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The shared pool is one of the most critical pieces of memory in the SGA, especially with regard to performance and scalability. A shared pool that is too small can kill performance to the point that the system appears to hang. A shared pool that is too large can have the same effect. A shared pool that is used incorrectly will be a disaster as well. What exactly is the shared pool The shared pool is where Oracle caches many bits of "program" data. When we parse a query, the parsed representation is cached there. Before we go through the job of parsing an entire query, Oracle searches the shared pool to see if the work has already been done. PL/SQL code that you run is cached in the shared pool, so the next time you run it, Oracle doesn't have to read it in from disk again. PL/SQL code is not only cached here, it is shared here as well. If you have 1,000 sessions all executing the same code, only one copy of the code is loaded and shared among all sessions. Oracle stores the system parameters in the shared pool. The data dictionary cache (cached information about database objects) is stored here. In short, everything but the kitchen sink is stored in the shared pool.

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You can also use multiline string literals: > let s = "All the kings horses - and all the kings men";; val s : string The operator .[] is used to access the elements of a string, and the property .Length retrieves its length: > let s = "Couldn't put Humpty";; val s : string > s.Length;; val it : int = 19 > s.[13];; val it : char = 'H' Strings are immutable; that is, a string value cannot be modified once built. For example, the Substring method on the string type doesn t modify the original string but returns a new string representing the result. As mentioned in 2, immutability is a key concept for many F# values, and you ll encounter it at many places in this book. If you attempt to mutate a string, you will get an error like the one shown here: > let s = "Couldn't put Humpty";; val s : string = "Couldn't put Humpty" > s.[13] <- 'h';; s.[13] <- 'h';; ^^ stdin(75,0): error: FS0001: Type error in the use of the overloaded operator 'set_Item'. The type 'string' does not support any operators named 'set_Item'

The shared pool is characterized by lots of small (generally 4KB or less) chunks of memory Bear in mind that 4KB is not a hard limit There will be allocations that exceed that size, but in general the goal is to use small chunks of memory to prevent the fragmentation that would occur if memory chunks were allocated in radically different sizes, from very small to very large The memory in the shared pool is managed on an LRU basis It is similar to the buffer cache in that respect if you don't use it, you'll lose it A supplied package called DBMS_SHARED_POOL may be used to change this behavior to forcibly pin objects in the shared pool You can use this procedure to load up your frequently used procedures and packages at database startup time, and make it so they are not subject to aging out.

Normally, though, if over time a piece of memory in the shared pool is not reused, it will become subject to aging out Even PL/SQL code, which can be rather large, is managed in a paging mechanism so that when you execute code in a very large package, only the code that is needed is loaded into the shared pool in small chunks If you don't use it for an extended period of time, it will be aged out if the shared pool fills up and space is needed for other objects The easiest way to break Oracle's shared pool is to not use bind variables As you saw in 1 Developing Successful Oracle Applications, not using bind variables can bring a system to its knees for two reasons: The system spends an exorbitant amount of CPU time parsing queries.

The simplest way to build strings is via concatenation using the + operator: > "Couldn't put Humpty" + " " + "together again";; val it : string = "Couldn't put Humpty together again"

The system uses large amounts of resources managing the objects in the shared pool as a result of never reusing queries..

If every query submitted to Oracle is a unique query with the values hard-coded, the concept of the shared pool is substantially defeated The shared pool was designed so that query plans would be used over and over again If every query is a brand-new, never-before-seen query, then caching only adds overhead The shared pool becomes something that inhibits performance A common but misguided technique that many use to try to solve this issue is adding more space to the shared pool, which typically only makes things worse than before As the shared pool inevitably fills up once again, it gets to be even more of an overhead than the smaller shared pool, for the simple reason that managing a big, full shared pool takes more work than managing a smaller, full shared pool The only true solution to this problem is to use shared SQL to reuse queries.