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Introduction
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Classroom Contents
Improve Your App UX with One Model Processing Insights from Batch and Streams
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- 1 Introduction
- 2 Steps to improve user experience
- 3 History of data processing at Google
- 4 What is MapReduce
- 5 The problem with MapReduce
- 6 From Java
- 7 The problem
- 8 Artificial splitting
- 9 Un unbounded data
- 10 Delays
- 11 How to deal with delays
- 12 MillVia
- 13 Timebased windows
- 14 Session windows
- 15 Event vs processing time
- 16 Stream vs Batch
- 17 Billing Pipeline
- 18 User Experience
- 19 Abuse Detection
- 20 Historical Systems
- 21 Apache Beam
- 22 Dataflow Example
- 23 Four Questions
- 24 MapReduce
- 25 When to omit results
- 26 Create a window
- 27 Wait for results
- 28 When to trigger
- 29 Triggers in Beam
- 30 Demo
- 31 refinements
- 32 how
- 33 what just happened
- 34 cancel pipeline
- 35 run on
- 36 update pipeline
- 37 QR code
- 38 Assign color
- 39 Running the pipeline
- 40 Patch pipeline
- 41 BigQuery
- 42 Color Smash
- 43 Hit Ratio
- 44 Aggregate
- 45 Back to the slides
