Applying Geospatial Analytics at a Massive Scale Using Kafka, Spark and Elasticsearch on DC/OS

Applying Geospatial Analytics at a Massive Scale Using Kafka, Spark and Elasticsearch on DC/OS

Linux Foundation via YouTube Direct link

Metrics

22 of 25

22 of 25

Metrics

Class Central Classrooms beta

YouTube playlists curated by Class Central.

Classroom Contents

Applying Geospatial Analytics at a Massive Scale Using Kafka, Spark and Elasticsearch on DC/OS

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Introduction
  2. 2 Traditional approach
  3. 3 DCOS
  4. 4 Trinity
  5. 5 Project Trinity
  6. 6 Examples
  7. 7 Temporal Operators
  8. 8 Aggregate Points
  9. 9 Aggregate Bins
  10. 10 Demo
  11. 11 Deployment Portability
  12. 12 Deploy across different environments
  13. 13 Installing DCOS
  14. 14 Installing Kafka
  15. 15 Installing Elasticsearch
  16. 16 Kafka Source
  17. 17 Map Interface Demo
  18. 18 Simulations
  19. 19 Challenges
  20. 20 Open Source Extensions
  21. 21 Autoscaling
  22. 22 Metrics
  23. 23 Stateful Processing
  24. 24 Batch Analysis
  25. 25 Recurring Analytics

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.