Foursquare - ML Presentation | PDF | Apache Hadoop | Data ManagementFoursquare uses big data analytics and machine learning techniques like recommendation engines and predictive modeling. They analyze billions of check-ins and other data from their 7 million…
Everybody Flumes
Everyone is integrating with ☞ Flume, the distributed, reliable, and available service for collecting, aggregating, and moving large amounts of log data. MongoDB: mongo-hadoop ☞ github.com/mongodb/mongo-hadoop Still experimental, but it has a Flume sync for storing log data into MongoDB. Cassandra: flume-cassandra-plugin☞ gitbuh.com/thobbs/flume-cassandra-plugin A new Cassandra plugin for Flume is
MongoDB Impressions
I’ve spent the past three days diving into MongoDB and jQuery. Mongo is a document database that makes it very simple to work with data–it’s basically object oriented vs SQL’s rigid table structure. Smarter people than I can tell you about its flexibility and built-in scalability. I’m attracted to it because I have a mildly complex page that crawls with SQL Server. L0ts of reasons for that–methods
MapReduce with MongoDB and Python
In this post, I'll present a demonstration of a map-reduce example with MongoDB and server side JavaScript. Based on the fact that I've been working with this technology recently, I thought it would be useful to present here a simple example of how it works and how to integrate with Python. For you, who doesn't know what is and the basics of how to use MongoDB, it is important to explain a litt
Pythonã‹ã‚‰MongoDBを使ã£ã¦ã¿ã‚‹ - stog's blog
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MongoDB Schema Design
I’ve put together a list of resources on schema design with MongoDB — you can say I’m a bit obsessed about NoSQL data modeling : Firstly, a video of Kyle Banker’s presentation discussing how the document model answers questions related to querying, access patterns, managing relationships. Graham Ashton also published his ☞ notes from Kyle’s talk. Then there’s Roger’s presentation covering MongoDB
ãƒãƒ³ã‚ºã‚ªãƒ³ã§åˆ†ã‹ã‚‹ MongoDB ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ« - babie, you're my home
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10分ã§ç†è§£ã™ã‚‹MongoDBã®ãƒ‘フォーマンス - (ﾟ∀ﾟ)o彡 sasata299's blog
2010å¹´04月25æ—¥00:16 NoSQL MySQL 10分ã§ç†è§£ã™ã‚‹MongoDBã®ãƒ‘フォーマンス MongoDBã£ã¦ã‚¹ã‚ーマレスãªDBã§ã€ã‚«ãƒ©ãƒ ãŒæ±ºã‚られãªã„よã†ãªå ´åˆã«ä½¿ã†ã¨åŠ¹æžœçš„ãªã‚“ã ã¨æ€ã†ã‚“ã§ã™ãŒã€ã€Œãã†ã„ã†ãƒ‡ãƒ¼ã‚¿ã¯ãƒãƒƒã‚·ãƒ¥ã«ã—ã¦ã€JSON å½¢å¼ã§ MySQL ã«ä¿å˜ã™ã‚Œã°è‰¯ã„ã®ã§ã¯ï¼Ÿã€ã¨ã„ã†æ„見をã„ãŸã ã„ãŸã®ã§ã€ãã®å ´åˆã¨ã®ãƒãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹æ¯”較をã—ã¦ã¿ã¾ã—ãŸã€‚ ※最åˆã¯ MySQL ã¨ã—㦠innodb ã§ã—ã‹è©•ä¾¡ã—ã¦ã„ãªã‹ã£ãŸãŸã‚ã€myisam ã®çµæžœã«ã¤ã„ã¦ã‚‚追記ã—ã¾ã—ãŸã€‚(2010/04/25追記) ベンãƒãƒžãƒ¼ã‚¯ç’°å¢ƒã®æº–å‚™ 試ã—ãŸç’°å¢ƒã¨ã—ã¦ã¯ã€MySQL 5.1.45, MongoDB 1.2.4 ã§ã™ã€‚MySQLå´ã¯ã“ã‚“ãªæ„Ÿã˜ã€‚ mysql> desc blogs; +------------+--------------+------+-----+---------
10 Gen 20100217 Hadoop Bay Area
1. What is MongoDB? What Makes Mongo Special? MapReduce MongoDB Or how I learned to stop worrying and love the database Mathias Stearn 10gen Bay Area Hadoop Meetup – February 17, 2010 Mathias Stearn MongoDB 2. What is MongoDB? What Makes Mongo Special? MapReduce The resulting [MongoDB] application has literally changed the way the pharma company conducts business. Whereas in the past, patient quer
スã‚ーマレスãªMongoDBã§ã‚«ãƒ©ãƒ を定義ã™ã‚‹ç†ç”± - (ﾟ∀ﾟ)o彡 sasata299's blog
2010å¹´04月14æ—¥22:30 NoSQL Ruby スã‚ーマレスãªMongoDBã§ã‚«ãƒ©ãƒ を定義ã™ã‚‹ç†ç”± ドã‚ュメント指å‘型データベースã§ã‚ã‚‹ MongoDB ã£ã¦ã€ã‚¹ã‚ーマレスãªã“ã¨ãŒå£²ã‚Šãªã®ã§ã™ãŒï¼ˆã‚‚ã¡ã‚んスケールã—ã‚„ã™ã„ã®ã‚‚大ãã„ã§ã™ãï¼ï¼‰å®Ÿéš›ã« MongoMapper ã‚„ Mongoid ãªã©ã®ãƒžãƒƒãƒ‘ーを利用ã—ã¦å®Ÿéš›ã®ã‚¢ãƒ—リã«çµ„ã¿è¾¼ã‚“ã§ä½¿ã†å ´åˆã¯ã‚«ãƒ©ãƒ を定義ã—ã¾ã™ï¼ˆå°‘ãªãã¨ã‚‚サンプルã¨ã‹ã¯å®šç¾©ã—ã¦ã‚‹ï¼‰ã€‚最åˆã¯ãã®æ„味ãŒã‚ˆãã‚ã‹ã‚Šã¾ã›ã‚“ã§ã—ãŸã€‚ã ã£ã¦ã€ã€ãã‡ã€‚ãã‚Œã ã¨ã‚¹ã‚ーマレスãŒåŠæ¸›ã¨ã„ã†ã‹ã€‚。確ã‹ã« migration ã¯ã—ãªãã¦ã„ã„ã§ã™ãŒã€‚ class Hoge include MongoMapper::Document key :name, String # スã‚ーマレスãªã®ã«â€¦ key :age, String end ã¾ãコードå´ãŒ 100% æ£ã—ãã¦ã€ãƒ‡ãƒ¼ã‚¿ã‚¹ãƒˆã‚¢å´ã¯
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CouchDBã¨MongoDBを比較ã—ã¦ã¿ãŸ - Masatomo Nakano Blog
ドã‚ュメント指å‘ãªKVSã£ã¦ã“ã¨ã¨ã€å—é¢ãŒä¼¼ã¦ã„ã‚‹ã¨è¨€ã†ã“ã¨ãらã„ã—ã‹æ¯”較ã™ã‚‹æ„味ãŒãªã•ãã†ãªCouchDBã¨MongoDBã ã‘ã©ã€ã“ã“2，3ヶ月ã§ä¸¡æ–¹ã‚’ãã‚Œãªã‚Šã«çªã£è¾¼ã‚“ã§è¦‹ã¦ããŸã®ã§æ¯”較ã—ã¦ã¿ãŸã€‚実装é¢ã‚„パフォーマンスã€ã¨ã„ã†ã“ã¨ã‚ˆã‚Šã¯ã©ã¡ã‚‰ã‹ã¨ã„ã†ã¨(ç§ãŒæ„Ÿã˜ã‚‹)æ€æƒ³çš„ãªã‚‚ã®ã‚„ã€ãƒ¦ãƒ¼ã‚¶å´ã‹ã‚‰ã®è¦–点ã§ã®æ¯”較。 共通ã™ã‚‹ã¨ã“ã‚ ã“ã‚Œã¯ã‚‚ã†ç°¡å˜ã«ã€ ドã‚ュメント指å‘データベース - RDBMSã®ã‚ˆã†ãªã‚«ãƒ©ãƒ ã¨è¨€ã£ãŸã‚‚ã®ã‚’æŒãŸãšã«ã‚¹ã‚ーマレスã§å¥½ããªæƒ…å ±ã‚’å…¥ã‚Œã‚‰ã‚Œã‚‹ Javascript/JSONを使用 - データ自体もJSONã¨ã„ã†Javascriptç”±æ¥ã®ãƒ•ã‚©ãƒ¼ãƒžãƒƒãƒˆã§æŒã¡(MongoDBã¯JSONã‚’å…ƒã«ã—ãŸBSONã¨ã„ã†ã‚‚ã®ã ãŒ)ã€ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã®ã‚¢ã‚¯ã‚»ã‚¹ã«ã¯Javascriptを使用ã™ã‚‹ スケールアウトã™ã‚‹ã‚ˆã†ã«è€ƒãˆã‚‰ã‚Œã¦ã„ã‚‹ NoSQLãªæµè¡Œ CouchDBã®ç‰¹å¾´ 機能をé™å®šã—ã¦ã„ã‚‹
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