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-----------------------------------------------------------0 SELECT STATEMENT Optimizer=CHOOSE (Cost=33 Card=1 Bytes=230) 1 0 HASH JOIN (Cost=33 Card=1 Bytes=230) 2 1 TABLE ACCESS (FULL) OF 'T1' (Cost=16 Card=15 Bytes=3330) 3 1 TABLE ACCESS (FULL) OF 'T2' (Cost=16 Card=3000 Bytes=24000) Note how the join cardinality has changed from 225 to just 1 because the index has been changed. Note, even more spectacularly, that the cardinality has been changed even though the execution plan doesn t even use the index! (I have an even more extraordinary example of this type of surprise in the script delete_anomaly.sql in the online code suite, where an execution plan changes because I create a bitmap index on a column that appears in the select list of a query I m not even going to try to think about why that one happens.) The problem with the descending index is that the existence of the index has caused the optimizer to generate a surprise extra predicate, which we can see if we switch from autotrace to dbms_xplan: -------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost | -------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 230 | 33 | |* 1 | HASH JOIN | | 1 | 230 | 33 | |* 2 | TABLE ACCESS FULL | T1 | 15 | 3330 | 16 | | 3 | TABLE ACCESS FULL | T2 | 3000 | 24000 | 16 | -------------------------------------------------------------------Predicate Information (identified by operation id): --------------------------------------------------1 - access("T2"."N1"="T1"."N1" AND SYS_OP_DESCEND("T2"."N1")=SYS_OP_DESCEND("T1"."N1")) 2 - filter("T1"."N2"=45) In 9i, the optimizer includes the sys_op_descend() predicate in the selectivity calculation. In 10g, the optimizer recognizes (I assume) that the sys_op_descend() predicate is the same as t2.n1 = t1.n1, and therefore doesn t double-count the effect.

// the array of players array<Player^>^ players; // spaces is the array of board spaces. static array<int, 2>^ spaces = gcnew array<int, { { 4, 0, 0, 1, 0, 0, 0, 4, 0, 0, 0, 1, 0, 0, 4 { 0, 2, 0, 0, 0, 3, 0, 0, 0, 3, 0, 0, 0, 2, 0 { 0, 0, 2, 0, 0, 0, 1, 0, 1, 0, 0, 0, 2, 0, 0 { 1, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 1 { 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0 { 0, 3, 0, 0, 0, 3, 0, 0, 0, 3, 0, 0, 0, 3, 0 { 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0 { 4, 0, 0, 1, 0, 0, 0, 5, 0, 0, 0, 1, 0, 0, 4 { 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0 { 0, 3, 0, 0, 0, 3, 0, 0, 0, 3, 0, 0, 0, 3, 0 { 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0 { 1, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 1 { 0, 0, 2, 0, 0, 0, 1, 0, 1, 0, 0, 0, 2, 0, 0 { 0, 2, 0, 0, 0, 3, 0, 0, 0, 3, 0, 0, 0, 2, 0 { 4, 0, 0, 1, 0, 0, 0, 4, 0, 0, 0, 1, 0, 0, 4

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If you feel a little uncomfortable with the way the previous pages have been describing and calculating join cardinalities, there is another way of looking at what goes on. It doesn t change what happens, or how the results drop out; it is just a different mental image that you could use to help you understand the way the arithmetic works. Consider the query from join_card_01.sql: select t1.v1, t2.v1 from t1, t2

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where and and ; t1.filter = 1 t2.join1 = t1.join1 t2.filter = 1 -- 25 values -- 50 / 30 values -- 50 values

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