Data in Motion - Streaming Static Data Efficiently in Akka Persistence

Data in Motion - Streaming Static Data Efficiently in Akka Persistence

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Intro

1 of 31

1 of 31

Intro

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Classroom Contents

Data in Motion - Streaming Static Data Efficiently in Akka Persistence

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  1. 1 Intro
  2. 2 Databases
  3. 3 Batch processing
  4. 4 Data at scale
  5. 5 Streaming static data
  6. 6 Pulling data from source
  7. 7 Inserts
  8. 8 Updates
  9. 9 Pushing data from source
  10. 10 Infinite streams of finite data source
  11. 11 Log data structure
  12. 12 Pulling data from a log
  13. 13 Akka Persistence Query Cassandra
  14. 14 Actor publisher
  15. 15 Events by persistence id
  16. 16 All persistence ids SELECT DISTINCT persistence_id, partition T
  17. 17 Events by tag
  18. 18 Akka Persistence Cassandra Replay
  19. 19 Non blocking asynchronous replay
  20. 20 Benchmarks
  21. 21 Alternative architecture
  22. 22 Event time processing
  23. 23 Ordering
  24. 24 Distributed causal stream merging
  25. 25 Exactly once delivery
  26. 26 Optimisation
  27. 27 Table and stream duality
  28. 28 Infinite streams application
  29. 29 Distributed systems
  30. 30 Challenges
  31. 31 Conclusion

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