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Calgary is a list count data retrieval engine designed to perform analyses on large scale databases containing millions of records. One use case for a Calgary database in an App or Macro is to offer users certain predetermined criteria (e.g. geography) to select and then return the corresponding data to them. A back-end process can combine multiple data sources, format and pre-filter as needed, and load them into a Calgary database that can be queried quickly by the app or macro . This way, the bulk of the processing happens outside of the app or macro allowing data to be returned more quickly.
Calgary Regression Test Module Business Problem: If you have recurring updates on Calgary files then this module will likely be useful to you. When a Calgary fiIe is updated, it is imperative to be able to check the file for consistency. Depending on the number of columns and indices contained in the file, this can sometimes pose a challenge. Actionable Results:
Compare two versions of a Calgary file to determine if columns and indices remain constant
Complete regression testing through a simple application interface
Easily identify indices where counts have changed over 10%
Overview: Have you ever found yourself in a situation where you want to compare a newly built Calgary file with the previous iteration, in order to see if all the columns are still there, the indices are still there and that they give similar results as the last time? This Module does just that, and gives you a nicely edited document showing the results. For the querying, the app goes through all the indices that are in the Calgary directory, selects a random value from the file to use as the query value, and compares counts from the new and the old dataset, highlighting in red if the counts are more than 10% different. Vertical: Any Required Input: Calgary file with indices (previous and updated versions you wish to test) Application Process: For best results, run as a .yxwz instead of a .yxmd. In the application interface, just navigate to the two files and press Start. Be aware that if you have a lot of indices and a lot of data, it may take a while to run, so if you just want to try it out, start with something small.