Etsy Search: How We Index and Query 26 Million One-of-a-kind Items
•
5 gostaram•1,871 visualizações
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/1rXaVvn. Aaron Gardner pulls back the covers on the Etsy Search ecosystem and how they got here -- the good, the bad, and the funky. Filmed at qconsf.com. Aaron Gardner is Engineering Director for Buyer Experience at Etsy, a marketplace where people around the world connect to buy and sell unique goods. Previous gigs include Meetup, Comcast, and some startups.
Recomendados
Recomendados
Mais conteúdo relacionado
Destaque
Destaque (12)
Semelhante a Etsy Search: How We Index and Query 26 Million One-of-a-kind Items
Semelhante a Etsy Search: How We Index and Query 26 Million One-of-a-kind Items (20)
Mais de C4Media
Mais de C4Media (20)
Último
Último (20)
Etsy Search: How We Index and Query 26 Million One-of-a-kind Items
- 1. Etsy Search Architecture How we Query & Index 26 Million One-of-a-Kind Items Aaron Gardner Engineering Director, Etsy agardner@etsy.com / @aargard QCon SF 2014 November 3rd, 2014
- 2. InfoQ.com: News & Community Site • 750,000 unique visitors/month • Published in 4 languages (English, Chinese, Japanese and Brazilian Portuguese) • Post content from our QCon conferences • News 15-20 / week • Articles 3-4 / week • Presentations (videos) 12-15 / week • Interviews 2-3 / week • Books 1 / month Watch the video with slide synchronization on InfoQ.com! http://www.infoq.com/presentations /etsy-search-ecosystem
- 3. Purpose of QCon - to empower software development by facilitating the spread of knowledge and innovation Strategy - practitioner-driven conference designed for YOU: influencers of change and innovation in your teams - speakers and topics driving the evolution and innovation - connecting and catalyzing the influencers and innovators Highlights - attended by more than 12,000 delegates since 2007 - held in 9 cities worldwide Presented at QCon San Francisco www.qconsf.com
- 6. Etsy by the numbers • 40 million members • 1+ million sellers • 26 million listed items • 25%+ of orders cross a border • $1.35 billion in sales in 2013
- 16. The Diagram
- 17. Etsy Search Architecture circa Nov 2014
- 18. –Kellan Elliott-McCrea - CTO, Etsy “The pursuit of learning is supported by simple architecture that easily adapts to new information.”
- 19. Etsy Search Architecture circa Nov 2014
- 20. Clusters & Bundles & Tiers, oh my
- 24. Life of a query https://www.etsy.com/search?q=guitar%20strap
- 25. Life of a query • A/B eligibility checks • stuff • Choose & query a search host
- 26. Pick search host randomly // COOL array_rand($servers); // LESS COOL (we used to do this) exdec(substr( md5($numServers.’+’.$query), 0,4)) % (count($servers));
- 27. Life of a query What’s this?
- 29. 1414677775480 search_args(query:guitar straps, limit:42, offset:0, sortBy:relevance, sortOrder:desc, filter:ListingSearchFilter(price_min: 0.0, price_max:0.0, ship_to:US, marketplace:null, color:null, user_id:0, tags:null, materials:null, currency_code:USD, fields:null, favorite_shop_user_ids:[], property_constraints:[], query:null, language:en-US, maturity:null, delivery_days:0, category2:null, ...
- 30. Thrift: Cross-Lang service & code- gen • Define API service & data types • Generates PHP & Java client/server code • Pros: — Fast, Easy to extend at low level • Cons — Not HTTP
- 31. Life of a query Find relevant items with standard Information Retrieval (IR) techniques
- 32. Life of a query Ranking uses scores published from Big Data ML stack
- 33. Life of a query [12345,31415926…]
- 34. Return only PKs from Search • Keep search index small, better for… • Replication • Caches • JVM GC happiness • Less data to send back to Webs • Web stack great at loading content by PKs
- 36. Query-Results Cache • key=query, val=PKs • serve-stale-while-revalidate • move cache out of JVM heap
- 39. The Banner Protocol Dance • Client picks search host • Send Thrift search query • Wait for 4-byte “OK” up to 10ms • If timeout: try another host • else “OK”: wait for real results
- 40. Sharding: Not When, but How
- 42. Patches upstream
- 43. qtime 95th: 850 —> 175ms 50th: 39 —> 20ms
- 46. Now let’s follow the data
- 47. Denorm DB = Speed & Sanity • We reindex a lot — For features, index cleanup • Tune denorm DB for speed • Don’t hurt user-serving DBs with indexers • 1 denorm store =1 dumb indexing lib • Easier to maintain, debug, & add new content
- 48. Denorm & Indexing • Sellers & buyers & crons do stuff • Web stack changes data in site DBs
- 49. Denorm & Indexing • Denorm Cron (PHP) finds IDs touched since a cursor • Spawns async PHP jobs to denorm & store blobs
- 50. Denorm & Indexing • Incremental indexers have own cron & cursor
- 51. Index Age for 8 Shards
- 52. Denorm Reuse
- 54. X
- 55. Events & Solr EFFs Solr External File Fields curlajax
- 58. 2x Everything
- 59. Magic Config File <?php /** * Which search cluster is live. * ------------------------------------------ * THIS IS A GENERATED FILE. DO NOT EDIT. * ------------------------------------------ * Generated on Sat, 01 Nov 14 06:35:03 +0000 */ $CONFIG[‘search_mtime'] = '1414823703'; $CONFIG['search_live'] = 'flop'; $CONFIG['search_dark'] = 'flip';
- 60. #1: push new code to Dark Side (Flop)
- 61. #2: push config to TEST that points to Dark Side with new code. You Test.
- 62. #3: push config to PROD that points to new code, making it The Live Side
- 63. Watch Graphs, Logs, IRC, etc.
- 64. One Last Thing
- 68. Watch the video with slide synchronization on InfoQ.com! http://www.infoq.com/presentations/etsy- search-ecosystem