Question # 1
| In RESTful Application Programming, which EML statement retrieves an object?
| | A. Find entity
| | B. Select entity
| | C. Get entity
| | D. Read entity
|
C. Get entity
Explanation:
In RESTful Application Programming, the EML statement that retrieves an object is GET entity. The GET entity statement is used to read data of an entity instance from the database or the transaction buffer. The GET entity statement can specify the entity name, the entity key, and the entity elements to be retrieved. The GET entity statement can also use the IN LOCAL MODE addition to bypass the access control, authorization control, and feature control checks. The GET entity statement returns a single entity instance or raises an exception if no instance is found or multiple instances match the key.
The other EML statements are not used to retrieve an object, but have different purposes and effects. These statements are:
FIND entity: This statement is used to search for entity instances that match a given condition. The FIND entity statement can specify the entity name, the entity elements to be returned, and the condition to be applied. The FIND entity statement can also use the IN LOCAL MODE addition to bypass the access control, authorization control, and feature control checks. The FIND entity statement returns a table of entity instances or an empty table if no instances match the condition.
SELECT entity: This statement is used to query data of entity instances from the database or the transaction buffer. The SELECT entity statement can specify the entity name, the entity elements to be returned, and the filter, order, and aggregation options to be applied. The SELECT entity statement can also use the IN LOCAL MODE addition to bypass the access control, authorization control, and feature control checks. The SELECT entity statement returns a table of entity instances or an empty table if no instances match the query.
READ entity: This statement is not a valid EML statement, but an ABAP statement. The READ statement is used to access a single row of an internal table using the table index or the table key. The READ statement can also use the TRANSPORTING addition to specify which fields should be returned, and the INTO addition to specify the target variable. The READ statement returns a single row of the internal table or raises an exception if no row is found or multiple rows match the key.
Question # 2
| What RESTful Application Programming object contains only the fields required for a particular app?
| | A. Database view
| | B. Metadata extension
| | C. Projection View
| | D. Data model view
|
C. Projection View
Explanation:
A projection view is a RESTful Application Programming object that contains only the fields required for a particular app. A projection view is a CDS view entity that defines a projection on an existing CDS view entity or CDS DDIC-based view. A projection view exposes a subset of the elements of the projected entity, which are relevant for a specific business service. A projection view can also define aliases, virtual elements, and annotations for the projected elements. A projection view is the top-most layer of a CDS data model and prepares data for a particular use case. A projection view can have different provider contracts depending on the type of service it supports, such as transactional query, analytical query, or transactional interface.
A database view is a CDS DDIC-based view that defines a join or union of database tables. A database view has an SQL view attached and can be accessed by Open SQL or native SQL. A database view can be used as a projected entity for a projection view, but it does not contain only the fields required for a particular app.
A metadata extension is a RESTful Application Programming object that defines additional annotations for a CDS view entity or a projection view. A metadata extension can be used to enhance the metadata of a CDS data model without changing the original definition. A metadata extension does not contain any fields, but only annotations.
A data model view is a CDS view entity that defines a data model based on database tables or other CDS view entities. A data model view can have associations, aggregations, filters, parameters, and annotations. A data model view can be used as a projected entity for a projection view, but it does not contain only the fields required for a particular app.
Question # 3
What are some of the reasons that Core Data Services are preferable to the classical approach to data modeling?
Note: There are 2 correct answers to this question.
| | A. They implement code pushdown.
| | B. They avoid data transfer completely.
| | C. They transfer computational results to the application server.
| | D. They compute results on the application server.
|
A. They implement code pushdown.
C. They transfer computational results to the application server.
Explanation:
Core Data Services (CDS) are preferable to the classical approach to data modeling for several reasons, but two of them are:
They implement code pushdown. Code pushdown is the principle of moving data-intensive logic from the application server to the database server, where the data resides. This reduces the data transfer between the application server and the database server, which improves the performance and scalability of the application. CDS enable code pushdown by allowing the definition of semantic data models and business logic in the database layer, using SQL and SQL-based expressions.
They transfer computational results to the application server. CDS allow the application server to access the data and the logic defined in the database layer by using Open SQL statements. Open SQL is a standardized and simplified subset of SQL that can be used across different database platforms. Open SQL statements are translated into native SQL statements by the ABAP runtime environment and executed on the database server. The results of the computation are then transferred to the application server, where they can be further processed or displayed.
Question # 4
| What would be the correct expression to change a given string value 'mr joe doe' into 'JOE' in an ABAP SQL field list? | A. SELECT FROM TABLE dbtabl FIELDS
Of1,
upper(left( 'mr joe doe', 6)) AS f2_up_left, f3, | B. SELECT FROM TABLE dbtabl FIELDS
Of1,
left(lower(substring( 'mr joe doe', 4, 3)), 3) AS f2_left_lo_sub, f3, | C. SELECT FROM TABLE dbtabl FIELDS
Of1,
substring(upper('mr joe doe'), 4, 3) AS f2_sub_up, f3,... | D. SELECT FROM TABLE dbtabl FIELDS
Of1,
substring(lower(upper( 'mr joe doe' ) ), 4, 3) AS f2_sub_lo_up, f3, |
C. SELECT FROM TABLE dbtabl FIELDS
Of1,
substring(upper('mr joe doe'), 4, 3) AS f2_sub_up, f3,...
Question # 5
| In ABAP SQL, which of the following retrieves the association field_Airline-Name of a CDS view? | | A. \_Airline-Name | | B. /_Airline Name | | C. @_Airline-Name | | D. "_Airline Name |
C. @_Airline-Name
Explanation:
In ABAP SQL, the syntax to retrieve the association field of a CDS view is to use the @ sign followed by the association name and the field name, separated by a period sign (.). For example, to retrieve the association field _Airline-Name of a CDS view, the syntax is @_Airline.Name. This syntax allows the access to the fields of the target data source of the association without explicitly joining the data sources1. The other options are incorrect because they use the wrong symbols or formats to access the association field.
References: 1: Path Expressions - ABAP Keyword Documentation
Question # 6
Which of the following actions cause an indirect change to a database table requiring a table conversion?
Note: There are 2 correct answers to this question. | | A. Renaming a field in a structure that is included in the table definition
| | B. Changing the field labels of a data element that is used in the table definition.
| | C. Deleting a field from a structure that is included in the table definition.
| | D. Shortening the length of a domain used in a data element that is used in the table definition.
|
A. Renaming a field in a structure that is included in the table definition
C. Deleting a field from a structure that is included in the table definition.
Explanation:
The following are the explanations for each action:
A: Renaming a field in a structure that is included in the table definition causes an indirect change to the database table, as the field name in the table is derived from the structure. This change requires a table conversion, as the existing data in the table must be copied to a new table with the new field name, and the old table must be deleted.
B: Changing the field labels of a data element that is used in the table definition does not cause an indirect change to the database table, as the field labels are only used for documentation and display purposes. This change does not require a table conversion, as the existing data in the table is not affected by the change.
C: Deleting a field from a structure that is included in the table definition causes an indirect change to the database table, as the field is removed from the table as well. This change requires a table conversion, as the existing data in the table must be copied to a new table without the deleted field, and the old table must be deleted.
D: Shortening the length of a domain used in a data element that is used in the table definition causes an indirect change to the database table, as the field length in the table is derived from the domain. This change requires a table conversion, as the existing data in the table must be checked for compatibility with the new field length, and any data that exceeds the new length must be truncated or rejected.
Question # 7
| Which of the following string functions are predicate functions? Note: There are 2 correct answers to this question. | | A. find_any_not_of()
| | B. contains_any_of()
| | C. count_any_of()
| | D. matchesQ |
B. contains_any_of()
D. matchesQ
Explanation:
String functions are expressions that can be used to manipulate character-like data in ABAP. String functions can be either predicate functions or non-predicate functions. Predicate functions are string functions that return a truth value (true or false) for a condition of the argument text. Non-predicate functions are string functions that return a character-like result for an operation on the argument text1.
The following string functions are predicate functions:
B. contains_any_of(): This function returns true if the argument text contains at least one of the characters specified in the character set. For example, the following expression returns true, because the text ‘ABAP’ contains at least one of the characters ‘A’, ‘B’, or ‘C’:
contains_any_of( val = ‘ABAP’ set = ‘ABC’ ).
D. matches(): This function returns true if the argument text matches the pattern specified in the regular expression. For example, the following expression returns true, because the text ‘ABAP’ matches the pattern that consists of four uppercase letters:
matches( val = ‘ABAP’ regex = ‘[A-Z]{4}’ ).
The following string functions are not predicate functions, because they return a character-like result, not a truth value:
A. find_any_not_of(): This function returns the position of the first character in the argument text that is not contained in the character set. If no such character is found, the function returns 0. For example, the following expression returns 3, because the third character of the text ‘ABAP’ is not contained in the character set ‘ABC’:
find_any_not_of( val = ‘ABAP’ set = ‘ABC’ ).
C. count_any_of(): This function returns the number of characters in the argument text that are contained in the character set. For example, the following expression returns 2, because there are two characters in the text ‘ABAP’ that are contained in the character set ‘ABC’:
count_any_of( val = ‘ABAP’ set = ‘ABC’ ).
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