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CHAPTER 1 WHAT DO YOU MEAN BY COST
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Execution Plan (9.2.0.6 instantiated view) ---------------------------------------------------------SELECT STATEMENT Optimizer=CHOOSE (Cost=15 Card=1 Bytes=95) HASH JOIN (Cost=15 Card=1 Bytes=95) TABLE ACCESS (FULL) OF 'T1' (Cost=2 Card=1 Bytes=69) VIEW OF 'AVG_VAL_VIEW' (Cost=12 Card=32 Bytes=832) SORT (GROUP BY) (Cost=12 Card=32 Bytes=224) TABLE ACCESS (FULL) OF 'T2' (Cost=5 Card=1024 Bytes=7168) Execution Plan (9.2.0.6 merged view) ---------------------------------------------------------SELECT STATEMENT Optimizer=CHOOSE (Cost=14 Card=23 Bytes=1909) SORT (GROUP BY) (Cost=14 Card=23 Bytes=1909) HASH JOIN (Cost=8 Card=32 Bytes=2656) TABLE ACCESS (FULL) OF 'T1' (Cost=2 Card=1 Bytes=76) TABLE ACCESS (FULL) OF 'T2' (Cost=5 Card=1024 Bytes=7168) As you can see from the execution plans, my example allows Oracle to aggregate table t2 and then join it to t1, but it also allows Oracle to join the two tables and then do the aggregation. The equivalent code for the merged view would look something like this: select t1.vc1, avg(t2.val) from t1, t2 where t1.vc2 = lpad(18,32) and t2.id_par = t1.id_par group by t1.vc1, t1.id_par ; So which of the two paths is better and which execution plan will the optimizer choose The answer to the first part of the question depends on the data distribution. If there is an efficient way to get from t1 to t2, and if there are only a couple of rows in t2 for each row in t1, and if the extra volume of data added to each row by t2 is small, then joining before aggregating will probably be the better idea. If there is no efficient way to get from t1 to t2, and there are lots of rows in t2 for each row in t1, and the extra volume of data added to each row by t2 is large, then aggregating before joining will probably be the better idea. I can tell you about the extremes that make the options possible, but I can t give you an immediate answer about all the possible variations in between. But the optimizer can make a pretty good estimate.
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CHAPTER 1 WHAT DO YOU MEAN BY COST
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The answer to the second part of the question depends on your version of Oracle. If you are still running 8i, then Oracle will aggregate the view and then perform the join without considering the alternative. If you are running 9i, Oracle will open up the view, join, and then aggregate without considering the alternative. If you are running 10g, Oracle will work out the cost of both alternatives separately, and take the cheaper one. You can see this if you rerun script view_merge_01.sql, but set event 10053 (which will be discussed in later chapters) to generate a trace file of the optimizer s cost calculations.
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As you go through the versions of Oracle, you will notice many examples of mechanisms that can be enabled or disabled at the system or session level by hidden parameters; there are also many mechanisms that can be enabled or disabled by hints at the SQL level. A common evolutionary path in the optimizer code seems to be the following: hidden by undocumented parameter and disabled in the first release; silently enabled but not costed in the second release; enabled and costed in the third release.
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In this specific example, the option to open up the aggregate view and merge it into the rest of the query depends on the hidden parameter _complex_view_merging, which defaults to false in 8i, but defaults to true from 9i onwards. You can force 8i to do complex view merging by changing this parameter although you may find some cases where you also need to use the merge() hint to make merging happen. You could also stop 9i and 10g from doing complex view merging by changing the value of this parameter, but it might be more sensible to use the no_merge() hint selectively which is what I did to get the first of the two execution plans shown previously. There are many features available to the optimizer to manipulate your query before optimizing it predicate pushing, subquery unnesting, and star transformation (perhaps the most dramatic example of query transformation) have been around for a long time. Predicate generation through transitive closure has also been around years, and predicate generation from constraints has come and gone across the versions. All these possibilities (not to mention the explicit query rewrite feature), and perhaps some others that I haven t even noticed yet, make it much harder to determine precisely what is going on with complex SQL unless you examine the details very closely ultimately wading through a 10053 trace. Fortunately, though, you won t often need to get down to this extreme, as the detail offered by explain plan is often enough to tell you that a transformation has occurred. A couple of hints, or a check of the optimizer-related parameters, will usually tell you whether a transformation is mandatory or optional, costed or uncosted, and how much control you have over it.
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