1/24/2024 0 Comments Sample data generator![]() open a terminal in the workspace path and run the following CDK command to deploy the solution.If the account is not CDK bootstrapped, you need to run the following command:.Use aws configure to configure the AWS CLI with the access key to the AWS account.The TDG PySpark glue Job is invoked to generate the test data.Ĭlone the GitHub repository in your local development environmentĪWS_ACCOUNT to the AWS account id where you intend to deploy the Test Data GeneratorĪWS_REGION to the AWS region id where you intend to deploy the Test Data Generator The Service IAM role required by TDG PySpark glue Job. The artefacts S3 Bucket and uploads the TDG PySpark library and YAML configuration file into it. The deployment to AWS account is done by using AWS Cloud Development Kit (CDK)ĪWS CDK generates the CloudFromation template and deploy it in the hosting AWS Account All configurations to the generator is configured through a YAML formatted file stored in the S3 artefact bucket. The Test Data Generator is based on PySpark library which is invoked through as a PySpark AWS Glue job. This can be used to generate dates of specific intervals such as a support ticket close date, deceased date, expiration date,… etc This generator produces random from a configurable start date column and a range. This generator produces random dates generator from a configurable date range. This can be used to generate IP address ranges for testing applications used for internet traffic monitoring or filtering. This generator produces random IP addresses. This can be used to generate float values such as salary, temperature, profit, statistical data. This generator produces random float/double data from an expression. This generator produces random integer data from a specified range. This can be used to generate fake emails, formatted phone numbers, comments, address like data, …etc. Strings from a Pattern: you can provide generic pattern for your string data. This can be used to generate categorical columns with predefined set of values such as order status, product types, marital status, gender.etc/ Strings from a Dictionary: you can provide a dictionary of words to pick up randomly by the generator. This can be used for generating random serial numbers, ordinal data, codes, identity numbers. Random Strings: you can specify the number of characters and the type of generated characters: numeric, alphabetic or alphanumeric values. This generator produces String data type with various mechanisms: you can specify the number of levels and how many nodes you want to generate per level. This is useful in generating multi-level hierarchical data. This generator produces a child key referencing the primary key. ![]() you can specify a prefix to and the number of leading zeros if required. This generator produces formatted unique values that can be used as partition key. The Test Data Generation Framework currently supports the following types: The required test data description is fully configurable through a YAML configuration file. You can spend many nights playing with these parameters, and obtain different databases that can produce trends and exceptions you can analyze for your demos.The AWS Glue Test Data Generator provides a configurable framework for Relational Test Data Generation using AWS Glue Pyspark Jobs. The transactions generated in the Sales table are not entirely random: there are parameters used to control the distribution of transactions over products, customers, stores, and time. You can customize all these files and produce any content you want. We added stores and customers using other files obtained by random data generation services. The content of the database is based on the Microsoft Contoso sample database. You must be a C# developer to partake in this game. Customize the C# code of the tool to implement new features. There is a Visual Studio solution with a C# project running in.You must alter configuration files and the PowerShell scripts. Produce your own Contoso database. Download the executable, customize the parameters, and run the scripts to control the content of the database in terms of volume and data distribution.Just download from the latest release: Contoso databases with different sizes are already available for download. Download an existing, ready-to-use Contoso database. You get a backup that you can restore on a SQL Server or Azure SQL instance.You can use the content available in different ways: You can customize the database generated in size and data distribution, developing your version of the Contoso database. Contoso Data Generator is a free open source tool to generate sample Contoso databases on SQL Server based on a star schema.
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