You deploy a tabular data model to an instance of Microsoft SQL Server Analysis Services (SSAS). The model uses an in-memory cache to store and query data. The data set is already the same size as the available RAM on the server. Data volumes are likely to continue to increase rapidly.
Your data model contains multiple calculated tables.
The data model must begin processing each day at 2:00 and processing should be complete by 4:00 the same day. You observe that the data processing operation often does not complete before 7:00. This is adversely affecting team members.
You need to improve the performance.
Solution: Change the storage mode for the data model to DirectQuery.
Does the solution meet the goal? residing in-memory, even complex queries can be incredibly fast. However, there are some limitations to using cached data. Namely, large data sets can exceed available memory, and data freshness requirements can be difficult if not impossible to achieve on a regular processing schedule. efficient. data (in the in-memory cache). Changes to the underlying source data can be immediately reflected in queries against the data model.
A.
Yes
B.
No
Explanation:
By default, tabular models use an in-memory cache to store and query data. When tabular models query data
DirectQuery overcomes these limitations while also leveraging RDBMS features making query execution more
With DirectQuery: +
Data is up-to-date, and there is no extra management overhead of having to maintain a separate copy of the
Datasets can be larger than the memory capacity of an Analysis Services server.
Etc.
References:https://docs.microsoft.com/en-us/sql/analysis-services/tabular-models/directquery-mode-ssastabular