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Innovations in computer networking have been closely linked to many of the innovations in relational database architectures and SQL over the years. Powerful minicomputers with mainframe network connections (such as Digital s VAX family) were the first popular platform for SQL-based databases. They offered a platform for decision support, based on data offloaded from mainframe systems. They also supported local data processing applications, for capturing business data and uploading it to corporate mainframe applications. UNIX-based servers and powerful local area networks (such as Sun s server products) drove another wave of DBMS growth and innovation. This era of databases and networks gave birth to the client/server architecture that dominated enterprise data processing in the 1990s. Later, the rise of enterprisewide networks and applications (such as Enterprise Resource Planning) created a need for a new level of database scalability and distributed database capability. Today, the exploding popularity of the Internet is driving still another wave of innovation, as very high peak-load transaction rates and personalized user interaction drive database caching and main-memory database technologies.
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When SQL-based databases were first deployed on minicomputer systems, the database and application architecture was very simple all of the processing, from screen display (presentation) to calculation and data processing (business logic) to database access occurred on the minicomputer s CPU. The advent of powerful personal computers and server platforms drove a major change in that architecture, for several reasons. The graphical user interface (GUI) of popular PC office automation software (spreadsheets, word processors, and so on) set a new standard for ease of use, and companies demanded the same style of interface from corporate applications. Supporting a GUI is processor-intensive and demands a high-bandwidth path from the processor to the display memory that holds the screen image. While some protocols emerged for running a GUI over the LAN (the X-windows protocol), the best place to run a production application s presentation-layer code was clearly on the PC itself. Economics was also a factor. Personal computer systems were much cheaper, on a cost-per-processing-power basis, than minicomputers or UNIX-based servers. If more of the processing for a business application could take place on lower-cost PCs, the overall hardware cost of deploying an application would be reduced. This was an argument for moving not just the presentation layer, but much of the business logic layer, onto the PC as well. Driven by these and other factors, the first client/server architectures emerged, shown in Figure 23-15. Many PC-based applications are still being deployed today using this architecture. SQL plays a key role as the client/server language. Requests are sent from the application logic (on the PC) to the DBMS (on the server) expressed in SQL statements. The answers come back across the network in the form of SQL completion status codes (for database updates) or SQL query results (for information requests).
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Figure 23-15.
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Client/Server Applications with Stored Procedures
Whenever an application is split across two or more networked computer systems, as in Figure 23-15, one of the major issues is the interface between the two halves of the split application. Each interaction across this interface now generates network traffic, and the network is always the slowest part of the overall system, both in its data transmission capacity (bandwidth) and in round-trip messaging delays (latency). With the architecture shown in Figure 23-15, each database access (that is, each SQL statement) generates at least one round trip across the network. In an OLTP application, typical transactions may require as many as a dozen individual SQL statements. For example, to take a customer s order for a single product in the simple structure of the sample database, the order-processing application might: I Retrieve the customer number based on the customer name (single-row SELECT) I Retrieve the customer s credit limit to verify creditworthiness (single-row SELECT) I Retrieve product information, such as price and quantity available (single-row SELECT) I Add a row to the ORDERS table for the new order (INSERT) I Update the product information to reflect the lower quantity available (UPDATE) I Update the customer s credit limit, reducing the available credit (UPDATE) I Commit the entire transaction (COMMIT) for a total of seven round trips between the application and the database. In a real-world application, the number of database accesses might be two or three times this amount. As transaction volumes grow, the amount of network traffic can be very significant. Database stored procedures provide an alternative architecture that can dramatically reduce the amount of network traffic, as shown in Figure 23-16. A stored procedure within the database itself incorporates the sequence of steps and the decision-making logic required to carry out all of the database operations associated with the transaction. Basically, part of the business logic that formerly resided within the application itself has been pushed across the network onto the database server. Instead of sending individual SQL statements to the DBMS, the application calls the stored procedure, passing the customer name, the product to be ordered, and the quantity desired. If all goes well, the stored procedure returns successfully. If a problem arises (such as lack of available product or a customer credit problem), a returned error code and message describes it. By using the stored procedure, the network traffic is reduced to a single client/server interaction. There are several other advantages to using stored procedures, but the reduction in network traffic is one of the major ones. It was a major selling advantage of Sybase SQL Server when it was first introduced and helped to position Sybase as a DBMS specialized for high-performance OLTP applications. With the popularity of stored procedures, every major general-purpose enterprise DBMS now offers this capability.
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