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|Types of Talend Interview Questions|
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Talend is an open-source data integration platform that provides solutions for data integration and data management. It offers various integration software and services for data management, data quality, data integration, Big data, data preparation, cloud storage, and enterprise application. It is designed to combine, convert, and update data in various business applications.
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Talend Open Studio
Talend Open Studio is an open-source ETL tool used for data integration and Big data. It is based on the eclipse developer and design tool. Talend Open Studio acts as a code generator that provides data transformation scripts and underlying programs in Java.
A component is a functional unit that is used to perform a single operation in Talend. With the help of drag and drop functions, we can use the components to perform operations. The component can be a snippet of Java code that is generated as a part of a job.
Launched in October 2006
The programming languages that are supported by Talend are as follows:
Talend Open Studio 5.6.0
Routines are reusable pieces of code that can be used to optimize data processing by the use of custom code. It also helps to improve the job capacity and the features of Talend studio. The routines are of two types:
In Talend Studio, the highest physical structure used for storing several kinds of data integration jobs, routines, metadata, etc., is known as Project.
tMap is an advanced component that integrates itself as a plugin to Talend Studio. It is used for mapping the data and also transforms and routes data from single or multiple sources to single or multiple destinations.
The functions of tMap are as follows:
To access the global and context variables, use the shortcut key Ctrl+spacebar.
Context variables are the user-defined parameters used by Talend that are defined as a job at runtime. These variables may change their values as a job from development to test and production environment.
There are three ways to define Context variables. They are as follows:
A subjob can be defined as a component or no. of components that are joined by the data flow. Each individual component can be considered as a Subjob when they are not connected to each other. A job can have one or more sub jobs.
It is required to export the job as a standalone program to schedule a job. Then using the Operating System scheduling tools such as Cron, Windows Scheduler, Linux, etc. we can schedule the jobs.
XMX parameter is used to specify the maximum heap size in java, whereas the XMS parameter is used to determine the initial heap size in java.
tXMLMap is a component used for routing and transforming XML data flows mainly, when processing numerous XML data sources, with or without flat data is to be joined.
tJavaFlex allows the user to add personalized code to integrate into the Talend program. With the use of the tJavaFlex function, we can enter three java code parts such as start, main, and end that constitute a kind of component to the desired operation.
tJava allows the user to enter personalized code to integrate into the Talend program. This code can be executed only once. It makes it possible to extend the functionalities of a Talend job using custom Java commands.
tContextLoad is used to load a context from a flow. This component performs two controls. It alerts when the parameters are defined in the incoming flow are not defined in Context, and another control is it also alerts when a context value is not initialized in the incoming flow.
To close a Hive connection automatically, we can use tPostJob and tHiveClose components.
Pig is a platform using a scripting language to express data flows. It programs the operation to transform data using Pig Latin, which is the language used for pig scripting.
The features that are available in the main window of Talend Open Studio are as follows:
In Talend Studio, Palette is used to find the components required to create or design a job.
In the Palette settings view, we can set the preferences for the component searching from the palette and from the component list that appears on the design workspace when adding a component without using the palette.
The string handling routines allows the user to carry out different types of operations and tests on the alphanumeric expressions, depending on the Java methods.
The following are the ways to improve the performance of a job in Talend:
The Outline view provides an easy way to check out where the design workspace is located. It allows the user to check the return values available in a component.
The following are the configurations that are required to connect HDFS:
Zookeeper client port service is required for coordinating the transactions between HBase and Talend Open Studio.
This component is used for correct mailing addresses associated with customer data to ensure a single customer view and better delivery for their customer mailings.
This is no possible; you cannot directly edit the code generated for a Talend Job.
No, it is not possible to use Binary or ASCII transfer mode in an SFTP connection. Because SFTP does not support any kind of transfer modes as it is an extension to SSH.
By default, the date pattern for a column of type Date in a schema is “dd-MM-yyyy”.
It depends on the way you use the information is used. Use Built-In for information that you only use once or very rarely. Use the Repository for information that you want to use repeatedly in multiple components or Jobs, such as a database connection.
|It belongs to Subjob Triggers||It belongs to Component Triggers|
|It is used to trigger the next subjob on the condition where the subjob is completed without any errors.||It is used to trigger the target component after the execution of the source component completes without any errors.|
|This link can be used only with the first component of the subjob.||This link can be used with any component in a job.|
By using the tNormalize component
tMap is an advanced component, which integrates itself as a plugin to Talend Studio tMap transforms and routes data from single or multiple sources to single or multiple destinations. It allows you to define the tMap routing and transformation properties.
tDenormalizeSortedRow combines in a group of all input sorted rows. The distinct values of the denormalized sorted rows are joined with item separators. It synthesized sorted input flow to save memory.
tDotNETRow helps you facilitate data transform by utilizing custom or built-in .NET classes.
tJoin joins two tables by doing an exact match on several columns. It compares columns from the main flow with reference columns from the lookup flow and outputs the main flow data and/or the rejected data.
Master data management, through which an organization builds and manages a single, consistent, accurate view of key enterprise data, has demonstrated substantial business value including improvements to operational efficiency, marketing effectiveness, strategic planning, and regulatory compliance. To date, however, MDM has been the privilege of a relatively small number of large, resource-rich organizations. Thwarted by the prohibitive costs of proprietary MDM software and the great difficulty of building and maintaining an in-house MDM solution, most organizations have had to forego MDM despite its clear value.
This technical note highlights the important new features and capabilities of version 5.6 of Talend’s comprehensive suite of Platform, Enterprise, and Open Studio solutions.
|Approach||Code generation||Meta driven|
|Monitoring||Enough tools to monitor logs||Enough tools to monitor logs|
|Risk||Equally complex like Pentaho||Equally complex like Talend|
|Data Quality (DQ)||Graphical User Interface (GUI) featured by Data Quality||GUI featured by DQ along with additional options|
|Interface||Moderate interface||Moderate interface|
|Speed||Moderate performance||Best when compared to Talend|
|Community Support||Strong community support||Strong community support|
|Deployment||Works on any java/Perl compatible machine||Runs on Java compatible machines.|
The schemas that are supported by Talend are as follows:
Connection defines whether the data has to be processed, data output, or the sequence of a job. The various kinds of connections that are available in Talend are as follows:
1. Row: The row connection handles the actual data. According to the nature of the flow process, it can be in the following types of row connections:
2. Iterate: The iterate connection is used to execute a loop of files contained in the directory, on the database entries, or the rows contained in a file.
3.Trigger: Trigger connections are used to define the processing sequence, so there is no data handles through these connections. The trigger connections are of two types:
4. Link: The Link connection can be used with ELT components only. These links are used to transfer the table schema information to the ELT component to be used in specific Database query statements.
Yes, it is possible to perform a Talend job partly using the command line. It is required to export the job along with its dependencies. After that, you can access its instruction files from the terminal.
Job design is a design with at least one component connected together that allows the user to develop and run the dataflow management processes. It interprets the business requirements into routines, programs, and code to implement the data flow.
Create a Standard job called Childjob. Open the context to define two variables, such as name and scope. These variables are used to pass a value from the parent job to a child job.
Yes, it is possible to exclude headers and footers easily before loading the data from the input files.
In Talend Open Studio, all expressions such as Input, Var, Output, and constraint statements can be viewed and edited with the use of the Expression editor. It provides visual comfort to write any function in a dedicated view.
|All the information is stored centrally in the repository.||All the information is stored locally on the job. It allows the user to enter and edit all the information.|
|It enables the user to import read-only information into the Job from the repository.||It allows the user to enter all the information manually.|
|It can be used overall by any Job in the project.||It can be used by the Job only.|
There are few ways in which the error can be handled in Talend are as follows:
In Talend, various jobs and Subjobs in multiple threads can be executed to reduce the runtime of a job. There are three ways for parallel execution in Talend are as follows:
From a results point of view, there are no differences between the two, nor are there significant performance differences. In general, choose the action that matches what you expect to be more common: Insert or Update if you think there are more inserts than updates, Update or Insert if you think there are more updates than inserts.
Yes, you can declare a static variable in a routine, and add the setter/getter methods for this variable in the routine. The variable is then accessible from different Jobs.
By selecting the preferences of the window menu, then by clicking on the color menu, we can change the background color of the job designer.
The following are the configurations that are required to connect HDFS:
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tPigLoad sets up a connection to the data source for a current transaction. It helps to load original input data to an output stream in a single transaction once the data has been validated.
No, it is not possible to define a schema at runtime. The schema defines the movement of data, so it should be defined while configuring the components or at some point of the layout.
|It can handle basic join cases only||It is a powerful component that can handle complicated cases.|
|It supports only unique join||It supports multiple types of join models such as first join, unique join, and all join, etc.,|
|It can accept only two input links such as main and lookup||It can allow multiple input links in which one link is main, and other links are lookups|
|It can accept only two output links such as main and reject||It can allow more than one output links|
|It can not filter the data using filter expressions||It can filter the data with the help of filter expressions;|
|It supports only inner join||It supports inner join and left outer join|
|Extract, Transform, and Load (ETL)||Extract, Load, and Transform (ELT)|
|The ETL process is that it extracts the data, transforms the data, and then it loads the data into the database.||The ELT process is that it extracts the data, loads it into the database, and then it transforms the data.|
|It is easy to implement||It requires good knowledge of tools to implement|
|It supports relational data||It supports the unstructured data|
|It does not provide Data lake support||It allows the use of Data lake support with unstructured data.|
|With the increase in the size of data, the processing slows down, and it requires to wait until the transformation completes||The processing does not depend on the size of the data.|
|It is used to transfer data from the source database to the destination data warehouse.||It is a data manipulation process, which is used in data warehousing.|
Keerthana Jonnalagadda working as a Content Writer at Mindmajix Technologies Inc. She writes on emerging IT technology related topics and likes to share the good quality content through her writings. You can reach her through LinkedIn.