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SQL Today and Tomorrow
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.
Enterprise Applications and Data Caching
Today, major applications from the large packaged enterprise software vendors are all based on SQL and relational databases. Examples include large Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Human Resources Management (HRM), Customer Relationship Management (CRM), financial management, and other packages from vendors such as SAP, Infor Global Solutions (formerly BAAN), Oracle (which acquired both PeopleSoft and Siebel Systems), the Sage Group, Microsoft, IBM, i2 Technologies, and others. These large-scale applications typically run on large UNIX or Windows server systems and place a heavy workload on the supporting DBMS. To isolate the applications and DBMS processing and apply more total processing power to the application, they often use a three-tier architecture shown in Figure 23-17.
Personal computer
Application server Database requests Enterprise application Display data
Database server
Windows application or browser
User input Display data
DBMS
Database
Front-end
Middle tier
Back-end
FIGURE 23-17
Three-tier architecture of a major enterprisewide application
23:
SQL Networking and Distributed Databases
Even with the use of stored procedures to minimize network traffic, the network and database access demands of the most data-intensive of these enterprise applications can outstrip the available network bandwidth and DBMS transaction rates. For example, consider a supply chain planning application that helps a manufacturing company determine the parts that it must order from suppliers. To generate a complete plan, the application must examine every open order and apply the product bill-of-materials to it. A complex product might involve hundreds of parts, some of which are themselves subassemblies consisting of dozens or hundreds of parts. If written using straightforward programming techniques, the planning application must perform a database inquiry to determine the parts makeup of every product, and then every subassembly, for every order, and it will accumulate the total needed information in the planning database for each of these parts. Using this technique, the application will take hours to process the hundreds of thousands of orders that may be currently on the books. In fact, the application will probably run so long that it cannot possibly complete its work during the typical overnight low-volume batch processing window of time during which the company normally runs such applications. To deliver acceptable performance, all data-intensive enterprise applications employ caching techniques, pulling the data forward out of the database server, closer to the application. In most cases, the application uses relatively primitive caching techniques. For example, it might read the bill-of-materials once and load it into main-memory data tables within the application program. By eliminating the heavily repeated product-structure queries, the program can dramatically improve its performance. Recently, enterprise application vendors have begun to use more complex caching techniques. They may replicate the most heavily accessed data (the hot data) in a duplicate database table, on the same system as the application itself. Main-memory databases offer an even higher-performance alternative and are already being used where there is a relatively small amount of hot data (tens to hundreds of megabytes). With the advent of 64-bit operating system architectures and continuing declines in memory prices, it is becoming practical to cache larger amounts of data (tens or hundreds of gigabytes). Advanced caching and replication will become more important in response to emerging business requirements. Leading-edge manufacturing companies want to move toward realtime planning, where incoming customer orders and changes immediately impact production plans. They want to offer more customized products, in more configurations, to more closely match customer desires. These and similar trends will continue to raise the volume and complexity of database access.
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