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Understandung Firebird optimizer, by Dmitry Yemanov (in English)
- 1. Understanding Firebird optimizer Dmitry Yemanov [email_address] Firebird Project
- 5. Mixed
- 7. Separate predicates: «base», «parent», «missing»
- 10. Choose the best index coverage for the given join order
- 11. Ensure early predicates evaluation
- 12. Decide about navigation or sorting
- 15. Not ready for «ad hoc» queries
- 23. Is a function of the estimated cardinalities
- 24. Linearly depends on the number of logical reads (page fetches)
- 26. N represents a number of the leaf pages to be scanned and thus depends on the average key length
- 27. Cost Aggregation SELECT * FROM T1 JOIN T2 ON T1.PK = T2.FK WHERE T1.VAL < 100 ORDER BY T1.RANK PLAN SORT ( JOIN ( T1 NATURAL, T2 INDEX (FK) ) ) Table T1: base cardinality = 1000 Table T2: base cardinality = 5000 Index FK: selectivity = 0.001 Final Row Set cost = 5000 cardinality = 2500 Sort cost = 5000 cardinality = 2500 Full Scan cost = 1000 cardinality = 1000 Filter cost = 1000 cardinality = 500 Index Scan cost = 7 cardinality = 5 Loop Join cost = 4000 cardinality = 2500
- 30. On index creation / activation
- 33. For large tables: number of data pages / average record length
- 35. Maintained per segment: (A), (A, B), (A, B, C)
- 36. Uniform value distribution is assumed
- 37. Stored on the index root page, visible through RDB$INDICES and RDB$INDEX_SEGMENTS
- 43. Clustering Factor Bad Clustering Factor Good Clustering Factor Index Key 1 Index Key 2 Index Key 3 Index Key 5 Index Key 4 Data Page 12 Data Page 25 Data Page 28 Data Page 57 Data Page 44 Data Page 12 Data Page 13 Data Page 14
- 46. Estimate how many indices would work best
- 47. Consider segment operations for compound indices
- 48. Special handling of different comparisons
- 49. Calculate selectivities for AND / OR operations
- 50. Thank you!