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The permissions that you need to run the Dataflow classic template depend on where you run the template, and whether your source and sink for the pipeline are in another project.

Required permissions for running a classic template To learn about the different kinds of Dataflow templates, their benefits, and when to choose a classic template, see Dataflow templates.

Create and stage the custom classic template.

Check if the pipeline I/O connectors support ValueProvider objects, and make changes as required.

Examples of such metadata include the name of your custom classic template and optional parameters.

Extend your template with additional metadata so that custom parameters are validated when the classic template is run.

Use DoFn objects that accept runtime parameters.

In your pipeline code, use the ValueProvider interface for all pipeline options that you want to set or use at runtime.

Details of this process are provided in subsequent sections. The following is a brief overview of the process. You use a command to generate the template from an existing pipeline. That you can customize for each job by changing specific pipeline parameters. In this document, you learn how to create a custom classic template from your Dataflow pipeline code.Ĭlassic templates package existing Dataflow pipelines to create reusable templates Save money with our transparent approach to pricing Migrate from PaaS: Cloud Foundry, OpenshiftĬOVID-19 Solutions for the Healthcare Industry

Cloud Storage text files to Cloud Spanner.

Cloud Storage SequenceFile files to Bigtable.

Cloud Storage Parquet files to Bigtable.

Cloud Storage Avro files to Cloud Spanner.

Cloud Spanner to text files on Cloud Storage.

Cloud Spanner to Avro files on Cloud Storage.

Bigtable to SequenceFile files on Cloud Storage.

Bigtable to Parquet files on Cloud Storage.

Bigtable to Avro files on Cloud Storage.BigQuery to TFRecord files on Cloud Storage.BigQuery to Parquet files on Cloud Storage.

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