Entity Relationships in a Document Database at ZendCon 2012

Unlike relational databases, document databases like CouchDB and MongoDB do not directly support entity relationships. This talk will explore patterns of modeling one-to-many and many-to-many entity relationships in a document database. These patterns include using an embedded JSON array, relating documents using identifiers, using a list of keys, and using relationship documents. This talk will explore how these entity relationship patterns equate to how entities are joined in a relational database. We'll take a look at the relevant differences between document databases and relational databases. For example, document databases do not have tables, each document can have its own schema, there is no built-in concept of relationships between documents, views/indexes are queried directly instead of being used to optimize more generalized queries, a column within a result set can contain a mix of logical data types, and there is typically no support for transactions across document boundaries.

Transcript

1. Entity Relationships in a Document Database MapReduce Views for SQL Users
2. You’re using a relational database, but have been relying heavily on denormalization to optimize read performance You would like to give up consistency in exchange for a high level of concurrency Your data model is a “ t” for documents (e.g. a CMS) When to Choose a Document Database
3. When Not to Choose a Document Database Your data ts better in a relational model—SQL is a powerful and mature language for working with relational data sets Consistency is critical to your application You haven’t bothered exploring scalability options for your current database
4. Incremental Map/Reduce "How fucked is my NoSQL database?" howfuckedismydatabase.com. 2009. http://howfuckedismydatabase.com/nosql/ (24 October 2012).
5. Entity Relationship Model
6. Join vs. Collation
7. 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
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" Publisher Books
10. 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
11. One to Many Relationships
12. Embedded Entities: Nest related entities within a document
13. 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
14. 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" } ] }
15. 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
16. 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"
17. 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
18. Related Documents: Reference an entity by its identi er
19. 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
20. Example: Publisher { "_id":"oreilly", "collection":"publisher", "name":"O'Reilly Media" }
21. Example: Related Book { "_id":"9780596155896", "collection":"book", "title":"CouchDB: The Definitive Guide", "publisher":"oreilly" }
22. Map Function function(doc) { if ("publisher" == doc.collection) { emit([doc._id, 0], doc.name); } if ("book" == doc.collection) { emit([doc.publisher, 1], doc.title); } }
23. 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"
24. 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
25. Many to Many Relationships
26. List of Keys: Reference entities by their identi ers
27. 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
28. Books and Related Authors
29. Example: Book { "_id":"9780596805029", "collection":"book", "title":"DocBook 5: The Definitive Guide" }
30. Example: Book { "_id":"9781565920514", "collection":"book", "title":"Making TeX Work" }
31. Example: Book { "_id":"9781565925809", "collection":"book", "title":"DocBook: The Definitive Guide" }
32. Example: Author { "_id":"muellner", "collection":"author", "name":"Leonard Muellner", "books":[ "9781565925809" ] }
33. Example: Author { "_id":"walsh", "collection":"author", "name":"Norman Walsh", "books":[ "9780596805029", "9781565925809", "9781565920514" ] }
34. 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); } } }
35. 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"
36. Authors and Related Books
37. 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
38. 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"}
39. 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"}
40. Or, we can reverse the references…
41. Example: Author { "_id":"muellner", "collection":"author", "name":"Leonard Muellner" }
42. Example: Author { "_id":"walsh", "collection":"author", "name":"Norman Walsh" }
43. Example: Book { "_id":"9780596805029", "collection":"book", "title":"DocBook 5: The Definitive Guide", "authors":[ "walsh" ] }
44. Example: Book { "_id":"9781565920514", "collection":"book", "title":"Making TeX Work", "authors":[ "walsh" ] }
45. Example: Book { "_id":"9781565925809", "collection":"book", "title":"DocBook: The Definitive Guide", "authors":[ "muellner", "walsh" ] }
46. 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); } } }
47. 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"
48. 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
49. Relationship Documents: Create a document to represent each individual relationship
50. 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
51. Example: Book { "_id":"9780596805029", "collection":"book", "title":"DocBook 5: The Definitive Guide" }
52. Example: Book { "_id":"9781565920514", "collection":"book", "title":"Making TeX Work" }
53. Example: Book { "_id":"9781565925809", "collection":"book", "title":"DocBook: The Definitive Guide" }
54. Example: Author { "_id":"muellner", "collection":"author", "name":"Leonard Muellner" }
55. Example: Author { "_id":"walsh", "collection":"author", "name":"Norman Walsh" }
56. Example: Relationship Document { "_id":"44005f2c", "collection":"book-author", "book":"9780596805029", "author":"walsh" }
57. Example: Relationship Document { "_id":"44005f72", "collection":"book-author", "book":"9781565920514", "author":"walsh" }
58. Example: Relationship Document { "_id":"44006720", "collection":"book-author", "book":"9781565925809", "author":"muellner" }
59. Example: Relationship Document { "_id":"44006b0d", "collection":"book-author", "book":"9781565925809", "author":"walsh" }
60. Books and Related Authors
61. 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
62. 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"}
63. 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"}
64. Authors and Related Books
65. 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
66. 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"}
67. 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"}
68. 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
69. Doctrine’s Object-Document Mapper (ODM)
70. Doctrine CouchDB[1] 1. http://docs.doctrine-project.org/projects/doctrine-couchdb/
71. Includes a CouchDB client library and ODM Maps documents using Doctrine’s persistence semantics Maps CouchDB views to PHP objects Document con ict resolution support Includes a write-behind feature for increased performance Features
72. De ning an Entity[1] /** @Document */ class BlogPost { /** @Id */ private $id; /** @Field(type="string") */ private $headline; /** @Field(type="string") */ private $text; /** @Field(type="datetime") */ private $publishDate; // getter/setter here } 1. http://docs.doctrine-project.org/projects/doctrine-couchdb/en/latest/reference/introduction.html#architecture
73. Persisting an Entity[1] $blogPost = new BlogPost(); $blogPost->setHeadline("Hello World!"); $blogPost->setText("This is a blog post going to be saved into CouchDB"); $blogPost->setPublishDate(new \DateTime("now")); $dm->persist($blogPost); $dm->flush(); 1. http://docs.doctrine-project.org/projects/doctrine-couchdb/en/latest/reference/introduction.html#architecture
74. Querying an Entity[1] // $dm is an instance of Doctrine\ODM\CouchDB \DocumentManager $blogPost = $dm->find("MyApp\Document\BlogPost", $theUUID); 1. http://docs.doctrine-project.org/projects/doctrine-couchdb/en/latest/reference/introduction.html#querying
75. Doctrine MongoDB ODM [1] 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/
76. Features Maps documents using Doctrine’s persistence semantics Map embedded documents Map referenced documents Uses batch inserts Performs atomic updates
77. De ning Entities[1] /** @MappedSuperclass */ abstract class BaseEmployee { /** @Id */ private $id; /** @EmbedOne(targetDocument="Address") */ private $address; // ... } 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
78. De ning Entities[1] /** @Document */ class Employee extends BaseEmployee { /** @ReferenceOne(targetDocument="Documents \Manager") */ private $manager; // ... } 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
79. De ning Entities[1] /** @Document */ class Manager extends BaseEmployee { /** @ReferenceMany (targetDocument="Documents\Project") */ private $projects = array(); // ... } 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
80. De ning Entities[1] /** @EmbeddedDocument */ class Address { /** @String */ private $address; /** @String */ private $city; /** @String */ private $state; /** @String */ private $zipcode; // ... } 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
81. De ning Entities[1] /** @Document */ class Project { /** @Id */ private $id; /** @String */ private $name; public function __construct($name) { $this->name = $name; } // ... } 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
82. Persisting Entities[1] $employee = new Employee(); $employee->setName('Employee'); $employee->setSalary(50000.00); $employee->setStarted(new \DateTime()); 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
83. Persisting Entities[1] $address = new Address(); $address->setAddress('555 Doctrine Rd.'); $address->setCity('Nashville'); $address->setState('TN'); $address->setZipcode('37209'); $employee->setAddress($address); 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
84. Persisting Entities[1] $project = new Project('New Project'); $manager = new Manager(); $manager->setName('Manager'); $manager->setSalary(100000.00); $manager->setStarted(new \DateTime()); $manager->addProject($project); 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
85. Persisting Entities[1] // $dm is an instance of Doctrine\ODM\MongoDB \DocumentManager $dm->persist($employee); $dm->persist($address); $dm->persist($project); $dm->persist($manager); $dm->flush(); 1. http://docs.doctrine-project.org/projects/doctrine-mongodb-odm/en/latest/reference/introduction.html#features-overview
86. Querying an Entity // $dm is an instance of Doctrine\ODM\MongoDB \DocumentManager $manager = $dm->find("Documents\Manager", $theID);
87. Final Thoughts
88. 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
89. 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)
90. 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
91. 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
92. http://oreilly.com/catalog/9781449303129/ http://oreilly.com/catalog/9781449303433/
93. Thank You @BradleyHolt http://bradley-holt.com https://joind.in/7040 Copyright © 2011-2012 Bradley Holt. All rights reserved.