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Physical Join Operators

Physical Join Operators. 2010. Ami Levin. Session Goals. SQL Server implements three different physical operators to perform joins. In this session we will see how each of these three operators work, its advantages and challenges.

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Physical Join Operators

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  1. Physical Join Operators 2010 Ami Levin

  2. Session Goals • SQL Server implements three different physical operators to perform joins. In this session we will see how each of these three operators work, its advantages and challenges. • We will try to understand the logic behind the optimizer’s decisions on which operator to use for various joins using (semi) real life examples and see examples about how to avoid common pitfalls.

  3. Equi-Inner-Join SELECTX,Y,Z… FROM[Table1] INNER JOIN [Table2] ON [Table1].[C1] = [Table2].[C1] AND [Table1].[C2] = [Table2].[C2] WHERE…

  4. Next Time • Outer Joins • Non Equi-Joins • Logical Processing Order • NULL Value Issues • Join Parallelism • Partitioned Joins

  5. What Is a Join

  6. Nested Loops Fetch next row from blue input Start No More Rows? Quit True False Find matching rows in red input

  7. Considerations • “Outer Loop” = The Number of Iterations • At Least One Small Input Preferable • “Inner Operation” = Work for Each Iteration • Index/Table Scan • Index Seek with Lookup • Covering Index Seek

  8. Foreign Key Joins • Joins Parents and Childs • Most Common Relationship is One-to-Many • Parent ISIndexed Primary Key or Unique • Indexing Foreign Keys Enables Efficient Use of Nested Loops

  9. Nested Loops DEMO

  10. Fetch next row from blue input Start Merge No More Rows? Quit True False Fetch next row from red input Rows Match? True False

  11. Considerations • Input Must be Pre-Sorted • By All Join Expression(s) • Pre-Sorted in Plan, not necessarily in DB… • Immediate& Sorted Match Outputs • FASTFIRSTROW Hint • Very Efficient and Simple Operator

  12. Merge DEMO

  13. Fetch next row from blue input Fetch next row from red input Start No more rows? No more rows? True True False Quit False Hash- Match Apply “hash” function Apply “hash” function Place row in “hash” bucket Probe bucket for matching rows

  14. Considerations • Hash Function Selection • CPU, Memory and potential I/O Overhead • No Sorting Whatsoever • Probing Costs Not Revealed • May Indicate Sub-Optimal Indexing

  15. Hash Match DEMO

  16. Conclusion

  17. For More Information • Books On Line • Microsoft White Papers • “SQL Server 2008 Internals” • Kalen Delaney, Kimberly L.Tripp and more… • Craig Freedman’s MSDN Blog • http://blogs.msdn.com/craigfr/about.aspx

  18. Physical Join Operators Q&A?

  19. Thank You

  20. P/X001 Designing High Scale OLTP systems Thomas Kejser P/L001 TSQL Techniques – Why and how to tune a routine Dave Ballantyne P/L002 Implementing Common Business Calculations in DAX Chris Webb P/L005 Consolidating data collection with SQLDIAG and analysing it all with SQLNexusChristian Bolton P/T007 Introduction to SQL Modelling Services Robert Hogg Coming up… • #SQLBITS

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