tDatabricksServerlessSQLWarehouseOutput Standard properties

Select the desired database type from the list and click Apply.

Property Type

Select the way the connection details will be set.

• Built-In: The connection details will be set locally for this component. You need to specify the values for all related connection properties manually.

• Repository: The connection details stored centrally in Repository > Metadata will be reused by this component.

  You need to click the [...] button next to it and in the pop-up Repository Content dialog box, select the connection details to be reused, and all related connection properties will be automatically filled in.

This property is not available when other connection component is selected from the Connection Component dropdown list.

Select this check box and in the Component List drop-down list, select the desired connection component to reuse the connection details you already defined.

Component list

Select the component that opens the database connection to be reused by this component.

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.

• Built-In: You create and store the schema locally for this component only.

• Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs.

When the schema to be reused has default values that are integers or functions, ensure that these default values are not enclosed within quotation marks. If they are, you must remove the quotation marks manually.

For more information, see Retrieving table schemas.

Click Edit schema to make changes to the schema. If you make changes, the schema automatically becomes built-in.

• 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.

Guess Schema

Click this button to generate schema columns based on the settings of database table columns.

JDBC URL

The JDBC URL of the database to be used.

Drivers

Complete this table to load the driver JARs needed. To do this, click the [+] button under the table to add as many rows as needed, each row for a driver JAR, then select the cell and click the [...] button at the right side of the cell to open the Module dialog box from which you can select the driver JAR to be used. For example, the driver jar RedshiftJDBC41-1.1.13.1013.jar for the Redshift database.

For more information, see Importing a database driver.

Driver Class

Enter the class name for the specified driver between double quotation marks. For example, for the RedshiftJDBC41-1.1.13.1013.jar driver, the name to be entered is com.amazon.redshift.jdbc41.Driver.

The database user authentication data.

To enter the password, click the [...] button next to the password field, enter the password in double quotes in the pop-up dialog box, and click OK to save the settings.

Specify a data source alias

Select this checkbox and in the Data source alias field displayed, specify the alias of a data source created on Talend Runtime side to use the shared connection pool defined in the data source configuration. This option works only when you deploy and run your Job in Talend Runtime.

If you use the component's own DB configuration, your data source connection will be closed at the end of the component. To prevent this from happening, use a shared DB connection with the data source alias specified.

This property is not available when other connection component is selected from the Connection Component dropdown list.

Table

Enter the name of the table into which data will be written.

Select an action to be performed on data of the table defined.

• Insert: Add new entries to the table. If duplicates are found, the Job stops.

• Update: Make changes to existing entries.

• Insert or update: Insert a new record in the index pool. If the record with the given reference already exists, an update would be made.

• Update or insert: Update the record with the given reference. If the record does not exist in the index pool, a new record would be inserted.

• Delete: Remove entries corresponding to the input flow.

Select this checkbox to clear data in the table before performing the selected action.

Die on error

Select the checkbox to stop the execution of the Job when an error occurs.

Clear the checkbox to skip any rows on error and complete the process for error-free rows.

When errors are skipped, you can collect the rows on error using a Row > Reject connection.

tStatCatcher Statistics

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

Specify the number of rows to be processed before committing batches of rows together into the database.

Additional Columns

This option allows you to call SQL functions to perform actions on columns, which are not insert, update or delete actions, or actions that require particular preprocessing. It is not offered if you create (with or without drop) the database table.

• Name: The name of the schema column to be inserted, or the name of the schema column used to replace an existing column.

• SQL expression: The SQL statement to be executed in order to insert or replace relevant column.

• Position: Select Before, After, or Replace according to the action to be performed on the reference column.

• Reference column: The name of the reference column that can be used to locate the new column to be inserted or that will be replaced.

Use field options

Select this check box and in the Fields options table displayed, select the check box for the corresponding column to customize a request, particularly if multiple actions are being carried out on the data.

• Key in update: Select the check box for the corresponding column based on which data is updated.
• Key in delete: Select the check box for the corresponding column based on which data is deleted.

• Updatable: Select the check box if data in the corresponding column can be updated.

• Insertable: Select the check box if data in the corresponding column can be inserted.

Select this check box to display each step during processing entries in a database.

Use batch

Select this check box to activate the batch mode for data processing, and in the Batch Size field displayed, specify the number of records to be processed in each batch.

Select this option to set a timeout period for queries or batch queries. The Job is terminated if a query times out. You can set the timeout period in seconds in the Timeout field.

ERROR_MESSAGE

The error message generated by the component when an error occurs. This is an After variable and it returns a string.

NB_LINE

The number of rows processed. This is an After variable and it returns an integer.

NB_LINE_INSERTED

The number of rows inserted. This is an After variable and it returns an integer.

NB_LINE_UPDATED

The number of rows updated. This is an After variable and it returns an integer.

NB_LINE_DELETED

The number of rows deleted. This is an After variable and it returns an integer.

NB_LINE_REJECTED

The number of rows rejected. This is an After variable and it returns an integer.

QUERY

The query statement being processed. This is a Flow variable and it returns a string.

Usage rule

This component must be used as an output component. It supports writing data to Databricks serverless SQL warehouse tables and can create a reject flow using a Row > Rejects link.

Click the [+] button to add a row in the table and fill the Code field with a context variable to choose your database connection dynamically from multiple connections planned in your Job. This feature is useful when you need to access database tables having the same data structure but in different databases, especially when you are working in an environment where you cannot change your Job settings, for example, when your Job has to be deployed and executed independent of Talend Studio.

For examples on using dynamic parameters, see Reading data from databases through context-based dynamic connections and Reading data from different MySQL databases using dynamically loaded connection parameters. For more information on Dynamic settings and context variables, see Dynamic schema and Creating a context group and define context variables in it.