![]() But if you plan to generate random grades for the students, you can take benefits from the RAND() T-SQL function and cast the result as the required numeric data type. The ID column with IDENTITY property will automatically generate sequence numbers without the need for any coding effort from your side. INSERT INTO Students (FirstName, LastName, BirthDate, STDAddress) VALUES ('Faisal','Ali','','London, St41')Īnother option is to generate random data depending on the data type of each column. INSERT INTO Students (FirstName, LastName, BirthDate, STDAddress) VALUES ('Faruk','Cedrik','','London, St24') INSERT INTO Students (FirstName, LastName, BirthDate, STDAddress) VALUES ('Mike','Zikle','','London, St18') For example, the script below will fill the Students table with 100K redundant testing records using the GO Number statement: INSERT INTO Students (FirstName, LastName, BirthDate, STDAddress) VALUES ('John','Horold','','London, St15') But the problem is that the SQL Server Query Optimizer will build a different plan on the development database from the one built on the production database due to the difference in the data distribution. To fill a table with a large amount of data, the easiest way is to write a simple script that keeps inserting identical records into the database table with the number of duplicates you need. There is no single straight-forward way to generate test data that will fit all scenarios, especially when you need to generate large amount of data to test the performance of complex queries and transactions in which you should cover all possible combinations of testing cases. ![]() Test data generation is useful for testing the performance of the application or a new functionality without changing the production data. The best and most secure alternative is to fill the development database tables with testing data. Restoring a copy of the production database to the development database server for testing purposes is not always a valid option, due to the critical data that is stored in these databases and should not be open for all employees to see, unless you are developing a new application and there is no production database yet. This is because the performance of a query that is processing 50 records will be different from the performance of the same query that is processing 50M rows. When testing the functionality of your application or the performance of a specific stored procedure or an ad-hoc query in the development environment, you need to have data stored in your development databases typical or similar to the data stored in the production databases.
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