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Building Real-Time Visualizations at Scale Mike Barry @msb5014 - PowerPoint PPT Presentation

Building Real-Time Visualizations at Scale Mike Barry @msb5014 Kevin Robinson @krob Hello! Hello! analytics.twitter.com Hello! Answers Building Real-time Visualizations Real-time Actionable User-focused Analytics at Twitter


  1. Building Real-Time Visualizations at Scale Mike Barry @msb5014 Kevin Robinson @krob

  2. Hello!

  3. Hello!

  4. analytics.twitter.com

  5. Hello!

  6. Answers

  7. Building Real-time Visualizations Real-time Actionable User-focused

  8. Analytics at Twitter Architecture Higher-level abstractions Human flexibility

  9. Realtime Realtime queue Job Dataset streaming events Query Mediator Batch Historic HDFS Job Dataset Typical Analytics Pipeline

  10. Do more work on write so that reads are fast

  11. How many impressions from X to Y?

  12. How many impressions from X to Y? from X to Y minute

  13. How many impressions from X to Y? from X to Y minute hour day

  14. Abstractions Scalding Storm Summingbird Tsar Heron

  15. Scaling up

  16. Communicate Fearlessly to Build Trust

  17. Human Flexibility Globally-available data + Flexible individuals + Hack weeks = innovation

  18. Analytics at Twitter Architecture Higher-level abstractions Human flexibility

  19. Initial assumptions Shortest path to usefulness Real users and data change everything

  20. Initial assumptions Shortest path to usefulness Real users and data change everything

  21. No data! Existing data sources? nope Predictable usage or distributions? nope hmm...

  22. Assumptions about data

  23. Assumptions about data

  24. How can we make them explicit?

  25. How can we make them explicit?

  26. Excel prototype

  27. Excel prototype

  28. Excel prototype

  29. Initial assumptions about data Shortest path to usefulness Real users and data change everything

  30. Initial assumptions about data Shortest path to usefulness Real users and data change everything

  31. Let’s build!

  32. Let’s build!

  33. Let’s build!

  34. Real-time computation

  35. Real-time computation

  36. Let’s build: Prototype feature

  37. Prototype feature

  38. Prototype feature

  39. Prototype feature

  40. Prototype feature

  41. Prototype feature

  42. Production feature

  43. More fault-tolerance

  44. More fault-tolerance Local Cascading jobs Subsets or samples of real data In-memory tests

  45. More fault-tolerance Local Cascading jobs Subsets or samples of real data In-memory tests More data only a command line away

  46. Ready for real users!

  47. Initial assumptions about data Shortest path to usefulness Real users and data change everything

  48. Initial assumptions about data Shortest path to usefulness Real users and data change everything

  49. High-touch feedback

  50. Exploring the data

  51. Real-time prototyping

  52. Real-time prototyping kafka logs gif

  53. Real-time prototyping

  54. Real-time prototyping

  55. Real-time prototyping sublime samples

  56. Real-time prototyping sublime samples

  57. Real-time prototyping sublime samples

  58. Real-time prototyping sublime samples

  59. Real-time prototyping sublime samples

  60. What’s the TL;DR?

  61. Answers Events

  62. Opinionated

  63. Opinionated

  64. TL;DR

  65. TL;DR

  66. TL;DR

  67. Initial assumptions about data Shortest path to usefulness Real users and data change everything

  68. Conclusion Lambda architecture Opening everything enables re-use Higher-level abstractions Full-stack iteration

  69. Thanks!

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