Recently, I was faced with two different questions at two different events and both of questions were directly or indirectly linked to high availability of cubes for querying. Those two questions were:
1) What is the difference between scale out and scale up?
2) How would use ensure 24 x 7 availability of a cube, considering the point that globally users are accessing the cube, and the cube should always remain available for querying?
The answer to the first question is when you need to achieve parallelism for concurrency in querying or processing, you distribute / replicate processing operations and/or data on multiple nodes. Scale up usually means that you increase the capacity of the host to enable the server to cater the incoming load. When the capacities of scaling up ends, scaling out steps in.
The next question was quite interesting, and the challenge was that I was in a situation to instantly think of a design and answer this query. I answered this question correctly, and to my delight, I found this whitepaper which is exactly what I answered. Such moments bring a lot of happiness and confidence that my knowledge has not gone stale and I can continue to provide consulting in MS BI business.
The presentation layer is coupled with SSAS query server. Data is read from relational engine and cube is processed on a separate server, which can be considered another layer altogether. After the cube is processed, query server and processing server are synchronized. For multi-server synchronization, SSIS is used. The below two diagrams demonstrates the same. Entire whitepaper can be read from here.
1) What is the difference between scale out and scale up?
2) How would use ensure 24 x 7 availability of a cube, considering the point that globally users are accessing the cube, and the cube should always remain available for querying?
The answer to the first question is when you need to achieve parallelism for concurrency in querying or processing, you distribute / replicate processing operations and/or data on multiple nodes. Scale up usually means that you increase the capacity of the host to enable the server to cater the incoming load. When the capacities of scaling up ends, scaling out steps in.
The next question was quite interesting, and the challenge was that I was in a situation to instantly think of a design and answer this query. I answered this question correctly, and to my delight, I found this whitepaper which is exactly what I answered. Such moments bring a lot of happiness and confidence that my knowledge has not gone stale and I can continue to provide consulting in MS BI business.
The presentation layer is coupled with SSAS query server. Data is read from relational engine and cube is processed on a separate server, which can be considered another layer altogether. After the cube is processed, query server and processing server are synchronized. For multi-server synchronization, SSIS is used. The below two diagrams demonstrates the same. Entire whitepaper can be read from here.
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