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Using adaptive cursor sharing (acs) to produce multiple optimal plans v2
- 1. Using Adaptive Cursor Sharing (ACS) to produce multiple Optimal Plans Carlos Sierra
- 2. Carlos Sierra Senior Technical Consultant at Enkitec § SQL Tuner handyman: developer, advisor, trainer, support § IT: Enkitec (<0.2), Oracle(17), UNISYS(12), Ford(3), others(3) § Florida(17), Venezuela(3), Puerto Rico(6), Michigan(1), Mexico(x) § Tools: SQLTXPLAIN(SQLT), SQLHC, TRCANLZR(TRCA), others § Motto: Life’s Good! 2
- 3. Adaptive Cursor Sharing (ACS) § Motivation § Mechanics § Test Case § Demo § Remarks 3
- 5. SQL Processing Hard parsing is expensive! § Hard parse side effects – CPU consumption – Latch contention § Excessive hard parsing – Affects concurrency – Restricts scalability § Mitigating hard parsing – Cursor sharing 5
- 6. Implementing Cursor Sharing Replacing literals with bind variables 6
- 7. Before Bind Peeking Before 9i CBO was blind to values passed § Predicate – WHERE channel_id = :b1 § Unknowns – Is :b1 between low and high values of channel_id? – Is :b1 a popular value of channel_id? – Are there any rows with value :b1 for channel_id? § Penalty – Possible suboptimal plans 7
- 8. With Bind Peeking 9i offers a partial solution § Predicate – WHERE channel_id = :b1 § Plan is determined by peeked values – EXEC :b1 := 9; § Optimal plan for 1st execution – CBO can use low/high and histograms on channel_id § Penalty – Possible suboptimal plans for subsequent executions on skewed data 8
- 9. Real-life Problem with Bind Peeking People Soft Payroll Application § WHERE employee BETWEEN :b1 AND :b2 § Payroll for one employee – :b1 = 123456 – :b2 = 123456 § Payroll for one company – :b1 = 000001 – :b2 = 999999 § Doing payroll for an employee first then entire company 9
- 10. With Adaptive Cursor Sharing 11g improves cursor sharing § Some queries are ACS candidates § Sophisticated non-persistent mechanism § Selectivity of predicates determine plan § Multiple optimal plans for a query! – If ACS is successfully applied § Penalty – Marginal increase in CPU and memory overhead 10
- 11. ACS Mechanics
- 12. ACS high-level Overview High level overview § If SQL with binds meets some requirements – Flag cursor as bind sensitive – Start monitoring data volume manipulated by cursor § If bind sensitive and data volume manipulated by cursor varies significantly – Flag cursor as bind aware – Start generating multiple optimal plans for this query on next hard parse § If bind aware then use selectivity of predicates to decide on plan 12
- 13. Bind Sensitive Minimum requirements § SQL has explicit binds – Or literals and cursor_sharing is “force” § Predicate: column + operand + bind_variable – Equality operand “=“ and histogram on column § Ex: channel_id = :b1 – Non-equality operand (range) regardless of histogram on column § “>”, “>=“, “<“, ‘<=“, BETWEEN, LIKE 13
- 14. Bind Aware How to become bind aware? § Significant changes in data volume manipulated by cursor – A few rows versus a few thousands of rows – A few thousands of rows versus a few millions of rows § Specifying /*+ BIND_AWARE */ CBO Hint – Bypasses the monitoring phase on data volume 14
- 15. Plan Selection Based on selectivity profile of predicates § Evaluate selectivity of predicates at soft parse § Compare to a non-persistent selectivity profile § If within ranges of a known profile then select associated plan § Else hard parse – Compute and execute newly generated plan – Create selectivity profile for new plan or update profile of existing plan § If ranges on selectivity profiles overlap then merge profiles 15
- 16. V$ dynamic views for ACS ACS non-persistent performance views § V$SQL – Shareable, bind sensitive and bind aware flags § V$SQL_CS_STATISTICS – Data volume manipulated (rows processed) § V$SQL_CS_HISTOGRAM – Record keeping of data volume per execution (small, medium, large) § V$SQL_CS_SELECTIVITY – Predicates selectivity profiles 16
- 17. ACS Test Case
- 18. Our Query with Literals Guesstimate execution plan then verify it with demo 0 18
- 21. Our Query with Bind Variables How many optimal execution plans can you foresee? 21
- 22. Multiple Optimal Plans for one Query Guesstimate optimal plan (access paths) for each query Query :b1 :b2 AP1 AP2 q1 9 33 N1 N2 q2 5 32 q3 2 999 q4 9 999 q5 2 33 22
- 23. Multiple Optimal Plans for one Query Guesstimate optimal plan (access paths) for each query Query :b1 :b2 AP1 AP2 q1 9 33 N1 N2 q2 5 32 N1 N2 q3 2 999 FTS FTS q4 9 999 N1 FTS q5 2 33 FTS N2 23
- 24. Multiple Optimal Plans for one Query Execute demos 1-5 and verify access paths Query :b1 :b2 AP1 AP2 q1 9 33 N1 N2 q2 5 32 N1 N2 q3 2 999 FTS FTS q4 9 999 N1 FTS q5 2 33 FTS N2 24
- 25. Bind Sensitive: Rows Processed Monitor v$sql_cs_statistics.rows_processed § Data volume manipulated – Fuzzy representation – S: few rows – M: thousands or rows – L: millions of rows § v$sql_cs_histogram – Bucket(0): S – Bucket(1): M – Bucket(2): L Rows Processed Query :b1 :b2 Optimal q1 9 33 N1/N2 37,382 q2 5 32 N1/N2 2 q3 2 999 FTS/FTS 8,021,324 q4 9 999 N1/FTS 6,233,815 q5 2 33 FTS/N2 1,825,131 25
- 26. ACS Demo
- 27. Demo 6: When Cursor becomes Bind Aware? Obtain rows processed from demo 1-5 then guesstimate aware flag Rows Processed Query :b1 :b2 Optimal Bucket q1 9 33 N1/N2 37,382 q2 5 32 N1/N2 2 q3 2 999 FTS/FTS 8,021,324 q4 9 999 N1/FTS 6,233,815 q5 2 33 FTS/N2 Aware Child Actual 1,825,131 27
- 28. Demo 6: When Cursor becomes Bind Aware? Obtain rows processed from demo 1-5 then guesstimate aware flag Rows Processed Query :b1 :b2 Optimal Bucket q1 9 33 N1/N2 37,382 1 q2 5 32 N1/N2 2 0 q3 2 999 FTS/FTS 8,021,324 2 q4 9 999 N1/FTS 6,233,815 2 q5 2 33 FTS/N2 1,825,131 Aware Child Actual 2 28
- 29. Demo 6: When Cursor becomes Bind Aware? Obtain rows processed from demo 1-5 then guesstimate aware flag Query :b1 :b2 Optimal q1 9 33 N1/N2 q2 5 32 N1/N2 q3 2 q4 q5 Rows Processed Bucket Aware 37,382 1 N 2 0 N 999 FTS/FTS 8,021,324 2 Y 9 999 N1/FTS 6,233,815 2 Y 2 33 FTS/N2 1,825,131 2 Child Actual Y 29
- 30. Demo 6: When Cursor becomes Bind Aware? Obtain rows processed from demo 1-5 then guesstimate aware flag Query :b1 :b2 Optimal q1 9 33 N1/N2 q2 5 32 N1/N2 q3 2 q4 q5 Rows Processed Bucket Aware Child Actual 37,382 1 N 0 N1/N2 2 0 N 0 N1/N2 999 FTS/FTS 8,021,324 2 Y 1 FTS/FTS 9 999 N1/FTS 6,233,815 2 Y 2 N1/FTS 2 33 FTS/N2 1,825,131 2 Y 3 FTS/N2 30
- 31. Demo 6: When Cursor becomes Bind Aware? Obtain rows processed from demo 1-5 then guesstimate aware flag Query :b1 :b2 Optimal q1 9 33 N1/N2 q2 5 32 N1/N2 q3 2 q4 q5 Rows Processed Bucket Aware Child Actual 37,382 1 N 0 N1/N2 2 0 N 0 N1/N2 999 FTS/FTS 8,021,324 2 Y 1 FTS/FTS 9 999 N1/FTS 6,233,815 2 Y 2 N1/FTS 2 33 FTS/N2 1,825,131 2 Y 3 FTS/N2 31
- 32. Demo 7: When Cursor becomes Bind Aware? Compute bucket and guesstimate aware flag and actual plan Rows Processed Query :b1 :b2 Optimal Bucket q5 2 33 FTS/N2 1,825,131 q4 9 999 N1/FTS 6,233,815 q3 2 999 FTS/FTS q2 5 32 N1/N2 2 q1 9 33 N1/N2 Aware Child Actual 37,382 8,021,324 32
- 33. Demo 7: When Cursor becomes Bind Aware? Compute bucket and guesstimate aware flag and actual plan Rows Processed Query :b1 :b2 Optimal Bucket q5 2 33 FTS/N2 1,825,131 2 q4 9 999 N1/FTS 6,233,815 2 q3 2 999 FTS/FTS 8,021,324 2 q2 5 32 N1/N2 2 0 q1 9 33 N1/N2 37,382 Aware Child Actual 1 33
- 34. Demo 7: When Cursor becomes Bind Aware? Compute bucket and guesstimate aware flag and actual plan Query :b1 :b2 Optimal q5 2 33 FTS/N2 q4 9 999 N1/FTS q3 2 999 FTS/FTS q2 5 32 q1 9 33 Rows Processed Bucket Aware 1,825,131 2 N 6,233,815 2 N 8,021,324 2 N N1/N2 2 0 N N1/N2 37,382 1 Child Actual Y 34
- 35. Demo 7: When Cursor becomes Bind Aware? Compute bucket and guesstimate aware flag and actual plan Query :b1 :b2 Optimal q5 2 33 FTS/N2 q4 9 999 N1/FTS q3 2 999 FTS/FTS q2 5 32 q1 9 33 Rows Processed Bucket Aware Child Actual 1,825,131 2 N 0 FTS/N2 6,233,815 2 N 0 FTS/N2 8,021,324 2 N 0 FTS/N2 N1/N2 2 0 N 0 FTS/N2 N1/N2 37,382 1 Y 1 N1/N2 35
- 36. Demo 7: When Cursor becomes Bind Aware? Compute bucket and guesstimate aware flag and actual plan Query :b1 :b2 Optimal q5 2 33 FTS/N2 q4 9 999 N1/FTS q3 2 999 FTS/FTS q2 5 32 q1 9 33 Rows Processed Bucket Aware Child Actual 1,825,131 2 N 0 FTS/N2 6,233,815 2 N 0 FTS/N2 8,021,324 2 N 0 FTS/N2 N1/N2 2 0 N 0 FTS/N2 N1/N2 37,382 1 Y 1 N1/N2 36
- 37. Demo 8: When Cursor becomes Bind Aware? Guesstimate aware flag and actual plan Rows Processed Query :b1 :b2 Optimal Bucket q5 2 33 FTS/N2 1,825,131 2 q4 9 999 N1/FTS 6,233,815 2 q3 2 999 FTS/FTS 8,021,324 2 q1 9 33 N1/N2 37,382 1 q2 5 32 N1/N2 2 Aware Child Actual 0 37
- 38. Demo 8: When Cursor becomes Bind Aware? Guesstimate aware flag and actual plan Query :b1 :b2 Optimal q5 2 33 FTS/N2 q4 9 999 N1/FTS q3 2 999 FTS/FTS q1 9 33 q2 5 32 Rows Processed Bucket Aware 1,825,131 2 N 6,233,815 2 N 8,021,324 2 N N1/N2 37,382 1 N N1/N2 2 0 Child Actual N 38
- 39. Demo 8: When Cursor becomes Bind Aware? Guesstimate aware flag and actual plan Query :b1 :b2 Optimal q5 2 33 FTS/N2 q4 9 999 N1/FTS q3 2 999 FTS/FTS q1 9 33 q2 5 32 Rows Processed Bucket Aware Child Actual 1,825,131 2 N 0 FTS/N2 6,233,815 2 N 0 FTS/N2 8,021,324 2 N 0 FTS/N2 N1/N2 37,382 1 N 0 FTS/N2 N1/N2 2 0 N 0 FTS/N2 39
- 40. Demo 8: When Cursor becomes Bind Aware? Guesstimate aware flag and actual plan Query :b1 :b2 Optimal q5 2 33 FTS/N2 q4 9 999 N1/FTS q3 2 999 FTS/FTS q1 9 33 q2 5 32 Rows Processed Bucket Aware Child Actual 1,825,131 2 N 0 FTS/N2 6,233,815 2 N 0 FTS/N2 8,021,324 2 N 0 FTS/N2 N1/N2 37,382 1 N 0 FTS/N2 N1/N2 2 0 N 0 FTS/N2 40
- 41. Real-life Problem with ACS People Soft Payroll Application § WHERE employee BETWEEN :b1 AND :b2 § Payroll for one employee – :b1 = 123456 – :b2 = 123456 § Payroll for one company – :b1 = 000001 – :b2 = 999999 § Doing payroll for a few employees first then entire company 41
- 42. Closing Remarks
- 43. Understanding Selectivity Profile From demo 6 Query :b1 :b2 Child q3 2 999 1 q4 9 999 2 q5 2 33 3 43
- 44. Understanding Selectivity Profile From demo 6 Query :b1 :b2 Child q3 2 999 1 q4 9 999 2 q5 2 33 3 44
- 45. Understanding Selectivity Profile From demo 6 Query :b1 :b2 Child q3 2 999 1 q4 9 999 2 q5 2 33 3 45
- 46. Remarks on Bind Sensitivity Based on experimental observation § Monitor V$SQL_CS_STATISTICS.rows_processed – If small number of rows then § V$SQL_CS_HISTOGRAM.bucket_id(0)++ – If medium number of rows then § V$SQL_CS_HISTOGRAM.bucket_id(1)++ – If large number of rows then § V$SQL_CS_HISTOGRAM.bucket_id(2)++ 46
- 47. Remarks on Bind Aware Based on experimental observation § Some cases where cursor may become bind aware – bucket_id(0) = bucket_id(1) > 0 – bucket_id(1) = bucket_id(2) > 0 – bucket_id(0) > 0 and bucket_id(2) > 0 § Or use /*+ BIND_AWARE */ CBO Hint – What if we cannot modify code? 47
- 48. Conclusions ACS can produce multiple optimal plans for one query § ACS only applies to a subset of queries with binds § ACS requires a ramp-up process (few executions) § In some cases cursor may fail to become bind aware § To force a cursor become bind aware use CBO Hint § ACS is not persistent § ACS works well with SQL Plan Management 48
- 49. Give Away Script sqlt/utl/coe_gen_sql_patch.sql (MOS 215187.1) § Creates a SQL Patch for one SQL_ID § Turns “on” EVENT 10053 for SQL_ID § Hints on SQL Patch – GATHER_PLAN_STATISTICS – MONITOR – BIND_AWARE § Consider using and customizing this free script 49
- 50. References and Contact Info Oracle Optimizer Blog § https://blogs.oracle.com/optimizer/ – Insight into the workings of the Optimizer § carlos.sierra@enkitec.com § http://carlos-sierra.net § @csierra_usa 50