A resume column includes a file which is a developer resume.īefore proceeding to the examples first understand what is BLOB.A photo column contains an employee picture.CREATE TABLE new_employee ( id INTEGER PRIMARY KEY, name TEXT NOT NULL, photo BLOB NOT NULL, resume BLOB NOT NULL) You can use the following query to create a table with a BLOB column. For this lesson, I am using the ‘new_employee’ table present in my SQLite database. Just one point on the first insert two statements - think a column length is needed as the subsequent insert fail.Please refer to creating an SQLite table from Python. Like the suggestion for using joins to create mass data, great time saver. Now you are ready for tests with realistic values on all the flags, statuses, and other anomalous artifacts in the original data-set. If obfuscating customer data is also a requirement, replace all the consonants in the sensitive data with an X, all the vowels with an A. If your FKs are setup well (cascading delete) this should complete the task, if not a few more deletes and hurray. (0.2% is too much, pick larger numbers 0.2% is not enough, pick smaller) This leaves a consistent 0.2% of the data that has variable spacing between records. One of my favorite ways of doing this, is to delete all the records where the ID (normally an identity int count-up) is not evenly divisible by one of two prime numbers.ĭelete from where ((ID/1129)*1129!=ID) and ((ID/1151)*1151!=ID) Find the big tables, and delete most of the records. So, first take a full restore of the production data. Normally the reason for a smaller test database is so that the big scripts will run fast enough on the test machine to have quick test cycles. Also, making your own test data will mean that it will only have features and behaviors you understand before the testing. Another example is the financial industry where the strict security rules prohibit us to restore production data to any test server. I have real life experience on this topic: I was working for an educational software company but the company did not use its own software so we did not have any real data. I provided the tip because there are certain scenarios when SQL developers cannot use production data for testing. Additionally, when you are working on a new application then by defintion you don't have access to production data.Īlso, the exercise of generating "pseudo" often forces developers to seriously analyze aspecits of their data and its relationships that they otherwise would never consider.īack To Top for the suggestion. Many of them would not let us have a production database backup and the rest should not have. We provided customers with an application that was full of HIPAA related infromation. I also support you comments about not having\using production data. You only call newId() once per row if you code it this way.Ĭase when checksum(newid()) % 2 = 0 Then 'Y' Else 'N' end I think you could use a case function for the Binary data element. I stumbled upon it a while ago and you can do quite a few things with it. Interesting post but check out this cool open source project Tibor Nagy Tibor Nagy Tibor Nagy Tibor Nagy Tibor Nagy Tibor Nagy Tibor Nagy Tibor Nagy Tibor Nagy ,firstname,lastname,emailid,salary,dob,phone,doj plz give me query as soon as possible How to generate random records upto 1 million for emp table consisting of such columns emp middlename Clearing Cache for SQL Server Performance Testing.Automate SQL Server Testing with Profiler, SQLCMD and SQL Server Integration Services.Create stored procedures to fill test database.Build supporting tables to generate the text values.For example cross joining two tables with one thousand records generates results of one million records. Cross joins and self joins can easily create large datasets so be cautious when using very big tables. You can take the above examples to quickly generate more and more different database records from a few row sample tables. SELECT * INTO TESTTABLE FROM NAMES1 CROSS JOIN NAMES2 Fill family names INSERT INTO NAMES2 VALUES ('Smith') CREATE TABLE (FIRST_NAME (20))ĬREATE TABLE (FAMILY_NAME (20))
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