Package-level declarations
Types
Specifies the type and number of accelerator cards attached to the instances of an instance. See GPUs on Compute Engine (https://cloud.google.com/compute/docs/gpus/).
Autoscaling Policy config associated with the cluster.
Node group identification and configuration information.
Auxiliary services configuration for a Cluster.
Basic algorithm for autoscaling.
Associates members, or principals, with a role.
The cluster config.
A selector that chooses target cluster for jobs based on metadata.
The status of a cluster and its instances.
Confidential Instance Config for clusters using Confidential VMs (https://cloud.google.com/compute/confidential-vm/docs)
Dataproc metric config.
Specifies the config of disk options for a group of VM instances.
Driver scheduling configuration.
Encryption settings for the cluster.
Endpoint config for this cluster
Environment configuration for a workload.
Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec.Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.
Common config settings for resources of Compute Engine cluster instances, applicable to all instances in the cluster.
The cluster's GKE config.
Parameters that describe cluster nodes.
A GkeNodeConfigAcceleratorConfig represents a Hardware Accelerator request for a node pool.
GkeNodePoolAutoscaling contains information the cluster autoscaler needs to adjust the size of the node pool to the current cluster usage.
The configuration of a GKE node pool used by a Dataproc-on-GKE cluster (https://cloud.google.com/dataproc/docs/concepts/jobs/dataproc-gke#create-a-dataproc-on-gke-cluster).
GKE node pools that Dataproc workloads run on.
A Dataproc job for running Apache Hadoop MapReduce (https://hadoop.apache.org/docs/current/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html) jobs on Apache Hadoop YARN (https://hadoop.apache.org/docs/r2.7.1/hadoop-yarn/hadoop-yarn-site/YARN.html).
A Dataproc job for running Apache Hive (https://hive.apache.org/) queries on YARN.
Identity related configuration, including service account based secure multi-tenancy user mappings.
Configuration for the size bounds of an instance group, including its proportional size to other groups.
The config settings for Compute Engine resources in an instance group, such as a master or worker group.
A reference to a Compute Engine instance.
Encapsulates the full scoping used to reference a job.
Job scheduling options.
Dataproc job status.
Specifies Kerberos related configuration.
The configuration for running the Dataproc cluster on Kubernetes.
Specifies the cluster auto-delete schedule configuration.
The runtime logging config of the job.
Cluster that is managed by the workflow.
Specifies the resources used to actively manage an instance group.
Specifies a Metastore configuration.
A Dataproc custom metric.
Deprecated. Used only for the deprecated beta. A full, namespace-isolated deployment target for an existing GKE cluster.
Node Group Affinity for clusters using sole-tenant node groups. The Dataproc NodeGroupAffinity resource is not related to the Dataproc NodeGroup resource.
Dataproc Node Group. The Dataproc NodeGroup resource is not related to the Dataproc NodeGroupAffinity resource.
Specifies an executable to run on a fully configured node and a timeout period for executable completion.
A job executed by the workflow.
Configuration for parameter validation.
Auxiliary services configuration for a workload.
A Dataproc job for running Apache Pig (https://pig.apache.org/) queries on YARN.
A Dataproc job for running Presto (https://prestosql.io/) queries. IMPORTANT: The Dataproc Presto Optional Component (https://cloud.google.com/dataproc/docs/concepts/components/presto) must be enabled when the cluster is created to submit a Presto job to the cluster.
A configuration for running an Apache PySpark (https://spark.apache.org/docs/latest/api/python/getting_started/quickstart.html) batch workload.
A Dataproc job for running Apache PySpark (https://spark.apache.org/docs/0.9.0/python-programming-guide.html) applications on YARN.
A list of queries to run on a cluster.
Validation based on regular expressions.
Reservation Affinity for consuming Zonal reservation.
Runtime information about workload execution.
Security related configuration, including encryption, Kerberos, etc.
Shielded Instance Config for clusters using Compute Engine Shielded VMs (https://cloud.google.com/security/shielded-cloud/shielded-vm).
Spark History Server configuration for the workload.
A Dataproc job for running Apache Spark (https://spark.apache.org/) applications on YARN.
A Dataproc job for running Apache SparkR (https://spark.apache.org/docs/latest/sparkr.html) applications on YARN.
A Dataproc job for running Apache Spark SQL (https://spark.apache.org/sql/) queries.
Historical state information.
A configurable parameter that replaces one or more fields in the template. Parameterizable fields: - Labels - File uris - Job properties - Job arguments - Script variables - Main class (in HadoopJob and SparkJob) - Zone (in ClusterSelector)
A Dataproc job for running Trino (https://trino.io/) queries. IMPORTANT: The Dataproc Trino Optional Component (https://cloud.google.com/dataproc/docs/concepts/components/trino) must be enabled when the cluster is created to submit a Trino job to the cluster.
Usage metrics represent approximate total resources consumed by a workload.
The usage snaphot represents the resources consumed by a workload at a specified time.
Validation based on a list of allowed values.
The Dataproc cluster config for a cluster that does not directly control the underlying compute resources, such as a Dataproc-on-GKE cluster (https://cloud.google.com/dataproc/docs/guides/dpgke/dataproc-gke-overview).
Specifies workflow execution target.Either managed_cluster or cluster_selector is required.
A YARN application created by a job. Application information is a subset of org.apache.hadoop.yarn.proto.YarnProtos.ApplicationReportProto.Beta Feature: This report is available for testing purposes only. It may be changed before final release.