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Users would then have access to the updated database by the next morning You would not have to exclude users from the system or wait for them to leave for the day Processing a large database can also consume a considerable amount of disk space The Analysis Services server not only creates a second copy of all the dimension and partition files created during the transaction, but it also uses additional temporary files to accumulate aggregations, particularly when creating aggregations from a large fact table Consequently, some databases are simply too large to process as a single transaction Analysis Services provides several options for processing individual components of a database These options allow you to create and manage extremely large databases, but they also require much more work to provide users continuous access to the cubes and to prevent including invalid or inconsistent values in the database ..

The default does not disconnect users from the secondary database when the next shipped log is ready to be loaded. Shipped transaction logs accumulate until all users are disconnected. This can obviously be problematic if you have a very busy database solution in which your users are running reports continually throughout the day. You can select the Disconnect Users In The Database When Restoring Backups check box, as shown in Figure 32-5, which disconnects users from the secondary database whenever the next shipped transaction log is ready to be loaded. The disconnection occurs based on the schedule that you have configured for the restore job.

You will have to decide upon an appropriate schedule for shipping the logs, and how to respond to connected users based on your business requirements, acceptable degree of latency, and operational behaviour. Note

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Don't forget that the restore jobs can have a different frequency than the transaction log backups and shipping jobs. The transaction logs accumulate until they are ready to be loaded.

When you process a dimension, the server creates a map that includes the path for each member of that dimension . Every cube that includes the dimension uses that map . When you process an existing dimension, the map is destroyed and a new map is created . Destroying the dimension map invalidates all the cubes that use the dimension . When you process an entire database, the dimensions are processed first and then all the cubes are processed as well . But when you process a single dimension, you make all the cubes that use that dimension inaccessible to client applications . Fortunately, you can make certain changes to a dimension without destroying the existing map . If you don t destroy the existing map, you don t invalidate existing cubes . Analysis Services allows you to update a dimension to make changes that don t destroy the dimension map . The most useful change you can then make is adding new members to a dimension . You can also rename, delete, or re-parent members . For example, you could re-parent the Helmets member by changing its category from Accessories to Clothing .

A log shipping solution can be particularly effective at scaling out your reporting requirements to different departments. Each department has its own version of a secondary database on a SQL Server instance against which they can report. One department s queries do not adversely affect another department s query performance. You have also provided a layer of fault tolerance, so if one department s secondary database crashes other departments will still be able to report with their secondary databases. Alternatively, for a true fault tolerance layer at the secondary database level, you can use Microsoft s Network Load Balancing (NLB) technology to provide both fault tolerance and load balancing. NLB allows client applications to connect to a single, virtualized IP address configured on the NLB cluster. The NLB cluster is responsible for automatically redirecting the client application to one of the physical IP addresses of the secondary databases that make up the NLB cluster, as shown in Figure 32-6. An additional benefit of implementing an NLB cluster is that it allows you to take your secondary

32

SQL Server instances offline to perform maintenance tasks without having to a reconfigure client applications.

A single NLB cluster can have up to 32 servers and can be scaled beyond this limit by using a round-robin domain name service (DNS) between multiple NLB clusters.

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