com.pulumi.gcp.dataproc.kotlin.outputs.ClusterClusterConfigWorkerConfig.kt Maven / Gradle / Ivy

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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.

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@file:Suppress("NAME_SHADOWING", "DEPRECATION")

package com.pulumi.gcp.dataproc.kotlin.outputs

import kotlin.Int
import kotlin.String
import kotlin.Suppress
import kotlin.collections.List

/**
 *
 * @property accelerators The Compute Engine accelerator configuration for these instances. Can be specified multiple times.
 * @property diskConfig Disk Config
 * @property imageUri 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.
 * @property instanceNames List of worker instance names which have been assigned
 * to the cluster.
 * @property machineType 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`).
 * @property minCpuPlatform 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.
 * @property minNumInstances The minimum number of primary worker instances to create.  If `min_num_instances` is set, cluster creation will succeed if the number of primary workers created is at least equal to the `min_num_instances` number.
 * @property numInstances 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`
 */
public data class ClusterClusterConfigWorkerConfig(
    public val accelerators: List? = null,
    public val diskConfig: ClusterClusterConfigWorkerConfigDiskConfig? = null,
    public val imageUri: String? = null,
    public val instanceNames: List? = null,
    public val machineType: String? = null,
    public val minCpuPlatform: String? = null,
    public val minNumInstances: Int? = null,
    public val numInstances: Int? = null,
) {
    public companion object {
        public fun toKotlin(javaType: com.pulumi.gcp.dataproc.outputs.ClusterClusterConfigWorkerConfig): ClusterClusterConfigWorkerConfig = ClusterClusterConfigWorkerConfig(
            accelerators = javaType.accelerators().map({ args0 ->
                args0.let({ args0 ->
                    com.pulumi.gcp.dataproc.kotlin.outputs.ClusterClusterConfigWorkerConfigAccelerator.Companion.toKotlin(args0)
                })
            }),
            diskConfig = javaType.diskConfig().map({ args0 ->
                args0.let({ args0 ->
                    com.pulumi.gcp.dataproc.kotlin.outputs.ClusterClusterConfigWorkerConfigDiskConfig.Companion.toKotlin(args0)
                })
            }).orElse(null),
            imageUri = javaType.imageUri().map({ args0 -> args0 }).orElse(null),
            instanceNames = javaType.instanceNames().map({ args0 -> args0 }),
            machineType = javaType.machineType().map({ args0 -> args0 }).orElse(null),
            minCpuPlatform = javaType.minCpuPlatform().map({ args0 -> args0 }).orElse(null),
            minNumInstances = javaType.minNumInstances().map({ args0 -> args0 }).orElse(null),
            numInstances = javaType.numInstances().map({ args0 -> args0 }).orElse(null),
        )
    }
}