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written to tempdb. This means that the read committed snapshot isolation level is the best solution to this problem. (If it can t be decided that dirty reads in the lists are acceptable, read uncommitted will provide the best performance.) The inconsistent reports The reports that contain inconsistent data are either experiencing non-repeatable or phantom reads. To solve this problem, the queries used in a report need to be combined in a transaction and use the repeatable read, serializable, or snapshot isolation level. Because the repeatable read isolation level doesn t protect against phantom reads, it will solve the problem only if the problem is non-repeatable reads. Both repeatable read and serializable drastically increase locked resouces. The reports are run against the same database as the order entry application; they should be avoided because they are highly likely to introduce blocking and deadlock problems. The snapshot isolation level will protect against both non-repeatable and phantom reads without introducing blocking or deadlock issues. Because the reports don t update data, update conflicts will not be a problem.

3. Which of the following properties and administrative tasks can be configured or performed simultaneously on more than one user object a. Last Name b. User Logon Name c. Disable Account d. Enable Account e. Reset Password f. Password Never Expires g. User Must Change Password At Next Logon

You assign an identifier to the constraint with the unique-key attribute so you can refer to it several times in one class mapping and group columns for the same constraint. However, the identifier isn t used in the DDL to name the constraint:

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To find out which stored procedures are performing poorly, you should examine the output of a SQL Trace (through Profiler or the trace stored procedures). Queries with value in the Duration column that is too high need to be optimized. When optimizing these queries, execute them in SQL Server Management Studio, examine their graphical execution, and consider rewriting the queries as well as redesigning the indexes on the queried tables. To reduce the query execution times from up to 30 minutes down to a couple of seconds, you will most likely have to do something other than design appropriate indexes. First, examine if these long response times are due to the finance queries being blocked by other users. If this is the issue, one solution may be to replicate the data to another SQL Server instance and execute the finance queries against this instance instead of the production server. If blocking is not the problem, either consider de-normalizing the tables to allow for shorter response times or using Analysis Services Cubes as a source for the finance department s queries.

create table CATEGORY ( ... CAT_NAME varchar(255) not null, PARENT_CATEGORY_ID integer, ... unique (CAT_NAME, PARENT_CATEGORY_ID) );

If you want to create a unique constraint with annotations that spans several columns, you need to declare it on the entity, not on a single column:

Because the problem has occurred suddenly and appears sporadically, it is not likely to be a memory issue. However, nothing should be overruled at this point. The first thing you should do is to execute Windows System Monitor using the key counters included in the baseline. Save the log results to the database or a log file. You will need to continue monitoring until the performance problem has been observed. Note the time when the issue occurred and when

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@Entity @Table(name = "CATEGORY", uniqueConstraints = { @UniqueConstraint(columnNames = {"CAT_NAME", "PARENT_CATEGORY_ID"} ) } ) public class Category { ... }

the monitoring stopped. At the same time, run a trace using the events from the baseline using SQL Server Profiler and log it to the database or a log file. Then, compare the resulting counter and trace logs to the log files created for the performance baseline. Note outliers and investigate to determine if they are indicative of the problem. It might be necessary to execute queries using various dynamic management views to investigate an outlier. It might also be necessary to repeat the monitoring until you determine a root cause. Once you identify a suspected cause, make the appropriate changes and repeat the monitoring to determine if the outliers are still present. Continue this process until you are confident that the problem has been identified and resolved. You should then create a new performance baseline for all database servers. This will be used for any issues that might arise in the future.

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