SAP C_HAMOD_2404 - SAP Certified Associate - Data Engineer - SAP HANA

TheKeep Flagproperty in an aggregation node ensures that columns not directly requested by a query are still included in the calculation process if they are critical for the correctness of the result. For example, these columns may serve as grouping or filter criteria in intermediate processing stages, even if not explicitly displayed in the final query output.

The characteristics of aSHARED replica tableinclude:

B. The replica table always stores real-time data: Ensures synchronization with the source table.

D. You can toggle queries routing between remote table data and replica table data: Flexibility in query routing allows efficient use of data.

E. You do not need to create the physical replica table manually: It is automatically created during the replication setup.

Virtual tables (A) are not referenced directly by consuming applications, and replica table naming (C) is typically system-defined.

Avoid defining joins on calculated columns (A):Joins on calculated columns can significantly impact performance because they require calculations before the join operation. It is better to minimize such scenarios.

Include all data flow logic within one calculation view (B):Consolidating logic within a single calculation view reduces complexity and improves maintainability, avoiding unnecessary data movement across multiple views.

Options C and D are less optimal because defining filters or aggregations on calculated columns can increase the computational overhead.

Parameter mapping in SAP HANA calculation views serves several purposes:

To push down filters to the lowest level calculation views:By mapping input parameters from a higher-level calculation view to those in underlying views, filters applied at the top level are propagated down to the base views. This ensures that data is filtered as early as possible in the data processing pipeline, reducing the volume of data transferred and processed, thereby enhancing performance.

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To pass variable values to external value help views:When using external views to provide value help (i.e., lists of possible values) for variables or input parameters, parameter mapping allows the values entered by the user to be passed to these external views. This enables dynamic and context-sensitive value help, improving the user experience by presenting relevant options based on prior selections.

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Options B and D are not correct in this context:

To convert the data types of input parameters:Parameter mapping does not inherently perform data type conversion. Data type consistency must be ensured when defining input parameters and their mappings.

To assign variables to one or more attributes:Parameter mapping is not used to assign variables to attributes; rather, it links input parameters and variables between different calculation views or external sources.

CREATE VIRTUAL TABLE on the remote source (B):This privilege allows the creation of virtual tables that reference remote tables in the target schema.

CREATE ANY on the target schema (C):This privilege ensures that virtual tables can be created in the specified target schema.

Option A (SELECT on the source object) and D (ALTER on the remote source) are not sufficient or required for creating a virtual table.

SQL expressions in a calculation view are used for dynamic data transformations and filtering. They can:

A. Generate a restricted column: Apply conditions to create columns with restricted values.

B. Define a filter: Apply SQL conditions to filter data dynamically.

C. Generate a calculated column: Derive new column values using calculations or expressions.

SQL expressions are not typically used for creating hierarchies (D) or currency conversion (E); these are handled by specific features or nodes in SAP HANA calculation views.

Areferential joinis chosen to ignore unnecessary data sources, as it assumes that corresponding records exist in the target table for every record in the source table. This join type avoids querying the target table when the data is not required, improving performance while maintaining logical integrity.

TheDynamic Joinoption in SAP HANA calculation views enables flexibility when joining tables with multiple columns. The reasons for enabling it include:

B. To allow data analysis at different levels of granularity with the same calculation view: Dynamic joins adjust to the query’s granularity requirements, enabling analysis at various levels without redesigning the calculation view.

D. To ensure that the join execution uses only the join columns requested in the query: This ensures efficient execution by only processing the relevant columns, reducing unnecessary computations.