaller documents Reduces the probability of document update con icts Related Documents

22. Example: Publisher { "_id":"oreilly", "collection":"publisher", "name":"O'Reilly Media" }

23. Example: Related Book { "_id":"9780596155896", "collection":"book", "title":"CouchDB: The Definitive Guide",

    "publisher":"oreilly" }

24. Map Function function(doc) { if ("publisher" == doc.collection) { emit([doc._id,

    0], doc.name); } if ("book" == doc.collection) { emit([doc.publisher, 1], doc.title); } }

25. Result Set key id value ["oreilly",0] "oreilly" "O'Reilly Media" ["oreilly",1]

    "9780596155896" "CouchDB: The Definitive Guide" ["oreilly",1] "9780596529260" "RESTful Web Services" ["oreilly",1] "9780596805791" "Building iPhone Apps with HTML, CSS, and JavaScript" ["oreilly",1] "9781565925809" "DocBook: The Definitive Guide"

26. When retrieving the entity on the “right” side of the

    relationship, one cannot include any data from the entity on the “left” side of the relationship without the use of an additional query Only works for one to many relationships Limitations

27. Many to Many Relationships

28. List of Keys: Reference entities by their identi ers

29. A document representing each “many” entity on the “left” side

    of the relationship Separate documents for each “many” entity on the “right” side of the relationship Each “many” entity on the “right” side of the relationship maintains a list of document identi ers for its related “many” entities on the “left” side of the relationship List of Keys

30. Books and Related Authors

31. Example: Book { "_id":"9780596805029", "collection":"book", "title":"DocBook 5: The Definitive Guide"

    }

32. Example: Book { "_id":"9781565920514", "collection":"book", "title":"Making TeX Work" }

33. Example: Book { "_id":"9781565925809", "collection":"book", "title":"DocBook: The Definitive Guide" }

34. Example: Author { "_id":"muellner", "collection":"author", "name":"Leonard Muellner", "books":[ "9781565925809" ]

    }

35. Example: Author { "_id":"walsh", "collection":"author", "name":"Norman Walsh", "books":[ "9780596805029", "9781565925809",

    "9781565920514" ] }

36. Map Function function(doc) { if ("book" == doc.collection) { emit([doc._id,

    0], doc.title); } if ("author" == doc.collection) { for (var i in doc.books) { emit([doc.books[i], 1], doc.name); } } }

37. Result Set key id value ["9780596805029",0] "9780596805029" "DocBook 5: The

    Definitive Guide" ["9780596805029",1] "walsh" "Norman Walsh" ["9781565920514",0] "9781565920514" "Making TeX Work" ["9781565920514",1] "walsh" "Norman Walsh" ["9781565925809",0] "9781565925809" "DocBook: The Definitive Guide" ["9781565925809",1] "muellner" "Leonard Muellner" ["9781565925809",1] "walsh" "Norman Walsh"

38. Authors and Related Books

39. function(doc) { if ("author" == doc.collection) { emit([doc._id, 0], doc.name);

    for (var i in doc.books) { emit([doc._id, 1], {"_id":doc.books[i]}); } } } Map Function

40. Result Set key id value ["muellner",0] "muellner" "Leonard Muellner" ["muellner",1]

    "muellner" {"_id":"9781565925809"} ["walsh",0] "walsh" "Norman Walsh" ["walsh",1] "walsh" {"_id":"9780596805029"} ["walsh",1] "walsh" {"_id":"9781565920514"} ["walsh",1] "walsh" {"_id":"9781565925809"}

41. Including Docs include_docs=true key id value doc (truncated) ["muellner",0] "muellner"

    … {"name":"Leonard Muellner"} ["muellner",1] "muellner" … {"title":"DocBook: The Definitive Guide"} ["walsh",0] "walsh" … {"name":"Norman Walsh"} ["walsh",1] "walsh" … {"title":"DocBook 5: The Definitive Guide"} ["walsh",1] "walsh" … {"title":"Making TeX Work"} ["walsh",1] "walsh" … {"title":"DocBook: The Definitive Guide"}

42. Or, we can reverse the references…

43. Example: Author { "_id":"muellner", "collection":"author", "name":"Leonard Muellner" }

44. Example: Author { "_id":"walsh", "collection":"author", "name":"Norman Walsh" }

45. Example: Book { "_id":"9780596805029", "collection":"book", "title":"DocBook 5: The Definitive Guide",

    "authors":[ "walsh" ] }

46. Example: Book { "_id":"9781565920514", "collection":"book", "title":"Making TeX Work", "authors":[ "walsh"

    ] }

47. Example: Book { "_id":"9781565925809", "collection":"book", "title":"DocBook: The Definitive Guide", "authors":[

    "muellner", "walsh" ] }

48. Map Function function(doc) { if ("author" == doc.collection) { emit([doc._id,

    0], doc.name); } if ("book" == doc.collection) { for (var i in doc.authors) { emit([doc.authors[i], 1], doc.title); } } }

49. Result Set key id value ["muellner",0] "muellner" "Leonard Muellner" ["muellner",1]

    "9781565925809" "DocBook: The Definitive Guide" ["walsh",0] "walsh" "Norman Walsh" ["walsh",1] "9780596805029" "DocBook 5: The Definitive Guide" ["walsh",1] "9781565920514" "Making TeX Work" ["walsh",1] "9781565925809" "DocBook: The Definitive Guide"

50. Queries from the “right” side of the relationship cannot include

    any data from entities on the “left” side of the relationship (without the use of include_docs) A document representing an entity with lots of relationships could become quite large Limitations

51. Relationship Documents: Create a document to represent each individual relationship

52. A document representing each “many” entity on the “left” side

    of the relationship Separate documents for each “many” entity on the “right” side of the relationship Neither the “left” nor “right” side of the relationship contain any direct references to each other For each distinct relationship, a separate document includes the document identi ers for both the “left” and “right” sides of the relationship Relationship Documents

53. Example: Book { "_id":"9780596805029", "collection":"book", "title":"DocBook 5: The Definitive Guide"

    }

54. Example: Book { "_id":"9781565920514", "collection":"book", "title":"Making TeX Work" }

55. Example: Book { "_id":"9781565925809", "collection":"book", "title":"DocBook: The Definitive Guide" }

56. Example: Author { "_id":"muellner", "collection":"author", "name":"Leonard Muellner" }

57. Example: Author { "_id":"walsh", "collection":"author", "name":"Norman Walsh" }

58. Example: Relationship Document { "_id":"44005f2c", "collection":"book-author", "book":"9780596805029", "author":"walsh" }

59. Example: Relationship Document { "_id":"44005f72", "collection":"book-author", "book":"9781565920514", "author":"walsh" }

60. Example: Relationship Document { "_id":"44006720", "collection":"book-author", "book":"9781565925809", "author":"muellner" }

61. Example: Relationship Document { "_id":"44006b0d", "collection":"book-author", "book":"9781565925809", "author":"walsh" }

62. Books and Related Authors

63. function(doc) { if ("book" == doc.collection) { emit([doc._id, 0], doc.title);

    } if ("book-author" == doc.collection) { emit([doc.book, 1], {"_id":doc.author}); } } Map Function

64. Result Set key id value ["9780596805029",0] "9780596805029" "DocBook 5: The

    Definitive Guide" ["9780596805029",1] "44005f2c" {"_id":"walsh"} ["9781565920514",0] "9781565920514" "Making TeX Work" ["9781565920514",1] "44005f72" {"_id":"walsh"} ["9781565925809",0] "9781565925809" "DocBook: The Definitive Guide" ["9781565925809",1] "44006720" {"_id":"muellner"} ["9781565925809",1] "44006b0d" {"_id":"walsh"}

65. Including Docs include_docs=true key id value doc (truncated) ["9780596805029",0] …

    … {"title":"DocBook 5: The Definitive Guide"} ["9780596805029",1] … … {"name":"Norman Walsh"} ["9781565920514",0] … … {"title":"Making TeX Work"} ["9781565920514",1] … … {"author","name":"Norman Walsh"} ["9781565925809",0] … … {"title":"DocBook: The Definitive Guide"} ["9781565925809",1] … … {"name":"Leonard Muellner"} ["9781565925809",1] … … {"name":"Norman Walsh"}

66. Authors and Related Books

67. function(doc) { if ("author" == doc.collection) { emit([doc._id, 0], doc.name);

    } if ("book-author" == doc.collection) { emit([doc.author, 1], {"_id":doc.book}); } } Map Function

68. Result Set key id value ["muellner",0] "muellner" "Leonard Muellner" ["muellner",1]

    "44006720" {"_id":"9781565925809"} ["walsh",0] "walsh" "Norman Walsh" ["walsh",1] "44005f2c" {"_id":"9780596805029"} ["walsh",1] "44005f72" {"_id":"9781565920514"} ["walsh",1] "44006b0d" {"_id":"9781565925809"}

69. Including Docs include_docs=true key id value doc (truncated) ["muellner",0] …

    … {"name":"Leonard Muellner"} ["muellner",1] … … {"title":"DocBook: The Definitive Guide"} ["walsh",0] … … {"name":"Norman Walsh"} ["walsh",1] … … {"title":"DocBook 5: The Definitive Guide"} ["walsh",1] … … {"title":"Making TeX Work"} ["walsh",1] … … {"title":"DocBook: The Definitive Guide"}

70. Queries can only contain data from the “left” or “right”

    side of the relationship (without the use of include_docs) Maintaining relationship documents may require more work Limitations

71. Final Thoughts

72. Document databases have no tables (and therefore no columns) Indexes

    (views) are queried directly, instead of being used to optimize more generalized queries Result set columns can contain a mix of logical data types No built-in concept of relationships between documents Related entities can be embedded in a document, referenced from a document, or both Document Databases Compared to Relational Databases

73. Caveats No referential integrity No atomic transactions across document boundaries

    Some patterns may involve denormalized (i.e. redundant) data Data inconsistencies are inevitable (i.e. eventual consistency) Consider the implications of replication—what may seem consistent with one database may not be consistent across nodes (e.g. referencing entities that don’t yet exist on the node)

74. Additional Techniques Use the startkey and endkey parameters to retrieve

    one entity and its related entities: startkey=["9781565925809"]&endkey=["9781565925809",{}] De ne a reduce function and use grouping levels Use UUIDs rather than natural keys for better performance Use the bulk document API when writing Relationship Documents When using the List of Keys or Relationship Documents patterns, denormalize data so that you can have data from the “right” and “left” side of the relationship within your query results

75. Cheat Sheet One to Many Many to Many <= N*

    Relations > N* Relations Embedded Entities Related Documents List of Keys Relationship Documents ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ * where N is a large number for your system

76. http://oreilly.com/catalog/9781449303129/ http://oreilly.com/catalog/9781449303433/

77. Thank You @BradleyHolt http://bradley-holt.com [email protected] Copyright © 2011-2012 Bradley Holt.

    All rights reserved.