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Exam Tip You can configure a transactional publication with both the Immediate Updating Sub scriber and Queued Updating Subscriber options. The Queued Updating Subscriber option can be used as a failover mechanism when the publisher is not available.
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You can configure transactional replication in two common architectures in addition to the normal one-way operation that is the default. You should not confuse each of these architectures with any other mechanism within the replication engine. These architectures still implement regular one-way transactional replication without any updating options. The implementation is done to cause changes to flow back and forth between publisher and subscriber, but it is still the transactional engine. The transactional engine does not detect or resolve data conflicts. Therefore, if you could be processing changes at both the publisher and subscriber that might generate a data conflict, you cannot implement transactional replication in either a bidirec tional or peer-to-peer architecture.
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Peer-to-peer replication is a new architecture in SQL Server 2005 that is available only in the Enterprise Edition. The basic architecture is to enable transactional replication to move data between two or more peers. A diagram of a peer-to-peer architecture is shown in Figure 11-6.
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Figure 11-6 Peer-to-peer transactional replication
Lesson 2: Transactional Replication
Peer-to-peer replication is an implementation of transactional replication. The basic idea is that you can take a set of tables and replicate them from Database1 to Database2 using transactional replication. You then create a publication over the same set of tables on Database2 and replicate them back to Database1 using transactional replication. In effect, each database participating in a peer-to-peer architecture replicates all changes to all other databases. To prevent transactions from endlessly looping around the architecture, you must have a rowguid column on each of the tables par ticipating in replication that enables the engine to identify the database originating the transaction. Peer-to-peer replication has a strict list of requirements that need to be met:
Each peer must have its own distributor. The table structure must be exactly the same among all peers. Queued updating and immediate updating options are not available. No data conflicts can occur.
Bidirectional Replication
Bidirectional replication is slightly different from peer-to-peer replication in the way that you configure it. This architecture is still transactional replication. The set of tables being replicated from Database1 to Database2 is the same set of tables being replicated from Database2 back to Database1, as shown in Figure 11-7.
Clients Distributor Clients
Transactions
Transactions
Distribution
Publisher/ Subscriber Subscriber/
Publisher
Figure 11-7 Bidirectional transactional replication
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Replication
To prevent transactions from looping between the two databases, you also must add the @loopback_detection parameter to each subscription. Although bidirectional replication can be accomplished as a subset of peer-to-peer replication, you can get some performance advantages. You do not need a separate distributor for each publisher or a rowguid column added to the tables participating in replication. The table structures can be different, although we have never encoun tered it. Data conflicts are not handled, and you must implement a bidirectional architecture using code. You cannot implement this architecture using a graphical user interface (GUI) to generate any of the components.
Monitoring
You commonly perform monitoring of replication architectures using the Replication Monitor. Within Replication Monitor, you can obtain statistics on the operational state of all publications, subscriptions, and agents. You can also view error and status history information to troubleshoot any issues that might be occurring. In previous versions, one of the most difficult questions to answer in a replicated environment dealt with bottlenecks. It was reasonably straightforward to determine how many transactions the replication engine was behind by executing the sp_browsereplcmds system stored procedure found in the distribution database. How ever, it was impossible to determine how long it would take the replication engine to catch up because timing information was not maintained across the environment. SQL Server 2005 introduced two important new features to the engine for monitor ing. As changes are moved by the Log Reader and Distribution Agents, the engine maintains statistics on the rate of data movement and how long it took to move data. By using these statistics, Replication Monitor can display continuous information that tells you how many transactions still need to be sent to subscribers as well as approx imately how long it will take to catch back up. Although the statistics in Replication Monitor provide good status information to determine how far behind subscribers are, it does not provide any granular detail. Replication Monitor displays a single statistic for the latency, but administrators can not tell whether the bottleneck is in the Log Reader Agent or whether the Distribution Agent is backing up. So tracer tokens were introduced to provide this granular detail.
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