The NON EMPTY CrossJoin causes the result to include only those rows where data is available for the specified measures and the WHERE clause limits the results to the year 2014. The following screenshot shows the results based on AdventureWorks sample data, listing the average unit price and total sales amount for each product subcategory and category. Without going into too much detail, let’s look at a simplified but nonetheless typical MDX query that Excel might generate for a PivotTable against a Power BI dataset. Note that MDX Fusion is not available with SQL Server Analysis Services 2019 or earlier. The corresponding MDX Fusion idea received several hundred votes on, and we are happy to announce availability of MDX Fusion at this point. Fewer SE queries mean fewer expensive scans over large datasets, which ultimately results in sizeable performance gains especially when connecting to a Tabular model or Power BI dataset in Direct Query mode. With MDX Fusion, the most common MDX query patterns can now trigger far fewer SE queries where previously numerous such SE queries were necessary for different granularities. The MDX query performance improvement is the result of a clever Formula Engine (FE) optimization aimed at reducing the number of Storage Engine (SE) queries per MDX query, similar to DAX optimizations known as DAX Fusion. For example, Excel users connecting to a Power BI dataset by using the Analyze in Excel feature, the XMLA endpoint, or the newly announced Power BI Datasets within Excel feature, will now notice significantly better PivotTable performance out of the box.
This MDX performance improvement alleviates some of the optimization burden for measures used in a PivotTable.
ANALYSIS SERVICES TABULAR VS MULTIDIMENSIONAL UPDATE
With a recent update of the Analysis Services Tabular engine in Power BI, Multidimensional Expressions (MDX) clients, such as Microsoft Excel, can now enjoy improved query performance.
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