TALEND-CORE-DEVELOPER Practice Questions

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.). Reference:

Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Referenced projects - 7.3]

To run a job that has been exported by a colleague to run outside Talend Studio, you need to extract

the content of the archive and run the batch file or the shell script. The archive file contains all the

files and libraries required to run the job independently from Talend Studio on any platform that

supports Java. The archive file also contains two executable files: a batch file (.bat) for Windows

platforms and a shell script (.sh) for Linux platforms. You need to run the appropriate file for your

platform by double-clicking on it or using a command line tool. This will launch the job and display its

output in a console window.

You do not need to extract the contents of the archive and run both the batch file and shell script,

install the job and start the resulting service, or extract the files from the archive and run the JAR file.

These methods are not correct or available in Talend Studio and may cause errors or unexpected

results. Reference: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Build

Job - 7.3]

Comprehensive and Detailed Explanation:

In Talend Management Console (TMC), a plan is a sequence of tasks executed in a defined order. The

types of tasks that can be added to a plan include:

Jobs (Option D): Standard data integration tasks designed in Talend Studio.

Big Data tasks (Option B): Tasks involving big data processing.

Routes (Option C): Tasks related to messaging routes.

However, Data services (Option A) refer to web services and are not typically added as tasks within a

plan.

Reference: Talend Management Console User Guide

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.

Reference: Talend Components Documentation

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.

Reference: Talend Official Documentation, Talend Studio User Guide

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 to define

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. Reference: Talend

Open Studio: Open-source ETL and Free Data Integration | Talend, [Joblets - 7.3], [tRunJob properties

- 7.3], [Contexts - 7.3]

Comprehensive and Detailed Explanation:

To filter customer records based on first name containing "Tom" and age greater than 18, the Filter

processor is the correct choice.

Filter (Option C) – Correct Answer:

Explanation:

The Filter processor allows users to set conditional rules to extract only the required data.

Users can specify conditions such as:

first_name CONTAINS "Tom"

AND

age > 18

This ensures that only relevant records are included in the output.

Why not other options?

Option A (Join): Used to combine data from multiple datasets based on a key field, not for filtering.

Option B (Aggregate): Used for summarizing data, such as calculating counts, sums, or averages.

Option D (Data Sampling): Used to select a random subset of data, not for filtering based on

conditions.

Reference: Talend Pipeline Designer User Guide

To identify execution times to verify the effectiveness of your changes, you can use one of these

methods:

Reading the time stamps from the execution console in the Run view. This method allows you to see

the start and end time of each subjob and component in your job, as well as the total execution time

of the job. You can also see the number of rows processed by each component and the status of the

job (success or failure).

Observing the execution times that annotate the flows in the Designer. This method allows you to

see the execution time of each flow (main, lookup, reject, etc.) between components in your job. You

can also see the number of rows processed by each flow and the throughput (rows per second) of

each flow.

You cannot use these methods to identify execution times:

Observing the execution time in the Code view. This method does not show you the execution time

of your job or its components, but only the generated code of your job in Java or Perl. The Code view

is useful for debugging or customizing your code, but not for measuring performance.

Comparing time stamps in Trace Debug mode. This method does not show you the execution time of

your job or its components, but only the values of each column for each row processed by your job.

The Trace Debug mode is useful for tracing data quality or transformation issues, but not for

measuring performance. Reference: Talend Open Studio: Open-source ETL and Free Data Integration

| Talend, [Run view - 7.3], [Designer - 7.3], [Code view - 7.3], [Trace Debug mode - 7.3]

Comprehensive and Detailed Explanation:

The tRESTRequest component in Talend Studio is designed to handle RESTful web service requests. It

supports the following HTTP methods:

GET: Retrieves data from the server.

POST: Submits data to the server, often causing a change in state or side effects.

PUT: Replaces all current representations of the target resource with the request payload.

PATCH: Applies partial modifications to a resource.

DELETE: Removes the specified resource from the server.

Therefore, the correct answer is A. GET, POST, PUT, PATCH, and DELETE.

Reference: Talend Components Documentation, HTTP Methods Overview

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.

Reference:

Talend Best Practices Guide: https://help.talend.com/r/en-US/8.0/software-dev-lifecycle-bestpractices-guide/branching-merging-and-tagging

Git documentation on tags: https://git-scm.com/docs/git-tag