Mongo db japan
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The document discusses MongoDB, an open-source document database. It provides an introduction to MongoDB, describing how it is implemented in C++ for performance and supports many platforms and languages. It also discusses how MongoDB is adopted by over 90,000 users per month with over 1,000 production deployments, and how it provides a non-relational data model with horizontal scalability and no complex transactions.
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![MongoDB Design Session
Blog Post Document
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?¡°roger¡±,
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?text:
?¡°Spirited
?Away¡±,
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?tags:
?[¡°Tezuka¡±,
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>db.posts.save(p)](https://image.slidesharecdn.com/mongodb-japan-101101040718-phpapp02/85/Mongo-db-japan-18-320.jpg)
![Query Posts Collection
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{ _id : ObjectId("4c4ba5c0672c685e5e8aabf3"),
author : "roger",
date : "Sat Jul 24 2010 19:47:11 GMT-0700 (PDT)",
text : "Spirited Away",
tags : [ "Tezuka", "Manga" ] }
Notes:
- _id is unique, but can be anything you¡¯d like](https://image.slidesharecdn.com/mongodb-japan-101101040718-phpapp02/85/Mongo-db-japan-19-320.jpg)
![{ _id : ObjectId("4c4ba5c0672c685e5e8aabf3"),
author : "roger",
date : "Sat Jul 24 2010 19:47:11 GMT-0700 (PDT)",
text : "Spirited Away",
tags : [ "Tezuka", "Manga" ],
comments : [
{
author : "Fred",
date : "Sat Jul 24 2010 20:51:03 GMT-0700 (PDT)",
text : "Best Movie Ever"
}
]}](https://image.slidesharecdn.com/mongodb-japan-101101040718-phpapp02/85/Mongo-db-japan-25-320.jpg)
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This document provides an overview of how to use MongoDB with CakePHP. It begins with an introduction to MongoDB, describing it as an open-source, non-relational database with many drivers including one for PHP. It then discusses how to connect to MongoDB using the PHP Mongo driver and perform basic CRUD operations. Finally, it demonstrates how to use a MongoDB datasource plugin for CakePHP, allowing models to transparently communicate with MongoDB collections using familiar CakePHP methods like find, save, and delete. Code examples are provided to show inserting, updating, and querying data in MongoDB from CakePHP.MongoDB: Optimising for Performance, Scale & Analytics
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Mongo db japan
- 2. Baseball World Series Giants lead 3-1 over Rangers
- 3. What is MongoDB? quick introduction design session deploy mongodb scaling
- 4. MongoDB adoption is very strong 90,000 Database downloads per month
- 6. Platform and Language support MongoDB is Implemented in C++ for best performance Platforms 32/64 bit ? Windows ? Linux, Mac OS-X, FreeBSD, Solaris
- 7. Platform and Language support MongoDB is Implemented in C++ for best performance Platforms 32/64 bit ? Windows ? Linux, Mac OS-X, FreeBSD, Solaris Language drivers for ? Ruby / Ruby-on-Rails ? Java / C# / JavaScript ? C / C++ ? Erlang ? Python, Perl ? others... .. and much more ! ..
- 8. non-?©\relational, ?next-?©\generation ? operational ?datastores ?and ?databases NoSQL Really Means:
- 10. RDBMS (Oracle, ?MySQL) New Gen. OLAP (vertica, ?aster, ? greenplum)
- 11. RDBMS (Oracle, ?MySQL) New Gen. OLAP (vertica, ?aster, ? greenplum) Non-relational Operational Stores (¡°NoSQL¡±)
- 12. Philosophy: ?maximize ?features ?-?©\ ?up ?to ?the ?¡°knee¡± ?in ?the ?curve, ?then ?stop depth ?of ?functionality scalability ?& ?performance ? memcached ? key/value ? RDBMS
- 13. Horizontally Scalable Architectures no ?joins no ?complex ?transactions+
- 14. New Data Models no ?joins no ?complex ?transactions+
- 15. Improved ways to develop New Data Models -?©\> ?
- 16. Terminology RDBMS MongoDB Table Collection Row(s) JSON ?Document Index Index Join Embedding ?& ?Linking Partition Shard Partition ?Key Shard ?Key
- 18. MongoDB Design Session Blog Post Document ?p ?= ?{author: ?¡°roger¡±, ? ? ? ? ? ? ? ?date: ?new ?Date(), ? ? ? ? ? ? ? ?text: ?¡°Spirited ?Away¡±, ? ? ? ? ? ? ? ?tags: ?[¡°Tezuka¡±, ?¡°Manga¡±]} >db.posts.save(p)
- 19. Query Posts Collection >db.posts.?nd() { _id : ObjectId("4c4ba5c0672c685e5e8aabf3"), author : "roger", date : "Sat Jul 24 2010 19:47:11 GMT-0700 (PDT)", text : "Spirited Away", tags : [ "Tezuka", "Manga" ] } Notes: - _id is unique, but can be anything you¡¯d like
- 20. Create index on any Field in Document // 1 means ascending, -1 means descending >db.posts.ensureIndex({author: 1}) >db.posts.?nd({author: 'roger'}) { _id : ObjectId("4c4ba5c0672c685e5e8aabf3"), author : "roger", ... } Secondary Index
- 21. Query operators Conditional operators: $ne, $in, $nin, $mod, $all, $size, $exists, $type, .. $lt, $lte, $gt, $gte, $ne, ... // ?nd posts with any tags >db.posts.?nd({tags: {$exists: true}})
- 22. Query operators Conditional operators: $ne, $in, $nin, $mod, $all, $size, $exists, $type, .. $lt, $lte, $gt, $gte, $ne, // ?nd posts with any tags >db.posts.?nd({tags: {$exists: true}}) Regular expressions: // posts where author starts with r >db.posts.?nd({author: /^r*/i })
- 23. Query operators Conditional operators: $ne, $in, $nin, $mod, $all, $size, $exists, $type, .. $lt, $lte, $gt, $gte, $ne, // ?nd posts with any tags >db.posts.?nd({tags: {$exists: true}}) Regular expressions: // posts where author starts with k >db.posts.?nd({author: /^k*/i }) Counting: // posts written by roger ? ?>db.posts.find({author: ?¡°roger¡±}).count()
- 24. Extending the Schema comment = {author: ¡°fred¡±, date: new Date(), text: ¡°Best Movie Ever¡±} update = { ¡®$push¡¯: {comments: comment}} ?>db.posts.update({_id: ?¡°...¡± ?}, ?update) Adding Comments to Blog
- 25. { _id : ObjectId("4c4ba5c0672c685e5e8aabf3"), author : "roger", date : "Sat Jul 24 2010 19:47:11 GMT-0700 (PDT)", text : "Spirited Away", tags : [ "Tezuka", "Manga" ], comments : [ { author : "Fred", date : "Sat Jul 24 2010 20:51:03 GMT-0700 (PDT)", text : "Best Movie Ever" } ]}
- 26. // create index on nested documents: >db.posts.ensureIndex({"comments.author": 1}) >db.posts.?nd({comments.author:¡±Fred¡±}) Secondary Index
- 28. Deploying MongoDB Primary Read ?/ ?Write
- 29. Deploying MongoDB Primary Secondary Read ?/ ?Write Replication
- 30. Setting Up MongoDB Primary Secondary Read ?/ ?Write Secondary ?for ?Backup Replication Replication
- 31. Setting Up MongoDB Primary Secondary Read ?/ ?Write Secondary ?for ?Backup Read Replication Replication
- 32. Setting Up MongoDB Primary Secondary Read ?/ ?Write Secondary ?for ?Backup Read Replication Replication Replicaset
- 33. Read Scalability : Replication write read ReplicaSet ?1 Primary Secondary Secondary
- 34. Write Scalability: Sharding write read ReplicaSet ?1 Primary Secondary Secondary ReplicaSet ?2 Primary Secondary Secondary ReplicaSet ?3 Primary Secondary Secondary key ?range ? 0 ?.. ?30 key ?range ? 31 ?.. ?60 key ?range ? 61 ?.. ?100
- 35. Monitoring ? We like Munin .. ? ... but other frameworks work as well ? Primary function: ? Measure stats over time ? Tells you what is going on with your system
- 36. MongoDB makes building applications easy Designed a Blog Schema Evolved the Schema Deployed MongoDB Scale MongoDB
- 37. MongoDB makes building applications easy Map / Reduce Capped Collections Tail-able Cursors Geo Indexing .. and much more ! ..
- 38. @mongodb conferences, ?appearances, ?and ?meetups http://www.10gen.com/events http://bit.ly/mongoG ? Facebook ? ? ? ? ? ? ? ? ? ?| ? ? ? ? ? ? ? ? ?Twitter ? ? ? ? ? ? ? ? ?| ? ? ? ? ? ? ? ? ?LinkedIn http://linkd.in/joinmongo download at mongodb.org We¡¯re Hiring ! roger@10gen.com