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Although it has no intrinsic meaning, the sum of the day-end balances of multiple accounts can be divided by the number of days in a period An average daily balance can be computed for an aggregate of accounts or a range of periods The star in Figure 11-4 includes facts for both approaches TIP A snapshot design can be embellished with additional facts to simplify the query and reporting process Period-begin and period-end balances are redundant but make many reports much easier to build Fully additive facts may summarize the quantity and magnitude of transactions of various types during the period; these facts are fully additive Average balance information may also be useful but is nonadditive A sum of daily balances for the period makes little sense on its own but is useful in computing averages across various dimensions Period-to-date metrics may also find a home in the snapshot table.

The CAST Expression (SQL2)

Table 8-2.

None of these embellishments is meant to take the place of the transaction fact table Even with the additional transaction counts and dollar amounts, the periodic snapshot still lacks the transaction-level detail of the original star in Figure 11-1 The transaction model remains of immense utility, though in many cases it may be unmanageably large..

You ll probably want to customize the default Performance Monitor options to highlight important information. On busy servers, this is a good way to measure the performance impact of enabling various types of replication and their settings. Also, depending on these settings, you might want to also change the interval used for monitoring replication performance statistics. The default update rate may be too high on servers that experience moderate usage. Finally, it s important to realize that other processes may be competing for resources on the same server. If replication transaction throughput is low, the problem might be related to one of many different parameters. For example, if your network connections are saturated, the servers may not be able to communicate properly. On the other hand, if your server is extremely busy, the problem might be due to database server processes competing for memory and CPU resources in generating and updating replication information. In any case, using Performance Monitor can help to determine the causes and effects of enabling replication on your servers.

Businesses often track a variety of period-to-date measurements. Examples include month-todate orders by customer, along with quarter-to-date, year-to-date, and lifetime-to-date versions. These measurements are similar to balance measurements in several ways. Like a balance, they measure the cumulative effect of activities, rather than activities themselves. Also, like a balance, these facts are not additive across the time dimension. It makes no sense to add together lifetime-to-date order dollars for a customer across two successive days. Period-to-date measurements are not usually stored in transaction fact tables, for the same reason that balance measurements are not stored with transactions. It would be impossible to determine the period-to-date status at a particular point in time unless there happens to be a transaction, and if there are two transactions on a single day, both will have the period-to-date value, risking double-counting. A snapshot fact table is the logical home for period-to-date measurements. It is sampled on a regular basis, in the same way that a useful period-to-date measurement is sampled, and it is defined by a specific combination of dimensions, in the same way the period-todate measurement is defined. The period component of the grain statement describes the point in time at which the measurement is collected; the other dimensions describe the entity being measured. For example, the fact table in Figure 11-4 contains one row per

The SQL standard has fairly restrictive rules about combining data of different types in expressions. It specifies that the DBMS shall automatically convert among very similar data types, such as 2-byte integers and 4-byte integers. However, if you try to compare numbers and character data, for example, the standard says that the DBMS should generate an error. The standard considers this an error condition even if the character string contains numeric data. You can, however, explicitly ask the DBMS to convert among data types using the CAST expression, whose syntax is shown in Figure 9-8.