Amazon Data Pipeline examples using Amazon CLI - Amazon Command Line Interface
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Amazon Data Pipeline examples using Amazon CLI

The following code examples show you how to perform actions and implement common scenarios by using the Amazon Command Line Interface with Amazon Data Pipeline.

Actions are code excerpts from larger programs and must be run in context. While actions show you how to call individual service functions, you can see actions in context in their related scenarios.

Each example includes a link to the complete source code, where you can find instructions on how to set up and run the code in context.

Topics

Actions

The following code example shows how to use activate-pipeline.

Amazon CLI

To activate a pipeline

This example activates the specified pipeline:

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

To activate the pipeline at a specific date and time, use the following command:

aws datapipeline activate-pipeline --pipeline-id df-00627471SOVYZEXAMPLE --start-timestamp 2015-04-07T00:00:00Z

The following code example shows how to use add-tags.

Amazon CLI

To add a tag to a pipeline

This example adds the specified tag to the specified pipeline:

aws datapipeline add-tags --pipeline-id df-00627471SOVYZEXAMPLE --tags key=environment,value=production key=owner,value=sales

To view the tags, use the describe-pipelines command. For example, the tags added in the example command appear as follows in the output for describe-pipelines:

{
    ...
        "tags": [
            {
                "value": "production",
                "key": "environment"
            },
            {
                "value": "sales",
                "key": "owner"
            }
        ]
    ...
}

  • For API details, see AddTags in Amazon CLI Command Reference.

The following code example shows how to use create-pipeline.

Amazon CLI

To create a pipeline

This example creates a pipeline:

aws datapipeline create-pipeline --name my-pipeline --unique-id my-pipeline-token

The following is example output:

{
    "pipelineId": "df-00627471SOVYZEXAMPLE"
}

  • For API details, see CreatePipeline in Amazon CLI Command Reference.

The following code example shows how to use deactivate-pipeline.

Amazon CLI

To deactivate a pipeline

This example deactivates the specified pipeline:

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

To deactivate the pipeline only after all running activities finish, use the following command:

aws datapipeline deactivate-pipeline --pipeline-id df-00627471SOVYZEXAMPLE --no-cancel-active

The following code example shows how to use delete-pipeline.

Amazon CLI

To delete a pipeline

This example deletes the specified pipeline:

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

  • For API details, see DeletePipeline in Amazon CLI Command Reference.

The following code example shows how to use describe-pipelines.

Amazon CLI

To describe your pipelines

This example describes the specified pipeline:

aws datapipeline describe-pipelines --pipeline-ids df-00627471SOVYZEXAMPLE

The following is example output:

{
  "pipelineDescriptionList": [
      {
          "fields": [
              {
                  "stringValue": "PENDING",
                  "key": "@pipelineState"
              },
              {
                  "stringValue": "my-pipeline",
                  "key": "name"
              },
              {
                  "stringValue": "2015-04-07T16:05:58",
                  "key": "@creationTime"
              },
              {
                  "stringValue": "df-00627471SOVYZEXAMPLE",
                  "key": "@id"
              },
              {
                  "stringValue": "123456789012",
                  "key": "pipelineCreator"
              },
              {
                  "stringValue": "PIPELINE",
                  "key": "@sphere"
              },
              {
                  "stringValue": "123456789012",
                  "key": "@userId"
              },
              {
                  "stringValue": "123456789012",
                  "key": "@accountId"
              },
              {
                  "stringValue": "my-pipeline-token",
                  "key": "uniqueId"
              }
          ],
          "pipelineId": "df-00627471SOVYZEXAMPLE",
          "name": "my-pipeline",
          "tags": []
      }
  ]
}

The following code example shows how to use get-pipeline-definition.

Amazon CLI

To get a pipeline definition

This example gets the pipeline definition for the specified pipeline:

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

The following is example output:

{
  "parameters": [
      {
          "type": "AWS::S3::ObjectKey",
          "id": "myS3OutputLoc",
          "description": "S3 output folder"
      },
      {
          "default": "s3://us-east-1.elasticmapreduce.samples/pig-apache-logs/data",
          "type": "AWS::S3::ObjectKey",
          "id": "myS3InputLoc",
          "description": "S3 input folder"
      },
      {
          "default": "grep -rc \"GET\" ${INPUT1_STAGING_DIR}/* > ${OUTPUT1_STAGING_DIR}/output.txt",
          "type": "String",
          "id": "myShellCmd",
          "description": "Shell command to run"
      }
  ],
  "objects": [
      {
          "type": "Ec2Resource",
          "terminateAfter": "20 Minutes",
          "instanceType": "t1.micro",
          "id": "EC2ResourceObj",
          "name": "EC2ResourceObj"
      },
      {
          "name": "Default",
          "failureAndRerunMode": "CASCADE",
          "resourceRole": "DataPipelineDefaultResourceRole",
          "schedule": {
              "ref": "DefaultSchedule"
          },
          "role": "DataPipelineDefaultRole",
          "scheduleType": "cron",
          "id": "Default"
      },
      {
          "directoryPath": "#{myS3OutputLoc}/#{format(@scheduledStartTime, 'YYYY-MM-dd-HH-mm-ss')}",
          "type": "S3DataNode",
          "id": "S3OutputLocation",
          "name": "S3OutputLocation"
      },
      {
          "directoryPath": "#{myS3InputLoc}",
          "type": "S3DataNode",
          "id": "S3InputLocation",
          "name": "S3InputLocation"
      },
      {
          "startAt": "FIRST_ACTIVATION_DATE_TIME",
          "name": "Every 15 minutes",
          "period": "15 minutes",
          "occurrences": "4",
          "type": "Schedule",
          "id": "DefaultSchedule"
      },
      {
          "name": "ShellCommandActivityObj",
          "command": "#{myShellCmd}",
          "output": {
              "ref": "S3OutputLocation"
          },
          "input": {
              "ref": "S3InputLocation"
          },
          "stage": "true",
          "type": "ShellCommandActivity",
          "id": "ShellCommandActivityObj",
          "runsOn": {
              "ref": "EC2ResourceObj"
          }
      }
  ],
  "values": {
      "myS3OutputLoc": "s3://my-s3-bucket/",
      "myS3InputLoc": "s3://us-east-1.elasticmapreduce.samples/pig-apache-logs/data",
      "myShellCmd": "grep -rc \"GET\" ${INPUT1_STAGING_DIR}/* > ${OUTPUT1_STAGING_DIR}/output.txt"
  }
}

The following code example shows how to use list-pipelines.

Amazon CLI

To list your pipelines

This example lists your pipelines:

aws datapipeline list-pipelines

The following is example output:

{
  "pipelineIdList": [
      {
          "id": "df-00627471SOVYZEXAMPLE",
          "name": "my-pipeline"
      },
      {
          "id": "df-09028963KNVMREXAMPLE",
          "name": "ImportDDB"
      },
      {
          "id": "df-0870198233ZYVEXAMPLE",
          "name": "CrossRegionDDB"
      },
      {
          "id": "df-00189603TB4MZEXAMPLE",
          "name": "CopyRedshift"
      }
  ]
}

  • For API details, see ListPipelines in Amazon CLI Command Reference.

The following code example shows how to use list-runs.

Amazon CLI

Example 1: To list your pipeline runs

The following list-runs example lists the runs for the specified pipeline.

aws datapipeline list-runs --pipeline-id df-00627471SOVYZEXAMPLE

Output:

    Name                       Scheduled Start        Status                     ID                                              Started                Ended
    -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1.  EC2ResourceObj             2015-04-12T17:33:02    CREATING                   @EC2ResourceObj_2015-04-12T17:33:02             2015-04-12T17:33:10
2.  S3InputLocation            2015-04-12T17:33:02    FINISHED                   @S3InputLocation_2015-04-12T17:33:02            2015-04-12T17:33:09    2015-04-12T17:33:09
3.  S3OutputLocation           2015-04-12T17:33:02    WAITING_ON_DEPENDENCIES    @S3OutputLocation_2015-04-12T17:33:02           2015-04-12T17:33:09
4.  ShellCommandActivityObj    2015-04-12T17:33:02    WAITING_FOR_RUNNER         @ShellCommandActivityObj_2015-04-12T17:33:02    2015-04-12T17:33:09

Example 2: To list the pipeline runs between the specified dates

The following list-runs example uses the --start-interval to specify the dates to include in the output.

aws datapipeline list-runs --pipeline-id df-01434553B58A2SHZUKO5 --start-interval 2017-10-07T00:00:00,2017-10-08T00:00:00

  • For API details, see ListRuns in Amazon CLI Command Reference.

The following code example shows how to use put-pipeline-definition.

Amazon CLI

To upload a pipeline definition

This example uploads the specified pipeline definition to the specified pipeline:

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

The following is example output:

{
  "validationErrors": [],
  "errored": false,
  "validationWarnings": []
}

The following code example shows how to use remove-tags.

Amazon CLI

To remove a tag from a pipeline

This example removes the specified tag from the specified pipeline:

aws datapipeline remove-tags --pipeline-id df-00627471SOVYZEXAMPLE --tag-keys environment

  • For API details, see RemoveTags in Amazon CLI Command Reference.