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NAME --------------------------db block gets from cache consistent gets from cache physical reads cache 3 rows selected. SQL>
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VALUE ----------103264732 5924585423 50572618
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The following calculation, based on the statistics I derived in the preceding code from the V$SYSSTAT view, show that the buffer cache hit ratio for my database is a little over 91 percent: 1 - (505726180)/(103264732 + 5924585494) = .916101734 As you can see from the formula for the buffer cache hit ratio, the lower the ratio of physical reads to the total logical reads, the higher the buffer cache hit ratio. You can use the V$BUFFER_POOL_STATISTICS view, which lists all buffer pools for the instance, to derive the hit ratio for the buffer cache: SQL> SELECT NAME, PHYSICAL_READS, DB_BLOCK_GETS, CONSISTENT_GETS, 1 - (PHYSICAL_READS/(DB_BLOCK_GETS + CONSISTENT_GETS)) "HitRatio" FROM V$BUFFER_POOL_STATISTICS; NAME ------DEFAULT SQL> In addition, you can use the Database Control s Memory Advisor to get advice regarding the optimal buffer cache size. The advice is presented in a graphical format, showing the trade-off between increasing the SGA and the reduction in DB time. You can use the V$DB_CACHE_ADVICE view (use V$SGA_TARGET_ADVICE to size the SGA_TARGET size) to see how much you need to increase the buffer cache to lower the physical I/O by a certain amount. Essentially, the output of the V$DB_CACHE_ADVICE view shows you how much you can increase your buffer cache memory before the gains in terms of a reduction in the amount of physical reads (estimated) are insignificant. The Memory Advisor simulates the miss rates in the buffer cache for caches of different sizes. In this sense, the Memory Advisor can keep you from throwing excess memory in a vain attempt at lowering the amount of physical reads in your system. Oracle blocks used during a full table scan involving a large table are aged out of the buffer cache faster than Oracle blocks from small-table full scans or indexed access. Oracle may decide to keep only part of the large table in the buffer cache to avoid having to flush out its entire buffer cache. Thus, your buffer cache hit ratio would be artificially low if you were using several large-table full scans. If your application involves many full table scans for some reason, increasing the buffer cache size isn t going to improve performance. Some DBAs are obsessed about achieving a high cache hit ratio, such as 99 percent or so. A high buffer cache hit ratio is no guarantee that your application response time and throughput will also be high. If you have a large number of full table scans or if your database is more of a data warehouse than an OLTP system, your buffer cache may be well below 100 percent, and that s not a bad thing. If your database consists of inefficient SQL, there will be an inordinately high number of logical reads, making the buffer cache hit ratio look good (say 99.99 percent), but this may not mean your database is performing efficiently. Please read the interesting article by Cary Millsap titled Why a 99%+ Database Buffer Cache Hit Ratio Is Not Ok (http:// www.hotsos.com/e-library/abstract.php id=6). PHYSICAL_READS DB_BLOCK_GETS CONSISTENT_GETS HitRatio --------------- -------------- ----------------- ---------50587859 103275634 5924671178 .991607779
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CHAPTER 20 PERFOR MAN CE TUNING: TUNING THE INSTA NCE
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Using Multiple Pools for the Buffer Cache
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You don t have to allocate all the buffer cache memory to a single pool. As 10 showed you, you can use three separate pools: the keep buffer pool, the recycle buffer pool, and the default buffer pool. Although you don t have to use the keep and default buffer pools, it s a good idea to configure all three pools so you can assign objects to them based on their access patterns. In general, you follow these rules of thumb when you use the multiple buffer pools: Use the recycle cache for large objects that are infrequently accessed. You don t want these objects to occupy a large amount of space unnecessarily in the default pool. Use the keep cache for small objects that you want in memory at all times. Oracle automatically uses the default pool for all objects not assigned to either the recycle or keep cache. Since version 8.1, Oracle has used a concept called touch count to measure how many times an object is accessed in the buffer cache. This algorithm of using touch counts for managing the buffer cache is somewhat different from the traditional modified LRU algorithm that Oracle used to employ for managing the cache. Each time a buffer is accessed, the touch count is incremented. A low touch count means that the block isn t being reused frequently, and therefore is wasting database buffer cache space. If you have large objects that have a low touch count but occupy a significant proportion of the buffer cache, you can consider them ideal candidates for the recycle pool. Listing 20-5 contains a query that shows you how to find out which objects have a low touch count. The TCH column in the x$bh table owned by the user SYS indicates the touch count. Listing 20-5. Determining Candidates for the Recycle Buffer Pool SQL> 2 3 4 5 6 7 8 9 10 11 12* SELECT obj object, count(1) buffers, (count(1)/totsize) * 100 percent_cache FROMx$bh, (select value totsize FROM v$parameter WHERE name ='db_block_buffers') WHERE tch=1 OR (tch = 0 and lru_flag <10) GROUP BY obj, totsize HAVING (count(1)/totsize) * 100 > 5 BUFFERS ------14288 12616 22459 PERCENT_CACHE ------------5.95333333 5.25666667 9.35791667
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