You created a calculation view that combines two tables in a join node. To improve the
runtime of your calculation view, you use a referential join to prune data sources.
How do you check if pruning occurs? Note: There are 2 correct answers to this question.
A. Check the SQL query generated by the Data Preview.
B. Use the SQL Analyzer to identify the tables used.
C. Enable the Debug Query mode to identify the source columns used.
D. Observe which columns are mapped using the Performance Analysis mode.
Explanation:
Join pruning is a runtime optimization where the HANA query optimizer eliminates unnecessary tables from the execution plan if they are not required to satisfy the requested columns. To verify if pruning occurs:
A. Check the SQL query generated by the Data Preview:
This is correct. In the SAP HANA calculation view Data Preview with the Raw Data or Analysis modes, you can enable SQL Display or view the generated SQL statement. The pruned tables will be absent from the FROM/JOIN clauses of the executed SQL.
B. Use the SQL Analyzer to identify the tables used:
This is correct. The SQL Analyzer tool in SAP HANA (or the Performance Trace in the HANA Database Explorer) shows the actual executed execution plan. You can examine the Plan Visualizer or operator list to confirm which tables are accessed; pruned tables will not appear in the plan.
Why the other options are incorrect:
C. Enable the Debug Query mode:
Incorrect. Debug Query mode in the Calculation View editor is used to trace data flow and intermediate results through nodes, not to analyze pruning at the SQL level. It shows data passing through nodes but does not confirm the absence of a table in the final SQL statement.
D. Observe which columns are mapped using the Performance Analysis mode:
Incorrect. "Performance Analysis mode" is not a standard SAP HANA tool for verifying pruning. While performance tools may show table accesses, the explicit check for pruning is best done via the generated SQL or execution plan, not column mapping observation.
Reference:
SAP HANA Modeling Guide ("Optimizing Calculation Views – Join Pruning") states that pruning can be verified by examining the executed SQL statement. The SAP HANA Performance Analysis Guide further recommends using the SQL Analyzer or Plan Visualizer to analyze runtime table access.
What is a calculation view query snapshot?
A. The stored results of a query on a calculation view
B. The results of a query generated by a front end tool on a calculation view
C. A record of the query statement executed on a calculation view
D. A bookmark of a frequently used navigation state of a query result
Explanation:
A calculation view query snapshot in SAP HANA is a captured record of the SQL query statement that is executed against a calculation view. It is primarily used for analysis, troubleshooting, and performance optimization.
Query snapshots allow developers and administrators to:
Analyze how a calculation view is queried
Reproduce query execution behavior
Investigate performance issues using the exact SQL generated at runtime
Importantly, a query snapshot does not store query results, but rather the query definition and execution context, making it lightweight and suitable for diagnostics.
❌ Why the Other Options Are Incorrect
A. The stored results of a query on a calculation view
Calculation view query snapshots do not persist result sets. Storing results would require materialization (for example, tables or caches), which is not the purpose of snapshots.
B. The results of a query generated by a front end tool on a calculation view
While snapshots can capture queries initiated by front-end tools, they store the query statement, not the returned data.
D. A bookmark of a frequently used navigation state of a query result
Bookmarks and navigation states are features of front-end analytics tools (such as SAP Analytics Cloud), not of SAP HANA calculation view query snapshots.
References
SAP Help Portal – Monitoring and Analyzing Calculation Views
SAP HANA Administration Guide – Query Snapshots
Your flowgraphs defines a template table as a data target. What triggers the generation of the template table?
A. Defining the flowgraph data target node
B. Building/deploying the flowgraph
C. Running the flowgraph
D. Saving the flowgraph
In a calculation view, why would you implement an SQL expression? Note: There are 3 correct answers to this question.
A. To generate a restricted column
B. To define a filter
C. To generate a calculated column
D. To generate hierarchies
E. To convert currencies
A calculation view consumes the data sources shown in the graphic. You want to identify which companies sold products in January AND February. What is the optimal way to do this?
A. Use an aggregation node.
B. Use a union node.
C. Use an intersect node.
D. Use a minus node.
Which type of join supports a temporal condition in a calculation view?
A. Text join
B. Referential join
C. Inner join
D. Left outer join
Why do we use Git when modeling calculation views?
A. To display dependencies in stacked scenarios
B. To automate the build process
C. To manage versions of source files
D. To enable collaboration between developers
What are possible consequences of unfolding? Note: There are 2 correct answers to this question.
A. Results are read from static cache.
B. Count-distinct results are incorrect.
C. SQL compilation time increases.
D. Query processing time improves.
You want to create a star schema using a calculation view. The measures are based on columns from two transaction tables. DIMENSION calculation views provide the attributes.What is the correct approach?
A. Combine the transaction tables using a star join node in a CUBE calculation view.
•Use a join node to join the DIMENSIONS to the resulting fact table.
B. Combine the transaction tables using a join node in a CUBE calculation view.
•Combine the DIMENSIONS using another join node.
•Use a star join node to combine both resulting fact and dimension tables.
C. Combine the transaction tables using a join node in a CUBE calculation view.
•Use a star join node to join the DIMENSIONS to the resulting fact table.
D. Combine the transaction tables using an aggregation node in a CUBE calculation view.
•Use a star join node to join the DIMENSIONS to the resulting fact table.
You are creating a procedure to be consumed in a DYNAMIC analytic privilege. What must you consider? Note: There are 2 correct answers to this question.
A. The procedure should have the value DEFINER for the security mode
B. The procedure should include an input parameter to specify the user ID
C. The procedure should return a table with the list of allowed values
D. The procedure should be defined as read-only
In a flowgraph, which node do you use to select only the required columns from a data source and to filter specific rows?
A. Projection
B. Aggregate
C. Case
D. Pivot
You create a user-provided service to access tables in external schemas.
In which file type do you assign the user-provided service to your database module?
A. hdiconfig
B. .mtar
C. .namespace
D. .yaml
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