Within the time frame of 2022 QRC3, 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.
Greedy Join Pruning
Greedy join pruning is an expert performance technique that allows pruning to occur independent of join type or cardinality settings. Greedy join pruning can speed up queries considerably when a query involves multiple joins. However, in contrast to join pruning it can have an impact on the results. Therefore, make sure to familiarize yourself with the technique, e.g., in the Developer Performance Guide
greedy pruning options
Greedy join pruning improves performance by join pruning optimization techniques that can be leveraged by expert calculation view modelers.
The graphical support of greedy join pruning is planned to become available with the SAP Business Application Studio release in October 2022.
Lineage/Impact Analysis Across HDI containers
Until now starting a lineage or impact analysis only listed objects within the same HDI container. It is now possible to track the dependency that includes objects that are outside of the current HDI container.
This will provide more detailed insights into data processing and dependencies of calculation view models
Intermediate Data Preview
It is now possible to separate the authorizations to run an intermediate data preview from the authorizations that are required to deploy into a container. With this it becomes easier to debug in e.g., productive containers while preventing the modification of productive objects.
Debugging can now happen with help of a user-provided service based on a database user with the authorizations to run a data preview but without privileges to change objects in the container. See blog for more details
start intermediate data preview
Using the intermediate data preview also for debugging productive HDI containers can speed-up the time for issue resolution.
System-Versioned and Application-Time Tables
When using system-versioned or application-time tables in calculation views, temporal timestamps can now be defined based on constants or input parameters to evaluate data in tables as of a certain timestamp or period. The timestamps can be selected for each individual data source using constants, expressions, or input parameters.
This simplifies time-traveling analytics with focus on data as of a certain time point or period.