~/talk

Synapse Q&A with PG

Talkat SQLBits 2023 · 2023-03-14..03-18· [data-engineering, databases]
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Serverless now reads Delta tables visible to serverless when Spark writes them, but pipelines cannot write Delta (only Spark engines can), and mapping data flows can read Delta but not write it. Views versus pre-transformed gold layers depends on volume, reuse and skills — large, repeated transforms push to Spark; long nested views hit resource grants and slow queries. Synapse ML adds AutoML, MLflow and Azure OpenAI hooks; self-hosted IR private routing is unsupported; dedicated pools cost-effectiveness depends on sizing — 500 DWU ≈ one node.

AI-written summary · about

  1. 0:00Introduction and team intro
  2. 1:49Synapse Espresso videos overview
  3. 3:40Lake house data transformation patterns
  4. 9:12Database designer and templates direction
  5. 11:36Databricks and Synapse integration
  6. 13:01Consistent data science experience
  7. 15:37Fast operational reporting methods
  8. 19:08Spark notebook session reuse
  9. 21:46Notebook type support plans
  10. 22:51Open table formats beyond Delta
  11. 23:42CI/CD in Azure DevOps plans
  12. 26:31Indexing in dedicated SQL pools
  13. 27:55Identity columns in Spark
  14. 28:37Reading Delta files in pipelines
  15. 29:39Consuming gold layer data
  16. 33:51Quick-fire audience questions
  17. 34:32Self-hosted IR private routing
  18. 35:37Synapse Link data lake support
  19. 36:20Dedicated SQL pool cost concerns
  20. 38:28Online scaling in Gen2
  21. 39:09KQL to SQL transition tips
  22. 40:10Spark pool Python library install
  23. 40:53On-prem GitLab server support
  24. 41:36Best data transformation tools
  25. 43:45CI/CD experience improvements
  26. 45:53UTF-8 support in dedicated pools
  27. 46:13Production workload under 500 DWUs
  28. 47:39Learning resources for beginners
  29. 49:04Closing and community thanks
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