Storm at Spotify

1. March 25, 2014 Neville Li neville@spotify.com @sinisa_lyh Storm at Spotify

2. •@Spotify since 2011 •Recommendation Team •Data & Backend •Storm, Scalding, Spark, Scala… About Me

3. March 25, 2014 Spotify in numbers Started in 2006, available in 55 markets 20+ million songs, 20,000 added per day 24+ million active users, 6+ million subscribers 1.5 billion playlists !

4. Big Data @spotify 600 node cluster Every day •400GB service logs •4.5TB user data •5,000 Hadoop jobs •61TB generated

5. March 25, 2014 What is Storm? In data-layman’s terms • Real time stream processing • Like Hadoop without HDFS • Like Map/Reduce with many reducer steps • Fault tolerant & guaranteed message processing Photo © Blaine Courts http://www.flickr.com/photos/blainecourts/8417266909/

6. Storm @spotify •storm-0.8.0 •22 node cluster •15+ topologies •200,000+ tuples per second •recommendation, ads, monitoring, analytics, etc.

7. “Never Gonna Give You Up” Rick Astley Map ! First Storm Application @Spotify 7

8. RT Market Launch Stats

9. Other Uses •Trending tracks •Email campaign •App performance tracking •UX tracking

10. Anatomy of A Storm Topology From play to recommendation

11. Social Listening Take 1 •PUB/SUB •Almost real-time •Spammy •Hard to scale All characters appearing in this work are fictitious. Any resemblance to real persons, living or dead, is purely coincidental. this

12. guy

13. again!

14. Social Listening Take 2 •Hadoop daily batch •High latency •M/R aggregation •Easier to scale

15. Social Listening Revamped •Kafka → Storm → Backend •Soft real-time •Aggregate trigger bolt •Easy to scale

16. Getting Data accesspoint playlist search storage social kafka

17. What are we transferring? •TSV logs with version type (moving to Avro) •Centralized Schema Repository •Parsers in Python Java •Log parsing splitting by topic in Kafka EndSong 21 username:Str timestamp:Int trackId:Str msPlayed:Int reasonStart:Str reasonEnd:Str … ClientEvent 15 username:Str platform:Str timestamp:Int jsonData: Str …

18. March 25, 2014 Getting Data Across the Globe Photo © Riley Kaminer http://www.flickr.com/photos/rwkphotography/3282192071/ Ashburn London Stockholm San

19. Jose Hadoop Storm big

20. kafka consumer LONDON

21. March 25, 2014 Topology EndSong

22. filter kafka

23. spout metadata

24. decorator listening

25. trigger privacy

26. filterZMTP

27. publisher metadata prefsfeed SUB GET GET

28. EndSong Filter Bolt •Discard some tuples –Skipped –Too short •Keep some fields –Context –Reasons

29. Metadata Decoration Bolt •tuple.getStringByField(“trackId”)! •Append fields in output tuple •[input fields…, “artistId”, “albumId”]! •Input fields as constructor argument •Reuse! monadic!

30. Async Batch RPC metadata tuple batch callback queueupstream REQ REP emit ack bolt

31. thread schedule network

32. thread

33. Listening Trigger Bolt •Rule based triggers –High intent –Repeats •In heap LRU cache –Repeat counter –Rate limiting

34. •Similar to metadata bolt •Async lookup •Ack all, emit some •In heap LRU cache •Cache private cases only Privacy Bolt

35. ZMTP Publisher service

36. discovery boltupstream register lookup subscribe feed

37. service •[uri, username, payload] •DNS SRV for discovery •ZMQ PUB socket on bolt •1+ subscribers •1+ redundant bolts •Tools for testing

38. Lessons Learned So Far

39. March 25, 2014 Development Process One git repository One storm-shared sub project → jar → Artifactory Many storm-team/application subprojects Sampled log for local development Turnable params in config files

40. Problem Factory topology storm •lein uberjar (or mvn) •maven-shade-plugin •relocate com.google.* guava

41. 10guava

42. 14 JVM relocation! patterncom.google.common/pattern! shadedPatternshaded.com.google.common/shadedPattern! /relocation

43. March 25, 2014 Language Choices Java for boring stuff - Cassandra, memcaced, RPC, etc. ! Clojure for fun stuff - algorithm heavy ! Scala - summingbird?

44. March 25, 2014 Deployment Puppet Shared cluster right now One per team in the future YARN? ! Monitoring from service side Photo © Ian Koppenbadger http://www.flickr.com/photos/runnerone/3391661946/

45. March 25, 2014 Thank You

46. March 25, 2014 Want to join the band? Check out http://www.spotify.com/jobs or @Spotifyjobs for more information. ! Neville Li neville@spotify.com @sinisa_lyh

Storm at Spotify

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Storm at Spotify