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API Task - Run Job

Warning

API access is migrating to Enterprise only. Beginning in Release 9.5, all new or renewed subscriptions have access to public API endpoints on the Enterprise product edition only. Existing customers on non-Enterprise editions will retain access their available endpoints (Legacy) until their subscription expires. To use API endpoints after renewal, you must upgrade to the Enterprise product edition or use a reduced set of endpoints (Current). For more information on differences between product editions in the new model, please visit Pricing and Packaging.

This section describes how to run a job using the APIs available in Dataprep by Trifacta.

A note about API URLs:

In the listed examples, URLs are referenced in the following manner:

<protocol>://<platform_base_url>/

In your product, these map references map to the following:

https://www.api.clouddataprep.com/

For more information, see API Reference.

Run Job Endpoints

Depending on the type of job that you are running, you must use one of the following endpoints:

Run job

Run a job to generate the outputs from a single recipe in a flow.

Tip

This method is covered on this page.

Endpoint

/v4/jobGroups/:id

Method

POST

Reference documentation

Dataprep by Trifacta: API Reference docs

Run flow

Run all outputs specified in a flow. Optionally, you can run all scheduled outputs.

Endpoint

/v4/flows/:id/run

Method

POST

Reference documentation

Dataprep by Trifacta: API Reference docs

Prerequisites

Before you begin, you should verify the following:

  1. Get authentication credentials. As part of each request, you must pass in authentication credentials to the platform. For more information, see Manage API Access Tokens.

    For more information, see Dataprep by Trifacta: API Reference docs

  2. Verify job execution. Run the desired job through the Trifacta Application and verify that the output objects are properly generated.

    Note

    By default, when scheduled or API jobs are executed, no validations are performed of any writesettings objects for file-based outputs. Issues with these objects may cause failures during transformation or publishing stages of job execution. Jobs of these types should be tested through the Trifacta Application first. A workspace administrator can disable the skipping of these validations.

  3. Acquire recipe (wrangled dataset) identifier. In Flow View, click the icon for the recipe whose outputs you wish to generate. Acquire the numeric value for the recipe from the URL. In the following, the recipe Id is 28629:

    http://<platform_base_url>/flows/5479?recipe=28629&tab=recipe
  4. Create output object. A recipe must have at least one output object created for it before you can run a job via APIs. For more information, see Flow View Page.

If you wish to apply overrides to the inputs or outputs of the recipe, you should acquire those identifiers or paths now. For more information, see "Run Job with Parameter Overrides" below.

Step - Run Job

Through the APIs, you can specify and run a job. To run a job with all default settings, construct a request like the following:

Note

A wrangledDataset is an internal object name for the recipe that you wish to run. Please see previous section for how to acquire this value.

Tip

You cannot apply overrides to the job definition through the API request. However, overrides can be specified through the Dataprep by Trifacta interface.

Endpoint

<protocol>://<platform_base_url>/v4/jobGroups

Authentication

Required

Method

POST

Request Body

{
  "wrangledDataset": {
    "id": 28629
  }
}

Response Code

201 - Created

Response Body

{
    "sessionId": "79276c31-c58c-4e79-ae5e-fed1a25ebca1",
    "reason": "JobStarted",
    "jobGraph": {
        "vertices": [
            21,
            22
        ],
        "edges": [
            {
                "source": 21,
                "target": 22
            }
        ]
    },
    "id": 961247,
    "jobs": {
        "data": [
            {
                "id": 21
            },
            {
                "id": 22
            }
        ]
    }
}

If the 201 response code is returned, then the job has been queued for execution.

Tip

Retain the id value in the response. In the above, 961247 is the internal identifier for the job group for the job. You will need this value to check on your job status.

For more information, see Dataprep by Trifacta: API Reference docs

Tip

You have queued your job for execution.

Step - Monitoring Your Job

You can monitor the status of your job through the following endpoint:

Endpoint

<protocol>://<platform_base_url>/v4/jobGroups/<id>/

Authentication

Required

Method

GET

Request Body

None.

Response Code

200 - Ok

Response Body

{
    "id": 961247,
    "name": null,
    "description": null,
    "ranfrom": "ui",
    "ranfor": "recipe",
    "status": "Complete",
    "profilingEnabled": true,
    "runParameterReferenceDate": "2019-08-20T17:46:27.000Z",
    "createdAt": "2019-08-20T17:46:28.000Z",
    "updatedAt": "2019-08-20T17:53:17.000Z",
    "workspace": {
        "id": 22
    },
    "creator": {
        "id": 38
    },
    "updater": {
        "id": 38
    },
    "snapshot": {
        "id": 774476
    },
    "wrangledDataset": {
        "id": 28629
    },
    "flowRun": null
}

When the job has successfully completed, the returned status message includes the following:

"status": "Complete",

For more information, see Dataprep by Trifacta: API Reference docs

Tip

You have executed the job. Results have been delivered to the designated output locations.

Step - Re-run Job

In the future, you can re-run the job using the same, simple request:

Endpoint

<protocol>://<platform_base_url>/v4/jobGroups

Authentication

Required

Method

POST

Request Body

{
  "wrangledDataset": {
    "id": 28629
  }
}

The job is re-run as it was previously specified.

For more information, see Dataprep by Trifacta: API Reference docs

Step - Run Job with Overrides - Files

As needed, you can specify runtime overrides for any of the settings related to the job definition or its outputs. For file-based jobs, these overrides include:

  • Data sources

  • Execution environment

  • profiling

  • Output file, format, and other settings

Input file overrides

You can override the file-based data sources your job run. In the following example, two datasets are overridden with new files.

Note

Overrides for data sources apply only to file-based sources. File-based sources that are converted during ingestion, such as Microsoft Excel files and JSON files, cannot be swapped in this manner.

Note

Overrides must be applied to the entire file path. As part of this overrides, you can redefine the bucket from which the source data is taken.

Endpoint

<protocol>://<platform_base_url>/v4/jobGroups

Authentication

Required

Method

POST

Request Body

{
  "wrangledDataset": {
    "id": 28629
  },
  "overrides": {
    "datasources": {
      "airlines - region 1": [
        "s3://my-new-bucket/test-override-input/airlines3.csv",
        "s3://my-new-bucket/test-override-input/airlines4.csv",
        "s3://my-new-bucket/test-override-input/airlines5.csv"
      ],
      "airlines - region 2": [
        "s3://my-new-bucket/test-override-input/airlines1.csv",
      ]
    }
  }
}

The job specified for recipe 28629 is re-run using the new data sources.

Notes:

  • The names of the datasources (airlines - region 1 and airlines - region 2) refer to the display name values for the datasets that are the sources for the wrangledDataset (recipe) in the flow.

  • You can use this API method to overwrite the bucket name for your source, but you must replace the entire path.

    • The parameterized list of files can be from different folders, too.

  • File type and size information is not displayed in the Job Details page for these overridden jobs.

  • No validation is performed on the existence of these files prior to execution. If the files do not exist, the job fails.

For more information, see Dataprep by Trifacta: API Reference docs

Output file overrides

Note

Override values applied to a job are not validated. Invalid overrides may cause your job to fail.

  1. Acquire the internal identifier for the recipe for which you wish to execute a job. In the previous example, this identifier was 28629.

  2. Construct a request using the following:

    Endpoint

    <protocol>://<platform_base_url>/v4/jobGroups

    Authentication

    Required

    Method

    POST

    Request Body:

    {
      "wrangledDataset": {
        "id": 28629
      },
      "overrides": {
        "profiler": true,
        "execution": "spark",
        "writesettings": [
          {
            "path": "<new_path_to_output>",
            "format": "csv",
            "header": true,
            "asSingleFile": true,
            "includeMismatches": true
          }
        ]
      },
      "ranfrom": null
    }
    
  3. In the above example, the job has been launched with the following overrides:

    1. Job will be executed on the Spark cluster. Other supported values depend on your product edition and available running environments:

      Value for overrides.execution

      Description

      photon

      Running environment on Trifacta node

      spark

      Spark on integrated cluster, with the following exceptions.

      databricksSpark

      Spark on Azure Databricks

      emrSpark

      Spark on AWS EMR

      dataflow

      Dataflow

    2. Job will be executed with profiling enabled.

    3. Output is written to a new file path.

    4. Output format is CSV to the designated path.

    5. Output has a header and is generated as a single file.

    6. Output will include values if they are mismatched for the column's data type.

      Note

      includeMismatches is false by default. You can set it to true as an override or as part of the output object definition.

  4. A response code of 201 - Created is returned. The response body should look like the following:

    {
    
        "sessionId": "79276c31-c58c-4e79-ae5e-fed1a25ebca1",
        "reason": "JobStarted",
        "jobGraph": {
            "vertices": [
                21,
                22
            ],
            "edges": [
                {
                    "source": 21,
                    "target": 22
                }
            ]
        },
        "id": 962221,
        "jobs": {
            "data": [
                {
                    "id": 21
                },
                {
                    "id": 22
                }
            ]
        }
    }
  5. Retain the id value, which is the job identifier, for monitoring.

Step - Run Job with Overrides - Tables

Note

This feature may not be available in all product editions. For more information on available features, see Compare Editions.

You can also pass job definition overrides for table-based outputs. For table outputs, overrides include:

  • Path to database to which to write (must have write access)

  • Connection to write to the target.

    Tip

    This identifier is for the connection used to write to the target system. This connection must already exist. For more information on how to retrieve the identifier for a connection, see

    Dataprep by Trifacta: API Reference docs

  • Name of output table

  • Target table type

    Tip

    You can acquire the target type from the vendor value in the connection response. For more information, see

    Dataprep by Trifacta: API Reference docs

  • action:

    Key value

    Description

    create

    Create a new table with each publication.

    createAndLoad

    Append your data to the table.

    truncateAndLoad

    Truncate the table and load it with your data.

    dropAndLoad

    Drop the table and write the new table in its place.

  • Identifier of connection to use to write data.

  1. Acquire the internal identifier for the recipe for which you wish to execute a job. In the previous example, this identifier was 28629.

  2. Construct a request using the following:

    Endpoint

    <protocol>://<platform_base_url>/v4/jobGroups

    Authentication

    Required

    Method

    POST

    Request Body:

    {
      "wrangledDataset": {
        "id": 28629
      },
      "overrides": {
        "publications": [
          {
            "path": [
              "prod_db"
            ],
            "tableName": "Table_CaseFctn2",
            "action": "createAndLoad",
            "targetType": "postgres",
            "connectionId": 3
          }
        ]
      },
      "ranfrom": null
    }
    
  3. In the above example, the job has been launched with the following overrides:

    Note

    When overrides are applied to publishing, any publications that are already attached to the recipe are ignored.

    1. Output path is to the prod_db database, using table name is Table_CaseFctn2.

    2. Output action is "create and load." See above for definitions.

    3. Target table type is a PostgreSQL table.

  4. A response code of 201 - Created is returned. The response body should look like the following:

    {
    
    
        "sessionId": "79276c31-c58c-4e79-ae5e-fed1a25ebca1",
        "reason": "JobStarted",
        "jobGraph": {
            "vertices": [
                21,
                22
            ],
            "edges": [
                {
                    "source": 21,
                    "target": 22
                }
            ]
        },
        "id": 962222,
        "jobs": {
            "data": [
                {
                    "id": 21
                },
                {
                    "id": 22
                }
            ]
        }
    }
  5. Retain the id value, which is the job identifier, for monitoring.

Step - Run Job with Overrides - Webhooks

Note

This feature may not be available in all product editions. For more information on available features, see Compare Editions.

When you execute a job, you can pass in a set of parameters as overrides to generate a webhook message to a third-party application, based on the success or failure of the job.

For more information on webhooks, see Create Flow Webhook Task.

  1. Acquire the internal identifier for the recipe for which you wish to execute a job. In the previous example, this identifier was 28629.

  2. Construct a request using the following:

    Endpoint

    <protocol>://<platform_base_url>/v4/jobGroups

    Authentication

    Required

    Method

    POST

    Request Body:

    {
      "wrangledDataset": {
        "id": 28629
      },
      "overrides": {
        "webhooks": [{
          "name": "webhook override",
          "url": "http://example.com",
          "method": "post",
          "triggerEvent": "onJobFailure",
          "body": {
            "text": "override" 
           },
          "headers": {
            "testHeader": "val1" 
           },
          "sslVerification": true,
          "secretKey": "123"
      }]
     }
    }
  3. In the above example, the job has been launched with the following overrides:

    Override setting

    Description

    name

    Name of the webhook.

    url

    URL to which to send the webhook message.

    method

    The HTTP method to use. Supported values: POST, PUT, PATCH, GET, or DELETE. Body is ignored for GET and DELETE methods.

    triggerEvent

    Supported values: onJobFailure - send webhook message if job fails onJobSuccess - send webhook message if job completes successfully onJobDone - send webhook message when job fails or finishes successfully

    body

    (optional) The value of the text field is the message that is sent.

    Note

    Some special token values are supported. See Create Flow Webhook Task.

    header

    (optional) Key-value pairs of headers to include in the HTTP request.

    sslVerification

    (optional) Set to true if SSL verification should be completed. If not specified, the value is true.

    secretKey

    (optional) If enabled, this value should be set to the secret key to use.

  4. A response code of 201 - Created is returned. The response body should look like the following:

    {
        "sessionId": "79276c31-c58c-4e79-ae5e-fed1a25ebca1",
        "reason": "JobStarted",
        "jobGraph": {
            "vertices": [
                21,
                22
            ],
            "edges": [
                {
                    "source": 21,
                    "target": 22
                }
            ]
        },
        "id": 962222,
        "jobs": {
            "data": [
                {
                    "id": 21
                },
                {
                    "id": 22
                }
            ]
        }
    }
  5. Retain the id value, which is the job identifier, for monitoring.

Step - Run Job with Parameter Overrides

You can pass overrides of the default parameter values as part of the job definition. You can use the following mechanism to pass in parameter overrides of the following types:

  • Datasets with parameters (variable type)

  • Output object parameters

  • Flow parameters

The syntax is the same for each type.

  1. Acquire the internal identifier for the recipe for which you wish to execute a job. In the previous example, this identifier was 28629.

  2. Construct a request using the following:

    Endpoint

    <protocol>://<platform_base_url>/v4/jobGroups

    Authentication

    Required

    Method

    POST

    Request Body:

    {
      "wrangledDataset": {
        "id": 28629
      },
      "overrides": {
        "runParameters": {
          "overrides": {
            "data": [
              {
                "key": "varRegion",
                "value": "02"
              }
            ]
          }
        }
      },
      "ranfrom": null
    }
  3. In the above example, the specified job has been launched for recipe 28629 . The run parameter varRegion has been set to 02 for this specific job. Depending on how it's defined in the flow, this parameter could influence change either of the following:

    1. The source for the imported dataset.

    2. The path for the generated output.

    3. A flow parameter reference in the recipe

    4. For more information, see Overview of Parameterization.

  4. A response code of 201 - Created is returned. The response body should look like the following:

    {
        "sessionId": "79276c31-c58c-4e79-ae5e-fed1a25ebca1",
        "reason": "JobStarted",
        "jobGraph": {
            "vertices": [
                21,
                22
            ],
            "edges": [
                {
                    "source": 21,
                    "target": 22
                }
            ]
        },
        "id": 962223,
        "jobs": {
            "data": [
                {
                    "id": 21
                },
                {
                    "id": 22
                }
            ]
        }
    }
  5. Retain the id value, which is the job identifier, for monitoring.

Step - Dataflow Execution Overrides

Note

Overrides applied to the jobGroup are merged with any overrides specified as part of the output objects associated with the wrangledDataset. For more information, see API Task - Manage Outputs.

If neither object has a specified override for a Dataflowproperty, the applicable project setting is used. See User Execution Settings Page.

General example

You can submit overrides to a specific set of Dataflow properties for your job execution. For general information on how these settings affect your jobs, see Run Job on Cloud Dataflow.

Note

If you are using automatic VPC network mode, then network, subnetwork, and usePublicIPs do not apply.

The following example shows how to run a job for a specified recipe with Dataflow property overrides applied to it:

Endpoint

https://www.api.clouddataprep.com/v4/jobGroups

Authentication

Required

Method

POST

Request Body:

{
  "wrangledDataset": {
    "id": 28629
  },
  "execution": "dataflow",
  "dataflowOptions": [
    {"region": "first-region"},
    {"zone": "second-zone"},
    {"machineType": "n1-standard-32"},
    {"network": ""},
    {"subnetwork": ""},
    {"autoscalingAlgorithm": "THROUGHPUT_BASED"},
    {"maxNumWorkers": "1000"},
    {"numWorkers": "10"}
  ]
}

Notes on properties:

  • You can submit empty or null values for property values in the payload. These values are submitted.

  • If you are not using auto-scaling on your job:

    • "autoscalingAlgorithm": "NONE",

    • Use "numWorkers" instead to specify the number of compute nodes to use for the job.

      Note

      This feature may not be available in all product editions. For more information on available features, see Compare Editions.

  • If you are using auto-scaling on your job:

    • "autoscalingAlgorithm": "throughput_based",

    • Use the "maxNumWorkers" and "numWorkers" instead to specify the number of compute nodes to use for the job.

      Note

      This feature may not be available in all product editions. For more information on available features, see Compare Editions.

Example using VPC

By default, Dataflow expects that submitted jobs are executed across publicly available IP addresses (usePublicUPs = true). As needed, you can use resources available through a VPC.

Note

Google Private Access must be enabled on your Virtual Private Cloud (VPC) for Dataprep by Trifacta to access it.

If needed, you can override the default settings to execute the job on workers that are available through your VPC.

The following example shows how to run a job for a specified recipe with Dataflow to use your specified VPC:

Endpoint

https://www.api.clouddataprep.com/v4/jobGroups

Authentication

Required

Method

POST

Request Body:

{
  "wrangledDataset": {
    "id": 28629
  },
  "execution": "dataflow",
  "dataflowOptions": [
    {"region": "first-region"},
    {"zone": "second-zone"},
    {"machineType": "n1-standard-32"},
    {"network": "my-network-name"},
    {"subnetwork": "my-subnetwork-url"},
    {"autoscalingAlgorithm": "THROUGHPUT_BASED"},
    {"serviceAccount": "my-service-account-name@<project-id>.iam.gserviceaccount.com"},
    {"numWorkers": "1"},
    {"maxNumWorkers": "1000"},
    {"usePublicIps": "false"}
  ]
}

Subnetwork values:

To specify a different sub-network, enter the URL of the sub-network. The URL should be in the following format:

regions/<REGION>/subnetworks/<SUBNETWORK>

where:

  • <REGION> is the region identifier specified under Regional Endpoint. These values must match.

  • <SUBNETWORK> is the subnetwork identifier.

If you have access to another project, you can execute your Dataflow job through it by specifying a full URL in the following form:

https://www.googleapis.com/compute/v1/projects/<HOST_PROJECT_ID>/regions/<REGION>/subnetworks/<SUBNETWORK>

where:

  • <HOST_PROJECT_ID> corresponds to the project identifier. This value must be between 6 and 30 characters. The value can contain only lowercase letters, digits, or hyphens. It must start with a letter. Trailing hyphens are prohibited.

Example with labels

You can use labels to assign billing information for the job in your project.

Note

This feature may not be available in all product editions. For more information on available features, see Compare Editions.

The following example shows how to run a job for a specified recipe with Dataflow labels applied to it:

Endpoint

https://www.api.clouddataprep.com/v4/jobGroups

Authentication

Required

Method

POST

Request Body:

{
  "wrangledDataset": {
    "id": 28629
  },
  "execution": "dataflow",
  "dataflowOptions": [
    {"region": "first-region"},
    {"zone": "second-zone"},
    {"machineType": "n1-standard-32"},
    {"network": ""},
    {"subnetwork": ""},
    {"autoscalingAlgorithm": "THROUGHPUT_BASED"},
    {"maxNumWorkers": "1000"},
    {"numWorkers": "10"},
    {"labels": [
      {
        "key": "first-new-label-key",
        "value": "first-new-label-value"
      },
      {
        "key": "second-new-label-key",
        "value": "second-new-label-value"
      }
    ]
   }
  ]
}

Notes on labels:

You can apply up to 64 labels for a job. For more information on the available properties, see Runtime Dataflow Execution Settings.