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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.

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Struct object represents in a uniform fashion, in Java, database objects belonging to any given database object type It represents the database object as an array of attributes, which are stored in an array of Java objects (ie, Object[]) For example, using this technique, a database object of type person and a database object of type address can both be mapped to a single javasqlStruct object and initialized with an appropriate set of attributes In 10, we will discuss how to materialize objects as strongly typed objects in Java A strongly typed object refers to an object belonging to a custom Java class specifically created to represent a given database object type in Java For example, when we use strongly typed Java objects, a database object of type person object would map to a Java object of a custom.

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.

Listing 5-11. NTP Access Control Configuration on a Cisco Router Router#configure terminal Enter configuration commands, one per line. End with CNTL/Z. Router(config)#interface Serial0 Router(config-if)#ntp disable Router(config-if)#exit Router(config)#access-list 199 deny udp any eq 123 any eq 123 Router(config)#access-list 199 permit ip any any Router(config)#interface Serial1 Router(config-if)#ip access-group 199 in Router(config-if)#exit Router(config)#access-list 55 permit host 192.168.1.51 Router(config)#access-list 55 permit host 192.168.10.151 Router(config)#access-list 55 permit host 192.168.100.251 Router(config)#access-list 77 permit 172.16.0.0 0.0.255.255 Router(config)#access-list 77 permit 172.18.1.0 0.255.255.255 Router(config)#access-list 77 permit 192.168.3.0 0.255.255.255

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 9999 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:// wwwhotsoscom/e-library/abstractphp id=6) PHYSICAL_READS DB_BLOCK_GETS CONSISTENT_GETS HitRatio --------------- -------------- ----------------- ---------50587859 103275634 5924671178 991607779.

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