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

To execute the compiled job outside Talend Studio, you need to right-click on the job in the Repository tree view and select Build Job option. This option allows you to export your job as an executable file that can be run independently from Talend Studio on any platform that supports Java. You can access this option by right-clicking on your job in the Repository tree view and selecting Build Job. This will open a dialog box where you can configure the build settings, such as destination folder, archive name, context, etc.

You do not need to click the Export button in the Edit Properties window, right-click on the job in the Repository and select Export items, or select Save As on the main File menu. These options are not used to execute the compiled job outside Talend Studio. The Export button in the Edit Properties window is used to export your job properties as an XML file. The Export items option is used to export your items (such as jobs, metadata, routines, etc.) as an archive file that can be imported into another project or workspace. The Save As option is used to save a copy of your job with a different name or location. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Build Job - 7.3]

To build a job to run outside Talend Studio that must run on both Linux and Windows, you need to select Build Job because jobs are runnable on all platforms. The Build Job option allows you to export your job as an executable file that can be run independently from Talend Studio on any platform that supports Java. You can access this option by right-clicking on your job in the Repository tree view and selecting Build Job. This will open a dialog box where you can configure the build settings, such as destination folder, archive name, context, etc.

You do not need to specify All for the Shell launcher option in the Build Job window, configure the job properties before building the job, or build one package for each platform. These methods are not necessary or available in Talend Studio and may cause errors or unexpected results. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Build Job - 7.3]

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]

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.​

Comprehensive and Detailed Explanation:

When a task executes on a Talend Remote Engine, the execution logs are handled as follows:​

Logs are stored in the file system of the server where the Remote Engine is running (Option A):

The Remote Engine writes execution logs to its local file system, typically in plain text or log formats. These logs provide detailed information about the task's execution and are essential for troubleshooting and monitoring.​

Logs can be downloaded from Talend Management Console (Option C):

Talend Management Console (TMC) aggregates execution logs from Remote Engines, allowing users to access and download them directly through the TMC interface. This centralized access simplifies monitoring and debugging across multiple environments.​

Why not other options?

Option B:While some components of Talend may use H2 databases for internal purposes, execution logs are not typically stored in an H2 database on the Remote Engine server.​

Option D:Execution logs are generally stored in plain text or standard log formats, not in Parquet format. Parquet is a columnar storage file format commonly used for efficient data processing, not for logging purposes.​

Comprehensive and Detailed Explanation:

In Talend Cloud Data Preparation, areciperefers to a sequence of data transformation steps applied to a dataset. These steps can include actions like filtering, cleansing, enriching, and formatting data to prepare it for analysis or reporting. The recipe ensures that the same transformations can be consistently reapplied to the dataset or similar datasets, promoting data consistency and efficiency. ​

Why not other options?

Option A:A recipe is not a dataset itself but a set of transformation instructions applied to a dataset.​

Option C:While semantic types are important, a recipe encompasses more than just listing them; it involves actionable transformations.​

Option D:Recipes are not datasets but are applied to datasets to achieve desired transformations.​

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:

To establish a centralized metadata connection to a database server in Talend Studio, follow these steps before constructing a Job that reads from the database:​

Create Db Connections Metadata to Describe the Database Connection (Option C):

In the Repository panel, right-click on "Metadata" and select "Create connection."​

Fill in the necessary details such as database type, host, port, database name, username, and password.​

Test the connection to ensure it is configured correctly.​

Save the connection metadata for reuse across multiple Jobs.​

Retrieve the Schemas from the Database Connection (Option E):

After creating the database connection metadata, expand it to view the available schemas.​

Retrieve the required schemas by importing the table structures.​

This step ensures that the schema definitions are centralized and can be reused in different Jobs.​

Drag the Db Connections Metadata onto the Designer to Read from the Database Component (Option D):

In the Repository, locate the previously created database connection metadata.​

Drag and drop the desired table or schema onto the Designer workspace.​

Talend Studio will automatically create the appropriate input component (e.g., tDBInput) configured with the connection and schema details.​

By following these steps, you ensure a centralized and consistent approach to managing database connections and schemas, promoting reusability and reducing configuration errors.​

Comprehensive and Detailed Explanation:

The Talend Trust Score™ is a feature of Talend Cloud Data Inventory that provides an assessment of a dataset's reliability and quality:​

Aggregates several metrics into a single score (Option A):

The Trust Score™ combines multiple factors, including validity, completeness, popularity, discoverability, and usage, into a single, comprehensive score. This aggregation helps users quickly gauge the overall trustworthiness of a dataset.​

Scales the Trust Score from 0 to 5 (Option C):

The Trust Score™ ranges from 0 to 5, with higher scores indicating better data quality and reliability. This standardized scale allows for easy comparison between datasets.​

Why not other options?

Option B:While data consumers can view and utilize the Trust Score™, it is automatically calculated by Talend based on specific metrics; users do not assign this score themselves.​

Option D:The Trust Score™ does not use a 0 to 10 scale; it specifically ranges from 0 to 5.​

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 create a generic schema from a schema defined in a Talend component, follow these steps:

Open the Repository View:

In Talend Studio, navigate to the Repository panel, typically located on the left side of the interface.

Locate the 'Generic schemas' Node:

Within the Repository, expand the 'Metadata' section to find the 'Generic schemas' node.

Initiate the Generic Schema Creation Process:

Right-click on 'Generic schemas' and select 'Create generic schema' from the context menu.

Define the Schema Properties:

In the schema creation wizard that appears, provide the necessary properties such as 'Name' and 'Description' for the new generic schema.

Set Up the Schema Structure:

Define the schema structure by adding columns and specifying their data types as required.

Finalize the Schema Creation:

Click 'Finish' to complete the creation process. The new generic schema will now be available under the 'Generic schemas' node in the Repository.

This method allows you to create a reusable generic schema that can be applied across multiple components and Jobs within Talend Studio.

A Joblet is a reusable piece of a job that can be used in multiple jobs as a single component. A tRunJob component is a component that allows you to call another job as a subjob within a parent job. When comparing a Joblet to a tRunJob component, these statements are true:

A Joblet uses the same context variables of the job in which it is used, unlike a tRunJob component. A context variable is a variable that can store a value that can be changed at runtime or between different contexts. A Joblet inherits the context variables from the job that contains it and does not have its own context variables. A tRunJob component can pass context variables from the parent job to the child job, or use a specific context for the child job.

Building a Joblet typically requires the use of generic input and trigger components. A Joblet can have one or more input and output flows that connect it with other components in a job. To create these flows, you need to use generic input and trigger components, such as tJobletInput, tJobletOutput, tJobletTriggerInput, and tJobletTriggerOutput. These components allow you todefine schemas and triggers for your Joblet without depending on specific components.

The nested job called by a tRunJob component cannot use the same context variables of the job in which it is used. A nested job is a job that is called by another job using a tRunJob component. A nested job can have its own context variables or receive context variables from its parent job, but it cannot use the same context variables as its parent job. This means that if you have two context variables with the same name in both jobs, they will be treated as separate variables and will not share values.

These statements are false when comparing a Joblet to a tRunJob component:

The performance of tRunJob component is better than running an equivalent job using a Joblet. The performance of a Joblet is better than running an equivalent job using a tRunJob component. This is because a Joblet is integrated into the main code of the job and does not require launching another JVM process or loading another metadata object like a tRunJob component does. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Joblets - 7.3], [tRunJob properties - 7.3], [Contexts - 7.3]