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Sql data generator open source4/29/2023 Configure MySQLĬonnect to the MySQL server with the root user: mysql -u root -pĬreate a new database: mysql> create database datagenerator Ĭreate a new user: mysql> create user identified by 'SomeNewPassword' This means the Apache is responding to requests and served us index.html page. Now we should have a working web server with PHP and MySQL support. Install PHP apt-get install php php-mysql libapache2-mod-php Install MySQL apt-get install mysql-server I would, however, love to see Data Generator as a Docker container.įirst and foremost, if you have just installed Ubuntu you need to refresh repositories: apt-get update Install Apache, PHP and MySQL I have chosen a dedicated VM as it makes it easier for me. You can install AMP (Apache, MySQL, PHP) locally on a Windows laptop. You can learn how to install Ubuntu virtual machine in Azure in my previous post I will be using Ubuntu Linux 18.04 for this demonstration. This could be either on Windows or Linux. The data generator is a PHP/MySQL application and therefore requires MySQL and PHP installed on the machine. The self-hosted version does not have any limitation. Ben has done a fantastic job and I would urge you to donate on the author’s website. In the online version, we can only generate 100 records at a time, which one can increase after a donation. My favourite is by Benjamin Keen because it is Open Source, free and self-hosted. There are a number of online tools available to generate mock-up data. The only way is to generate test customers born on February 29th In that case, our production data would never trigger this particular business rule and we would never be able to validate it. For example, we could have a business rule that awards customers born on February 29th but we may not have such customers. Problem with this approach is that it may not fully satisfy our business logic. We must also not store any sensitive or personal information in non-production systems and doing so could be against Data Protection Regulations (GDPR).Ī common approach is to refresh test environments from production and thus load production data for testing. As data professionals, we often need test data, whether for functional testing, to satisfy business logic criteria or for non-functional, to satisfy performance requirements.
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