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SQL Anywhere 11.0.0 » SQL Anywhere Server - SQL Usage » Monitoring and Improving Database Performance » Application profiling tutorials


Setting up for the application profiling tutorials

Use the application profiling tutorials to learn how to use the Application Profiling Wizard and the Database Tracing Wizard to analyze common performance problems including deadlocks, slow statements, index fragmentation, table fragmentation, and slow procedures.


The following tutorials use the test database app_profiling.db which you create, and not the sample database (demo.db). Do not use the sample database to complete the tutorials.

You must have PROFILE authority to perform application profiling. For the application profiling tutorials, connect as a user with DBA authority.

You need to perform the following procedure before trying the application profiling tutorials. The procedure creates a test database app_profiling.db using data from the sample database. The test database is used in all application profiling tutorials.

To create a testing database

  1. Create the directory C:\AppProfilingTutorial.

  2. Open a command prompt and type the following command to create the test database app_profiling.db. The samples-dir is the location of your Samples directory:

    dbunload -c "UID=DBA;PWD=sql;DBF=samples-dir\demo.db" -an C:\AppProfilingTutorial\app_profiling.db 

    For example, on a computer with Microsoft Windows XP and SQL Anywhere installed in the default locations, the command would be:

    dbunload -c "UID=DBA;PWD=sql;DBF=C:\Documents and Settings\All Users\Documents\SQL Anywhere 11\Samples\demo.db" -an C:\AppProfilingTutorial\app_profiling.db

    For more information about the location of samples-dir, see Samples directory.


In the application profiling tutorials, tracing information is stored in the same database that you are profiling (app_profiling.db). However, if you profile a database that experiences heavy loads, you should consider storing tracing data in a separate database to avoid impacting performance on the production database.

See also