Breaking Out of the Proprietary Cage - Real-time Data Warehouses in Open Source

Breaking Out of the Proprietary Cage - Real-time Data Warehouses in Open Source

Linux Foundation via YouTube Direct link

How do distributed queries work?

12 of 16

12 of 16

How do distributed queries work?

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Breaking Out of the Proprietary Cage - Real-time Data Warehouses in Open Source

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  1. 1 Intro
  2. 2 What makes analytic applications special?
  3. 3 SQL data warehouses run analytic queries
  4. 4 What ClickHouse is not
  5. 5 Merge Tree is the workhorse table engine
  6. 6 Merge Tree data layout
  7. 7 Detailed storage layout within a single part /var/lib/clickhouse/data/airline/ontime
  8. 8 Adding CPUs boosts parallelized execution
  9. 9 Effect on storage is dramatic
  10. 10 Materialized views restructure/reduce data
  11. 11 Alternative pattern: Tiered storage
  12. 12 How do distributed queries work?
  13. 13 Pattern: Kafka-based ingestion pipelines
  14. 14 Alternative ingest pattern: Kafka engine
  15. 15 Pattern: Grafana visualization
  16. 16 Pattern: Operation on Kubernetes

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