You can change properties of these data generators to define the range and format of the data being generated as well. It uses several built in data generators which generate random data or generate data from other data sources as per your column data type. Data Generation Plan contains how you want your test data to be generated for your specific tables and columns. One of them is generating random test data using Data Generation Plan. This post was originally published on March 30, 2020.Visual Studio Database edition provides several features for database development and testing. We can also generate an INSERT statement: I have made mine accessible via the Internet for test purposes but you can keep yours within the local network, there is no need to expose it: Result In my example, on a VM with 2 CPUs (Standard D2s v3) generating INSERT SQL Statement for 10000 records is instant. After that, you will be able to start using your own data generator without any limitations… well, the only limitation is the performance of your VM and how quickly it can generate data sets. On the next screens, you will be configuring User Account types and which plugins to install. Grant access to the cache folder as per documentation: chmod 777 /var/Now, navigate to your servers IP or DNS and follow the wizard:Ĭonfigure the MySQL connection with the information we have created earlier in this post: Now, we have to copy the extracted package to the DocumentRoot folder: cp -a generatedata-3.2.8/ /var/www/html/ To quit vim press Esc, then : and type q and press Enter I use VIM: vi /etc/apache2/sites-enabled/nf
First, we need to install unzip: apt-get install unzipīy default, the Apache webserver is looking for websites to be in /var/To see the configuration you can open it in the text editor. The guide is available on their GitHub page but I will take you through it step by step: Reload privileges to take into effect: flush privileges Install data generator Now, grant the new user privileges to the database: mysql> grant all privileges ON datagenerator. 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.