![]() On the first load, a sample set of data will be checked to determine the best type of encoding applicable for that column. One can’t do math on hash encodingĮncoding is done automatically to conserve space. ![]() DATA ID is the index allocated to the string when it is inserted in the table for the first time. Useful for very sparse value distribution. You could then subtract 15 to get to a smaller number that has to be stored (DATA ID) 1.5, 2.5 and 3.5 will be multiplied by 10 to get a whole number. Value: one just has to do math to get to the answer.Encoding: everything is converted to integers, even strings (as it is the fastest data type).When loading data, it goes through various stages: Accommodate changes without forcing reload, if possible.Query Performance is much more important than Processing Performance.The xVelocity engine is designed with 3 principles in mind: Here is a small summary with screen shots from the session. I can really recommend watching the presentation which is available at: They discuss all the ins-and-outs of the xVelocity engine. The extracts below were all taken from a session conducted by Ashvini Sharma and Allan Folting at TechEd North America 2012. This will also result in better compression in the Tabular model. This is true for both Tabular and Multi-dimensional projects. Good practice dictates pushing as many calculations as far back as possible e.g. Best practices around processing and query optimisation ![]() Here is a good blog from Dan English talking to retail and marketing calendars and how to deal with the relevant DAX time calculations: ģ. The date time column in the Time table should be at day granularity (without fractions of a day).For instance, even though your transaction table may only have sales data up to May 2012, the Time table should have dates up to December 2012 (same goes for fiscal years). ![]()
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