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Creating Code-39 in Java Extensions and Anomalies

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Given our understanding of the basic calculation for well-behaved queries and nice data, we can now move on to some of the many variations on a theme that can appear.
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CHAPTER 10 JOIN CARDINALITY
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One special case that we haven t examined yet is what the optimizer does about joins that are range-based joins. The answer is simple: the optimizer uses a predetermined fixed value as the selectivity of this join predicate just as it did with single tables and bind variables. For example, rerun script join_card_01.sql, but change the single join predicate from t2.join1 = t1.join1 to t2.join1 > t1.join1 The autotrace output shows that the cardinality has changed from 2,000 to 4,000. The selectivity of 1/40 (from the t2.join1 end of the join) has been replaced by a flat 5% (1/20). You might note, in passing, that the join mechanism has switched from a hash join to a merge join. Hash joins can work only for equalities; they cannot be used for range-based joins. Execution Plan (autotrace 9.2.0.6) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=68 Card=4000 Bytes=136000) 1 0 MERGE JOIN (Cost=68 Card=4000 Bytes=136000) 2 1 SORT (JOIN) (Cost=34 Card=200 Bytes=3400) 3 2 TABLE ACCESS (FULL) OF 'T2' (Cost=28 Card=200 Bytes=3400) 4 1 SORT (JOIN) (Cost=35 Card=400 Bytes=6800) 5 4 TABLE ACCESS (FULL) OF 'T1' (Cost=28 Card=400 Bytes=6800) Now change the predicate to t2.join1 between t1.join1 - 1 and t1.join1 + 1 and the join cardinality changes to 200. Remember that the optimizer treats between :bind1 and :bind2 as a pair of independent predicates and multiplies 1/20 by 1/20 to get a selectivity of 1/400 (0.025%). It has done exactly the same here. The selectivity of the join has changed from the original 1/40 to 1/400, so the cardinality has dropped by the same factor of 10 from 2,000 to 200. Execution Plan (autotrace 9.2.0.6) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=68 Card=200 Bytes=6800) 1 0 MERGE JOIN (Cost=68 Card=200 Bytes=6800) 2 1 SORT (JOIN) (Cost=34 Card=200 Bytes=3400) 3 2 TABLE ACCESS (FULL) OF 'T2' (Cost=28 Card=200 Bytes=3400) 4 1 FILTER 5 4 SORT (JOIN) 6 5 TABLE ACCESS (FULL) OF 'T1' (Cost=28 Card=400 Bytes=6800) Of course, you can t help noticing that the original join clause t2.join1 = t1.join1 with a calculated cardinality of 2,000 is going to identify a proper subset of our new range-based join t2.join1 between t1.join1 - 1 and t1.join1 + 1, which has been given a calculated cardinality of 200. Clearly there is a problem of consistency that needs to be addressed in the strategy for calculating range-based joins.
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CHAPTER 10 JOIN CARDINALITY
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I shall explain the significance of the filter operation on line 4 in 13. You might notice, though, a little reporting error that has made the sort(join) line below the filter lose its cost figure which should 34 (as in line 2) even though the merge join on line 1 does know about it.
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Not Equal
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The next special case is inequalities: t1.join1 != t2.join1. The same rule that we learned for single-table selectivity applies here the selectivity (not(t1.join1 = t2.join1)) is simply 1 selectivity (t1.join1 = t2.join1). For example, if we have the following query (based on join_card_04.sql again): select t1.v1, t2.v1 from t1, t2 where and ; t2.join1 != t1.join1 t2.join2 != t1.join2 -- (30 / 40 values for num_distinct) -- (50 / 40 values for num_distinct)
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where we used 1/40 * 1/50 in our calculations when both predicates were equalities, we would now use 39/40 * 49/50 because we now have two inequalities. There are some quirky side effects to this bugs, even. Consider a query with a disjunct (OR) between two predicates: select t1.v1, t2.v1 from t1, t2 where or ; t2.join1 = t1.join1 t2.join2 = t1.join2 -- (30 / 40 values for num_distinct) -- (50 / 40 values for num_distinct)
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All three major versions of Oracle report the cardinality of this query as 2,125,000 (see join_card_05.sql in the online code suite), but the only version where autotrace gives you a sensible clue about what is going on is 10g, where the autotrace output looks like this: Execution Plan (10.1.0.4 autotrace) ---------------------------------------------------------0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=120 Card=2125000 Bytes=72250000) 1 0 CONCATENATION 2 1 HASH JOIN (Cost=60 Card=2000000 Bytes=68000000) 3 2 TABLE ACCESS (FULL) OF 'T1' (TABLE) (Cost=28 Card=10000 Bytes=170000) 4 2 TABLE ACCESS (FULL) OF 'T2' (TABLE) (Cost=28 Card=10000 Bytes=170000) 5 1 HASH JOIN (Cost=60 Card=125000 Bytes=4250000)
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