Skip to main content Skip to complementary content

tDataprepRun Standard properties for an on-premises deployment

These properties are used to configure the on-premises version of tDataprepRun running in the Standard Job framework.

The Standard tDataprepRun component belongs to the Talend Data Preparation family.

The component in this framework is available in all subscription-based Talend products.

Basic settings

URL

Type the URL to the Talend Data Preparation web application, between double quotes.

If you are working with Talend Cloud Data Preparation, use the URL for the corresponding data center to access the application, for example, https://tdp.us.cloud.talend.com for the AWS US data center.

For the URLs of available data centers, see Talend Cloud regions and URLs.

Username

Type the email address that you use to log in the Talend Data Preparation web application, between double quotes.

Password

Click the [...] button and type your user password for the Talend Data Preparation web application, between double quotes.

If you are working with Talend Cloud Data Preparation and if:

  • SSO is enabled, enter an access token in the field.
  • SSO is not enabled, enter either an access token or your password in the field.

When using the default preparation selection properties:

Preparation

To complete the Preparation field, do one of the following:
  • click Choose an existing preparation and select one of the previously created preparations in a pop-up dialog box. This dialog box shows the name, path, author, and last modification date of each preparation.

  • click Or create a new one and create a new preparation based on your input data.

Click this button to edit the preparation in Talend Data Preparation that corresponds to the ID defined in the Preparation field.

Version

If you have created several versions of your preparation, you can choose which one you want to use in the Job. To complete the Version field, click Choose a Version to select from the list of existing versions, including the current version of the preparation.

Schema and Edit Schema

A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. When you create a Spark Job, avoid the reserved word line when naming the fields.

Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available:

  • View schema: choose this option to view the schema only.

  • Change to built-in property: choose this option to change the schema to Built-in for local changes.

  • Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion.

    If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the Repository Content window.

Click Sync columns to retrieve the schema from the previous component connected in the Job.

tDataprepRun offers the advantage of the dynamic schema feature. This feature allows you to retrieve unknown columns from source files or to copy batches of columns from a source without mapping each column individually. For further information about dynamic schema, see Dynamic schema.

Information noteNote: The dynamic schema feature is not supported when creating a new preparation. It is designed for the purpose of retrieving unknown columns and is recommended to be used for this purpose only.

Fetch Schema

Click this button to retrieve the schema from the preparation defined in the Preparation field.

When using the Dynamic preparation selection:

Dynamic preparation selection

Select this checkbox to define a preparation path and version using context variables. The preparation will be dynamically selected at runtime.

Preparation path

Use a context variable to define a preparation path. Paths with or without the initial / are supported.

Preparation version

Use a context variable to define the version of the preparation to use. Preparation versions are referenced by their number. As a consequence, to execute the version #2 of a preparation for example, the expected value is "2". To use the current version of the preparation, the expected value is "Current state".

Schema and Edit Schema

A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. When you create a Spark Job, avoid the reserved word line when naming the fields.

Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available:

  • View schema: choose this option to view the schema only.

  • Change to built-in property: choose this option to change the schema to Built-in for local changes.

  • Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion.

    If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the Repository Content window.

Click Sync columns to retrieve the schema from the previous component connected in the Job.

Fetch Schema

Click this button to dynamically retrieve the schema from the preparations defined by the context variable in the Preparation path field. If the fetch is successful, any previously configured schema will be overwritten. If the fetch fails, the current schema is kept.

Advanced settings

Limit Preview

Specify the number of rows to which you want to limit the preview.

This option works only when creating a new preparation.

tStatCatcher Statistics

Select this check box to gather the Job processing metadata at the Job level as well as at each component level.

Global Variables

Global Variables

ERROR_MESSAGE: the error message generated by the component when an error occurs. This is an After variable and it returns a string. This variable functions only if the Die on error check box is cleared, if the component has this check box.

A Flow variable functions during the execution of a component while an After variable functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl+Space to access the variable list and choose the variable to use from it.

For more information about variables, see Using contexts and variables.

Usage

Usage rule

This component is an intermediary step. It requires an input flow as well as an output.

Limitations

  • If the dataset is updated after the tDataprepRun component has been configured, the schema needs to be fetched again.

  • If a context variable was used in the URL of the dataset, you cannot use the button to edit the preparation directly in Talend Data Preparation.

Did this page help you?

If you find any issues with this page or its content – a typo, a missing step, or a technical error – please let us know!