Package com.pulumi.gcp.dataproc.inputs

Class ClusterClusterConfigWorkerConfigArgs

  • public final class ClusterClusterConfigWorkerConfigArgs
extends com.pulumi.resources.ResourceArgs

    • Method Detail

      • accelerators

        public java.util.Optional<com.pulumi.core.Output<java.util.List<ClusterClusterConfigWorkerConfigAcceleratorArgs>>> accelerators()
        Returns:
        The Compute Engine accelerator configuration for these instances. Can be specified multiple times.

      • imageUri

        public java.util.Optional<com.pulumi.core.Output<java.lang.String>> imageUri()
        Returns:
        The URI for the image to use for this worker. See [the guide](https://cloud.google.com/dataproc/docs/guides/dataproc-images) for more information.

      • instanceNames

        public java.util.Optional<com.pulumi.core.Output<java.util.List<java.lang.String>>> instanceNames()

      • machineType

        public java.util.Optional<com.pulumi.core.Output<java.lang.String>> machineType()
        Returns:
        The name of a Google Compute Engine machine type to create for the worker nodes. If not specified, GCP will default to a predetermined computed value (currently `n1-standard-4`).

      • minCpuPlatform

        public java.util.Optional<com.pulumi.core.Output<java.lang.String>> minCpuPlatform()
        Returns:
        The name of a minimum generation of CPU family for the master. If not specified, GCP will default to a predetermined computed value for each zone. See [the guide](https://cloud.google.com/compute/docs/instances/specify-min-cpu-platform) for details about which CPU families are available (and defaulted) for each zone.

      • numInstances

        public java.util.Optional<com.pulumi.core.Output<java.lang.Integer>> numInstances()
        Returns:
        Specifies the number of worker nodes to create. If not specified, GCP will default to a predetermined computed value (currently 2). There is currently a beta feature which allows you to run a [Single Node Cluster](https://cloud.google.com/dataproc/docs/concepts/single-node-clusters). In order to take advantage of this you need to set `"dataproc:dataproc.allow.zero.workers" = "true"` in `cluster_config.software_config.properties`