In addition to understanding which query engine is affecting performance, it’s essential to identify specific query and system attributes that are contributing to performance problems. Key areas to investigate when troubleshooting query performance issues
Less than 50% of the Query Begin/End total time, the problem is in the formula engine. 50% or more of the Query Begin/End total time, the problem is in the storage engine. To determine which engine is the source of the problem, add up the cumulative durations indicated in Query Subcube/Verbose, Progress Report Begin/End, Get Data from Aggregation, VertiPaq SE Query Begin/End, and Direct Query End and compare to the Query Begin/End total time. Time spent querying back to the relational data source for the data This data is stored, pre-calculated data typically needed to handle the workload in the environment (Multidimensional mode)ĭuration the formula engine is querying to the storage engine (Tabular mode) Time spent getting data from aggregations. The following table provides details on the Profiler trace events that are most important when troubleshooting SSAS performance challenges.ĭuration the formula engine is querying to the storage engine (Multidimensional mode)īegin and end of file reads (Multidimensional mode) Once you've ruled that out, SQL Server Profiler trace events can determine which query engine-formula or storage-is creating the bottleneck. The first thing you need to determine when looking at performance problems is whether processing activities are happening at the same time as querying activities. In Tabular mode, data is typically already in-memory, unless there are paging or memory pressure issues usually has no physical I/O. In Multidimensional mode, can read from the file system on the server both physical disk input/output (I/O) as well as Windows file cache. 
The table below breaks down the primary features of each type of engine. Either engine can be the source of a performance bottleneck troubleshooting identifies which engine is the problem. When performing queries, SSAS uses two primary engines: the formula engine and the storage engine.
Similar to backups on relational databasesįinding the source of SSAS performance bottlenecks. Creates or updates data and recalculates and reorganizes existing data, primarily through XML for Analysis (XMLA). Similar to querying relational databases. Data Analysis Expressions (DAX) most often used in Tabular mode. Multidimensional Expressions (MDX) most often used in Multidimensional mode. Many of the same concepts and best practices applied to queries and backups in relational databases such as SQL Server can be applied to or used to understand querying and processing in SSAS. Querying and processing activities affect SSAS performance-whether you’re using Multidimensional mode or Tabular mode.
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