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Each block in a segment has a block header. Part of this block header is a transaction table. Entries will be made in the transaction table to describe which transactions have what rows/elements on the block locked. The initial size of this transaction table is specified by the INITRANS setting for the object. For tables, this defaults to 2 (indexes default to 2 as well). This transaction table will grow dynamically as needed up to MAXTRANS entries in size (given sufficient free space on the block, that is). Each allocated transaction entry consumes 23 to 24 bytes of storage in the block header. Note that as of Oracle 10g, MAXTRANS is ignored all segments have a MAXTRANS of 255.

The shared pool is a very important part of the Oracle SGA, and sizing it appropriately for your instance will help avoid several types of Oracle instance bottlenecks. Unlike the database buffer cache, which holds actual data blocks, the shared pool holds executable PL/SQL code and SQL statements, as well as information regarding the data dictionary tables. The data dictionary is a set of key tables that Oracle maintains, and it contains crucial metadata about the database tables, users, privileges, and so forth. Proper sizing of the shared pool area benefits you in a couple of ways. First, your response times will be better because you re reducing processing time if you don t have to recompile the same Oracle code each time a user executes a query, you save time. Oracle will reuse the previously compiled code if it encounters the same code again. Second, more users can use the system because the reuse of code makes it possible for the database to serve more users with the same resources. Both the I/O rates and the CPU usage will diminish when your database uses its shared pool memory effectively. The following sections discuss the library cache and the data dictionary cache, both of which are components of the shared pool.

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All application code, whether it is pure SQL code or code embedded in the form of PL/SQL program units, such as procedures and packages, is parsed first and executed later Oracle stores all compiled SQL statements in the library cache component of the shared pool The library cache component of the shared pool memory is shared by all users of the database Each time you issue a SQL statement, Oracle first checks the library cache to see if there is an already parsed and ready-to-execute form of the statement in there If there is, Oracle uses the library cache version, reducing the processing time considerably this is called a soft parse If Oracle doesn t find an execution-ready version of the SQL code in the library cache, the executable has to be built fresh this is called a hard parse.

LIBRARY$ NTAB$ HISTGRM$ RGROUP$ RGCHILD$ TYPE$ COLLECTION$ METHOD$ RESULT$ PARAMETER$ ATTRIBUTE$ TS$ FET$ USER$ TSQ$ SMON_SCN_TIME

A heap organized table is probably used 99 percent (or more) of the time in applications. A heap organized table is the type of table you get by default when you issue the CREATE TABLE statement. If you want any other type of table structure, you need to specify that in the CREATE statement itself. A heap is a classic data structure studied in computer science. It is basically a big area of space, disk, or memory (disk in the case of a database table, of course) that is managed in an apparently random

Oracle uses the library cache part of the shared pool memory for storing newly parsed code If there isn t enough free memory in the shared pool, Oracle will jettison older code from the shared pool to make room for your new code All hard parses involve the use of critical system resources, such as processing power, and internal Oracle structures, such as latches; you must make every attempt to reduce their occurrence High hard-parse counts will lead to resource contention and a consequent slowdown of the database when responding to user requests You should make decisions about the library cache size based on hit and miss ratios on the library cache as I explain in 20 If your system is showing more than the normal amount of misses (meaning that code is being reparsed or reexecuted often), it is time to increase the library cache memory.

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