Calculation View Features of QRC2 2022

Within the time frame of 2022 QRC2, several new calculation view features have been released in SAP HANA Cloud that can be used with SAP Business Application Studio. Some of these features are highlighted below.

You can find examples that illustrate the individual features here. An overview of features of other releases can be found here.

Calculation View Snapshots

In tab “Snapshots” you can define individual queries for calculation views. Based on these queries procedures are generated that create, drop and insert into snapshot tables:

Define a snapshot query

This provides a flexible means to store results as they are at a certain point in time. The life-cycle of these procedures is controlled by the calculation view.

In addition, a calculation view can be generated to easily toggle between the online and snapshot data:

Generate Interface View

Interface View that implements constant union pruning

With snapshots you have now an easy and flexible means to serve queries that do not need online data and by this reduce resource consumption. See the modeling guide and performance guide for developers for more information.

Comments in Expressions

Use comments in expressions to better document the intention behind expressions. This will help during later refactoring and improve collaborative working.

Comments can be entered using one of the two styles:

/* comment */

-- comment

Comments in calculated columns

Comments in filter expressions

Mapping of Session Variables

Session variables can now be mapped into input parameters. This helps to re-use existing calculation views with input parameters in scenarios in which session variables should be used.

Example

Input parameter “IP_temperature” is filled by session variable “SV_temperature”

Input parameter “IP_temperature” is used to filter on column “temperature”

SELECT
    "SalesOrderID",
    "temperature",
    SUM("year") AS "year",
    SUM("amount") AS "amount"
FROM "mapSessionVariable"
    (placeholder."$$IP_MinimumID$$"=>'1')
GROUP BY
    "SalesOrderID",
    "temperature"

Results

a) Setting session variable to “old” data

SET 'SV_temperature'='old';

b) Setting session variable to “new” data:

SET 'SV_temperature'='new'

Median Aggregation