![Step 2: MapCalculate a score for each item based on page views, conversion, inventory, and merchandising inputm = function(){ [snip] if ( hourly.visits > 0 && this.quantity_sold > 0 ) { var rate = this.quantity_sold / hourly.visits; points = parseInt(100*rate); v += points; explanation += "Conversion rate of " + points + "% ”; } else if ( hourly.visits == null || hourly.visits == 0 ) { v += 500; explanation += "Product has never been seen (500 points). "; } [snip] emit( { gift_product_look_guid : this._id }, { score : v, explanation : explanation}});}](https://image.slidesharecdn.com/mongosf-giltgroupe-100430185450-phpapp01/85/Real-time-ecommerce-analytics-with-MongoDB-at-Gilt-Groupe-Michael-Bryzek-Michael-Nutt-11-320.jpg)
![Step 2: ReduceReduce is a passthroughr = function( pid , values ){ return values[0];}Map Reduce run every 15 minutes via CRON – results stored in a collection named “scores”res = db.gift_product_looks.mapReduce( m , r , { out : "scores" } );](https://image.slidesharecdn.com/mongosf-giltgroupe-100430185450-phpapp01/85/Real-time-ecommerce-analytics-with-MongoDB-at-Gilt-Groupe-Michael-Bryzek-Michael-Nutt-12-320.jpg)
Real time ecommerce analytics with MongoDB at Gilt Groupe (Michael Bryzek & Michael Nutt)
- 1. Real Time Ecommerce Analytics at Gilt GroupeMichael Bryzek, CTO & FounderMichael Nutt, Senior EngineerMongo SF - April 30, 2010We’re hiring: [email protected]/invite/michael
- 2. What is Gilt Groupe?The world’s best brands at up to 70% offSales start every day at noonSimple, luxurious online experienceRelentless focus on the customer. . . A fast growing young company
- 4. What does noon look like in Tech?
- 5. What does noon look like?
- 6. MongoDB at Gilt GroupeReal time analytics is a sweet spot for MongoDBTwo production examples we’ll share today at Gilt Groupe:Selecting product to sell based on real time dataHummingbird: Real time visualization of site traffic
- 7. Using MongoDB for Real Time AnalyticsGoal: Improve conversion of our gifts section (www.gilt.com/gifts) by ensuring good products are being promoted at the right timeChallenge: High traffic makes it hard to collect and analyze data in a scalable and fast wayApproach:Capture data in real time in MongoDBAnalyze w/ Map ReduceUpdate txn systemsRepeat
- 8. Step 1: Data CaptureJava server speaks JSON/HTTP, writes to MongoDB
- 9. Each page view receive a list of every item on the page and its position via AJAX
- 10. Purchase data sent by background job post purchaseStep 1: Data CaptureStoring Data in Java_db = new Mongo().getDB("gifts");_listing_visits = _db.getCollection("listing_visits");--------------------------------------------------BasicDBObject record = new BasicDBObject();record.put("gift_product_look_guid", de.giftProductLookGuid);record.put("product_look_guid", de.productLookGuid);record.put("sale_id", info.saleId);record.put("user_guid", info.userGuid);record.put("subsite_id", info.subsiteId);record.put("created_at", info.createdAt);record.put("position", position);_listing_visits.save(record);
- 11. Step 2: MapCalculate a score for each item based on page views, conversion, inventory, and merchandising inputm = function(){ [snip] if ( hourly.visits > 0 && this.quantity_sold > 0 ) { var rate = this.quantity_sold / hourly.visits; points = parseInt(100*rate); v += points; explanation += "Conversion rate of " + points + "% ”; } else if ( hourly.visits == null || hourly.visits == 0 ) { v += 500; explanation += "Product has never been seen (500 points). "; } [snip] emit( { gift_product_look_guid : this._id }, { score : v, explanation : explanation}});}
- 12. Step 2: ReduceReduce is a passthroughr = function( pid , values ){ return values[0];}Map Reduce run every 15 minutes via CRON – results stored in a collection named “scores”res = db.gift_product_looks.mapReduce( m , r , { out : "scores" } );
- 13. Step 3: Update Transactional SystemsMongo + server run on ec2
- 14. Send “scores” collection back to our primary data center, storing latest scores in our primary relational database
- 15. Gift items are always sorted by score – transactional system only needed an “order by score desc” clauseQuestions before we move on to Hummingbird?
- 19. Node.jsAsynchronous, evented web frameworkhttp://nodejs.org
- 20. var mongo = require(’lib/mongodb’);var db = new mongo.Db('hummingbird', new mongo.Server('localhost', 27017, {}), {});db.createCollection('visits', function(err, collection) { db.collection('visits', function(err, collection) { collection.insert(env); });});
- 21. DEMO