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SQL Today and Tomorrow
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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 by adding more computer systems with a copy of the replicated table.
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Insert/update/query requests
Front-end server
Load-distribution software
Database server
DBMS
DBMS
Database server
Replicated table
N-way replication
Replicated table
FIGURE 23-8
Replication for load balancing
23:
SQL Networking and Distributed Databases
This type of mirrored table approach can be highly effective if the ratio of database queries to database updates is very high (for example, 95 percent read access / 5 percent update access). If the percentage of updates is too high, the potential for conflicts and the replication overhead can diminish the effectiveness and scalability of the overall configuration. Efficiency also decreases with each increase in the number of replicated systems, since the replication overhead rises. One common way to get more efficiency out of a mirrored table configuration like the one in Figure 23-8 is to divide updates to the table based on some rule. For example, if the mirrored table is a customer table, the primary key may be the customer name. The frontend load-balancing software can then be written so that updates for customer names starting with A through M are routed to the one system, and updates for customer names starting with N through Z are routed to the other system. This eliminates the possibility of update conflicts. Because the table remains fully replicated under this scenario, read access requests can still be distributed randomly between the two systems to balance the workload. This type of approach can be quite effective in achieving scalable database performance with replicated tables. It can be fairly easily extended from a two-way scheme to an N-way scheme, where updates are split among three or more database servers.
Distributed Database Access
Over the last several years, research into fully distributed database access has slowly but surely found its way into commercial products. Today, many of the mainstream enterprise database products offer at least some level of transparent distributed database access. As noted earlier in the Remote Data Transparency section, the performance implications of distributed database access and updates can be quite substantial. Two very similar-looking queries can create massively different amounts of network traffic and overhead. A single query, carried out in a brute force method or an optimized method, can create the same differences, depending on the quality of the optimization done by the DBMS. Because of these challenges, all of the vendors have taken a step-by-step approach to delivering distributed database access. When IBM first announced its blueprint for distributed data management in its SQL products, it defined a four-stage approach. IBM s four stages, shown in Table 23-1, provide an excellent framework for understanding distributed data management capabilities and their implications.
Stage Remote request Remote transaction Distributed transaction Distributed request Description Each SQL statement accesses a single remote database; each statement is a transaction. Each SQL statement accesses a single remote database; multistatement transactions are supported for a single database. Each SQL statement accesses a single remote database; multistatement transactions are supported across multiple databases. Each SQL statement may access multiple databases; multistatement transactions are supported across multiple databases.
PART VI
TABLE 23-1
IBM s Four-Stage Approach for Distributed Database Access
Part VI:
SQL Today and Tomorrow
The IBM scheme provides a simple model for defining the distributed data access problem: a user of one computer system needs to access data stored on one or more other computer systems. The sophistication of the distributed access increases at each stage. Thus, the capabilities provided by a given DBMS can be described in terms of which stage it has reached. In addition, within each stage, a distinction can be made between read-only access (with the SELECT statement) and update access (with the INSERT, DELETE, and UPDATE statements). A DBMS product often provides read-only capability for a given stage before full update capability is provided.
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