C_HANADEV_18 Exam Dumps - SAP Certified Development Associate - SAP HANA 2.0 SPS06

 The UNNEST operator is an SQL Script element that transforms a set of arrays into an intermediate table variable. The UNNEST operator takes one or more array expressions as input and returns a table variable with one or more columns, each corresponding to an array expression. The table variable has as many rows as the maximum length of the input arrays, and the values in each column are taken from the corresponding array elements. If an input array has fewer elements than the maximum length, the missing values are padded with NULLs. The UNNEST operator can be used in the FROM clause of a SELECT statement, or in the INTO clause of a SET statement.

For example, suppose you have two arrays A and B, where A = [1, 2, 3] and B = [4, 5]. You can use the UNNEST operator to transform them into a table variable T as follows:

SET T = UNNEST (A, B);

The result is:

Table

A

B

1

4

2

5

3

NULL

You can also use the UNNEST operator to transform an array of complex types, such as structs or tables, into a table variable with multiple columns. For example, suppose you have an array C of struct type, where C = [{x: 1, y: 2}, {x: 3, y: 4}]. You can use the UNNEST operator to transform it into a table variable U as follows:

SET U = UNNEST (C.x, C.y);

The result is:

Table

C.x

C.y

1

2

3

4

The following SQL Script elements are not used to transform a set of arrays into an intermediate table variable, but for other purposes:

• OSET: This is a data type that represents an ordered set, which is a collection of distinct values that preserves the order of insertion. OSETs can be used to store and manipulate ordered data, such as ranking or sorting results. OSETs can be created by using the OSET constructor or the OSET_AGG aggregate function.
• ARRAY: This is a data type that represents an array, which is a collection of values that can have duplicates and are accessed by their position. Arrays can be used to store and manipulate complex or multi-dimensional data, such as matrices or tensors. Arrays can be created by using the ARRAY constructor or the ARRAY_AGG aggregate function.
• UNSET: This is not a valid SQL Script element, but a possible typo for UNNEST.

References:

• [SAP HANA Platform Documentation], SAP HANA SQL and System Views Reference, Chapter 2: SQL Data Types and Literals, Section 2.2: Collection Types, Subsection 2.2.2: Array Type, pp. 36-38.
• [SAP HANA Platform Documentation], SAP HANA SQL and System Views Reference, Chapter 2: SQL Data Types and Literals, Section 2.2: Collection Types, Subsection 2.2.3: Ordered Set Type, pp. 38-40.
• [SAP HANA Platform Documentation], SAP HANA SQL and System Views Reference, Chapter 3: SQL Expressions, Section 3.6: Collection Expressions, Subsection 3.6.2: UNNEST Operator, pp. 69-70.

 Filter expressions can be used in a calculation view to restrict or modify the data that is displayed or processed by the view. Filter expressions can be used in the following nodes of a calculation view12:

• Aggregation: An aggregation node is a node that applies aggregation functions, such as sum, count, or average, to the data that is passed from the previous node. Filter expressions can be used in an aggregation node to filter the data before or after the aggregation, or to define the aggregation level or the measure attributes. For example, you can use a filter expression to show only the sales data for a specific region or product category, or to calculate the average revenue per customer.
• Union: A union node is a node that combines the data from two or more nodes that have the same structure and data types. Filter expressions can be used in a union node to filter the data from each input node, or to filter the data from the output node. For example, you can use a filter expression to exclude the duplicate rows from the union result, or to show only the data that matches a certain condition from each input node.

The other options are not correct because filter expressions cannot be used in these nodes of a calculation view. A star join node is a node that joins a fact table with one or more dimension tables, based on the common key attributes. A star join node does not support filter expressions, but it supports input parameters, which are variables that can be used to filter the data at runtime. A rank node is a node that ranks the data according to a specified order and criteria. A rank node does not support filter expressions, but it supports rank filters, which are conditions that can be used to limit the number or percentage of rows in the rank result. References:

• SAP HANA Platform, SAP HANA Modeling Guide for SAP HANA Web Workbench, Calculation Views
• SAP HANA Platform, SAP HANA Developer Guide for SAP HANA Web IDE, Developing Database Modules, Developing Calculation Views, Using Filter Expressions

The correct action is to define a User Details view using select on the user entity and using the association to read the address information. This way, you can leverage the power of CDS associations to create a join between the user and address entities without explicitly specifying the join condition. You can also use the association path to access the address fields in the view definition. This approach simplifies the data model and avoids redundancy. Option A is incorrect because it selects from the address entity instead of the user entity, which is not the desired output. Option B is incorrect because it extends the user entity with address columns, which is unnecessary and violates the normalization principle. Option D is incorrect because it creates a calculation view instead of a CDS view, which is not the requirement. Calculation views are graphical or scripted views that can be used for complex calculations and data transformations, but they are not CDS artifacts. References:

• SAP HANA 2.0 SPS06 - Application Development for SAP HANA1, Section 2.2.2, p. 32-33
• SAP HANA 2.0 SPS06 - Core Data Services for SAP HANA2, Section 2.3, p. 25-26
• SAP HANA 2.0 SPS06 - Calculation View Modeling3, Section 1.1, p. 7

Dynamic SQL allows you to construct and execute SQL statements at run time, using variables and expressions that may not be supported in SQLScript. However, it also has some drawbacks, such as:

• Limited opportunities for optimization: The SQL statement is potentially recompiled every time it is executed, which may affect the performance and resource consumption. The optimizer cannot use static information, such as data types, cardinalities, or indexes, to generate an optimal execution plan. The statement may also bypass the SQL cache, which stores the results of frequently executed queries for faster retrieval.
• Additional SQL execution privileges are required: The user who executes the dynamic SQL statement must have the necessary privileges to access the objects and operations referenced in the statement. This may pose a security risk, as the user may gain access to sensitive data or perform unauthorized actions. To prevent SQL injection attacks, the dynamic SQL statement should be validated and sanitized before execution.

The other options are incorrect, because:

• It is possible to bind the result of a dynamic SQL statement to a SQLScript variable, using the INTO clause of the EXECUTE IMMEDIATE statement. For example, EXECUTE IMMEDIATE 'SELECT COUNT(*) FROM "TABLE"' INTO lv_count;
• It is possible to use SQLScript variables in a dynamic SQL statement, using the USING clause of the EXECUTE IMMEDIATE statement. For example, EXECUTE IMMEDIATE 'SELECT * FROM "TABLE" WHERE "COLUMN" = ?' USING lv_value;

References: SAP HANA Developer Guide, Chapter 6, Section 6.4.2, page 2111.

To prevent changes to existing line items of the sap.test::myTable table, you can use the OData service that specifies the update authorization as no-authorization for the table. This means that the OData service does not allow any update operations on the table, such as PUT, PATCH, or MERGE. The option A shows the code snippet that defines the OData service with this restriction. The other options do not have the update no-authorization clause for the table, and therefore, they do not prevent changes to the existing line items. References: OData Service Authorization, OData Security Considerations.