components built using Talend component Kit can be shared as component archives (.car). These CAR files are executable files allowing to easily deploy the components it contains to any compatible version of Talend Studio. component developers can generate .car files from their projects to share their components and make them available for other users, as detailed in this document. This document assumes that you have a component archive (.car) file and need to deploy it to Talend Studio. The component archive (.car) is executable and exposes the studio-deploy command which takes a Talend Studio home path as parameter. When executed, it installs the dependencies into the Studio and registers the component in your instance. For example: You can also upload the dependencies to your Nexus server using the following command: In this command, Nexus URL and repository name are mandatory arguments. All other arguments are optional. If arguments contain spaces or special symbols, you need to quote the whole value of the argument. For example: Talend Studio allows you to share components you have created using Talend component Kit to other users working on the same remote project. Remote projects are available with Enterprise versions of Talend Studio only. Also, note that this feature has been removed in Studio since 7.3 release. Make sure you are connected to a remote project and the artifact repository for component sharing has been properly configured. On the toolbar of the Studio main window, click or click File > Edit Project Properties from the menu bar to open the Project Settings dialog box. In the tree view of the dialog box, select Repository Share to open the corresponding view. Select the Propagate components update to Artifact Repository check box. In the Repository ID field, specify the artifact repository configured for component sharing, and then click Check connection to verify the connectivity. Click Apply and Close to validate the settings and close the dialog box. Create a folder named patches at the root of your Talend Studio installation directory, then copy the .car files of the components you want share to this folder. Restart your Talend Studio and connect to the remote project. The components are deployed automatically to the repository and available in the Palette for other users when connected to a remote project with the same sharing repository configuration. My custom component builds correctly but does not appear in Talend Studio, how to fix it? This issue can be caused by the icon specified in the component metadata. Make sure to specify a custom icon for the component and the component family. These custom icons must be in PNG format to be properly handled by Talend Studio. Remove SVG parameters from the talend.component.server.icon.paths property in the HTTP server configuration. Refer to this section. Learn more about defining custom icons for components in this document.

To develop new components, Talend component Kit requires a build tool in which you will import the component project generated from the starter. You will then be able to install and deploy it to Talend applications. A Talend component Kit plugin is available for each of the supported build tools. talend-component-maven-plugin helps you write components that match best practices and generate transparently metadata used by Talend Studio. You can use it as follows: This plugin is also an extension so you can declare it in your build/extensions block as: Used as an extension, the goals detailed in this document will be set up. The Talend component Kit plugin integrates some specific goals within Maven build lifecycle. For example, to compile the project and prepare for deploying your component, run mvn clean install. Using this command, the following goals are executed: The build is split into several phases. The different goals are executed in the order shown above. Talend component Kit uses default goals from the Maven build lifecycle and adds additional goals to the building and packaging phases. Goals added to the build by Talend component Kit are detailed below. The default lifecycle is detailed in Maven documentation. The Talend component Kit plugin for Maven integrates several specific goals into Maven build lifecycle. To run specific goals individually, run the following command from the root of the project, by adapting it with each goal name, parameters and values: The first goal is a shortcut for the maven-dependency-plugin. It creates the TALEND-INF/dependencies.txt file with the compile and runtime dependencies, allowing the component to use it at runtime: The scan-descriptor goal scans the current module and optionally other configured folders to precompute the list of interesting classes for the framework (components, services). It allows to save some bootstrap time when launching a job, which can be useful in some execution cases: Configuration - excluding parameters used by default only: Name Description User property Default output Where to dump the scan result. Note: It is not supported to change that value in the runtime. talend.scan.output ${project.build.outputDirectory}/TALEND-INF/scanning.properties scannedDirectories Explicit list of directories to scan. talend.scan.scannedDirectories If not set, defaults to ${project.build.outputDirectory} scannedDependencies Explicit list of dependencies to scan - set them in the groupId:artifactId format. The list is appended to the file to scan. talend.scan.scannedDependencies - The svg2png goal scans a directory - default to target/classes/icons - to find .svg files and copy them in a PNG version size at 32x32px and named with the suffix _icon32.png to enable the studio to read it: Configuration: Name Description User property Default icons Where to scan for the SVG icons to convert in PNG. talend.icons.source ${project.build.outputDirectory}/icons workarounds By default the shape of the icon will be enforce in the RGB channels (in white) using the alpha as reference. This is useful for black/white images using alpha to shape the picture because Eclipse - Talend Studio - caches icons using RGB but not alpha channel, pictures not using alpha channel to draw their shape should disable that workaround. talend.icons.workaround true if you use that plugin, ensure to set it before the validate mojo otherwise validation can miss some png files. This goal helps you validate the common programming model of the component. To activate it, you can use following execution definition: It is bound to the process-classes phase by default. When executed, it performs several validations that can be disabled by setting the corresponding flags to false in the block of the execution: Name Description User property Default validateInternationalization Validates that resource bundles are presents and contain commonly used keys (for example, _displayName) talend.validation.internationalization true validateModel Ensures that components pass validations of the componentManager and Talend component runtime talend.validation.model true validateSerializable Ensures that components are Serializable. This is a sanity check, the component is not actually serialized here. If you have a doubt, make sure to test it. It also checks that any @Internationalized class is valid and has its keys. talend.validation.serializable true validateMetadata Ensures that components have an @Icon and a @Version defined. talend.validation.metadata true validateDataStore Ensures that any @DataStore defines a @HealthCheck and has a unique name. talend.validation.datastore true validateDataSet Ensures that any @DataSet has a unique name. Also ensures that there is a source instantiable just filling the dataset properties (all others not being required). Finally, the validation checks that each input or output component uses a dataset and that this dataset has a datastore. talend.validation.dataset true validatecomponent Ensures that the native programming model is respected. You can disable it when using another programming model like Beam. talend.validation.component true validateActions Validates action signatures for actions not tolerating dynamic binding (@HealthCheck, @DynamicValues, and so on). It is recommended to keep it set to true. talend.validation.action true validateFamily Validates the family by verifying that the package containing the @components has a @Icon property defined. talend.validation.family true validateDocumentation Ensures that all components and @Option properties have a documentation using the @Documentation property. talend.validation.documentation true validateLayout Ensures that the layout is referencing existing options and properties. talend.validation.layout true validateOptionNames Ensures that the option names are compliant with the framework. It is highly recommended and safer to keep it set to true. talend.validation.options true validateLocalConfiguration Ensures that if any TALEND-INF/local-configuration.properties exists then keys start with the family name. talend.validation.localConfiguration true validateOutputConnection Ensures that an output has only one input branch. talend.validation.validateOutputConnection true validatePlaceholder Ensures that string options have a placeholder. It is highly recommended to turn this property on. talend.validation.placeholder false locale The locale used to validate internationalization. talend.validation.locale root The asciidoc goal generates an Asciidoc file documenting your component from the configuration model (@Option) and the @Documentation property that you can add to options and to the component itself. Name Description User property Default level Level of the root title. talend.documentation.level 2 (==) output Output folder path. It is recommended to keep it to the default value. talend.documentation.output ${classes}/TALEND-INF/documentation.adoc formats Map of the renderings to do. Keys are the format (pdf or html) and values the output paths. talend.documentation.formats - attributes Asciidoctor attributes to use for the rendering when formats is set. talend.documentation.attributes - templateEngine Template engine configuration for the rendering. talend.documentation.templateEngine - templateDir Template directory for the rendering. talend.documentation.templateDir - title Document title. talend.documentation.title ${project.name} version The component version. It defaults to the pom version talend.documentation.version ${project.version} workDir The template directory for the Asciidoctor rendering - if 'formats' is set. talend.documentation.workdDir ${project.build.directory}/talend-component/workdir attachDocumentations Allows to attach (and deploy) the documentations (.adoc, and formats keys) to the project. talend.documentation.attach true htmlAndPdf If you use the plugin as an extension, you can add this property and set it to true in your project to automatically get HTML and PDF renderings of the documentation. talend.documentation.htmlAndPdf false To render the generated documentation in HTML or PDF, you can use the Asciidoctor Maven plugin (or Gradle equivalent). You can configure both executions if you want both HTML and PDF renderings. Make sure to execute the rendering after the documentation generation. If you prefer a HTML rendering, you can configure the following execution in the asciidoctor plugin. The example below: Generates the components documentation in target/classes/TALEND-INF/documentation.adoc. Renders the documentation as an HTML file stored in target/documentation/documentation.html. If you prefer a PDF rendering, you can configure the following execution in the asciidoctor plugin: If you want to add some more content or a title, you can include the generated document into another document using Asciidoc include directive. For example: To be able to do that, you need to pass the generated_doc attribute to the plugin. For example: This is optional but allows to reuse Maven placeholders to pass paths, which can be convenient in an automated build. You can find more customization options on Asciidoctor website. Testing the rendering of your component configuration into the Studio requires deploying the component in Talend Studio. Refer to the Studio documentation. In the case where you need to deploy your component into a Cloud (web) environment, you can test its web rendering by using the web goal of the plugin: Run the mvn talend-component:web command. Open the following URL in a web browser: localhost:8080. Select the component form you want to see from the treeview on the left. The selected form is displayed on the right. Two parameters are available with the plugin: serverPort, which allows to change the default port (8080) of the embedded server. Its associated user property is talend.web.port. serverArguments, that you can use to pass Meecrowave options to the server. Learn more about that configuration at openwebbeans.apache.org/meecrowave/meecrowave-core/cli.html. Make sure to install the artifact before using this command because it reads the component JAR from the local Maven repository. Finally, you can switch the lang of the component UI (documentation, form) using language query parameter in the webapp. For instance localhost:8080?language=fr. If you built a custom UI (JS + CSS) bundle and want to test it in the web application, you can configure it in the pom.xml file as follows: This is an advanced feature designed for expert users. Use it with caution. component archive (.car) is the way to bundle a component to share it in the Talend ecosystem. It is an executable Java archive (.jar) containing a metadata file and a nested Maven repository containing the component and its dependencies. This command creates a .car file in your build directory. This file can be shared on Talend platforms. This command has some optional parameters: Name Description User property Default attach Specifies whether the component archive should be attached. talend.car.attach true classifier The classifier to use if attach is set to true. talend.car.classifier component metadata Additional custom metadata to bundle in the component archive. - - output Specifies the output path and name of the archive talend.car.output ${project.build.directory}/${project.build.finalName}.car packaging Specifies the packaging - ${project.packaging} type Specifies the type: `connector' or server `extension' talend.car.type connector This CAR is executable and exposes the studio-deploy command which takes a Talend Studio home path as parameter. When executed, it installs the dependencies into the Studio and registers the component in your instance. For example: You can also upload the dependencies to your Nexus server using the following command: In this command, Nexus URL and repository name are mandatory arguments. All other arguments are optional. If arguments contain spaces or special symbols, you need to quote the whole value of the argument. For example: The deploy-in-studio goal deploys the current component module into a local Talend Studio instance. Name Description User property Default studioHome Path to the Studio home directory talend.component.studioHome - studioM2 Path to the Studio maven repository if not the default one talend.component.studioM2 - You can use the following command from the root folder of your project: The help goal displays help information on talend-component-maven-plugin. Call mvn talend-component:help -Ddetail=true -Dgoal= to display the parameter details of a specific goal. Name Description User property Default detail Displays all settable properties for each goal. detail false goal The name of the goal for which to show help. If unspecified, all goals are displayed. goal - indentSize Number of spaces per indentation level. This integer should be positive. indentSize 2 lineLength Maximum length of a display line. This integer should be positive. lineLength 80

The Remote Engine is a key piece for executing components with Talend Pipeline Designer. To customize it for testing purposes, a helper tool is available. The following content and the tool it describes are not officially supported as a Talend Cloud feature and are provided "as it" without any guarantee. The remote-engine-customizer is a simple tool that reads the Remote Engine docker-compose.yml file, extracts the connectors image and rebuilds it adding configured connectors to the image. By default, it replaces the original image with the newly built one and saves the old file in the .remote_engine_customizer/backup/ directory of the Remote Engine. The customizer is provided as a docker container. You can run the tool using the register-component-archive command: You can get more details about the tool with the following command: You can find out all the available versions at hub.docker.com/r/tacokit/remote-engine-customizer/tags. The command accepts the following parameters: When running using the docker container, you must mount several files/folders. For example: Once you have built the new image, you must restart the Remote Engine. You can verify that the new image is available by running docker run --entrypoint sh -it [newimage] before.

To be able to see and use your newly developed components, you need to integrate them to the right application. Currently, you can deploy your components to Talend Studio as part of your development process to iterate on them: Iterating on component development with Talend Studio You can also share your components externally and install them using a component archive (.car) file. Sharing and installing components in Talend Studio Check the versions of the framework that are compatible with your version of Talend Studio in this document. If you were used to create custom components with the Javajet framework and want to get to know the new approach and main differences of the component Kit framework, refer to this document.

Talend component Kit provides a migration mechanism between two versions of a component to let you ensure backward compatibility. For example, a new version of a component may have some new options that need to be remapped, set with a default value in the older versions, or disabled. This tutorial shows how to create a migration handler for a component that needs to be upgraded from a version 1 to a version 2. The upgrade to the newer version includes adding new options to the component. This tutorial assumes that you know the basics about component development and are familiar with component project generation and implementation. To follow this tutorial, you need: Java 8 A Talend component development environment using Talend component Kit. Refer to this document. Have generated a project containing a simple processor component using the Talend component Kit Starter. First, create a simple processor component configured as follows: Create a simple configuration class that represents a basic authentication and that can be used in any component requiring this kind of authentication. Create a simple output component that uses the configuration defined earlier. The component configuration is injected into the component constructor. The version of the configuration class corresponds to the component version. By configuring these two classes, the first version of the component is ready to use a simple authentication mechanism. Now, assuming that the component needs to support a new authentication mode following a new requirement, the next steps are: Creating a version 2 of the component that supports the new authentication mode. Handling migration from the first version to the new version. The second version of the component needs to support a new authentication method and let the user choose the authentication mode he wants to use using a dropdown list. Add an Oauth2 authentication mode to the component in addition to the basic mode. For example: The options of the new authentication mode are now defined. Wrap the configuration created above in a global configuration with the basic authentication mode and add an enumeration to let the user choose the mode to use. For example, create an AuthenticationConfiguration class as follows: Using the @ActiveIf annotation allows to activate the authentication type according to the selected authentication mode. Edit the component to use the new configuration that supports an additional authentication mode. Also upgrade the component version from 1 to 2 as its configuration has changed. The component now supports two authentication modes in its version 2. Once the new version is ready, you can implement the migration handler that will take care of adapting the old configuration to the new one. What can happen if an old configuration is passed to the new component version? It simply fails, as the version 2 does not recognize the old version anymore. For that reason, a migration handler that adapts the old configuration to the new one is required. It can be achieved by defining a migration handler class in the @Version annotation of the component class. An old configuration may already be persisted by an application that integrates the version 1 of the component (Studio or web application). Add a migration handler class to the component version. Create the migration handler class MyOutputMigrationHandler. the incoming version, which is the version of the configuration that we are migrating from a map (key, value) of the configuration, where the key is the configuration path and the value is the value of the configuration. You need to be familiar with the component configuration path construction to better understand this part. Refer to Defining component layout and configuration. As a reminder, the following changes were made since the version 1 of the component: The configuration BasicAuth from the version 1 is not the root configuration anymore, as it is under AuthenticationConfiguration. AuthenticationConfiguration is the new root configuration. The component supports a new authentication mode (Oauth2) which is the default mode in the version 2 of the component. To migrate the old component version to the new version and to keep backward compatibility, you need to: Remap the old configuration to the new one. Give the adequate default values to some options. In the case of this scenario, it means making all configurations based on the version 1 of the component have the authenticationMode set to basic by default and remapping the old basic authentication configuration to the new one. if a configuration has been renamed between 2 component versions, you can get the old configuration option from the configuration map by using its old path and set its value using its new path. You can now upgrade your component without losing backward compatibility.

By default, input components are designed to receive a one-time batch of data to process. By enabling the streaming mode, you can instead set your component to process a continuous incoming flow of data. When streaming is enabled on an input component, the component tries to pull data from its producer. When no data is pulled, it waits for a defined period of time before trying to pull data again, and so on. This period of time between tries is defined by a strategy. This document explains how to configure this strategy and the cases where it can fit your needs. Before enabling streaming on your component, make sure that it fits the scope and requirements of your project and that regular batch processing cannot be used instead. Streaming is designed to help you dealing with real-time or near real-time data processing cases, and should be used only for such cases. Enabling streaming will impact the performance when processing batches of data. You can enable streaming right from the design phase of the project by enabling the Stream toggle in the basic configuration of your future component in the component Kit Starter. Doing so adds a default streaming-ready configuration to your component when generating the project. This default configuration implements a constant pause duration of 500 ms between retries, with no limit of retries. Without any configuration, streaming components have an infinite lifecycle and will never stop. Sometimes, you may need to stop component after a certain amount of records read or time elapsed. You can add configuration that helps you to stop the data reading in your input component when it reaches required limitations. To enable it you need to set true in PartitionMapper#stoppable. An important condition is that PartitionMapper#infinite should also be true. Here’s a sample code: There are two reading stop conditions (can be combined): maxDurationMs : stop after n milliseconds elapsed. maxRecords : stop after n records read. See next subsections for configuring those values. If you choose to use a stoppable streaming component, you will have certainly to adapt your code according the backend technology and how to read values. For instance, if in your component you read 100 values at once and the maxRecords value is 50, you may lose 50 values (if the 100 values were acknowledged). In that case, to build a correct strategy in your component, you can access to stop condition values. To access these informations use the @PostConstruct method with @Option annotation in your Emitter class. Available options: Option.MAX_DURATION_PARAMETER : reflects the maxDurationMs parameter. Option.MAX_RECORDS_PARAMETER : reflects the maxRecords parameter. Here a code sample: If your streaming connector (infinite=true) is defined with the stoppable=true, you will have a design time UI for specifying stop strategy: Cloud Studio By default, in the setting those values are set to -1. It means infinity behavior. At runtime, you can set system properties to apply the strategy. You need to prefix properties with the component’s family. .talend.input.streaming.maxRecords .talend.input.streaming.maxDurationMs You can also use the LocalConfiguration (see next section) with the following properties: talend.input.streaming.maxRecords talend.input.streaming.maxDurationMs If streaming was not enabled at all during the project generation or if you need to implement a more specific configuration, you can change the default settings according to your needs: Add the infinite=true parameter to your component class. Define the number of retries allowed in the component family LocalConfiguration, using the talend.input.streaming.retry.maxRetries parameter. It is set by default to Integer.MAX_VALUE. Define the pausing strategy between retries in the component family LocalConfiguration, using the talend.input.streaming.retry.strategy parameter. Possible values are: constant (default). It sets a constant pause duration between retries. exponential. It sets an exponential backoff pause duration. See the tables below for more details about each strategy. Parameter Description Default value talend.input.streaming.retry.constant.timeout Pause duration for the constant strategy, in ms. 500 Parameter Description Default value talend.input.streaming.retry.exponential.exponent Exponent of the exponential calculation. 1.5 talend.input.streaming.retry.exponential.randomizationFactor Randomization factor used in the calculation. 0.5 talend.input.streaming.retry.exponential.maxDuration Maximum pausing duration between two retries. 5*60*1000 (5 minutes) talend.input.streaming.retry.exponential.initialBackOff Initial backoff value. 1000 (1 second) The values of these parameters are then used in the following calculations to determine the exact pausing duration between two retries. For more clarity in the formulas below, parameter names have been replaced with variables. First, the current interval duration is calculated: `A = min(B xx E^I, F)` Where: A: currentIntervalMillis B: initialBackOff E: exponent I: current number of retries F: maxDuration Then, from the current interval duration, the next interval duration is calculated: `D = min(F, A + ((R xx 2-1) xx C xx A))` Where: D: nextBackoffMillis F: maxDuration A: currentIntervalMillis R: random C: randomizationFactor

Since the 1.1.25 release, the dynamic column feature is supported in Studio with component-runtime components. Dynamic column is available with Enterprise versions of Talend Studio only. In Studio, we can define for each component a schema with associated metadata. To access those informations in your component, you’ve to do a few things: Using the @Structure annotation API: @org.talend.sdk.component.api.configuration.ui.widget.Structure According the specified field type, you will acess to the column names list with List a subset or all wanted metadata with List (see below) Then, we should have a class SchemaInfo as following: Defining a specific class for holding metadata If you don’t want just only column names (using List), you’ll have to define a custom class. Available Studio metadata informations Field name Type Name in Studio label String Column originalDbColumnName String Db Column key Boolean Key type String DB Type talendType String Type nullable Boolean Nullable pattern String Date Pattern length int Length precision int Precision defaultValue String Default comment String Comment Available since 1.43.x release As Talend component Kit Schema's types aren’t matching all Studio types, we wrap those types in wider types (like Character or char wrapped into String, Short to Integer, and so on…). Anyway, the original type coming from Studio’s IPersistableRow is stored in record’s schema properties under the property name talend.studio.type. Studio managed types are: id_BigDecimal, id_Boolean, id_Byte, id_byte[], id_Character, id_Date, id_Double, id_Document, id_Dynamic, id_Float, id_Integer, id_List, id_Long, id_Object, id_Short, id_String. When handling an output connector designed for Studio, you should have to check for this property to get an accurate type for output. For instance, java.math.BigDecimal is handled in framework as a Type.STRING, so when an output connector will receive a record, in studio context, you’ll need to check for the property and cast it correctly. Here is a simple processor before writing to backend destination: This usage of properties is cumbersome but may fix some potential issues for now. We plan to widen managed types in Record and Schema in a few iterations (No ETA defined yet). There are two annotations allowing to discover a component’s schema: @DiscoverSchema (only for input components) @DiscoverSchemaExtended (all components) Prototype: As you may pass other parameters to method, ensure to use the above naming : incomingSchema for the schema and branch for the outgoing branch. Example: Try to find an action in declared Service class search an action of type @DiscoverSchema named like the input dataset. search an action of type @DiscoverSchemaExtended named like the input dataset. search an action of type @DiscoverSchema. Execute a fake job with component to retrieve output schema. Try to find an action in declared Service class search an action of type @DiscoverSchemaExtended named like the input dataset. search an action of type @DiscoverSchemaExtended.

This tutorial shows how to create components that consume a REST API. The component developed as example in this tutorial is an input component that provides a search functionality for Zendesk using its Search API. Lombok is used to avoid writing getter, setter and constructor methods. You can generate a project using the Talend components Kit starter, as described in this tutorial. The input component relies on Zendesk Search API and requires an HTTP client to consume it. The Zendesk Search API takes the following parameters on the /api/v2/search.json endpoint. query : The search query. sort_by : The sorting type of the query result. Possible values are updated_at, created_at, priority, status, ticket_type, or relevance. It defaults to relevance. sort_order: The sorting order of the query result. Possible values are asc (for ascending) or desc (for descending). It defaults to desc. Talend component Kit provides a built-in service to create an easy-to-use HTTP client in a declarative manner, using Java annotations. No additional implementation is needed for the interface, as it is provided by the component framework, according to what is defined above. This HTTP client can be injected into a mapper or a processor to perform HTTP requests. This example uses the basic authentication that supported by the API. The first step is to set up the configuration for the basic authentication. To be able to consume the Search API, the Zendesk instance URL, the username and the password are needed. The data store is now configured. It provides a basic authentication token. Once the data store is configured, you can define the dataset by configuring the search query. It is that query that defines the records processed by the input component. Your component is configured. You can now create the component logic. Mappers defined with this tutorial don’t implement the split part because HTTP calls are not split on many workers in this case. Once the component logic implemented, you can create the source in charge of performing the HTTP request to the search API and converting the result to JsonObject records. You now have created a simple Talend component that consumes a REST API. To learn how to test this component, refer to this tutorial.

The component Kit Starter lets you design your components configuration and generates a ready-to-implement project structure. The Starter is available on the web or as an IntelliJ plugin. This tutorial shows you how to use the component Kit Starter to generate new components for MySQL databases. Before starting, make sure that you have correctly setup your environment. See this section. When defining a project using the Starter, do not refresh the page to avoid losing your configuration. Before being able to create components, you need to define the general settings of the project: Create a folder on your local machine to store the resource files of the component you want to create. For example, C:/my_components. Open the Starter in the web browser of your choice. Select your build tool. This tutorial uses Maven, but you can select Gradle instead. Add any facet you need. For example, add the Talend component Kit Testing facet to your project to automatically generate unit tests for the components created in the project. Enter the component Family of the components you want to develop in the project. This name must be a valid java name and is recommended to be capitalized, for example 'MySQL'. Once you have implemented your components in the Studio, this name is displayed in the Palette to group all of the MySQL-related components you develop, and is also part of your component name. Select the Category of the components you want to create in the current project. As MySQL is a kind of database, select Databases in this tutorial. This Databases category is used and displayed as the parent family of the MySQL group in the Palette of the Studio. Complete the project metadata by entering the Group, Artifact and Package. By default, you can only create processors. If you need to create Input or Output components, select Activate IO. By doing this: Two new menu entries let you add datasets and datastores to your project, as they are required for input and output components. Input and Output components without dataset (itself containing a datastore) will not pass the validation step when building the components. Learn more about datasets and datastores in this document. An Input component and an Output component are automatically added to your project and ready to be configured. components added to the project using Add A component can now be processors, input or output components. A datastore represents the data needed by an input or output component to connect to a database. When building a component, the validateDataSet validation checks that each input or output (processor without output branch) component uses a dataset and that this dataset has a datastore. You can define one or several datastores if you have selected the Activate IO step. Select Datastore. The list of datastores opens. By default, a datastore is already open but not configured. You can configure it or create a new one using Add new Datastore. Specify the name of the datastore. Modify the default value to a meaningful name for your project. This name must be a valid Java name as it will represent the datastore class in your project. It is a good practice to start it with an uppercase letter. Edit the datastore configuration. Parameter names must be valid Java names. Use lower case as much as possible. A typical configuration includes connection details to a database: url username password. Save the datastore configuration. A dataset represents the data coming from or sent to a database and needed by input and output components to operate. The validateDataSet validation checks that each input or output (processor without output branch) component uses a dataset and that this dataset has a datastore. You can define one or several datasets if you have selected the Activate IO step. Select Dataset. The list of datasets opens. By default, a dataset is already open but not configured. You can configure it or create a new one using the Add new Dataset button. Specify the name of the dataset. Modify the default value to a meaningful name for your project. This name must be a valid Java name as it will represent the dataset class in your project. It is a good practice to start it with an uppercase letter. Edit the dataset configuration. Parameter names must be valid Java names. Use lower case as much as possible. A typical configuration includes details of the data to retrieve: Datastore to use (that contains the connection details to the database) table name data Save the dataset configuration. To create an input component, make sure you have selected Activate IO. When clicking Add A component in the Starter, a new step allows you to define a new component in your project. The intent in this tutorial is to create an input component that connects to a MySQL database, executes a SQL query and gets the result. Choose the component type. Input in this case. Enter the component name. For example, MySQLInput. Click Configuration model. This button lets you specify the required configuration for the component. By default, a dataset is already specified. For each parameter that you need to add, click the (+) button on the right panel. Enter the parameter name and choose its type then click the tick button to save the changes. In this tutorial, to be able to execute a SQL query on the Input MySQL database, the configuration requires the following parameters:+ a dataset (which contains the datastore with the connection information) a timeout parameter. Closing the configuration panel on the right does not delete your configuration. However, refreshing the page resets the configuration. Specify whether the component issues a stream or not. In this tutorial, the MySQL input component created is an ordinary (non streaming) component. In this case, leave the Stream option disabled. Select the Record Type generated by the component. In this tutorial, select Generic because the component is designed to generate records in the default Record format. You can also select Custom to define a POJO that represents your records. Your input component is now defined. You can add another component or generate and download your project. When clicking Add A component in the Starter, a new step allows you to define a new component in your project. The intent in this tutorial is to create a simple processor component that receives a record, logs it and returns it at it is. If you did not select Activate IO, all new components you add to the project are processors by default. If you selected Activate IO, you can choose the component type. In this case, to create a Processor component, you have to manually add at least one output. If required, choose the component type: Processor in this case. Enter the component name. For example, RecordLogger, as the processor created in this tutorial logs the records. Specify the Configuration Model of the component. In this tutorial, the component doesn’t need any specific configuration. Skip this step. Define the Input(s) of the component. For each input that you need to define, click Add Input. In this tutorial, only one input is needed to receive the record to log. Click the input name to access its configuration. You can change the name of the input and define its structure using a POJO. If you added several inputs, repeat this step for each one of them. The input in this tutorial is a generic record. Enable the Generic option and click Save. Define the Output(s) of the component. For each output that you need to define, click Add Output. The first output must be named MAIN. In this tutorial, only one generic output is needed to return the received record. Outputs can be configured the same way as inputs (see previous steps). You can define a reject output connection by naming it REJECT. This naming is used by Talend applications to automatically set the connection type to Reject. Your processor component is now defined. You can add another component or generate and download your project. To create an output component, make sure you have selected Activate IO. When clicking Add A component in the Starter, a new step allows you to define a new component in your project. The intent in this tutorial is to create an output component that receives a record and inserts it into a MySQL database table. Output components are Processors without any output. In other words, the output is a processor that does not produce any records. Choose the component type. Output in this case. Enter the component name. For example, MySQLOutput. Click Configuration Model. This button lets you specify the required configuration for the component. By default, a dataset is already specified. For each parameter that you need to add, click the (+) button on the right panel. Enter the name and choose the type of the parameter, then click the tick button to save the changes. In this tutorial, to be able to insert a record in the output MySQL database, the configuration requires the following parameters:+ a dataset (which contains the datastore with the connection information) a timeout parameter. Closing the configuration panel on the right does not delete your configuration. However, refreshing the page resets the configuration. Define the Input(s) of the component. For each input that you need to define, click Add Input. In this tutorial, only one input is needed. Click the input name to access its configuration. You can change the name of the input and define its structure using a POJO. If you added several inputs, repeat this step for each one of them. The input in this tutorial is a generic record. Enable the Generic option and click Save. Do not create any output because the component does not produce any record. This is the only difference between an output an a processor component. Your output component is now defined. You can add another component or generate and download your project. Once your project is configured and all the components you need are created, you can generate and download the final project. In this tutorial, the project was configured and three components of different types (input, processor and output) have been defined. Click Finish on the left panel. You are redirected to a page that summarizes the project. On the left panel, you can also see all the components that you added to the project. Generate the project using one of the two options available: Download it locally as a ZIP file using the Download as ZIP button. Create a GitHub repository and push the project to it using the Create on Github button. In this tutorial, the project is downloaded to the local machine as a ZIP file. Once the package is available on your machine, you can compile it using the build tool selected when configuring the project. In the tutorial, Maven is the build tool selected for the project. In the project directory, execute the mvn package command. If you don’t have Maven installed on your machine, you can use the Maven wrapper provided in the generated project, by executing the ./mvnw package command. If you have created a Gradle project, you can compile it using the gradle build command or using the Gradle wrapper: ./gradlew build. The generated project code contains documentation that can guide and help you implementing the component logic. Import the project to your favorite IDE to start the implementation. The component Kit Starter allows you to generate a component development project from an OpenAPI JSON descriptor. Open the Starter in the web browser of your choice. Enable the OpenAPI mode using the toggle in the header. Go to the API menu. Paste the OpenAPI JSON descriptor in the right part of the screen. All the described endpoints are detected. Unselect the endpoints that you do not want to use in the future components. By default, all detected endpoints are selected. Go to the Finish menu. Download the project. When exploring the project generated from an OpenAPI descriptor, you can notice the following elements: sources the API dataset an HTTP client for the API a connection folder containing the component configuration. By default, the configuration is only made of a simple datastore with a baseUrl parameter.

The component configuration is defined in the <component_name>Configuration.java file of the package. It consists in defining the configurable part of the component that will be displayed in the UI. To do that, you can specify parameters. When you import the project in your IDE, the parameters that you have specified in the starter are already present. All input and output components must reference a dataset in their configuration. Refer to Defining datasets and datastores. components are configured using their constructor parameters. All parameters can be marked with the @Option property, which lets you give a name to them. For the name to be correct, you must follow these guidelines: Use a valid Java name. Do not include any . character in it. Do not start the name with a $. Defining a name is optional. If you don’t set a specific name, it defaults to the bytecode name. This can require you to compile with a -parameter flag to avoid ending up with names such as arg0, arg1, and so on. Examples of option name: Option name Valid myName my_name my.name $myName Parameter types can be primitives or complex objects with fields decorated with @Option exactly like method parameters. It is recommended to use simple models which can be serialized in order to ease serialized component implementations. For example: Using this kind of API makes the configuration extensible and component-oriented, which allows you to define all you need. The instantiation of the parameters is done from the properties passed to the component. A primitive is a class which can be directly converted from a String to the expected type. It includes all Java primitives, like the String type itself, but also all types with a org.apache.xbean.propertyeditor.Converter: BigDecimal BigInteger File InetAddress ObjectName URI URL Pattern LocalDateTime ZonedDateTime The conversion from property to object uses the Dot notation. For example, assuming the method parameter was configured with @Option("file"): matches Lists rely on an indexed syntax to define their elements. For example, assuming that the list parameter is named files and that the elements are of the FileOptions type, you can define a list of two elements as follows: if you desire to override a config to truncate an array, use the index length, for example to truncate previous example to only CSV, you can set: Similarly to the list case, the map uses .key[index] and .value[index] to represent its keys and values: Avoid using the Map type. Instead, prefer configuring your component with an object if this is possible. You can use metadata to specify that a field is required or has a minimum size, and so on. This is done using the validation metadata in the org.talend.sdk.component.api.configuration.constraint package: Ensure the decorated option size is validated with a higher bound. API: @org.talend.sdk.component.api.configuration.constraint.Max Name: maxLength Parameter Type: double Supported Types: — java.lang.CharSequence Sample: Ensure the decorated option size is validated with a lower bound. API: @org.talend.sdk.component.api.configuration.constraint.Min Name: minLength Parameter Type: double Supported Types: — java.lang.CharSequence Sample: Validate the decorated string with a javascript pattern (even into the Studio). API: @org.talend.sdk.component.api.configuration.constraint.Pattern Name: pattern Parameter Type: java.lang.string Supported Types: — java.lang.CharSequence Sample: Ensure the decorated option size is validated with a higher bound. API: @org.talend.sdk.component.api.configuration.constraint.Max Name: max Parameter Type: double Supported Types: — java.lang.Number — int — short — byte — long — double — float Sample: Ensure the decorated option size is validated with a lower bound. API: @org.talend.sdk.component.api.configuration.constraint.Min Name: min Parameter Type: double Supported Types: — java.lang.Number — int — short — byte — long — double — float Sample: Mark the field as being mandatory. API: @org.talend.sdk.component.api.configuration.constraint.Required Name: required Parameter Type: - Supported Types: — java.lang.Object Sample: Ensure the decorated option size is validated with a higher bound. API: @org.talend.sdk.component.api.configuration.constraint.Max Name: maxItems Parameter Type: double Supported Types: — java.util.Collection Sample: Ensure the decorated option size is validated with a lower bound. API: @org.talend.sdk.component.api.configuration.constraint.Min Name: minItems Parameter Type: double Supported Types: — java.util.Collection Sample: Ensure the elements of the collection must be distinct (kind of set). API: @org.talend.sdk.component.api.configuration.constraint.Uniques Name: uniqueItems Parameter Type: - Supported Types: — java.util.Collection Sample: When using the programmatic API, metadata is prefixed by tcomp::. This prefix is stripped in the web for convenience, and the table above uses the web keys. Also note that these validations are executed before the runtime is started (when loading the component instance) and that the execution will fail if they don’t pass. If it breaks your application, you can disable that validation on the JVM by setting the system property talend.component.configuration.validation.skip to true. Datasets and datastores are configuration types that define how and where to pull the data from. They are used at design time to create shared configurations that can be stored and used at runtime. All connectors (input and output components) created using Talend component Kit must reference a valid dataset. Each dataset must reference a datastore. Datastore: The data you need to connect to the backend. Dataset: A datastore coupled with the data you need to execute an action. Make sure that: a datastore is used in each dataset. each dataset has a corresponding input component (mapper or emitter). This input component must be able to work with only the dataset part filled by final users. Any other property implemented for that component must be optional. These rules are enforced by the validateDataSet validation. If the conditions are not met, the component builds will fail. Make sure that: a datastore is used in each dataset. each dataset has a corresponding input component (mapper or emitter). This input component must be able to work with only the dataset part filled by final users. Any other property implemented for that component must be optional. These rules are enforced by the validateDataSet validation. If the conditions are not met, the component builds will fail. A datastore defines the information required to connect to a data source. For example, it can be made of: a URL a username a password. You can specify a datastore and its context of use (in which dataset, etc.) from the component Kit Starter. Make sure to modelize the data your components are designed to handle before defining datasets and datastores in the component Kit Starter. Once you generate and import the project into an IDE, you can find datastores under a specific datastore node. Example of datastore: A dataset represents the inbound data. It is generally made of: A datastore that defines the connection information needed to access the data. A query. You can specify a dataset and its context of use (in which input and output component it is used) from the component Kit Starter. Make sure to modelize the data your components are designed to handle before defining datasets and datastores in the component Kit Starter. Once you generate and import the project into an IDE, you can find datasets under a specific dataset node. Example of dataset referencing the datastore shown above: The display name of each dataset and datastore must be referenced in the message.properties file of the family package. The key for dataset and datastore display names follows a defined pattern: ${family}.${configurationType}.${name}._displayName. For example: These keys are automatically added for datasets and datastores defined from the component Kit Starter. When deploying a component or set of components that include datasets and datastores to Talend Studio, a new node is created under Metadata. This node has the name of the component family that was deployed. It allows users to create reusable configurations for datastores and datasets. With predefined datasets and datastores, users can then quickly fill the component configuration in their jobs. They can do so by selecting Repository as Property Type and by browsing to the predefined dataset or datastore. Studio will generate connection and close components auto for reusing connection function in input and output components, just need to do like this example: Then the runtime mapper and processor only need to use @Connection to get the connection like this: The component server scans all configuration types and returns a configuration type index. This index can be used for the integration into the targeted platforms (Studio, web applications, and so on). Mark a model (complex object) as being a dataset. API: @org.talend.sdk.component.api.configuration.type.DataSet Sample: Mark a model (complex object) as being a datastore (connection to a backend). API: @org.talend.sdk.component.api.configuration.type.DataStore Sample: Mark a model (complex object) as being a dataset discovery configuration. API: @org.talend.sdk.component.api.configuration.type.DatasetDiscovery Sample: The component family associated with a configuration type (datastore/dataset) is always the one related to the component using that configuration. The configuration type index is represented as a flat tree that contains all the configuration types, which themselves are represented as nodes and indexed by ID. Every node can point to other nodes. This relation is represented as an array of edges that provides the child IDs. As an illustration, a configuration type index for the example above can be defined as follows: If you need to define a binding between properties, you can use a set of annotations: If the evaluation of the element at the location matches value then the element is considered active, otherwise it is deactivated. API: @org.talend.sdk.component.api.configuration.condition.ActiveIf Type: if Sample: Allows to set multiple visibility conditions on the same property. API: @org.talend.sdk.component.api.configuration.condition.ActiveIfs Type: ifs Sample: Where: target is the element to evaluate. value is the value to compare against. strategy (optional) is the evaluation criteria. Possible values are: CONTAINS: Checks if a string or list of strings contains the defined value. DEFAULT: Compares against the raw value. LENGTH: For an array or string, evaluates the size of the value instead of the value itself. negate (optional) defines if the test must be positive (default, set to false) or negative (set to true). operator (optional) is the comparison operator used to combine several conditions, if applicable. Possible values are AND and OR. The target element location is specified as a relative path to the current location, using Unix path characters. The configuration class delimiter is /. The parent configuration class is specified by ... Thus, ../targetProperty denotes a property, which is located in the parent configuration class and is named targetProperty. When using the programmatic API, metadata is prefixed with tcomp::. This prefix is stripped in the web for convenience, and the previous table uses the web keys. For more details, refer to the related Javadocs. A common use of the ActiveIf condition consists in testing if a target property has a value. To do that, it is possible to test if the length of the property value is different from 0: target: foo - the path to the property to evaluate. strategy: LENGTH - the strategy consists here in testing the length of the property value. value: 0 - the length of the property value is compared to 0. negate: true - setting negate to true means that the strategy of the target must be different from the value defined. In this case, the LENGTH of the value of the foo property must be different from 0. The following example shows how to implement visibility conditions on several fields based on several checkbox configurations: If the first checkbox is selected, an additional input field is displayed. if the second or the third checkbox is selected, an additional input field is displayed. if both second and third checkboxes are selected, an additional input field is displayed. In some cases, you may need to add metadata about the configuration to let the UI render that configuration properly. For example, a password value that must be hidden and not a simple clear input box. For these cases - if you want to change the UI rendering - you can use a particular set of annotations: Provide a default value the UI can use - only for primitive fields. API: @org.talend.sdk.component.api.configuration.ui.DefaultValue Allows to sort a class properties. API: @org.talend.sdk.component.api.configuration.ui.OptionsOrder Request the rendered to do what it thinks is best. API: @org.talend.sdk.component.api.configuration.ui.layout.AutoLayout Advanced layout to place properties by row, this is exclusive with @OptionsOrder. the logic to handle forms (gridlayout names) is to use the only layout if there is only one defined, else to check if there are Main and Advanced and if at least Main exists, use them, else use all available layouts. API: @org.talend.sdk.component.api.configuration.ui.layout.GridLayout Allow to configure multiple grid layouts on the same class, qualified with a classifier (name) API: @org.talend.sdk.component.api.configuration.ui.layout.GridLayouts Put on a configuration class it notifies the UI an horizontal layout is preferred. API: @org.talend.sdk.component.api.configuration.ui.layout.HorizontalLayout Put on a configuration class it notifies the UI a vertical layout is preferred. API: @org.talend.sdk.component.api.configuration.ui.layout.VerticalLayout Mark a table column filled by component’s schema auto. Only for studio. API: @org.talend.sdk.component.api.configuration.ui.widget.BasedOnSchema Mark a field as being represented by some code widget (vs textarea for instance). API: @org.talend.sdk.component.api.configuration.ui.widget.Code Mark a field as being a credential. It is typically used to hide the value in the UI. API: @org.talend.sdk.component.api.configuration.ui.widget.Credential Mark a field as being a date. It supports and is implicit - which means you don’t need to put that annotation on the option - for java.time.ZonedDateTime, java.time.LocalDate and java.time.LocalDateTime and is unspecified for other types. API: @org.talend.sdk.component.api.configuration.ui.widget.DateTime Mark a string field as being represented by selected module list widget, only for studio API: @org.talend.sdk.component.api.configuration.ui.widget.ModuleList Mark a option as being represented by file or directory widget. Only for studio. API: @org.talend.sdk.component.api.configuration.ui.widget.Path Mark a List or List

component-runtime-junit is a test library that allows you to validate simple logic based on the Talend component Kit tooling. To import it, add the following dependency to your project: This dependency also provides mocked components that you can use with your own component to create tests. The mocked components are provided under the test family: emitter : a mock of an input component collector : a mock of an output component The collector is "per thread" by default. If you are executing a Beam (or concurrent) job, it will not work. To switch to a JVM wide storage, set the talend.component.junit.handler.state system property to static (default being thread). You can do it in a maven-surefire-plugin execution. You can define a standard JUnit test and use the SimplecomponentRule rule: The rule can also be defined as a @ClassRule to start it once per class and not per test as with @Rule. To go further, you can add the ServiceInjectionRule rule, which allows to inject all the component family services into the test class by marking test class fields with @Service: The JUnit 5 integration is very similar to JUnit 4, except that it uses the JUnit 5 extension mechanism. The entry point is the @Withcomponents annotation that you add to your test class, and which takes the component package you want to test. You can use @Injected to inject an instance of componentsHandler - which exposes the same utilities than the JUnit 4 rule - in a test class field : If you use JUnit 5 for the first time, keep in mind that the imports changed and that you need to use org.junit.jupiter.api.Test instead of org.junit.Test. Some IDE versions and surefire versions can also require you to install either a plugin or a specific configuration. As for JUnit 4, you can go further by injecting test class fields marked with @Service, but there is no additional extension to specify in this case: Streaming components have the issue to not stop by design. The Job DSL exposes two properties to help with that issue: streaming.maxRecords: enables to request a maximum number of records streaming.maxDurationMs: enables to request a maximum duration for the execution of the input You can set them as properties on the job: Using the test://collector component as shown in the previous sample stores all records emitted by the chain (typically your source) in memory. You can then access them using theSimplecomponentRule.getCollectedData(type). Note that this method filters by type. If you don’t need any specific type, you can use Object.class. The input mocking is symmetric to the output. In this case, you provide the data you want to inject: The component configuration is a POJO (using @Option on fields) and the runtime configuration (ExecutionChainBuilder) uses a Map. To make the conversion easier, the JUnit integration provides a SimpleFactory.configurationByExample utility to get this map instance from a configuration instance. Example: The same factory provides a fluent DSL to create the configuration by calling configurationByExample without any parameter. The advantage is to be able to convert an object as a Map or as a query string in order to use it with the Job DSL: It handles the encoding of the URI to ensure it is correctly done. When writing tests for your components, you can force the maxBatchSize parameter value by setting it with the following syntax: $configuration.$maxBatchSize=10. The SimplecomponentRule also allows to test a mapper unitarily. You can get an instance from a configuration and execute this instance to collect the output. Example: As for a mapper, a processor is testable unitary. However, this case can be more complex in case of multiple inputs or outputs. Example: The rule allows you to instantiate a Processor from your code, and then to collect the output from the inputs you pass in. There are two convenient implementations of the input factory: MainInputFactory for processors using only the default input. JoinInputfactory with the withInput(branch, data) method for processors using multiple inputs. The first argument is the branch name and the second argument is the data used by the branch. If needed, you can also implement your own input representation using org.talend.sdk.component.junit.ControllableInputFactory. The following artifact allows you to test against a Spark cluster: The testing relies on a JUnit TestRule. It is recommended to use it as a @ClassRule, to make sure that a single instance of a Spark cluster is built. You can also use it as a simple @Rule, to create the Spark cluster instances per method instead of per test class. The @ClassRule takes the Spark and Scala versions to use as parameters. It then forks a master and N slaves. Finally, the submit* method allows you to send jobs either from the test classpath or from a shade if you run it as an integration test. For example: This testing methodology works with @Parameterized. You can submit several jobs with different arguments and even combine it with Beam TestPipeline if you make it transient. The integration of that Spark cluster logic with JUnit 5 is done using the @WithSpark marker for the extension. Optionally, it allows you to inject—through @SparkInject—the BaseSpark handler to access the Spark cluster meta information. For example, its host/port. Example: Currently, SparkClusterRule does not allow to know when a job execution is done, even by exposing and polling the web UI URL to check. The best solution at the moment is to make sure that the output of your job exists and contains the right value. awaitability or any equivalent library can help you to implement such logic: To wait until a file exists and check that its content (for example) is the expected one, you can use the following logic: The HTTP JUnit module allows you to mock REST API very simply. The module coordinates are: This module uses Apache Johnzon and Netty. If you have any conflict (in particular with Netty), you can add the shaded classifier to the dependency. This way, both dependencies are shaded, which avoids conflicts with your component. It supports both JUnit 4 and JUnit 5. The concept is the exact same one: the extension/rule is able to serve precomputed responses saved in the classpath. You can plug your own ResponseLocator to map a request to a response, but the default implementation - which should be sufficient in most cases - looks in talend/testing/http/_.json. Note that you can also put it in talend/testing/http/.json. JUnit 4 setup is done through two rules: JUnit4HttpApi, which is starts the server. JUnit4HttpApiPerMethodConfigurator, which configures the server per test and also handles the capture mode. If you don’t use the JUnit4HttpApiPerMethodConfigurator, the capture feature is disabled and the per test mocking is not available. For tests using SSL-based services, you need to use activeSsl() on the JUnit4HttpApi rule. You can access the client SSL socket factory through the API handler: Sometimes the query parameters are sensitive and you don’t want to store them when capturing. In such cases, you can drop them from the captured data (.json) and the mock implementation will be able to match the request ignoring the query parameters. JUnit 5 uses a JUnit 5 extension based on the HttpApi annotation that you can add to your test class. You can inject the test handler - which has some utilities for advanced cases - through @HttpApiInject: The injection is optional and the @HttpApi annotation allows you to configure several test behaviors. For tests using SSL-based services, you need to use @HttpApi(useSsl = true). You can access the client SSL socket factory through the API handler: The strength of this implementation is to run a small proxy server and to auto-configure the JVM: http[s].proxyHost, http[s].proxyPort, HttpsURLConnection#defaultSSLSocketFactory and SSLContext#default are auto-configured to work out-of-the-box with the proxy. It allows you to keep the native and real URLs in your tests. For example, the following test is valid: If you execute this test, it fails with an HTTP 400 error because the proxy does not find the mocked response. You can create it manually, as described in component-runtime-http-junit, but you can also set the talend.junit.http.capture property to the folder storing the captures. It must be the root folder and not the folder where the JSON files are located (not prefixed by talend/testing/http by default). In most cases, use src/test/resources. If new File("src/test/resources") resolves the valid folder when executing your test (Maven default), then you can just set the system property to true. Otherwise, you need to adjust accordingly the system property value. When set to false, the capture is enabled. Instead, captures are saved in a false/ directory. When the tests run with this system property, the testing framework creates the correct mock response files. After that, you can remove the system property. The tests will still pass, using google.com, even if you disconnect your machine from the Internet. If you set the talend.junit.http.passthrough system property to true, the server acts as a proxy and executes each request to the actual server - similarly to the capturing mode. With its @ParameterizedTest, you can want to customize the name of the output file for JUnit 5 based captures/mocks. Concretely you want to ensure the replay of the same method with different data lead to different mock files. By default the framework will use the display name of the test to specialize it but it is not always very friendly. If you want some more advanced control over the name you can use @HttpApiName("myCapture.json") on the test method. To parameterize the name using @HttpApiName, you can use the placeholders ${class} and ${method} which represents the declaring class and method name, and ${displayName} which represents the method name. Here is an example to use the same capture file for all repeated test: And here, the same example but using different files for each repetition:

This tutorial is the continuation of Talend Input component for Hazelcast tutorial. We will not walk through the project creation again, So please start from there before taking this one. This tutorial shows how to create a complete working output component for Hazelcast As seen before, in Hazelcast there is multiple data source type. You can find queues, topics, cache, maps… In this tutorials we will stick with the Map dataset and all what we will see here is applicable to the other types. Let’s assume that our Hazelcast output component will be responsible of inserting data into a distributed Map. For that, we will need to know which attribute from the incoming data is to be used as a key in the map. The value will be the hole record encoded into a json format. Bu that in mind, we can design our output configuration as: the same Datastore and Dataset from the input component and an additional configuration that will define the key attribute. Let’s create our Output configuration class. Let’s add the i18n properties of our configuration into the Messages.properties file The skeleton of the output component looks as follows: @Version annotation indicates the version of the component. It is used to migrate the component configuration if needed. @Icon annotation indicates the icon of the component. Here, the icon is a custom icon that needs to be bundled in the component JAR under resources/icons. @Processor annotation indicates that this class is the processor (output) and defines the name of the component. constructor of the processor is responsible for injecting the component configuration and services. Configuration parameters are annotated with @Option. The other parameters are considered as services and are injected by the component framework. Services can be local (class annotated with @Service) or provided by the component framework. The method annotated with @PostConstruct is executed once by instance and can be used for initialization. The method annotated with @PreDestroy is used to clean resources at the end of the execution of the output. Data is passed to the method annotated with @ElementListener. That method is responsible for handling the data output. You can define all the related logic in this method. If you need to bulk write the updates accordingly to groups, see Processors and batch processing. Now, we will need to add the display name of the Output to the i18n resources file Messages.properties Let’s implement all of those methods We will create the outpu contructor to inject the component configuration and some additional local and built in services. Built in services are services provided by TCK. Here we find: configuration is the component configuration class hazelcastService is the service that we have implemented in the input component tutorial. it will be responsible of creating a hazelcast client instance. jsonb is a built in service provided by tck to handle json object serialization and deserialization. We will use it to convert the incoming record to json format before inseting them into the map. Nothing to do in the post construct method. but we could for example initialize a hazle cast instance there. but we will do it in a lazy way on the first call in the @ElementListener method Shut down the Hazelcast client instance and thus free the Hazelcast map reference. We get the key attribute from the incoming record and then convert the hole record to a json string. Then we insert the key/value into the hazelcast map. Let’s create a unit test for our output component. The idea will be to create a job that will insert the data using this output implementation. So, let’s create out test class. Here we start by creating a hazelcast test instance, and we initialize the map. we also shutdown the instance after all the test are executed. Now let’s create our output test. Here we start preparing the emitter test component provided bt TCK that we use in our test job to generate random data for our output. Then, we use the output component to fill the hazelcast map. By the end we test that the map contains the exact amount of data inserted by the job. Run the test and check that it’s working. Congratulation you just finished your output component.