Graphical calculation views in SAP HANA are designed to model data flows based on tabular data sets. A data source node in a graphical calculation view must provide a structured, tabular result.

- Table Function: A table function is a user-defined function that returns its result as a table. This makes it a valid and powerful data source, allowing complex procedural logic to be encapsulated and used within a graphical model.

- Row Table: SAP HANA supports both row-store and column-store tables. Both types can be used as fundamental data sources in a calculation view. The graphical modeler allows the inclusion of any table from the catalog, irrespective of its underlying storage type.

B. Procedure: A procedure is a unit of procedural logic that is called for execution and does not return a table directly in a way that can be consumed as a data source node in a graphical flow.

D. Scalar function: A scalar function returns a single value, not a table. While it can be used within expressions (e.g., for a calculated column), it cannot serve as a primary data source node.

1. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Business Application Studio:

Section: "Add Data Sources to the Calculation View"

Content: This section explicitly lists the objects that can be used as data sources. It states

"You can add data sources such as tables

views

calculation views

and table functions to the calculation view editor." This directly supports options A (Table function) and C (Row table

as it is a type of table).

Reference: SAP Help Portal

SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Business Application Studio

"Calculation Views" -> "Model Data" -> "Add Data Sources to the Calculation View".

2. SAP HANA SQLScript Reference:

Section: "User-Defined Functions"

Content: This guide differentiates between table functions and scalar functions. It defines a table function as returning a value of type table (RETURNS TABLE (...)) and a scalar function as returning a single scalar value (RETURNS ). This distinction clarifies why a table function is a valid data source (it provides a table) while a scalar function is not.

Reference: SAP Help Portal

SAP HANA SQLScript Reference

"User-Defined Functions".

A referential join is a performance optimization technique used in SAP HANA Calculation Views. It is semantically similar to an inner join but operates under the assumption that referential integrity is maintained between the two tables (i.e., for every row in the fact table, a corresponding entry exists in the dimension table). The primary benefit is that the query optimizer can engage in "join pruning." If a query does not request any columns from the dimension table (the right table), the optimizer can completely avoid executing the join, thereby ignoring the unnecessary data source and improving query performance.

A. A referential join assumes referential integrity, which is related to cardinality, but it does not automate the setting of cardinality rules. The modeler must still define them.

B. Reusing join settings is not a specific function of the referential join type; it's a more general modeling environment feature, if available at all.

C. While referential joins are often used in a series (e.g., in a star schema), this is not the reason for choosing this specific join type over others like inner or left outer joins.

1. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Business Application Studio

Section: "Creating Joins in the Join Node".

Reference Detail: The guide states

"The referential join is an optimized join... The query optimizer can decide to not execute the join if the fields from the right table are not requested by the query." This directly supports the concept of ignoring an unnecessary data source for performance.

2. SAP HANA Cloud

SAP HANA Database Performance Guide for Developers

Section: "Join Pruning".

Reference Detail: This guide explains join pruning as a key optimization feature. It details that when referential joins are used and the dimension table attributes are not needed

the join is eliminated from the execution plan

which is the technical basis for the correct answer.

The simplest and most direct approach to pivot data from rows into columns within a cube calculation view is to use restricted columns (also known as restricted measures). This feature is specifically designed for this purpose. You can create a separate restricted column for each year (e.g., 2021, 2022, 2023) based on the original sales measure. Each restricted column will have a filter applied to it based on the 'YEAR' attribute. This method is declarative, easy to implement in the graphical editor, and is the standard best practice for this common reporting requirement, making it the simplest solution.

A. Create a filter expression that uses an OR operator.

This would only filter the rows to include the specified years but would not transform the row values into separate columns for each year.

B. Create 3 calculated columns.

While functionally possible using IF or CASE statements, this is more complex than using restricted columns and is not considered the simplest or most optimized approach.

C. Implement a union node and map each year as a separate column.

A union node combines result sets vertically (adds rows). Using it to create columns is a highly complex and inefficient workaround, not a simple approach.

1. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Business Application Studio

Section: "Creating Restricted Measures".

The guide states

"Restricted measures allow you to filter a measure by one or more dimensions... This is a common requirement in reporting

for example

to show the revenue of the current and the previous year side-by-side." This directly validates that using restricted measures (columns) is the intended and standard method for the scenario described in the question.

2. SAP HANA Modeling Guide for SAP HANA Studio (HANA 2.0 SPS 07)

Section: "Create Restricted Columns".

This document explains

"You can restrict the values of a measure based on the values of one or more attributes... For example

to view the net sales for a specific region

you can create a restricted column on the net sales measure and restrict the values for a specific region." This confirms the purpose of a restricted column is to create a new measure column based on a filter condition

which is precisely what is required to create a separate sales column for each year.

The Debug Query mode for a calculation view is a specific analysis tool within the SAP HANA development environment. Its primary purpose is to help developers understand how the SAP HANA optimizer executes a specific SQL query against the view. It visually displays the logical model of the calculation view and highlights which nodes (data sources) were actually accessed and which were "pruned." Pruning is an optimization technique where the engine avoids reading from data sources that are not necessary to satisfy the columns and filters of the query, significantly improving performance.

A. To set breakpoints and step through the execution

This describes the functionality of the SQLScript Debugger, which is used for debugging procedural code within procedures, functions, or calculation view script nodes, not for analyzing the data flow of the entire graphical view.

C. To understand how tables are partitioned

Table partitioning is a physical storage characteristic. Information about partitioning is found in system views (e.g., MTABLEPARTITIONS) or through database administration tools, not the calculation view debugger.

D. To check which database engines are invoked

While related to performance, the detailed breakdown of which engines (OLAP, Join, Calculation Engine) are used for specific operations is best seen using the "Visualize Plan" or "Explain Plan" features.

1. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Web IDE for SAP HANA:

In the section "Analyzing Queries on Calculation Views

" the subsection "Debug a Calculation View" states: "You can use the debug query feature to analyze an SQL query on a calculation view... The debugger helps you understand the data flow in the calculation view nodes and to identify the nodes that are not executed (pruned nodes) for a given SQL query." This directly supports the function of identifying un-accessed data sources.

2. SAP HANA Modeling Guide for SAP HANA Studio (SPS 12):

Section 5.1.10.2

"Debugging Calculation Views

" explains: "The debugger helps you understand the data flow in the calculation view nodes and to identify the nodes that are not executed (pruned nodes) for a given SQL query." This confirms that identifying pruned nodes is the key feature.

3. SAP HANA SQLScript Reference:

The section on "Debugging SQLScript" details the procedure for setting breakpoints and stepping through code

which clearly distinguishes it from the Debug Query mode for graphical views

thereby invalidating option A.

In SAP HANA Calculation Views, when creating a parent-child hierarchy, you must define how to handle orphan nodes (nodes whose specified parent does not exist in the dataset). The system provides several options for this scenario. Two of these options are to treat each orphan node as a new root node, effectively creating a hierarchy with multiple roots (a forest), or to assign all orphan nodes as direct children of a single, specified, existing root node (e.g., an 'Unassigned' category).

A. The parent for an orphan node is assigned based on predefined rules (e.g., making it a root or assigning to a specific node), not by a dynamic expression.

B. Assigning orphan nodes to a leaf node is structurally invalid, as a leaf node, by definition, cannot have children.

1. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Business Application Studio

Section: "Create Parent-Child Hierarchies".

This guide details the properties of parent-child hierarchies. For the "Orphan Nodes" property

it explicitly lists the options: Error

Ignore

Root Nodes

and Assign to Root Node. This directly supports options D ("Define them as additional root nodes" which corresponds to Root Nodes) and C ("Assign them to an existing node at the root level" which corresponds to Assign to Root Node).

2. SAP HANA Platform 2.0 SPS 07

SAP HANA Modeling Guide

Chapter: "Creating Hierarchies"

Section: "Create Parent-Child Hierarchies".

Page/Section Reference: In the "Properties of Parent-Child Hierarchies" subsection

the handling of "Orphan Nodes" is described. The available settings confirm that orphans can be treated as Root Nodes or assigned to a specific Root Node

validating answers C and D. The guide does not mention assignment via expression or to a leaf node.

In SAP HANA graphical calculation views, the UNION node combines the result sets of its data sources, behaving like a SQL UNION ALL operation. This means that if the same customer name exists in both source tables, it will appear twice in the output of the union node. To remove these duplicates and ensure each customer name appears only once, an AGGREGATION node must be placed above the UNION node. By grouping the data by the customer name column in the aggregation node, the result set is consolidated, effectively producing a distinct list of customer names.

A. Define a restricted column in a union node.

A restricted column is used to filter the data from a source before the union operation occurs, not to deduplicate the combined result set after.

B. Add an intersect node above the union node.

An INTERSECT node returns only the rows that are common to all data sources. This would incorrectly exclude customers that exist in only one of the two tables.

D. In the union node, map both source customer name columns to one target column.

This mapping is a required step to configure the UNION node itself. However, it only combines the data into a single column; it does not perform any deduplication.

1. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Business Application Studio

"Create Union Nodes": This guide explains that the union node is used to combine result sets. The standard behavior is to append results

not to automatically remove duplicates. The subsequent step for deduplication is aggregation. (Reference: The concept is foundational to the tool's operation

described in the section on Union nodes).

2. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Business Application Studio

"Create Aggregation Nodes": This section details how aggregation nodes are used to summarize or group data. It states

"You can use the aggregation node to summarize data for a group of rows by calculating values in a column." Grouping by the customer name column without applying a specific aggregate function (or using MIN/MAX) on it results in a distinct list. (Reference: Section on Aggregation Node functionality).

3. HA300 - SAP HANA 2.0 SPS07 - Modeling

Unit 4: Calculation Views

Lesson: Using Union Nodes and Lesson: Using Aggregation Nodes. The official SAP courseware demonstrates that a UNION node combines data sources and an AGGREGATION node is subsequently used to group data

which is the standard method for achieving a DISTINCT result on specific columns within the graphical editor.

The correct procedure for implementing currency conversion on a measure within an SAP HANA Calculation View begins with defining the column's semantics. The measure must be assigned the semantic type "Amount with Currency Code" to link it to its corresponding currency unit column. Following this, the conversion feature is explicitly enabled for that specific measure. The final step involves configuring the conversion parameters, which includes specifying the source and target currencies, the client, the conversion date, and the exchange rate type to be used for the lookup in the currency tables (e.g., TCURV, TCURR, TCURX).

A: Defining an expression in a calculated column is a manual approach; SAP HANA provides a built-in, optimized engine for currency conversion that does not require manual expressions.

B: The conversion logic is configured directly on the properties of a specific measure, not as a separate rule that is assigned to the entire calculation view.

D: This option is less precise. "Build the conversion rule" is a vague description of the configuration steps that are explicitly and correctly detailed in option C.

1. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Business Application Studio

Section: "Model Business Scenarios"

Subsection: "Converting Currencies in Calculation Views". This guide explicitly states

"To convert currencies

you must first assign the semantic type

Amount with Currency Code to the measure... In the properties pane of the measure

set the Enable for Conversion toggle button to ON." It then details the configuration of source/target currency

conversion date

and rate type.

2. SAP HANA Modeling Guide (for SAP HANA Platform)

Section: "Creating Calculation Views"

Subsection: "Applying Currency Conversion". This document outlines the same prerequisite: "In the Semantics node of the view

select a measure... and assign the semantic type Amount with Currency Code." It then describes enabling the conversion and setting the parameters like Target Currency

Exchange Rate Type

and Conversion Date.

The OPTIMIZED linked database feature is a specific SAP HANA capability designed for efficient cross-database queries exclusively between SAP HANA systems. Its primary characteristic is simplifying data access by eliminating the need for virtual tables, which are required by the more general Smart Data Access (SDA) feature. Instead, users can directly query remote objects using a three-part naming convention: ... This direct access, combined with the homogeneous HANA-to-HANA landscape, allows the query optimizer on the target (local) system to have full knowledge of the remote database's objects and statistics, leading to highly optimized execution plans.

A. While metadata caching is used to achieve optimization, the more fundamental characteristics are the feature's scope (HANA-to-HANA) and its unique syntax, which enable these optimizations.

B. The Linked Database feature is explicitly designed to avoid the creation of virtual tables (hidden or otherwise), which is its main simplification compared to standard Smart Data Access (SDA).

1. SAP HANA Cloud

SAP HANA Database Administration Guide

Section: "Linked Database".

This guide states

"Linked database is a feature for executing cross-database SELECT queries between SAP HANA databases." This directly supports option C.

It also specifies the access method: "Instead

you can directly access tables in the remote database using the syntax ..." This directly supports option D and refutes option B.

2. SAP Note 2919784 - FAQ: SAP HANA Linked Database

Version 4

Published 2023-08-08.

The note's answer to "What is Linked Database?" reiterates that it is for "cross-database SELECT queries between SAP HANA databases" (C) and that "Instead of creating virtual tables for remote tables

you can directly access tables in the remote database using the syntax..." (D)

which explicitly contradicts B.

3. SAP HANA Platform 2.0 SPS 07

SAP HANA Administration Guide for SAP HANA Platform

Section: "2.10.3 Linked Database".

This document describes Linked Database as a "simplified alternative to Smart Data Access for HANA-to-HANA scenarios" (C). It also highlights the benefit that "No virtual tables are required on the local database" (refutes B). The optimizer's "full knowledge" is mentioned as the key to optimization

which is enabled by the HANA-to-HANA context.

The performance of SAP HANA calculation views is critically dependent on their design and complexity. Aggregating data as early as possible within the view's data flow is a core optimization principle. This reduces the size of intermediate result sets that need to be processed by subsequent nodes, such as joins, leading to significantly faster execution. Similarly, limiting the number of stacked calculation views (i.e., views built on top of other views) is a crucial best practice. Deeply stacked models increase compilation time and complexity for the query optimizer, which can result in less efficient execution plans.

A. Avoid union pruning: Union pruning is a performance optimization feature that excludes irrelevant data sources in a union node based on filters. Avoiding it would degrade, not improve, performance.

B. Partition large tables: While partitioning underlying tables improves query performance, it is a physical data storage strategy, not a direct modeling technique applied within the calculation view's design itself.

1. SAP HANA Cloud

SAP HANA Database Modeling Guide for SAP Web IDE for SAP HANA - Section: Performance Guidelines for Calculation Views. This guide explicitly states

"Filter and aggregate data at the earliest possible stage." It also advises

"Keep models simple. Avoid creating a deep stack of calculation views because this can lead to poor performance." This directly supports answers D and C.

2. SAP HANA SQL and System Views Reference - Section: MDEVEXPENSIVESTATEMENTS. Analyzing expensive statements often reveals issues caused by complex models with many stacked views or late aggregation

reinforcing the importance of the principles in answers C and D.

3. SAP HANA Administration Guide - Section: Managing Tables. This guide details table partitioning as a general performance technique for managing large tables at the physical layer

confirming that option B is a valid but less direct technique compared to the modeling-specific advice in C and D.

When a flowgraph is built (activated/deployed) in SAP HANA, the system generates different runtime objects based on its configuration. For a flowgraph designed for batch processing, a stored procedure is generated. This procedure can then be called to execute the data transformation logic. For flowgraphs designed for continuous, real-time data movement, a real-time task is generated. This task can be started and stopped to manage the ongoing data flow. A replication task is a specific and common implementation of a real-time task, created to handle near real-time data replication between a source and SAP HANA.

A. Batch Task: The runtime object generated for a batch-mode flowgraph is a stored procedure. "Batch Task" describes the execution type, not the generated database object itself.

C. Function: Flowgraphs are designed for data movement and transformation (ETL/ELT processes) and generate procedures or tasks, not scalar or table functions which are used for calculations within queries.

1. SAP HANA Smart Data Integration and SAP HANA Smart Data Quality Documentation:

Reference for Procedure and Real-time Task: In the section "Flowgraphs

" under "Executing Flowgraphs

" the documentation states: "When you activate a flowgraph

the system generates a stored procedure (for batch data flows) or a task (for real-time data flows)." This directly supports answers B and D.

Reference for Replication Task: The section "Creating a Replication Task" explains that these tasks are used for real-time data replication and can be based on a flowgraph definition. This supports answer E.

2. SAP HANA SQL and System Views Reference:

Reference for Procedure: The CREATE PROCEDURE statement documentation describes the object generated for batch flowgraphs. The generated procedure is located in the SYSDI schema and its name is derived from the flowgraph name.

Reference for Task: The CREATE TASK statement documentation details the runtime object created for real-time flowgraphs

which is managed using START TASK

SUSPEND TASK

and DROP TASK commands. This confirms the nature of the objects in answers D and E.