![]() ![]() Add the literal value “\t” to add a tab separator, and then repeat the process used for LastName and FirstName values using names_t.ģ) Run CreateNamesSet.rcl with RowGen, either on the command line or from the IRI Workbench GUI, to produce the tab-delimited t file of first and last names, which will be used in both the generation of usernames and in the final test file build that populates our prototype collection.įor Usernames, we will create a set file that utilizes the t file generated above. Name the first field “LastName” and choose the method that will select values from an IRI-provided set file called “names_t”. A set file is a list of one or more tab-delimited values that may already exist, or need to be generated manually or automatically from database columns through the ‘Generate New Set File’ wizard in IRI RowGen.ġ) Create a compound data value (first and last names combined) job script named “CreateNamesSet.rcl” that RowGen can execute to produce a set file call the output “t” because these names will also be used as the basis for our usernames.Ģ) Create three fields to be generated in t: last name, tab separator, and first name. ![]() ![]() To create our test data, we must first generate some set files. In the example, we know that our collection will be made up of customers who all have Usernames, First and Last Names, Email Addresses, and Credit Card Numbers. See this article for typical planning considerations. You must first consider the structure and content of the test data for your collection (MongoDB table) needs. This article explains how to create test data MongoDB can use via IRI RowGen, specifying the parameters for a synthetic, but realistic, CSV file that MongoDB can import for functional and performance testing. Note that both FieldShield and RowGen are included in the IRI Voracity data management platform, which offers four ways to create test data.Īlthough MongoDB is a fine cross-platform, document-oriented NoSQL database, it has no convenient way to generate and populate large or complex collection prototypes that can be used to test queries or plan capacity. ![]() This means you can use RowGen to generate test JSON files for import into MongoDB (not unlike the method shown below in this article), or use FieldShield to mask data in Mongo tables into test targets. As you will read, RowGen would create the necessary test data and create a CSV file that would be loaded into MongoDB using the Mongo Import Utility.Ģ019 Update: IRI now also offers JSON and direct driver support to move data between MongoDB collections and SortCL-compatible IRI software products like RowGen or FieldShield. Introduction: This example demonstrates an older method of using IRI RowGen to generate and populate large or complex collection prototypes for testing or system capacity using flat files. ![]()
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