![]() ![]() Support for Power BI DirectQuery semantic models To ensure query processing does not overburden your data source, use the MaxParallelism property setting to specify a fixed number of threads that can be used for parallel operations. By executing operations in parallel, the Analysis Services engine can improve query performance by taking advantage of scalability large data sources may be able to provide. The engine can then execute those operations against the data source in parallel. This improvement enables the Analysis Services engine to analyze DAX queries against a DirectQuery data source and identify independent storage engine operations. DAX queries run faster with Horizontal Fusion, especially in DirectQuery mode. Fewer data source queries mean fewer round trips and fewer expensive scans over large data sources, which results in sizeable DAX performance gains and reduced processing demand at the data source. Multiple smaller data source queries are fused together into a larger data source query. This version introduces Horizontal Fusion, a query execution plan optimization aimed at reducing the number of data source queries required to generate and return results. Generally Available (GA) Horizontal fusion ![]() This enhancement may require you to upgrade tabular and multidimensional model databases to ensure proper encryption. This update includes enhancement to the schema write operation encryption algorithm. SQL Server 2022 Analysis Services Cumulative Update 1 (CU1) Encryption upgrade ![]()
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