1. Schema Design with MongoDB Dwight Merriman CEO 10gen

2. What is document-oriented? JSON objects Not relational Not OODB Database schema != program “schema”

4. Choose a schema that makes queries easy makes queries fast facilitates atomicity facilitates sharding

5. Key question: embed vs. link “Contains relationship” : embed Embed = “pre-joined” Links: client/server turnarounds On a close call, embed. Use rich documents. Note the 4MB object size limit Arbitrary limit but pushes one towards good designs

11. Map-Reduce

12. { _id : … } Should be: Unique Invariant Ideally, not reused (delete; insert) ObjectID type often best for a sharded collection

13. Trees mongodb.org/display/DOCS/Trees+in+MongoDB

14. Single “Table” Inheritance Works Well > t.find() { type:’irregular-shape’, area:99 } { type:’circle’, area:3.14, radius:1 } { type:’square’, area:4, d:2 } { type:’rect’, area:8, x:2, y:4 } > t.find( { radius : { $gt : 2.0 } } ) > t.ensureIndex( { radius : 1 } ) // fine

16. Single document to fetch per page

17. One location on disk for whole tree

18. You can see full structure easily

19. Cons:

20. Hard to search

21. Hard to get back partial results

23. (3) Array of Ancestors > t = db.mytree; > t.find() { "_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" } { "_id" : "g", "ancestors" : [ "a", "b", "d" ], "parent" : "d" } > t.ensureIndex( { ancestors : 1 } ) > // find all descendents of b: > t.find( { ancestors : 'b' }) { "_id" : "c", "ancestors" : [ "a", "b" ], "parent" : "b" } { "_id" : "d", "ancestors" : [ "a", "b" ], "parent" : "b" } { "_id" : "g", "ancestors" : [ "a", "b", "d" ], "parent" : "d" } > // get all ancestors of f: > anc = db.mytree.findOne({_id:'f'}).ancestors [ "a", "e" ] > db.mytree.find( { _id : { $in : anc } } ) { "_id" : "a" } { "_id" : "e", "ancestors" : [ "a" ], "parent" : "a" }

24. Atomicity Atomicity at the document level $operators Compare and swap

25. Compare and Swap > t=db.inventory > s = t.findOne( {sku:'abc'} ) > --s.qty; > t.update({_id:s._id, qty:qty_old}, s); > db.getLastError() {"err" : , "updatedExisting" : true , "n" : 1 , "ok" : 1} // it worked

26. Compare and Swap > t=db.inventory > s = t.findOne( {sku:'abc'} ) > --s.qty; > t.update({_id:s._id, qty:qty_old}, s); > db.getLastError() {"err" : , "updatedExisting" : true , "n" : 1 , "ok" : 1} // it worked Oops?

27. Compare and Swap - Better > t=db.inventory > s = t.findOne( {sku:'abc'} ) > obj_old = Object.extend({}, s); > --s.qty; > // t.update({_id:s._id, qty:qty_old}, s); > t.update( obj_old , s); > print( db.getLastError().ok ? “worked” : “try again” );

28. Compare and Swap – versions update( { _id : myid, ver : last_ver }, { $set : { x : “abc”, y : 99 }, $inc : { ver : 1 } } )

30. Compare and Swap > t=db.inventory > s = t.findOne( {sku:'abc'} ) > --s.qty; > t.update({_id:s._id, qty:qty_old}, s); > db.getLastError() {"err" : , "updatedExisting" : true , "n" : 1 , "ok" : 1} // it worked

31. Compare and Swap > t=db.inventory > s = t.findOne( {sku:'abc'} ) > --s.qty; > t.update({_id:s._id, qty:qty_old}, s); > db.getLastError() {"err" : , "updatedExisting" : true , "n" : 1 , "ok" : 1} // it worked

32. Sharding and Schemas Shard key selection Restrictions on unique indexes Consider using may collections when that is natural 10 SN

33. Other Considerations Cappedcollections

34. Questions? Get involved with the MongoDB project! Coding, drivers, frameworks, documentation, translation, consulting, evangelism, suggestions, vote on jira…spread the word.