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The Dictionary Cache
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The dictionary cache, as mentioned earlier, caches data dictionary information. This cache is much smaller than the library cache, and to increase or decrease it you modify the shared pool accordingly. If your library cache is satisfactorily configured, chances are that the dictionary cache is going to be fine too. You can get an idea about the efficiency of the dictionary cache by using the following query: SQL> SELECT (sum(gets - getmisses - fixed)) / SUM(gets) 2 "data dictionary hit ratio" from v$rowcache; data dictionary hit ratio ------------------------.936781093 SQL>
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Usually, it s a good idea to shoot for a dictionary hit ratio as high as 95 to 99 percent, although Oracle itself sometimes seems to refer to a figure of 85 percent as being adequate. To increase the library cache ratio, you simply increase the shared pool size for the instance.
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Hard Parsing and Soft Parsing
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You may recall from the last chapter that all SQL code goes through the parse, optimize, and execute phases. When an application issues a statement, Oracle first sees whether a parsed version of the statement already exists. If it does, the result is a so-called soft parse and is considered a library cache hit. If, during a parse phase or the execution phase, Oracle isn t able to find the parsed version or the executable version of the code in the shared pool, it will perform a hard parse, which means that the SQL statement has to be reloaded into the shared pool and parsed completely. During a hard parse, Oracle performs syntactic and semantic checking, checks the object and system privileges, builds the optimal execution plan, and finally loads it into the library cache. A hard parse involves a lot more CPU usage and is inefficient compared to a soft parse, which depends on reusing previously parsed statements. Hard parsing involves building all parse information from scratch, and therefore it s more resource intensive. Besides involving a higher CPU usage, hard parsing involves a large number of latch gets, which may increase the response time of the query. The ideal situation is where you parse once and execute many times. Otherwise, Oracle has to perform a hard parse.
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High hard parse rates lead to severe performance problems, so it s critical that you reduce hard parse counts in your database.
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A soft parse simply involves checking the library cache for an identical statement and reusing it. The major step of optimizing the SQL statement is completely omitted during a soft parse. There s no parsing (as done during a hard parse) during a soft parse, because the new statement is hashed and its hash value is compared with the hash values of similar statements in the library cache. During a soft parse, Oracle only checks for the necessary privileges. For example, even if there s an identical statement in the library cache, your statement may not be executed if Oracle determines during the (soft) parsing stage that you don t have the necessary privileges. Oracle recommends that you treat a hard parse rate of more than 100 per second as excessive.
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Using SQL Trace and TKPROF to Examine Parse Information
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In 19, you learned how to use the SQL Trace and TKPROF utilities to trace SQL statement execution. One of the most useful pieces of information the SQL Trace utility provides concerns the hard and soft parsing information for a query. The following simple example demonstrates how you can derive the parse information for any query: 1. Enable tracing in the session by using the following command: SQL> ALTER SESSION SET SQL_TRACE=TRUE; Session altered. SQL> To make sure none of your queries were parsed before, flush the shared pool, which removes all SQL statements from the library cache: SQL> ALTER SYSTEM FLUSH SHARED_POOL; System altered. SQL>
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