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CHAPTER 2 TABLESCANS
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The first one enables collection of cache statistics, the second one enables the use of cache statistics for optimization and since it can be set at the session level, it can t really hurt to try fiddling with it (on a test database). set autotrace traceonly explain alter session set "_optimizer_cache_stats" = true; select count(*) from t1; alter session set "_optimizer_cache_stats" = false; select count(*) from t1; set autotrace off In this particular test, the cost of the tablescan with _optimizer_cache_stats set to false was 5,030 (this was following on from the 2KB block test earlier). When I switched _optimizer_cache_stats to true, the cost dropped to 5,025. Unfortunately, I couldn t see any SQL accessing cache_stats_1$ during the optimization phase when I enabled cache stats. On the other hand, the optimizer always accessed the empty tab_stats$ and ind_stats$ tables to optimize a new statement. I m still in the dark about what this scattered collection of observations means but there seem to be at least two groups in Oracle Corporation who are working on ideas about including localized cache hit ratios into the optimizer. If or when the feature goes into production, it s sure to fix some existing problems; it s also likely to create some new ones. How, for example, do you work out what the execution plan was 24 hours after a performance problem has come and gone, when the localized cache hit ratios have changed or you re only allowed to run diagnostics on the UAT system where the localized cache hit ratios have nothing to do with the figures you get from production (You may have to license the AWR whether you like it or not.)
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Parallel query (or parallel execution as it became in 8i) is another feature of the Oracle database where a seemingly small change in the costing strategy produces a dramatic change in the cost calculations. The best place to see this is in our nice simple tablescan; and the change for this simple operation is so dramatic that you won t have any trouble believing how much difference it could make to a more complex query. Re-create the table from our first test, and run the following queries against it with autotrace enabled. Repeat the following queries in 8i, 9i, and 10g, first with system statistics disabled (script parallel.sql in the online code suite) and then using the system statistics defined earlier in the chapter (see script parallel_2.sql in the online code suite): select select select select select select select select /*+ /*+ /*+ /*+ /*+ /*+ /*+ /*+ parallel(t1,1) parallel(t1,2) parallel(t1,3) parallel(t1,4) parallel(t1,5) parallel(t1,6) parallel(t1,7) parallel(t1,8) */ */ */ */ */ */ */ */ count(*) count(*) count(*) count(*) count(*) count(*) count(*) count(*) from from from from from from from from t1; t1; t1; t1; t1; t1; t1; t1;
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CHAPTER 2 TABLESCANS
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Assuming you have parameter parallel_max_servers set to at least 8, you should get results similar to those in Table 2-5 for the cost of the query.
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Table 2-5. Effects of different degrees of parallelism
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1,518 1,518 1,518 1,518 1,518 1,518 1,518 1,518
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9i (I/O)
1,519 760 507 380 304 254 217 190
10g (I/O)
1,519 844 563 422 338 282 242 211
9i (CPU)
5,031 2,502 1,668 1,252 1,002 835 716 627
10g (CPU)
5,030 2,779 1,852 1,389 1,111 926 794 695
Ignore, for the moment, the last two columns, which are reporting the results with CPU costing enabled, and focus on the first three sets of costs. You will notice that the values for 9i and 10g don t quite agree with each other, but at least they are reasonably close to (serial cost / degree of parallelism). But the most obvious feature is that the cost in 8i never changes, no matter what the degree of parallelism. Essentially, 8i costs and optimizes your query for the best serial path, and then runs it in parallel. On the other hand, 9i assumes that it can execute a completely collision-free 100% parallel run, effectively optimizing for a set of data downsized by a factor of (degree of parallelism). Allowing for small rounding errors, the numbers from 10g suggest that it has introduced a parallel efficiency factor of 90% in the arithmetic. The actual figures suggest the following version-dependent formulae for a parallel tablescan:
8i 9i 10g Cost at degree N = serial cost Cost at degree N = ceil(serial cost / N ) Cost at degree N = ceil(serial cost / (0.9 * N))
This leaves you with three issues to consider. First, 8i is not optimizing parallel queries properly. Second, as you upgrade, costs of parallel execution can change dramatically, and you may not be able to predict the side effects. Third, the arithmetic used by 9i assumes that there will be absolutely no interference between parallel execution slaves and that s not going to be very realistic in most cases. The change between 8i and 9i is controlled by parameter optimizer_percent_parallel (hidden from 9i onwards as _optimizer_percent_parallel). In 8i, the default value was zero in other words, calculate as serial. In 9i the default value is 101 which causes Oracle to perform its calculations on the basis of 100% parallelism. You can, in theory, set the parameter to any value between 0 and 101. If you do, then the optimizer does a straight-line interpolation between the serial cost (the Resc figure in a
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