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Connection pooling significantly reduces the overhead associated with creating and destroying database connections. Connection pooling also improves the scalability of solutions by reducing the number of concurrent connections a database must maintain. Many of these connections sit idle for a significant portion of their lifetimes. With connection pooling, the first time you create a connection, the .NET Framework checks the pool to see whether a connection is available. If the pool hasn t yet reached its limit, a new connection will be created and added to it. The next time you attempt to use a connection with the identical connection string, instead of a new connection being created and opened, the existing connection in the pool is used. When you close the connection, it is returned to the pool until it is needed again. Once created, a pool exists until your process terminates. The SQL Server and Oracle data providers encapsulate connection-pooling functionality that they enable by default. One connection pool exists for each unique connection string you specify when you open a new connection. Each time you open a new connection with a connection string that you used previously, the connection is taken from the existing pool. Only if you specify a different connection string will the data provider create a new connection pool. You can control some characteristics of your pool using the connection string settings described in Table 8-2.

reference constant values or expressions that reference variables whose values are constant. For example, both of the calculations in the following code fragment could be replaced with a simple assignment statement: n = 10 * 20 * 400; i = 10; j = 20; ij = i * j; In the latter case, the assignments to the variables i and j could also be eliminated if these variables were not used elsewhere in the code.

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Specifies the maximum time in seconds that a connection is allowed to live in the pool before it s closed. The age of a connection is tested only when the connection is returned to the pool. This setting is useful for minimizing pool size if the pool is not heavily used and also ensures optimal load balancing is achieved in clustered database environments. The default value is 0, which means connections exist for the life of the current process. Supported only by the SQL Server data provider. Specifies whether connections are reset as they are taken from the pool. A value of True (the default) ensures a connection s state is reset but requires an additional communication with the database. Specifies the maximum number of connections that should be in the pool. Connections are created and added to the pool as required until this value is reached. If a request for a connection is made but there are no free connections, the calling code will block until a connection becomes available or times out. The default value is 100.

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Another way to reduce or eliminate redundant computations is to perform copy propagation transformations, which eliminate cases in which values are copied from one location or variable to another in order to simply assign their value to another variable. Given an assignment of the form f = g, subsequent uses of f, called copies, use g instead. Consider a code fragment such as the following: i = 10; x[j] = i; y[MIN] = b; b = i; Copy propagation transformation might result in a fragment that looks like the following: i = 10; x[j] = 10; y[MIN] = b; b = 10; In this example, copy propagation enables the code to assign values from a static location, which is faster than looking up and copying the value of a variable, and also saves time by eliminating assigning a value to a variable that is itself subsequently used only to propagate that value throughout the code. In some cases, copy propagation itself may not provide direct optimizations, but simply facilitates other transformations, such as code motion and dead code elimination. Constant propagation is a related optimization to copy propagation transformation that optimizes code by replacing variables with constant values wherever possible. Copy propagation focuses on eliminating needless copies between different variables, while constant propagation focuses on eliminating needless copies between predefined values and variables.

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