Shared pool is very important part of the production system.It contains all the neccessary element for execution of the SQL statement and PL/SQL programs.
If you use shared pool effectively you can reduce resource consumption in at least four ways
Parse overhead is avoided if the SQL statement is already in the shared pool. This saves CPU resources on the host and elapsed time for the end user.
Latching resource usage is significantly reduced, which results in greater scalability.
Shared pool memory requirements are reduced, because all applications use the same pool of SQL statements and dictionary resources.
I/O resources are saved, because dictionary elements that are in the shared pool do not require disk access.
Main components of shared pool are library cache (executable forms of SQL cursors, PL/SQL programs, and Java classes.) and the dictionary cache (usernames, segment information, profile data, tablespace information, and sequence numbers. )
The Library Cache
The library cache stores the executable (parsed or compiled) form of recently referenced SQL and PL/SQL code. The dictionary cache stores data referenced from the data dictionary. This caches are managed by LRU algorithm to ìage outî memory structures that have not been reused over time. Allocation of memory from the shared pool is performed in chunks. This allows large objects (over 5k) to be loaded into the cache without requiring a single contiguous area, hence reducing the possibility of running out of enough contiguous memory due to fragmentation. Starting with 9i The Shared Pool divide its shared memory areas into subpools. Each subpool will have Free List Buckets (containing pointers to memory chunks within the subpool ) and , memory structure entries, and LRU list. This architecture is designed to to increase the throughput of shared pool in that now each subpool is protected by a Pool child latch. This means there is no longer contention in the Shared Pool for a single latch as in earlier versions.
Infrequently, Java, PL/SQL, or SQL cursors may make allocations out of the shared pool that are larger than 5k then Oracle must search for and free enough memory to satisfy this request. This operation could conceivably hold the latch resource for detectable periods of time, causing minor disruption to other concurrent attempts at memory allocation. To allow these allocations to occur most efficiently, Oracle segregates a small amount of the shared pool. This memory is used if the shared pool does not have enough space. The segregated area of the shared pool is called the reserved pool which is also divided into subpools. Smaller objects will not fragment the reserved list, helping to ensure the reserved list will have large contiguous chunks of memory. Once the memory allocated from the reserved list is freed, it returns to the reserved list.
The library cache holds the parsed and executable versions of SQL and PL/SQL code
Parsing, which includes syntactic and semantic verification of SQL statements and checking of object privileges to perform the actions.
Optimization, where the Oracle optimizer evaluates how to process the statement with the
least cost, after it evaluates several alternatives.
Execution, where Oracle uses the optimized physical execution plan to perform the action
stated in the SQL statement.
Fetching, which only applies to SELECT statements where Oracle has to return rows to you.
This step isnít necessary in any nonquery-type statements. Parsing is a resource-intensive operation, and if your application needs to execute the same
SQL statement repeatedly, having a parsed version in memory will reduce contention for latches, CPU, I/O, and memory usage. The first time Oracle parses a statement, it creates a parse tree. The optimization step is necessary only for the first execution of a SQL statement. Once the statement is optimized, the best access path is encapsulated in the access plan. Both the parse tree and the access plan are stored in the library cache before the statement is executed for the first time. Future invocation of the same statement will need to go through only the last stage, execution, which avoids the overhead of parsing and optimizing as long as Oracle can find the parse tree and access plan in the library cache. Of course, if the statement is a SQL query, the last step will be the fetch
The library cache, being limited in size, discards old SQL statements when thereís no more room for new SQL statements. The only way you can use a parsed statement repeatedly for multiple executions is if a SQL statement is identical to the parsed statement. Two SQL statements are identical if they use exactly the same code, including case and spaces. The reason for this is that when Oracle compares a new statement to existing statements in the library cache, it uses simple string comparisons. In addition, any bind variables used must be similar in data type and size. Here are a couple of examples that show you how picky Oracle is when it comes to considering whether two SQL statements are identical.
Data Dictionary Cache
This part of the Shared Pool memory structure is used for storing the most recently used data definitions in the Oracle DB. These data definitions may include information about: database files, tables, indexes, privileges, users, etc.
Caching these inforamtion in memory improves the performance especially for queries and updates using DML. During the parsing phase, the server process scans this memory structure to resolve the database object names and validate access.
This area contains the binary form, executable by Oracle, of the SQL and PL/SQL cursors.