# tRestWebServiceOutput (deprecated)

Availability-note[Deprecated](https://help.talend.com/r/en-US/Cloud/labels-on-talend-help-center/availability-deprecated)

This content is deprecated.

Serves as a REpresentational State Transfer (REST) Web service client that continuously sends HTTP requests to a REST Web service provider in real time and gets the responses.

Information noteDeprecation: Spark Streaming is deprecated beginning with the R2026-09 release. Use Spark Structured Streaming instead.

## tRestWebServiceOutput properties for Apache Spark Streaming

These properties are used to configure tRestWebServiceOutput running in the Spark Streaming Job framework.

The Spark Streaming tRestWebServiceOutput component belongs to the Webservice family.

The streaming version of this component is available in Talend Real-Time Big Data Platform and in Talend Data Fabric.

## Basic settings

| Properties | Description |
| --- | --- |
| Schema and Edit<br>Schema | A schema is a row description. It defines the number of fields<br>(columns) to be processed and passed on to the next component. When you create a Spark<br>Job, avoid the reserved word line when naming the<br>fields.<br><br>The schema of this component is read-only. You can click<br>Edit schema to view the schema.<br><br>This read-only *payload* column is used to carry the body<br>of the request to be processed. Note that you must define a same *payload* column in the schema of the preceding component to send data to this<br>read-only column. |
| URL | Enter the URL address of the REST Web server to be invoked. |
| HTTP Method | From this list, select an HTTP method that describes the desired action. The specific<br>meanings of the HTTP methods are subject to definitions of your Web service provider. Listed<br>below are the generally accepted HTTP methods:<br><br><ul> <li> <p> <span>PUT</span>: updates data based on the given parameters, or                if the data does not exist, creates it.</p> </li> <li> <p> <span>POST</span>: creates and uploads data based on the given                parameters.</p> </li> <li> <p> <span>DELETE</span>: removes data based on the given parameters.            </p> </li> </ul> |
| HTTP Headers | Enter the name-value pair(s) for HTTP headers to define the parameters of the requested<br>HTTP operation.<br><br>For the specific definitions of HTTP headers, consult your REST Web service provider. For<br>reference information, visit http://en.wikipedia.org/wiki/List\_of\_HTTP\_headers. |

## Advanced settings

| Properties | Description |
| --- | --- |
| Use SSL/TLS | Select this checkbox to enable the SSL or TLS encrypted connection.<br><br>Then you need to use the tSetKeystore<br>component in the same Job to specify the encryption information. |

## Usage

| Usage guidance | Description |
| --- | --- |
| **Usage rule** | This component is used as an end component and requires an input link.<br><br>This component, along with the Spark Streaming component Palette it belongs to, appears<br>only when you are creating a Spark Streaming Job.<br><br>Note that in this documentation, unless otherwise explicitly stated, a scenario presents<br>only Standard Jobs, that is to say traditional<br>Talend<br>data<br>integration Jobs. |
| Spark Connection | In the Spark<br>Configuration tab in the Run<br>view, define the connection to a given Spark cluster for the whole Job. In<br>addition, since the Job expects its dependent jar files for execution, you must<br>specify the directory in the file system to which these jar files are<br>transferred so that Spark can access these files:<br><br><ul> <li> <div> <span>Yarn mode</span> (Yarn client or Yarn cluster):<ul> <li> <p>When using Google Dataproc, specify a bucket in the                                            <span>Google Storage staging bucket</span>                                        field in the <span>Spark configuration</span>                                        tab.</p> </li> <li> <p>When using HDInsight, specify the blob to be used for Job                                        deployment in the <span>Windows Azure Storage                                            configuration</span> area in the <span>Spark                                            configuration</span> tab.</p> </li> <li>When using Altus, specify the S3 bucket or the Azure                                    Data Lake Storage for Job deployment in the <span>Spark                                        configuration</span> tab.</li> <li> <p>When using on-premises distributions, use                                        the configuration component corresponding to the file system                                        your cluster is using. Typically, this system is HDFS and so                                        use <a href="https://help.qlik.com/talend/r/en-US/8.0/components/hdfs/thdfsconfiguration">tHDFSConfiguration</a>.</p> </li> </ul> </div> </li> <li> <p> <span>Standalone mode</span>: use the                            configuration component corresponding to the file system your cluster is                            using, such as <a href="https://help.qlik.com/talend/r/en-US/8.0/components/hdfs/thdfsconfiguration-properties-for-apache-spark-batch">tHDFSConfiguration Apache Spark Batch</a> or <a href="https://help.qlik.com/talend/r/en-US/8.0/components/amazon-s3/ts3configuration-properties-for-apache-spark-batch">tS3Configuration Apache Spark Batch</a>.</p> <p>If you are using Databricks without any configuration component present                            in your Job, your business data is written directly in DBFS (Databricks                            Filesystem).</p> </li> </ul><br><br>This connection is effective on a per-Job basis. |