The Process Data command is run on each table in the model, typically in a multi-threaded asynchronous manner.
Ssas tabular model with adventureworks database full#
In addition, this technique can be used regardless of your processing strategy.ĭuring a Full Process there are two primary stages: Process Data Command and Recalc. While there are many processing strategies, we will focus on a Full Process strategy as it is very simple to implement and very common. Understanding how the Analysis Services engine works in detail, and following tabular development best practices, can allow for the most efficient processing from the beginning. After gaining more experience with a specific model and across many models, it becomes easier to gauge if processing is taking longer than expected. However, it is still up to the developer to determine if those times seem too long. Knowing the amount of time of each step during processing allows insight into where to further investigate. It is also important to note that, while processing times for a model may be taking longer than anticipated, it could be that the model is already running as efficiently as possible. Once you understand what is taking the most time, it becomes easier to focus on what can be done to improve performance. It can sometimes be hard to understand which part is taking the most time. The step of processing a model can be time-consuming for many reasons. Processing a tabular model is the necessary step to bring data from one or more sources and transform it into a compressed in-memory data structure. In this post I’d like to share a technique that may help identify an opportunity to improve processing performance. In my experience, I have answered “yes” to both questions. Have you ever wanted to decrease the processing time so you can process the tabular model more often?
Have you ever developed or worked on tabular models that take longer to process than you expect?
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