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Choose the correct responses to each of the multiple-choice questions. Note that there may be more than one correct response to each question. 1. Performance requirements a. Should be set after the SQL statements are tuned b. Provide a way to identify statements that need tuning c. Are best when they contain complex criteria d. Provide a way to know when to stop tweaking a query e. Are developed just to make the auditors happy 2. Disk reads and writes can be minimized by a. Allocating buffers of suf cient size b. Placing all the database les on one disk drive c. Putting the entire database in memory d. Adding indexes for all the important table columns e. Spreading les across all available disk drives 3. The computer system can be tuned by a. Collecting database statistics b. Applying available security patches c. Selecting fast and reliable hardware

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but the DESCRIBE OUTPUT form of the statement is the default, and the most common practice is to omit the keyword OUTPUT. Returning to the dynamic query example of Figure 18-9, the cursor has been opened at callout 7, and it s time to fetch rows of query results at callout 8. Again, the SQL2 form of the FETCH statement is slightly modified to use the SQL2-style descriptor:

FETCH sqlcurs USING SQL DESCRIPTOR qrydesc;

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One of the most important applications for the earliest database management systems was production planning for manufacturing companies. If an automobile manufacturer decided to produce 10,000 units of one car model and 5000 units of another model, it needed to know how many parts to order from its suppliers. To answer the question, the product (a car) had to be decomposed into assemblies (engine, body, chassis), which were decomposed into subassemblies (valves, cylinders, spark plugs), and then into sub-subassemblies, and so on. Handling this list of parts, known as a bill of materials, was a job tailor-made for computers. The bill of materials for a product has a natural hierarchical structure. To store this data, the hierarchical data model, illustrated in Figure 4-2, was developed. In this model, each record in the database represented a specific part. The records had parent/child relationships, linking each part to its subpart, and so on.

d. Following the DBMS tuning recommendations e. Consulting a tuning guide for the operating system 4. Ef cient table design includes

Figure 4-2.

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To access the data in the database, a program could perform the following tasks: I Find a particular part by number (such as the left door) I Move down to the first child (the door handle) I Move up to its parent (the body) I Move sideways to the next child (the right door) Retrieving the data in a hierarchical database thus required navigating through the records, moving up, down, and sideways one record at a time. One of the most popular hierarchical database management systems was IBM s Information Management System (IMS), first introduced in 1968. The advantages of IMS and its hierarchical model follow. I Simple structure. The organization of an IMS database was easy to understand. The database hierarchy paralleled that of a company organization chart or a family tree. I Parent/child organization. An IMS database was excellent for representing parent/child relationships, such as A is a part of B or A is owned by B. I Performance. IMS stored parent/child relationships as physical pointers from one data record to another, so that movement through the database was rapid. Because the structure was simple, IMS could place parent and child records close to one another on the disk, minimizing disk input/output.

4:

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IMS is still a very widely used DBMS on IBM mainframes. Its raw performance makes it the database of choice in high-volume transaction-processing applications such as processing bank ATM transactions, verifying credit card numbers, and tracking the delivery of overnight packages. Although relational database performance has improved dramatically over the last decade, the performance requirements of applications such as these have also increased, so IMS continues to have a role. In addition, the large amount of corporate data stored in IMS databases insures that IMS use will continue long after relational databases have eliminated the performance barrier.

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