Latinoware

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Latinoware

  1. 1. base de dados orientada a documentos para aplicações Web Kristina Chodorow
  2. 2. Who am I? Software Engineer at Here from New York City
  3. 3. Why Use Non-Relational DBs?
  4. 4. CAP • Consistency nome : "joe" nome : "joe" • Availability • Partitioning
  5. 5. Key-Value Stores Key Value foo bar x 123 ts 6:13:26 12/3/1945 data x9Fx44x1e Tokyo Cabinet, Dynamo, MemcacheDB
  6. 6. Key-Value Stores •Fast •Too simple •Simple
  7. 7. Column-Oriented Cassandra
  8. 8. Document-Oriented { date : Date(2007-05-07), time : { start : 9.25, end : 10.25 } sum : 0, comments : ["task 1", "run 4", "testing module"] } vs.
  9. 9. Consistency Availability Partitioning
  10. 10. Consistency Availability master Partitioning slave
  11. 11. Consistency Availability Partitioning slave
  12. 12. Consistency Availability Partitioning master
  13. 13. Consistency Availability slave Partitioning master
  14. 14. Consistency Availability Partitioning Pair Router Pair Pair ...eventual consistency
  15. 15. Introduction to MongoDB
  16. 16. A JavaScript Database $ mongodb-linux-1.0/bin/mongo MongoDB shell version: 1.0.0 url: test connecting to: test type "help" for help >
  17. 17. JSON and BSON Strict JSON types: { x : null, y : true, z : 123, w : "xyz", a : { b : 1 }, c : [1, 2, 3] } Mongo JSON adds: { ts : new Date(), query : /regex/ig, _id : new ObjectId() }
  18. 18. Collections, not Tables
  19. 19. Collections { date : Date(2007-05-07), time : { start : 9.25, end : 10.25 } sum : 0, comments : ["task 1", "run 4"] }
  20. 20. Using the Shell > db test > use xyz > db xyz > db.splorch.find() >
  21. 21. Inserting > db.foo.insert({name : "Joe", age : 34}) > db.foo.find({name : "Joe"}) { "_id" : ObjectId("2fe3e4d892aa73234c910bed"), "name" : "Joe", "age" : 34 }
  22. 22. Object Ids an autogenerated primary key "_id" : ObjectId("2fe3e4d892aa73234c910bed") 12 bytes: 2fe3e4d892aa73234c910bed |------||----||--||----| ts mac pid inc
  23. 23. Nested Objects > db.blog.insert({title : "First Post", content : "Hello, world!", author : {name : "Joe", id : 123}, comments : [] })
  24. 24. Querying posts = db.blog.find({ "author" : "Joe"}) commentsByFred = db.blog.find({ "comments.author" : "Fred"}) commentedByFred = db.blog.find({ "comments.author" : /fred/i})
  25. 25. Speaking of indexing… db.people.ensureIndex({"age" : 1}); db.people.ensureIndex({ "name" : -1, "ts" : -1, "comments.author" : 1 });
  26. 26. Updating db.blog.update({title : "First Post"}, { $push : { comments : { author : "Fred", comment : "Dumb post." } } });
  27. 27. …which gives us: > db.blog.findOne() { _id : ObjectId("4ae06192213900000000745c"), "title" : "First Post", "content" : "Hello, world!" "author" : {"name" : "Joe", "id" : 123} "comments" : [{ "author" : "Fred", "comment" : "Dumb post" }] }
  28. 28. $ instead of >, <, =, etc. $gt, $gte, $lt, $lte, $eq, $neq, $exists, $set, $mod, $where, $in, $nin, $inc $push, $pull, $pop, $pushAll, $popAll db.foo.bar.find({x : {$gt : 4}})
  29. 29. $where db.blog.findOne({$where : 'this.y == (this.x + this.z)'}); Will work: {"x" : 1, "y" : 4, "z" : 3} {"x" : "hi", "y" : "hibye", "z" : "bye"} Won’t work: {"x" : 1, "y" : 1}
  30. 30. Optimizing $where db.blogs.findOne({ name : "Sally", age : {'$gt' : 18}, $where : 'Array.sort(this.interests)[2] == "volleyball"'});
  31. 31. Cursors cursor = db.blah.find(array("foo" : "bar")) while (cursor.hasNext()) { obj = cursor.next() }
  32. 32. Applications
  33. 33. soliMAP @trackmeet FetLife Dextify2
  34. 34. Paging cursor = db.results.find() .sort({"ts" : -1}) .skip(page_num * results_per_page) .limit(results_per_page);
  35. 35. Logging • insert/update/remove is fast • Capped collections • Schemaless • $inc for counts
  36. 36. Storing Files Max: 4Mb
  37. 37. Storing Files (More than 4 Mb)
  38. 38. Storing Files J J J chunks J J J J J J _id : J files
  39. 39. Storing Files ObjectId fileId = new ObjectId(); fileObj = { _id : fileId, filename : "ggbridge.png", user : "joe", takenIn : "San Francisco" } chunkObj = { fileId : fileId, chunkNum : N data : <binary data> }
  40. 40. Aggregation group =~ GROUP BY Map/Reduce db.runCommand({ mapreduce : <collection>, map : <mapfunction>, reduce : <reducefunction> [, query : <query filter object>] [, out : <outputcollectionname>] [, keeptemp: <true|false>] [, finalize : <finalizefunction>] })
  41. 41. www.mongodb.org
  42. 42. Drivers C#, Erlang, Factor
  43. 43. Thank you! kristina@10gen.com @kchodorow @mongodb irc.freenode.net#mongodb www.mongodb.org

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