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Local system Statement Transaction Transaction Statement Statement Statement
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Distributed data access: distributed transactions
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The third stage of distributed data access, as defined by IBM, is a distributed transaction (a distributed unit of work in IBM parlance), shown in Figure 23-11. At this stage, each individual SQL statement still queries or updates a single database on a single remote computer system. However, the sequence of SQL statements within a transaction may access two or more databases located on different systems. When the transaction is committed or rolled back, the DBMS guarantees that all parts of the transaction on all of the systems involved in the transaction will be committed or rolled back. The DBMS specifically guarantees that there will not be a partial transaction, where the transaction is committed on one system and rolled back on another. Distributed transactions support the development of very sophisticated transactionprocessing applications. For example, in the corporate network of Figure 23-1, a PC orderprocessing application can query the inventory databases on two or three different distribution center servers to check the inventory of a scarce product and then update the databases to commit inventory from multiple locations to a customer s order. The DBMS ensures that other concurrent orders do not interfere with the remote access of the first transaction. Distributed transactions are much more difficult to provide than the first two stages of distributed data access. It s impossible to provide distributed transactions without the active cooperation of the individual DBMS systems involved in the transaction. For this reason, the DBMS brands that support distributed transactions almost always support them only for a homogeneous network of databases, all managed by the same DBMS brand (that is, an all-Oracle or all-Sybase network). A special transaction protocol, called the two-phase commit protocol, is used to implement distributed transactions and ensure that they provide the all-or-nothing requirement of a SQL transaction. The details of this protocol are described later in the section The Two-Phase Commit Protocol.
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Distributed Requests
The final stage of distributed data access in the IBM model is a distributed request, shown in Figure 23-12. At this stage, a single SQL statement may reference tables from two or more databases located on different computer systems. The DBMS is responsible for automatically carrying out the statement across the network. A sequence of distributed request statements can be grouped together as a transaction. As in the previous distributed transaction stage, the DBMS must guarantee the integrity of the distributed transaction on all systems that are involved.
23:
SQL Networking and Distributed Databases
Local system Statement Transaction Transaction Statement Statement Statement
Remote system DBMS
Remote system DBMS
FIGURE 23-12
Distributed data access: distributed requests
The distributed request stage doesn t make any new demands on the DBMS transactionprocessing logic, because the DBMS already had to support transactions across system boundaries at the previous distributed transaction stage. However, distributed requests pose major new challenges for the DBMS optimization logic. The optimizer must now consider network speed when it evaluates alternate methods for carrying out a SQL statement. If the local DBMS must repeatedly access part of a remote table (for example, when making a join), it may be faster to copy part of the table across the network in one large bulk transfer rather than repeatedly retrieving individual rows across the network. The relative sizes of the tables on the local and remote system are also relevant optimization factors, as is the selectivity of any search conditions in the SELECT clause. For some queries, the search conditions may select only one or a few rows on the local system and hundreds of rows on the remote system, so they should be applied locally first. For other queries involving the same tables, the relative selectivity may be reversed, and the remote search condition should be applied. For still other queries, the join condition itself may limit the rows that participate in both the local and remote systems, and it may be most efficient to apply it first. In each case, the cost of the query is not just the cost of the database access, but also the cost of shipping the results of intermediate query execution steps back and forth across the network. The optimizer must also decide which copy of the DBMS should handle statement execution. If most of the tables are on a remote system, it may be a good idea for the remote DBMS on that system to execute the statement. However, that may be a bad choice if the remote system is heavily loaded. Thus, the optimizer s task is both more complex and much more important in a distributed request. Ultimately, the goal of the distributed request stage is to make the entire distributed database look like one large database to the user. Ideally, the user would have full access to any table in the distributed database and could use SQL transactions without knowing anything about the physical location of the data. Unfortunately, this ideal scenario would quickly prove impractical in real networks. In a network of any size, the number of tables in the distributed database would quickly become very large, and users would find it impossible to find data of interest. The user-ids of every database in the organization would have to be coordinated to make sure that a given user-id uniquely identified a user in all databases. Database administration would also be very difficult.
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