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One efficient way to replicate parts of a table across a network is to divide the table horizontally, placing different rows of the table on different systems. Figure 23-5 shows a simple example where a horizontal table split is useful. In this application, a company operates three distribution centers, each with its own computer system and DBMS to manage an inventory database and order processing. A central database is also maintained for production-planning purposes. To support this environment, the PRODUCTS table is split horizontally into three parts and expanded to include a LOCATION column that tells where the inventory is located. The central copy of the table contains all of the rows. The rows of the table that describe inventory in each distribution center are replicated in the local database managed by that center s DBMS.
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In this case, most updates to the PRODUCTS table take place at the distribution center itself, as it processes orders. Because distribution center replicas are mutually exclusive (that is, a row from the PRODUCTS table appears in only one distribution center replica), update conflicts are avoided. The replicas in the distribution center can periodically transmit updates to the central database to keep it up to date.
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Another efficient way to manage table replication is to divide the table vertically, replicating different columns of the table on different systems. Figure 23-6 shows a simple example of a vertical table split. The SALESREPS table has been expanded to include new columns of personnel information (phone number, marital status, and so on), and its information is needed in two databases one in the order-processing department and the other in the personnel department. Most of the activity in each department focuses on one or two columns of the table, but many queries and reports use both personnel-related and order-related columns. To accommodate this application, the SALESREPS table is replicated on both systems, but conceptually, it is split vertically into two parts. The columns of the table that store personnel data (NAME, AGE, HIRE_DATE, PHONE, MARRIED) are owned by the personnel system. It wins any conflicts related to updates on these columns. The other columns (EMPL_NUM, QUOTA, SALES, REP_OFFICE) are owned by the order-processing system. It wins update conflicts related to these columns. Because the entire table is replicated on
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Figure 23-6.
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both systems, either system can be used to generate reports and handle ad hoc inquiries, and all of these can be processed locally. Only updates involve the replication mechanism, generate network traffic, and potentially require conflict resolution.
Mirrored Tables
When table replication is used to achieve high availability (that is, resistance to computer or database failure), the entire table is typically mirrored, as shown in Figure 23-7. The easiest way to implement this configuration is if one system is the active system and another is a hot standby. In this scheme, all database access normally flows to the active system (System A), which replicates any updates to the standby system (System B). Only in the event of system failure does the database access switch over to the standby system, but it has fresh data because of the replicated table. The disadvantage of this scheme is that it wastes the standby computer system under normal operation. The system must be paid for and maintained, but it doesn t add any data processing capacity. For this reason, high-availability systems are often designed to also provide load balancing, as shown in Figure 23-8. In this configuration, some front-end software intercepts DBMS access requests and evenly distributes them between the two (or more) computer systems. Under normal operation, both (all) systems contribute data processing power; none is wasted. Furthermore, it s conceptually easy to grow the data processing power, simply by adding more computer systems with a copy of the replicated table.
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