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However, for the purposes of getting a reasonable approximation, I m happy to stick with an assumption that the optimizer is inventing something like an 80/20 split between clustered rows and scattered rows as its built-in rule for bitmap indexes. I suspect there is a formula similar to the formula for the adjusted dbf_mbrc (see 2) for modifying the cost of the bitmap calculation; but usually you only need a reasonable approximation to determine why an execution plan is being ignored or accepted, and the basic 80/20 approximation is good enough for me at present.

If we run with the 80/20 figures and live with the fact that any predictions we make are going to have small errors, what sort of precision are we likely to see with more complex queries Let s start with a simple bitmap and in script bitmap_cost_02.sql in the online code suite: select small_vc from t1 where and ; n1 = 2 n3 = 2 -- one in 20 -- one in 25

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We start with the standard rules we learned for B-trees. The index on n1 has 20 distinct values and 60 leaf blocks, n3 has 25 distinct values and 63 leaf blocks; both indexes have a blevel of 1, which can therefore be ignored. The cost of scanning the indexes to find the relevant bitmaps will be ceiling(60/20) + ceiling(63/25): a total of 6, which we then scale up to 6.6 because of the bitmap multiplier of 1.1. If the data were truly random, each of our queries would return one row in 500 (20 * 25), which means 20 rows out of the available 10,000 so the easy bit of the arithmetic tells us that we should see a plan with a cardinality of 20. Using the 80/20 approximation, 4 of those rows will be widely scattered (which in this case means four separate blocks), and 16 of them will be clustered; but we have 9 rows per block on average, which means we need an extra two blocks for those 16 rows for a total of six blocks. So we predict that the total cost will be round(6.6 + 6) = 13. Running the query with autotrace enabled we see the following: Execution Plan (9.2.0.6 version) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=13 Card=20 Bytes=340) 1 0 TABLE ACCESS (BY INDEX ROWID) OF 'T1' (Cost=13 Card=20 Bytes=340) 2 1 BITMAP CONVERSION (TO ROWIDS) 3 2 BITMAP AND 4 3 BITMAP INDEX (SINGLE VALUE) OF 'T1_I3' 5 3 BITMAP INDEX (SINGLE VALUE) OF 'T1_I1' For confirmation, we can check the 10053 trace to find the following:

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