nerdexam
Microsoft

70-467 · Question #80

You need to scale out SSAS. What should you do?

The correct answer is D. Synchronize the cube from ServerB to ServerC each day. SSAS scale-out separates processing from querying by synchronizing the fully processed cube from a processing server to one or more dedicated query servers.

Design BI infrastructure

Question

You need to scale out SSAS. What should you do?

Options

  • ABack up the cube on ServerB and restore it on ServerC each day.
  • BCreate an empty cube on ServerC and link to the objects in the cube on ServerB.
  • CProcess the cube on both ServerB and ServerC each day.
  • DSynchronize the cube from ServerB to ServerC each day.

How the community answered

(46 responses)
  • A
    15% (7)
  • B
    7% (3)
  • C
    2% (1)
  • D
    76% (35)

Why each option

SSAS scale-out separates processing from querying by synchronizing the fully processed cube from a processing server to one or more dedicated query servers.

ABack up the cube on ServerB and restore it on ServerC each day.

Backup and restore is a disaster recovery and migration technique - it is slower and more manual than synchronization, and is not designed as a recurring scale-out mechanism.

BCreate an empty cube on ServerC and link to the objects in the cube on ServerB.

Linked objects in SSAS allow referencing metadata objects from another database but do not replicate cube data to another server, so query load is not actually distributed.

CProcess the cube on both ServerB and ServerC each day.

Processing the cube independently on both servers each day risks data inconsistencies between nodes if source data changes mid-process, and it doubles processing resource costs without using the proper synchronization pattern.

DSynchronize the cube from ServerB to ServerC each day.Correct

SSAS supports a scale-out architecture where one server handles resource-intensive cube processing and the completed database is then synchronized to one or more read-only query servers using the Synchronize Database command or XMLA. This isolates processing overhead from user query traffic, ensuring query servers remain responsive. Daily synchronization keeps query servers current while avoiding the cost of redundant reprocessing on each node.

Concept tested: SSAS scale-out via cube database synchronization

Source: https://learn.microsoft.com/en-us/analysis-services/multidimensional-models/synchronize-analysis-services-databases

Topics

#SSAS synchronization#cube scale-out#SSAS high availability#read-only replica

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