How Apache Spark 3.0 and Delta Lake Enhance Data Lake Reliability

How Apache Spark 3.0 and Delta Lake Enhance Data Lake Reliability

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Data Quality Framework

37 of 39

37 of 39

Data Quality Framework

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How Apache Spark 3.0 and Delta Lake Enhance Data Lake Reliability

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  1. 1 Introduction
  2. 2 Who is Danny
  3. 3 Free Download
  4. 4 Databricks
  5. 5 Download the book
  6. 6 Adaptive Query Execution
  7. 7 Apache Spark 30
  8. 8 Performance
  9. 9 Spark Catalyst Optimizer
  10. 10 Logical Physical Planning
  11. 11 Aqe Fundamentals
  12. 12 Broadcast Hash Joins
  13. 13 Why not always broadcast join
  14. 14 Dynamically switch join strategies
  15. 15 Flipping the switch
  16. 16 Off script partitioning
  17. 17 Coalescence
  18. 18 Table Size
  19. 19 Coalescing
  20. 20 Traditional Data Warehousing Problem
  21. 21 Split Partitioning
  22. 22 QA Questions
  23. 23 Dynamic Partition Pruning
  24. 24 Dynamic Partition Pruning Before Optimization
  25. 25 Filter Scan
  26. 26 Results
  27. 27 Pseudo Rush
  28. 28 Building Ecosystem
  29. 29 Data Lake Reliability
  30. 30 Catalog API
  31. 31 SQL Statement Support
  32. 32 Partial Rights
  33. 33 Delete
  34. 34 Delete from Events
  35. 35 History Retention
  36. 36 Data Source v2 Catalog API
  37. 37 Data Quality Framework
  38. 38 Improved Performance
  39. 39 More About Delta

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