Hi Eila, It looks like you're attempting to set the option on the GoogleCloudOptions class directly, I think you want to set it on an instance of PipelineOptions that you've viewed as GoogleCloudOptions. Like this example from https://cloud.google.com/dataflow/docs/guides/specifying-exec-params#configuring-pipelineoptions-for-execution-on-the-cloud-dataflow-service
# Create and set your PipelineOptions. options = PipelineOptions(flags=argv) # For Cloud execution, specify DataflowRunner and set the Cloud Platform # project, job name, staging file location, temp file location, and region. options.view_as(StandardOptions).runner = 'DataflowRunner' google_cloud_options = options.view_as(GoogleCloudOptions) google_cloud_options.project = 'my-project-id' ... # Create the Pipeline with the specified options. p = Pipeline(options=options) Alternatively you should be able to just specify --worker_machine_type at the command line if you're parsing the PipelineOptions from sys.argv. Does that help? Brian On Tue, May 12, 2020 at 8:30 AM OrielResearch Eila Arich-Landkof < [email protected]> wrote: > Hello, > > I am trying to check if the setting of the resources are actually being > implemented. > What will be the right way to do it. > *the code is:* > GoogleCloudOptions.worker_machine_type = 'n1-highcpu-96' > > and *the dataflow view is *the following (nothing that reflects > the highcpu machine. > Please advice > > Thanks, > Eila > Resource metrics > Current vCPUs > > 1 > > Total vCPU time > > 0.07 vCPU hr > > Current memory > > 3.75 GB > > Total memory time > > 0.264 GB hr > > Current PD > > 250 GB > > Total PD time > > 17.632 GB hr > > Current SSD PD > > 0 B > > Total SSD PD time > > 0 GB hr > > > -- > Eila > <http://www.orielresearch.com> > Meetup <https://www.meetup.com/Deep-Learning-In-Production/> >
