Editing Your Pipeline - AWS Data Pipeline

Editing Your Pipeline

To change some aspect of one of your pipelines, you can update its pipeline definition. After you change a pipeline that is running, you must re-activate the pipeline for your changes to take effect. In addition, you can re-run one or more pipeline components.


While the pipeline is in the PENDING state and is not activated, you can't make any changes to it. After you activate a pipeline, you can edit the pipeline with the following restrictions. The changes you make apply to new runs of the pipeline objects after you save them and then activate the pipeline again.

  • You can't remove an object

  • You can't change the schedule period of an existing object

  • You can't add, delete, or modify reference fields in an existing object

  • You can't reference an existing object in an output field of a new object

  • You can't change the scheduled start date of an object (instead, activate the pipeline with a specific date and time)

Editing a Pipeline Using the AWS CLI

You can edit a pipeline using the command line tools.

First, download a copy of the current pipeline definition using the get-pipeline-definition command. By doing this, you can be sure that you are modifying the most recent pipeline definition. The following example uses prints the pipeline definition to standard output (stdout).

aws datapipeline get-pipeline-definition --pipeline-id df-00627471SOVYZEXAMPLE

Save the pipeline definition to a file and edit it as needed. Update your pipeline definition using the put-pipeline-definition command. The following example uploads the updated pipeline definition file.

aws datapipeline put-pipeline-definition --pipeline-id df-00627471SOVYZEXAMPLE --pipeline-definition file://MyEmrPipelineDefinition.json

You can retrieve the pipeline definition again using the get-pipeline-definition command to ensure that the update was successful. To activate the pipeline, use the following activate-pipeline command:

aws datapipeline activate-pipeline --pipeline-id df-00627471SOVYZEXAMPLE

If you prefer, you can activate the pipeline from a specific date and time, using the --start-timestamp option as follows:

aws datapipeline activate-pipeline --pipeline-id df-00627471SOVYZEXAMPLE --start-timestamp YYYY-MM-DDTHH:MM:SSZ

To re-run one or more pipeline components, use the set-status command.