Rename, copy, delete, or keep columns

This page explains how to rename, copy, delete, or keep columns when you prepare data in the Wrangler workspace of the Cloud Data Fusion Studio.

Rename a column

To rename a column in the Wrangler workspace, click a column name and enter a new name. Wrangler adds the rename directive to the recipe.

Copy a column

To understand the impact of using a new directive on a dataset, you can copy a column into a new column with a different name and apply directives there.

To copy a column, follow these steps:

  1. Go to Wrangler workspace in Cloud Data Fusion.
  2. On the Data tab, go to a column name and click the arrow_drop_down expander arrow.
  3. Select Copy column and enter a name for the new column.

Wrangler copies the column and adds the copy directive to the recipe.

Delete a column

For datasets with many columns, you can improve pipeline performance and save resources by deleting unnecessary columns. With fewer columns, the pipeline run completes faster. This is especially true for pipelines that include a Joiner transformation.

To delete a column from a dataset, follow these steps:

  1. Go to Wrangler workspace in Cloud Data Fusion.
  2. On the Data tab, go to a column name and click the arrow_drop_down expander arrow.
  3. Select Delete column.

Wrangler deletes the column and adds the drop directive to the recipe.

Keep a column

You can keep a column in a dataset and delete all other columns.

To keep a column, follow these steps:

  1. Go to Wrangler workspace in Cloud Data Fusion.
  2. On the Data tab, go to a column name and click the arrow_drop_down expander arrow.
  3. Select Keep column.

Wrangler deletes all columns in the dataset, except the one you chose, and adds the keep directive to the recipe.

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