Se ha denunciado esta presentación.
Utilizamos tu perfil de LinkedIn y tus datos de actividad para personalizar los anuncios y mostrarte publicidad más relevante. Puedes cambiar tus preferencias de publicidad en cualquier momento.

An Introduction To NoSQL & MongoDB

My talk on NoSQL & MongoDB from Refresh Cambridge, July 2011

  • Inicia sesión para ver los comentarios

An Introduction To NoSQL & MongoDB

  1. An Introduction ToNoSQL & MongoDB<br />Lee Theobald<br />Twitter: @Leesy<br />Email:<br />
  2. NoSQL<br />A form of database management system that is non-relational.<br />Systems are often schema less, avoid joins & are easy to scale.<br />The term NoSQL was coined in 1998 by Carlo Strozzi and then again in early 2009 with the no:sql(east) conference<br />A better term would have been “NoREL” but NoSQL caught on. Think of it more as meaning “Not Only SQL”<br />
  3. But Why Choose NoSQL?<br />Amount of data stored is on the up & up.<br />Facebook is rumoured to hold over 50TB of data in their NoSQL system for their inbox search<br />The data we store is more complex than 15 years ago.<br />Easy Distribution<br />With all this data is needs to be easy to be able to add/remove servers without any disruption of service.<br />
  4. Choose Your Flavour<br />Key-Value Store<br />Graph<br />BigTable<br />Document Store<br />
  5. Key-Value Store<br />Data is stored in (unsurpisingly) key/value pairs.<br />Designed to handle lots of data and heavy load<br />Based on a Amazon’s Dynamo Paper<br />Example: Voldermort ( - Developed by the guys at LinkedIn<br />
  6. Graph<br />Focuses on modeling data & associated connections<br />Inspired by mathematical Graph Theory.<br />Example: FlockDB ( – developed by Twitter<br />
  7. BigTable / Column Families<br />Based on the BigTable paper from Google<br />Data is grouped by columns, not rows.<br />Example: Cassandra ( – Originally developed by Facebook, now and Apache project.<br />
  8. Document Store<br />Data stored as whole documents.<br />JSON & XML are popular formats<br />Maps well to an Object Orientated programming model<br />Example: CouchDB ( or …<br />{<br /> “id”: “123”,<br /> “name”: “Oliver Clothesoff”,<br /> “dob”: {<br /> “year”: 1985,<br /> “month”: 5,<br /> “day”: 12<br /> }<br />}<br />
  9. MongoDB!<br />Short for humongous<br />Open source with development lead by 10Gen<br />Document Based<br />Schema-less<br />Highly Scalable<br />MapReduce<br />Easy Replication & Sharding<br />
  10. Familiar Structure<br />A MongoDB instance is made up of a number of databases.<br />These contain a number of collections & you can have collections nested under other collections.<br />Compare it to MySQL which has databases and tables.<br />
  11. Inserts – As Easy As Pie<br />use cookbook;<br />{<br /> “name”: “Cherry Pie”,<br /> “ingredients”: [“cherries”, “pie”],<br /> “cooking_time”: 30<br />});<br />
  12. Searching – A Piece Of Cake!<br />{<br /> “cooking_time”: { “$gte”: 10, “$lt”: 30 }<br />}<br /><br />
  13. Some More Advanced Syntax<br />Limiting Results<br />db.find().limit(10);<br />Skipping results<br />db.find().skip(5);<br />Sorting<br />db.find().sort({cooking_time: -1});<br />Cursors:<br />var cur = db.find().cursor();<br />cur.forEach( function(x) { print(tojson(x)); });<br />
  14. MapReduce<br />Great way of doing bulk manipulation or aggregation.<br />2 or 3 functions written in JavaScript that execute on the server.<br />An example use could be generating a list of top queries from some search logs.<br />
  15. Map Function<br />Takes some input of the form of key/value pairs, performs some calculations and returns 0 or more key/value pairs<br />map = function() {<br /> if (!this.query) {<br /> return;<br /> }<br /> emit (this.query, {count: 1});<br />}<br />
  16. Reduce Function<br />Takes the results from the map function, does something (normally combine the results) and produces output in key/value pairs<br />reduce = function(key, values) {<br />var count = 0;<br />values.forEach(function(v) {<br /> count += v[‘count’];<br /> }<br /> return {count: count;}<br />}<br />
  17. Replica Sets<br />Master/Slave configuration<br />If your primary server goes down, one of the secondary ones takes overautomatically<br />Extremely easy to setup<br />
  18. Auto Sharding – Horizontal Scaling<br />
  19. Other Features<br />GridFS support – Distributed file storage<br />Geospatial indexing<br />It’s constantly in development so new features are being worked on all the time!<br />
  20. Why Not Try It Yourself<br />Download it at:<br />Online tutorial at:<br />Some handy MongoDB sites:<br />MongoDB Cookbook:<br />Kyle Banker’s blog:<br />There’salso a load of handyreferencecards, stickers and otherMongoDBfreebiesupfront!<br />
  21. Thanks For Listening<br />Any questions?<br />