# Cube Calculation Views

Objectives
After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

• Create a cube calculation view using the graphical calculation view editor

## Cube Calculation Views

When you would like to create a calculation view that includes measures, you use a calculation view of the type cube.

By default, all the measures in this type of calculation view will always be aggregated by the attributes requested by the query. So, even though the calculation view may be able to provide many attributes, the measures are always automatically aggregated only by the attributes that were requested by the query.

For example, your cube calculation view provides the measure: revenue, and the attributes: country and city. The query requests only country, and so revenue is summed by country and not by city. If the next query requests the measure: revenue, and the attributes: country and city, then the revenue would be summed by city and also country. This means you would have two levels of aggregation.

This type of calculation view is optimized for ad-hoc analysis, where unpredictable slice and dice is required over the measures by any combination of attributes within the model.

## Cube with Star Join Calculation View

An extension to the cube calculation view is the cube with star join.

In addition to the capabilities of the cube type of calculation view, a cube with star join calculation view allows you to connect dimension calculation views so that you significantly expand the analysis capabilities by providing additional attributes. For example, if you create a sales cube calculation view, which provides only limited attributes such as a product number, you could then join the product dimension calculation view to provide many more product related attributes such as product description, supplier, color and price. You could then aggregate the sales revenues by product color, supplier and so on.

Cube with star join calculation views are the most advanced type of calculation view and are popular in analytical scenarios where ad-hoc analysis is required. Cube with star join calculation views are processing by a dedicated SAP HANA Cloud OLAP engine to provide high performance.

The type of joins between the fact and dimension tables within the star schema can be defined in the Star Join node. The available joins are as follows:

• Referential Join

• Inner Join

• Left Outer Join

• Right Outer Join

• Full Outer Join, with some specific restrictions (see above)

• Text Join

### Shared Columns from DIMENSION Calculation Views

In a cube with star join calculation view, the Columns tab of the Semantics node separates columns into two categories:

• Private

Private columns are columns that are defined inside the calculation view itself. These can be measures or attributes. You have full control over these columns.

• Shared

Shared columns are columns that are defined "externally", in one or more dimension calculation views that are referenced by your cube with star join calculation view. On these columns, you have logically less control, because they are potentially "shared" with other cube with star join calculation view. Still, you can hide some of these columns to keep only the ones that you need.

Regarding the shared columns, their Name and Label properties cannot be changed, compared with a private column, but you can define an Alias Name and an Alias Label. Moreover, providing Alias Names is mandatory if column names from the underlying dimension calculation views conflict with each other or conflict with the private column names.

## Create a CUBE with Star Join Calculation View

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