Pipeline examples

Updating data in a destination table

You might want to pipe data and then update the data often.

To update a destination table:

  1. Click the Pipeline button, select an existing pipeline that you executed before, and click OK.

    The pipeline definition displays. Since this pipeline has been executed before, the table exists in the destination database.

  2. Select the Update option in the pipeline definition.

  3. Execute the pipeline.

    The destination table is updated with current data from the source database.

Reproducing a table definition with no data

You can force a pipeline to create a table definition and not pipe data. To do this, you must use Quick Select, SQL Select, or Query as the data source. It is easiest to do it using SQL Select.

To reproduce a table definition with no data:

  1. Click the Pipeline button, click New, select SQL Select as the data source and specify the source and destination databases, and click OK.

  2. In the Select painter, open the table you want to reproduce and select all columns.

  3. On the Where tab page, type an expression that will never evaluate to true, such as 1 = 2.

  4. Click the SQL Select button to create the pipeline definition.

  5. Select the Extended Attributes check box.

  6. Click the Execute button to execute the pipeline.

    The table definition is piped to the destination database, but no rows of data are piped. You can open the new table in the Database painter and then click the Grid, Table, or Freeform button to view the data. As specified, there is no data.

    If you use a data source other than SQL Select, you can follow the previous procedure, but you need to edit the data source of the pipeline to open the Select painter in step 2.

Piping a table to many databases

In the Data Pipeline painter workspace, you can execute a pipeline many times with a different destination database each time.

To pipe a table to many databases:

  1. Select File>Destination Connect from the menu bar to change the destination to the database you want.

  2. Execute the pipeline.

  3. Repeat steps 1 and 2 for each database you want.