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C_ABAPD_2309日本語版問題集

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SAP Certified Associate - Back-End Developer - ABAP Cloud 認定 C_ABAPD_2309 試験問題 (Q61-Q66):

質問 # 61
You are given the following information:

1.
The data source "spfli" on line #2 is an SAP HANA
database table
2.
"spfli" will be a large table with over one million rows.
3.
This program is the only one in the system that accesses
the table.
4.
This program will run rarely.
Based on this information, which of the following general
settings should you set for the spfli database table? Note:
There are 2 correct answers to this question.

A. "Load Unit to "Column Loadable"
B. "Load Unit' to 'Page Loadable"
C. "Storage Type" to "Column Store"
D. "Storage Type" to "Row Store"

正解：B、D

解説：
Explanation
Based on the given information, the spfli database table should have the following general settings:
"Storage Type" to "Row Store": This setting determines how the data is stored in the SAP HANA database. Row store is suitable for tables that are accessed by primary key or by a small number of columns. Column store is suitable for tables that are accessed by a large number of columns or by complex analytical queries. Since the spfli table is a large table with over one million rows, and this program is the only one in the system that accesses the table, it is likely that the program will use primary key access or simple queries to access the table. Therefore, row store is a better choice than column store for this table12.
"Load Unit" to "Page Loadable": This setting determines how the data is loaded into the memory when the table is accessed. Page loadable means that the data is loaded in pages of 16 KB each, and only the pages that are needed are loaded. Column loadable means that the data is loaded in columns, and only the columns that are needed are loaded. Since the spfli table is a row store table, and this program will run rarely, it is more efficient to use page loadable than column loadable for this table. Page loadable will reduce the memory consumption and the loading time of the table13.
References: 1: Table Types in SAP HANA | SAP Help Portal 2: [Row Store vs Column Store in SAP HANA | SAP Blogs] 3: [Load Unit | SAP Help Portal]

質問 # 62
Why would you use Access Controls with CDS Views? Note: There are 2 correct answers to this question.

A. Only the data corresponding to the user's authorization is transferred from the database to the application layer.
B. You do not have to remember to implement AUTHORITY CHECK statements.
C. The system field sy-subrc is set, giving you the result of the authorization check
D. All of the data from the data sources is loaded into your application automatically and filtered there according to the user's authorization.

正解：A、B

解説：
Explanation
You would use Access Controls with CDS Views for the following reasons:
A). Only the data corresponding to the user's authorization is transferred from the database to the application layer. This is true because Access Controls allow you to define CDS roles that specify the authorization conditions for accessing a CDS view. The CDS roles are evaluated for every user at runtime and the system automatically adds the restrictions to the selection conditions of the CDS view.
This ensures that only the data that the user is authorized to see is read from the database and transferred to the application layer. This improves the security and the performance of the data access1.
C). You do not have to remember to implement AUTHORITY CHECK statements. This is true because Access Controls provide a declarative and centralized way of defining the authorization logic for a CDS view. You do not have to write any procedural code or use the AUTHORITY CHECK statement to check the user's authorization for each data source or field. The system handles the authorization check automatically and transparently for you2.
The following reasons are not valid for using Access Controls with CDS Views:
B). The system field sy-subrc is set, giving you the result of the authorization check. This is false because the system field sy-subrc is not used by Access Controls. The sy-subrc field is used by the AUTHORITY CHECK statement to indicate the result of the authorization check, but Access Controls do not use this statement. Instead, Access Controls use CDS roles to filter the data according to the user's authorization2.
D). All of the data from the data sources is loaded into your application automatically and filtered there according to the user's authorization. This is false because Access Controls do not load all the data from the data sources into the application layer. Access Controls filter the data at the database layer, where the data resides, and only transfer the data that the user is authorized to see to the application layer. This reduces the data transfer and the memory consumption of the application layer1.
References: 1: Access Controls | SAP Help Portal 2: ABAP CDS - Access Control - ABAP Keyword Documentation

質問 # 63
Which of the following are parts of answers to this question.

A. Partitioning attributes
B. Semantic table attributes
C. Field list
D. Extension

正解：C、D

解説：
A CDS view is a data definition that defines a data structure and a data selection from one or more data sources. A CDS view consists of several parts, but two of them are:
Extension: An extension is an optional clause that allows a CDS view to extend another CDS view by adding new elements, annotations, or associations. The extension clause has the syntax EXTEND VIEW view_name WITH view_name. The first view_name is the name of the CDS view that is being extended, and the second view_name is the name of the CDS view that is doing the extension1.
Field list: A field list is a mandatory clause that specifies the elements of the CDS view. The field list has the syntax SELECT FROM data_source { element_list }. The data_source is the name of the data source that the CDS view selects data from, and the element_list is a comma-separated list of elements that the CDS view exposes. The elements can be fields of the data source, expressions, associations, or annotations2.
The following example shows a CDS view that extends another CDS view and defines a field list:
@AbapCatalog.sqlViewName: 'ZCDS_EXT' define view Z_CDS_Extension extend view Z_CDS_Base with Z_CDS_Extension as select from ztable { // field list key ztable.id as ID, ztable.name as Name, ztable.age as Age, // extension @Semantics.currencyCode: true ztable.currency as Currency } The other options are not parts of a CDS view, but rather related concepts:
Partitioning attributes: Partitioning attributes are attributes that are used to partition a table into smaller subsets of data. Partitioning attributes are defined in the ABAP Dictionary for transparent tables and can improve the performance and scalability of data access. Partitioning attributes are not part of the CDS view definition, but rather the underlying table definition3.
Semantic table attributes: Semantic table attributes are attributes that provide additional information about the meaning and usage of a table. Semantic table attributes are defined in the ABAP Dictionary for transparent tables and can be used to enhance the data modeling and consumption of the table. Semantic table attributes are not part of the CDS view definition, but rather the underlying table definition4.

質問 # 64
Refer to the Exhibit.

Using ABAP SQL, which select statement selects the mat field on line #17?

A. SELECT mat FROM demo sales cds material ve...
B. SELECT mat FROM demo_sales_cds_so_i_ve...
C. SELECT mat FROM Material...
D. SELECT mat FROM demo_sales_so_i...

正解：B

解説：
Using ABAP SQL, the select statement that selects the mat field on line #17 is:
SELECT mat FROM demo_sales_cds_so_i_ve...
This statement selects the mat field from the CDS view demo_sales_cds_so_i_ve, which is defined on line #1. The CDS view demo_sales_cds_so_i_ve is a projection view that projects the fields of the CDS view demo_sales_cds_so_i, which is defined on line #2. The CDS view demo_sales_cds_so_i is a join view that joins the fields of the database table demo_sales_so_i, which is defined on line #3, and the CDS view demo_sales_cds_material_ve, which is defined on line #4. The CDS view demo_sales_cds_material_ve is a value help view that provides value help for the material field of the database table demo_sales_so_i. The mat field is an alias for the material field of the database table demo_sales_so_i, which is defined on line #91.
The other options are not valid because:
A) SELECT mat FROM Material... is not valid because Material is not a valid data source in the given code. There is no CDS view or database table named Material.
C) SELECT mat FROM demo_sales_so_i... is not valid because demo_sales_so_i is not a valid data source in the given code. There is no CDS view named demo_sales_so_i, only a database table. To access a database table, the keyword TABLE must be used, such as SELECT mat FROM TABLE demo_sales_so_i...
D) SELECT mat FROM demo sales cds material ve... is not valid because demo sales cds material ve is not a valid data source in the given code. There is no CDS view or database table named demo sales cds material ve. The correct name of the CDS view is demo_sales_cds_material_ve, with underscores instead of spaces.

質問 # 65
In this nested join below in which way is the join evaluated?

A. From the bottom to the top in the order of the on conditions:
1.
a is joined with b
2.
b is joined with c
B. From the left to the right in the order of the tables:
1.
a is joined with b
2.
b is joined with c
C. From the top to the bottom in the order of the on conditions
1.
b is joined with c
2.
a is joined with b
D. From the right to the left in the order of the tables:
1.
b is joined with c.
2.
b is joined with a.

正解：C

解説：
The nested join is evaluated from the top to the bottom in the order of the ON conditions. This means that the join expression is formed by assigning each ON condition to the directly preceding JOIN from left to right. The join expression can be parenthesized implicitly or explicitly to show the order of evaluation. In this case, the implicit parentheses are as follows:
SELECT * FROM (a INNER JOIN (b INNER JOIN c ON b~c = c~c) ON a~b = b~b) This means that the first join expression is b INNER JOIN c ON b~c = c~c, which joins the columns of tables b and c based on the condition that b~c equals c~c. The second join expression is a INNER JOIN (b INNER JOIN c ON b~c = c~c) ON a~b = b~b, which joins the columns of table a and the result of the first join expression based on the condition that a~b equals b~b. The final result set contains all combinations of rows from tables a, b, and c that satisfy both join conditions.

質問 # 66
......

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