Talend-Core-Developer Talend Core Certified Developer Exam Questions and Answers

Comprehensive and Detailed Explanation:

In Talend's Enterprise Service Bus (ESB) routes, the appropriate component to read a CSV file iscFileInputDelimited. This component is specifically designed for Camel routes to handle delimited files like CSVs.​

Comprehensive and Detailed Explanation:

In Talend, when multiple components need to share the same database connection, thetDBConnectioncomponent is used.

tDBConnection (Correct Answer - Option D):

This component establishes a database connection that can bereused by multiple database components(such as tDBInput, tDBOutput, and tDBRow) within the same Job.

Reduces redundant connection creation,improving performance and efficiency.

To use it, other database components must set"Use an existing connection"in their configuration.

Why not other options?

tDBOutput (Option A):Used for writing data to a database but does not manage shared connections.

tDBRun (Option B):Used to execute a subJob but does not handle database connections.

tDBCommit (Option C):Used for committing transactions, but it requires a shared connection (which tDBConnection provides).

In a tMap component, naming an output row correctly helps in managing data flow efficiently. The correct methods are:

A. Click the name of the table in the Map Editor window and edit it.

Open tMap, locate the output table, and click its name to edit it directly.

B. Assign the name when defining a new output table in the Map Editor window.

When adding a new output table, you can name it immediately in the Map Editor.

D. Assign the name when connecting a new output component.

When you connect an output component to tMap, you can assign a custom row name.

Tags are used to mark specific points in the development lifecycle of a project. This can be done for a variety of reasons, such as:

To mark the completion of a major feature or release

To mark the start of a new development phase (e.g., QA, production)

To mark a known good state of the codebase (e.g., before a risky change)

Tags can be used to create branches, which can then be used to develop and test new features or bug fixes. They can also be used to deploy the codebase to different environments (e.g., development, staging, production).

Examples of when to use a tag:

When you are ready to release a new version of your application to production.

When you have completed a major feature or milestone in the development of your application.

Before making a risky change to your codebase, such as a database migration or refactoring.

When you need to deploy your application to a different environment, such as staging or production.

Benefits of using tags:

Tags can help you to keep track of the different versions of your codebase.

Tags can help you to roll back to a previous version of your codebase if necessary.

Tags can help you to deploy your codebase to different environments.

Tags can help you to collaborate with other developers more effectively.

Comprehensive and Detailed Explanation:

When multiple Jobs require connections to the same database server but with different credentials, the recommended approach is:​

Set the Property Type to Built-in and Set All the Relevant Properties Manually (Option C):

In each tDBInput component, set the 'Property Type' to 'Built-in.'​

Manually enter the connection details, including the specific username and password required for that particular Job.​

This approach ensures that each Job uses its own set of credentials, maintaining the necessary security and access controls.​

To create an empty Joblet, you need to right-click on the Joblet Designs node in the Repository tree view and select Create Joblet option. This will open a dialog box where you can enter the name and description of your Joblet and select an icon for it. You can then design your Joblet by adding components and links to it in the Designer workspace.

You cannot create an empty Joblet by creating an empty job, then exporting it as a Joblet by right-clicking it in the Repository, creating an empty job and using the file menu to save it as Joblet, or right-clicking a space in the Designer and selecting refactor to Joblet. These methods are not available in Talend Studio and may cause errors or unexpected results. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Joblets - 7.3]

Comprehensive and Detailed Explanation:

To calculate the overall Trust Score™ for multiple customer datasets:​

Use the search bar to filter the customer datasets, and the score will automatically update (Option B):

Filtering datasets using the search functionality aggregates the Trust Scores of the selected datasets, providing an overall score for the group.​

Why not other options?

Option A: Reviewing individual ratings does not provide an aggregated Trust Score™.​

Option C: Marking datasets does not trigger an automatic update of the aggregated score.​

Option D: Manual calculation is unnecessary as the system provides automatic aggregation upon filtering.​

Comprehensive and Detailed Explanation:

After publishing a Job from Talend Studio to Talend Cloud, you can execute it using the Talend Management Console (TMC) by following these steps:​

Add a task and then run the task (Option A):

In TMC, navigate to theManagementsection and selectTasks.​

Click onAdd Task, choose the published artifact (your Job), configure necessary parameters, and save the task.​

Once the task is created, you can run it manually or schedule it for execution.​

Select the artifact name, add and configure a task, then run the task (Option D):

In TMC, go to theArtifactssection to view your published Jobs.​

Select the desired artifact and click onAdd Task.​

Configure the task settings as needed and save it.​

After creating the task, you can execute it immediately or set up a schedule.​

Why not other options?

Option B:TMC does not support directly running a Job by clicking on the artifact name without first creating a task.​

Option C:While you can select and configure an existing task, the initial step requires creating the task associated with the artifact.​

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]

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.

 To copy Job1 from Branch1 to Branch2 and preserve the change history when connecting Studio to Talend Administration Center, you need to use the Copy to branch option. This option allows you to copy a job or a folder from one branch to another branch in the same project without losing the version history. You can access this option by switching to Branch1, right-clicking on Job1 in the Repository tree view, and selecting Copy to branch. This will open a dialog box where you can select Branch2 as the target branch and confirm the copy operation.

You do not need to use the import items, create standard job, or paste over options. These options are not used to copy jobs between branches and preserve the change history. The import items option is used to import items (such as jobs, metadata, routines, etc.) from an archive file that can be exported from another project or workspace. The create standard job option is used to create a new job with a name and a description. The paste over option is used to overwrite an existing job with another job that has been copied or cut from the same or another project. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Copy to branch - 7.3]

To reuse a job named testJob from a referenced project named project_ref in your main job, you need to navigate to @Referenced project, @project_ref, Job Designs, Standard, then select testJob. A referenced project is a project that can be accessed from another project in read-only mode. You can add a referenced project to your main project by using the Project Settings window in Talend Studio. You can then browse the items (such as jobs, metadata, routines, etc.) of the referenced project in the Repository tree view under the @Referenced project node. You can drag and drop any item from the referenced project to your main job design workspace.

You do not need to use import items, create standard job, or navigate to Metadata options. These options are not used to reuse jobs from referenced projects. The import items option is used to import items (such as jobs, metadata, routines, etc.) from an archive file that can be exported from another project or workspace. The create standard job option is used to create a new job with a name and a description. The Metadata node in the Repository tree view is used to store and manage metadata definitions for various data sources (such as databases, files, web services,etc.). References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Referenced projects - 7.3]

Comprehensive and Detailed Explanation:

The validity of a dataset in Talend's Trust Score™ framework is determined by:​

Number of valid and invalid values across the dataset sample (Option B):

This metric assesses the quality of the data by evaluating the proportion of valid entries compared to invalid ones. A higher number of valid values indicates better data quality.​

Use of semantic types across the dataset sample (Option C):

Semantic types help in understanding the meaning and context of data fields. Consistent and correct application of semantic types ensures that data is interpreted accurately, contributing to its validity.​

Why not other options?

Option A: User ratings and certification pertain to the popularity axis, reflecting user trust and endorsement, not the intrinsic validity of the data.​

Option D: The number of empty rows relates to the completeness axis, indicating missing data, rather than directly affecting validity.​