A. Breaking when an input column fulfills a condition
B. Breaking on a selected line of code
C. Advancing one row at a time
D. Advancing one column at a time
E. Filtering which data is propagated by a flow
正解：A、C
解説：
Trace Debug mode is a feature that allows you to trace each row processed by your job components and see the values of each column in each row. You can access this mode by opening the Debug Run tab of the Run view and clicking on Trace Debug button.
The capabilities that Trace Debug mode provides are:
* Breaking when an input column fulfills a condition. You can set breakpoints on traces based on a condition or an expression that involves input data columns. For example, you can set a breakpoint to pause your job when a customer name contains a certain string or when a product price exceeds a certain value. To set a breakpoint based on a condition, you need to right-click on a trace on your jobdesign workspace and select Show Breakpoint Setup option. This will open a dialog box where you can enter a condition or an expression for your breakpoint.
* Advancing one row at a time. You can advance the execution of your job one row at a time by using the Step Over button in the toolbar of the Run view. This will allow you to see how each row is processed by your job components and how it affects the output data.
The capabilities that Trace Debug mode does not provide are:
* Filtering which data is propagated by a flow. You cannot filter which data is propagated by a flow in Trace Debug mode. A flow is a link that shows the data transfer between components in your job design workspace. In Trace Debug mode, you can see the data flow on each trace and inspect the values of each column for each row processed by your job. However, you cannot change which rows are propagated by a flow based on a condition or an expression.
* Advancing one column at a time. You cannot advance the execution of your job one column at a time in Trace Debug mode. You can only advance the execution of your job one row at a time by using the Step Over button in the toolbar of the Run view. This will allow you to see how each row is processed by your job components and how it affects the output data. However, you cannot see how each column is processed by your job components and how it affects the output data.
* Breaking on a selected line of code. You cannot break on a selected line of code in Trace Debug mode.
You can only break on a trace based on a condition or an expression that involves input data columns.
To break on a selected line of code, you need to use Java Debug mode. Java Debug mode allows you to debug your job code in Java or Perl and see the values of each variable or expression in your code. You can access this mode by switching to the Java perspective and clicking on the Debug button in the toolbar of the Code view. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Trace Debug mode - 7.3], [Java Debug mode - 7.3]
質問 # 43
You are using a tRESTClient component to call a REST service. Which advanced option should you use to convert the response from the server to the document type?
A. Convert Response To HTML Document
B. Convert Response To JSON Document
C. Convert Response To XML Document
D. Convert Response To DOM Document
正解：D
解説：
Comprehensive and Detailed Explanation:
In Talend Studio, the tRESTClient component includes an advanced setting called"Convert Response To DOM Document". When this option is selected, the response from the REST service is converted into a DOM (Document Object Model) document. This allows for structured processing of the response data within Talend workflows.
質問 # 44
What is the default port for the REST Endpoint when using tRESTRequest in Talend Studio?
A. 0
B. 1
C. 2
D. 3
正解：D
解説：
Comprehensive and Detailed Explanation:
The defaultREST endpoint port for tRESTRequest in Talend Studio is 8090.
* Port 8090 (Correct Answer - Option D):
* When running a REST service insideTalend Studio, the default listening port is8090.
* This can be changed in the component settings if required.
* Other port options explained:
* 5040 & 5070: Not default ports used for Talend REST services.
* 8040: Used inTalend Runtime, not in Studio.
質問 # 45
Which characteristics distinguish Traces Debug from Java Debug?
Choose 2 answers
A. Allow row-by-row inspection of data flows
B. Requires a separate perspective
C. Require Java development experiences
D. Supports breakpoints based on input data condition
正解：A、D
解説：
Trace Debug and Java Debug are two modes that allow you to debug your jobs in Talend Studio. Trace Debug mode allows you to trace each row processed by your job components and see the values of each column in each row. Java Debug mode allows you to debug your job code in Java or Perl and see the values of each variable or expression in your code.
The characteristics that distinguish Trace Debug from Java Debug are:
* Trace Debug mode allows row-by-row inspection of data flows, while Java Debug mode does not. Data flows are the links that show the data transfer between components in your job design workspace. In Trace Debug mode, you can see the data flow on each trace and inspect the values of each column for each row processed by your job. You can also use filters to display only the rows that match a condition or an expression. In Java Debug mode, you cannot see the data flow on each trace or inspect the values of each column for each row.
* Trace Debug mode supports breakpoints based on input data condition, while Java Debug mode does not. Breakpoints are points where the execution of your job pauses and waits for your action. You can use breakpoints to inspect your data or debug your logic at specific points of your job execution. In Trace Debug mode, you can set breakpoints on traces based on a condition or an expression that involves input data columns. For example, you can set a breakpoint to pause your job when a customer name contains a certain string or when a product price exceeds a certain value. In Java Debug mode, you can only set breakpoints on lines of code based on a condition or an expression that involves variables or expressions.
The characteristics that do not distinguish Trace Debug from Java Debug are:
* Both modes require a separate perspective. A perspective is a set of views and editors that are arranged in a specific way to support a specific task. In Talend Studio, you can switch between different perspectives, such as Integration, Debug, Profiling, etc. To use Trace Debug mode, you need to switch to the Debug perspective by clicking on the Open Perspective button and selecting Debug. To use Java Debug mode, you need to switch to the Java perspective by clicking on the Open Perspective button and selecting Java.
* Neither mode requires Java development experience. Although Java Debug mode allows you to debug your job code in Java or Perl, you do not need to have Java development experience to use it. You can use the graphical interface of Talend Studio to design your job components and properties without writing any code. You can also use the Code view to see the generated code of your job in Java or Perl and modify it if needed. However, you do not need to write any code from scratch or understand all the details of the code to use Java Debug mode. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Trace Debug mode - 7.3], [Java Debug mode - 7.3]
質問 # 46
How many sample dataset records and rows can be displayed in Talend Cloud Data Preparation?
A. 1,000
B. All the available records
C. 10,000
D. 5,000
正解：C
解説：
Comprehensive and Detailed Explanation:
In Talend Cloud Data Preparation, the platform is designed to handle large datasets efficiently by displaying a sample of the data to the user. By default, Talend Cloud Data Preparation can display up to 10,000 records from a dataset. This sampling approach ensures that users can interact with and analyze their data without performance issues that might arise from loading an entire large dataset into memory. Users have the option to view the first 10,000 records (Head sample) or 10,000 randomly selected records (Random sample) to get a representative understanding of the dataset's content.
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