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For up-to-date documentation of Dataprep, please visit us at https://help.alteryx.com/Dataprep/.

   

Contents:

Review and modify the settings related to how your jobs are executed on Dataflow. These settings are available to individual users and apply to their usage of the product only.

Dataflow Execution Settings

NOTE: Changes made to your execution settings set at the project level do not affect any overrides that have been previously applied at the individual job level. Job-level overrides remain as configured.


Tip: For more information on how the following settings affect your jobs, see Dataflow Execution Settings.

SettingDescription

Regional endpoint

A region is a specific geographical location where you can run your resources.

Zone

A sub-section of region, a zone contains specific resources.

Select Auto Zone to allow the platform to choose the zone for you.

Machine type

Choose the type of machine on which to run your job. The default is n1-standard-1.

Making changes to Region, Zone, or Machine Type can affect the time and cost of job executions. For more information, see https://cloud.google.com/dataflow/docs/concepts/regional-endpoints.

For more information on machine types, https://cloud.google.com/compute/docs/machine-types.

Advanced Settings

NOTE: Changes made to your advanced settings set at the project level do not affect any overrides that have been previously applied at the individual job level. Job-level overrides remain as configured.

SettingDescription

VPC network mode

Select the network mode to use.

If the network mode is set to Auto (default), the job is executed over publicly available IP addresses. Do not set values for Network, Subnetwork, and Worker IP address configuration.

NOTE: Unless you have specific reasons to modify these settings, you should leave them as the default values. These network settings apply to job execution. Preview and sampling use the default network settings.

For Custom VPC networks:

  1. Specify the name of the VPC network in your region.
  2. Specify the short or full URL of the Subnetwork. If both Network and Subnetwork are specified, Subnetwork is used. See https://cloud.google.com/dataflow/docs/guides/specifying-networks.
  3. Review and specify the Worker IP address configuration setting. See below.

For more information:

Network

To use a different VPC network, enter the name of the VPC network to use as an override for this job. Click Save to apply the override.

Subnetwork

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

regions/<REGION>/subnetworks/<SUBNETWORK>

where:

  • <REGION> is the region identifier specified under Region. These values must match.
  • <SUBNETWORK> is the subnetwork identifier.

If you have access to another project within your organization, 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.

Click Save to apply the override.

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

SettingDescription

Worker IP address configuration

If the VPC Network mode is set to custom, then choose one of the following:

  • Allow public IP addresses - Use Dataflow workers that are available through public IP addresses. No further configuration is required.
  • Use internal IP addresses only - Dataflow workers use private IP addresses for all communication.
    • If a Subnetwork is specified, then the Network value is ignored.
    • The specified Network or Subnetwork must have Private Google Access enabled.

Autoscaling algorithms

The type of algorithm to use to scale the number of Google Compute Engine instances to accommodate the size of your job. Possible values:

  • Throughput based - Scaling is determined by the volume of data expected to be passed through Dataflow.
  • None - None algorithm is applied.
    • If none is selected, use Initial Number of Workers to specify a fixed number of Google Compute Engine instances.

Initial number of workers

Number of Google Compute Engine instances with which to launch the job. This number may be adjusted as part of job execution. This number must be an integer between 1 and 1000, inclusive.

Maximum number of workers

Maximum number of Google Compute Engine instances to use during execution. This number must be an integer between 1 and 1000, inclusive, and must be greater than the initial number of workers. 

Service account

Every Dataprep by Trifacta job executed in Dataflow requires that the job be submitted through a service account. By default, Dataprep by Trifacta uses a single Compute Engine service account under which jobs from all project users are run.

Optionally, you can specify a different service account under which to run your jobs for the project.

NOTE: When using a named service account to access data and run jobs in other projects, you must be granted the roles/iam.serviceAccountUser role on the service account to use it.

NOTE: Individual users can specify service accounts under which their jobs are run. If companion service accounts are enabled, each user must have a service account specified for use.

For more information on service accounts, see Google Service Account Management.

Labels

Create or assign labels to apply to the billing for the Dataprep by Trifacta jobs run in your project. You may reference up to 64 labels.

NOTE: Each label must have a unique key name.

For more information, see https://cloud.google.com/resource-manager/docs/creating-managing-labels.

Notes on behavior:

  • Values specified here are applied to all jobs executed within the project. 
  • If property values are not specified here, then the properties are not passed in with any job execution, and the default  Dataprep by Trifacta property values are used. 
  • The property values specified here can be overridden by property values specified for individual jobs. For more information, see Dataflow Execution Settings.

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