close()

Close httplib2 connections.

create(parent, body=None, x__xgafv=None)

Create a session template synchronously.

Args:
parent: string, Required. The parent resource where this session template will be created. (required)
body: object, The request body.
The object takes the form of:

{ # A representation of a session template.
"createTime": "A String", # Output only. The time when the template was created.
"creator": "A String", # Output only. The email address of the user who created the template.
"description": "A String", # Optional. Brief description of the template.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"idleTtl": "A String", # Optional. Applies to sessions only. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 1 hour if not set. If both ttl and idle_ttl are specified for an interactive session, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
"kmsKey": "A String", # Optional. The Cloud KMS key to use for encryption.
"networkTags": [ # Optional. Tags used for network traffic control.
"A String",
],
"networkUri": "A String", # Optional. Network URI to connect workload to.
"serviceAccount": "A String", # Optional. Service account that used to execute workload.
"stagingBucket": "A String", # Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
"subnetworkUri": "A String", # Optional. Subnetwork URI to connect workload to.
"ttl": "A String", # Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
},
"peripheralsConfig": { # Auxiliary services configuration for a workload. # Optional. Peripherals configuration that workload has access to.
"metastoreService": "A String", # Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
"sparkHistoryServerConfig": { # Spark History Server configuration for the workload. # Optional. The Spark History Server configuration for the workload.
"dataprocCluster": "A String", # Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]
},
},
},
"jupyterSession": { # Jupyter configuration for an interactive session. # Optional. Jupyter session config.
"displayName": "A String", # Optional. Display name, shown in the Jupyter kernelspec card.
"kernel": "A String", # Optional. Kernel
},
"labels": { # Optional. Labels to associate with sessions created using this template. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values can be empty, but, if present, must contain 1 to 63 characters and conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a session.
"a_key": "A String",
},
"name": "A String", # Required. The resource name of the session template.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for session execution.
"autotuningConfig": { # Autotuning configuration of the workload. # Optional. Autotuning configuration of the workload.
"scenarios": [ # Optional. Scenarios for which tunings are applied.
"A String",
],
},
"cohort": "A String", # Optional. Cohort identifier. Identifies families of the workloads having the same shape, e.g. daily ETL jobs.
"containerImage": "A String", # Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
"properties": { # Optional. A mapping of property names to values, which are used to configure workload execution.
"a_key": "A String",
},
"repositoryConfig": { # Configuration for dependency repositories # Optional. Dependency repository configuration.
"pypiRepositoryConfig": { # Configuration for PyPi repository # Optional. Configuration for PyPi repository.
"pypiRepository": "A String", # Optional. PyPi repository address
},
},
"version": "A String", # Optional. Version of the batch runtime.
},
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"updateTime": "A String", # Output only. The time the template was last updated.
"uuid": "A String", # Output only. A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.
}

x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # A representation of a session template.
"createTime": "A String", # Output only. The time when the template was created.
"creator": "A String", # Output only. The email address of the user who created the template.
"description": "A String", # Optional. Brief description of the template.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"idleTtl": "A String", # Optional. Applies to sessions only. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 1 hour if not set. If both ttl and idle_ttl are specified for an interactive session, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
"kmsKey": "A String", # Optional. The Cloud KMS key to use for encryption.
"networkTags": [ # Optional. Tags used for network traffic control.
"A String",
],
"networkUri": "A String", # Optional. Network URI to connect workload to.
"serviceAccount": "A String", # Optional. Service account that used to execute workload.
"stagingBucket": "A String", # Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
"subnetworkUri": "A String", # Optional. Subnetwork URI to connect workload to.
"ttl": "A String", # Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
},
"peripheralsConfig": { # Auxiliary services configuration for a workload. # Optional. Peripherals configuration that workload has access to.
"metastoreService": "A String", # Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
"sparkHistoryServerConfig": { # Spark History Server configuration for the workload. # Optional. The Spark History Server configuration for the workload.
"dataprocCluster": "A String", # Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]
},
},
},
"jupyterSession": { # Jupyter configuration for an interactive session. # Optional. Jupyter session config.
"displayName": "A String", # Optional. Display name, shown in the Jupyter kernelspec card.
"kernel": "A String", # Optional. Kernel
},
"labels": { # Optional. Labels to associate with sessions created using this template. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values can be empty, but, if present, must contain 1 to 63 characters and conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a session.
"a_key": "A String",
},
"name": "A String", # Required. The resource name of the session template.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for session execution.
"autotuningConfig": { # Autotuning configuration of the workload. # Optional. Autotuning configuration of the workload.
"scenarios": [ # Optional. Scenarios for which tunings are applied.
"A String",
],
},
"cohort": "A String", # Optional. Cohort identifier. Identifies families of the workloads having the same shape, e.g. daily ETL jobs.
"containerImage": "A String", # Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
"properties": { # Optional. A mapping of property names to values, which are used to configure workload execution.
"a_key": "A String",
},
"repositoryConfig": { # Configuration for dependency repositories # Optional. Dependency repository configuration.
"pypiRepositoryConfig": { # Configuration for PyPi repository # Optional. Configuration for PyPi repository.
"pypiRepository": "A String", # Optional. PyPi repository address
},
},
"version": "A String", # Optional. Version of the batch runtime.
},
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"updateTime": "A String", # Output only. The time the template was last updated.
"uuid": "A String", # Output only. A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.
}

delete(name, x__xgafv=None)

Deletes a session template.

Args:
  name: string, Required. The name of the session template resource to delete. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
}

get(name, x__xgafv=None)

Gets the resource representation for a session template.

Args:
name: string, Required. The name of the session template to retrieve. (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # A representation of a session template.
"createTime": "A String", # Output only. The time when the template was created.
"creator": "A String", # Output only. The email address of the user who created the template.
"description": "A String", # Optional. Brief description of the template.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"idleTtl": "A String", # Optional. Applies to sessions only. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 1 hour if not set. If both ttl and idle_ttl are specified for an interactive session, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
"kmsKey": "A String", # Optional. The Cloud KMS key to use for encryption.
"networkTags": [ # Optional. Tags used for network traffic control.
"A String",
],
"networkUri": "A String", # Optional. Network URI to connect workload to.
"serviceAccount": "A String", # Optional. Service account that used to execute workload.
"stagingBucket": "A String", # Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
"subnetworkUri": "A String", # Optional. Subnetwork URI to connect workload to.
"ttl": "A String", # Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
},
"peripheralsConfig": { # Auxiliary services configuration for a workload. # Optional. Peripherals configuration that workload has access to.
"metastoreService": "A String", # Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
"sparkHistoryServerConfig": { # Spark History Server configuration for the workload. # Optional. The Spark History Server configuration for the workload.
"dataprocCluster": "A String", # Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]
},
},
},
"jupyterSession": { # Jupyter configuration for an interactive session. # Optional. Jupyter session config.
"displayName": "A String", # Optional. Display name, shown in the Jupyter kernelspec card.
"kernel": "A String", # Optional. Kernel
},
"labels": { # Optional. Labels to associate with sessions created using this template. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values can be empty, but, if present, must contain 1 to 63 characters and conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a session.
"a_key": "A String",
},
"name": "A String", # Required. The resource name of the session template.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for session execution.
"autotuningConfig": { # Autotuning configuration of the workload. # Optional. Autotuning configuration of the workload.
"scenarios": [ # Optional. Scenarios for which tunings are applied.
"A String",
],
},
"cohort": "A String", # Optional. Cohort identifier. Identifies families of the workloads having the same shape, e.g. daily ETL jobs.
"containerImage": "A String", # Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
"properties": { # Optional. A mapping of property names to values, which are used to configure workload execution.
"a_key": "A String",
},
"repositoryConfig": { # Configuration for dependency repositories # Optional. Dependency repository configuration.
"pypiRepositoryConfig": { # Configuration for PyPi repository # Optional. Configuration for PyPi repository.
"pypiRepository": "A String", # Optional. PyPi repository address
},
},
"version": "A String", # Optional. Version of the batch runtime.
},
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"updateTime": "A String", # Output only. The time the template was last updated.
"uuid": "A String", # Output only. A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.
}

list(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)

Lists session templates.

Args:
parent: string, Required. The parent that owns this collection of session templates. (required)
filter: string, Optional. A filter for the session templates to return in the response. Filters are case sensitive and have the following syntax:field = value AND field = value ...
pageSize: integer, Optional. The maximum number of sessions to return in each response. The service may return fewer than this value.
pageToken: string, Optional. A page token received from a previous ListSessions call. Provide this token to retrieve the subsequent page.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # A list of session templates.
"nextPageToken": "A String", # A token, which can be sent as page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.
"sessionTemplates": [ # Output only. Session template list
{ # A representation of a session template.
"createTime": "A String", # Output only. The time when the template was created.
"creator": "A String", # Output only. The email address of the user who created the template.
"description": "A String", # Optional. Brief description of the template.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"idleTtl": "A String", # Optional. Applies to sessions only. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 1 hour if not set. If both ttl and idle_ttl are specified for an interactive session, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
"kmsKey": "A String", # Optional. The Cloud KMS key to use for encryption.
"networkTags": [ # Optional. Tags used for network traffic control.
"A String",
],
"networkUri": "A String", # Optional. Network URI to connect workload to.
"serviceAccount": "A String", # Optional. Service account that used to execute workload.
"stagingBucket": "A String", # Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
"subnetworkUri": "A String", # Optional. Subnetwork URI to connect workload to.
"ttl": "A String", # Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
},
"peripheralsConfig": { # Auxiliary services configuration for a workload. # Optional. Peripherals configuration that workload has access to.
"metastoreService": "A String", # Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
"sparkHistoryServerConfig": { # Spark History Server configuration for the workload. # Optional. The Spark History Server configuration for the workload.
"dataprocCluster": "A String", # Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]
},
},
},
"jupyterSession": { # Jupyter configuration for an interactive session. # Optional. Jupyter session config.
"displayName": "A String", # Optional. Display name, shown in the Jupyter kernelspec card.
"kernel": "A String", # Optional. Kernel
},
"labels": { # Optional. Labels to associate with sessions created using this template. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values can be empty, but, if present, must contain 1 to 63 characters and conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a session.
"a_key": "A String",
},
"name": "A String", # Required. The resource name of the session template.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for session execution.
"autotuningConfig": { # Autotuning configuration of the workload. # Optional. Autotuning configuration of the workload.
"scenarios": [ # Optional. Scenarios for which tunings are applied.
"A String",
],
},
"cohort": "A String", # Optional. Cohort identifier. Identifies families of the workloads having the same shape, e.g. daily ETL jobs.
"containerImage": "A String", # Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
"properties": { # Optional. A mapping of property names to values, which are used to configure workload execution.
"a_key": "A String",
},
"repositoryConfig": { # Configuration for dependency repositories # Optional. Dependency repository configuration.
"pypiRepositoryConfig": { # Configuration for PyPi repository # Optional. Configuration for PyPi repository.
"pypiRepository": "A String", # Optional. PyPi repository address
},
},
"version": "A String", # Optional. Version of the batch runtime.
},
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"updateTime": "A String", # Output only. The time the template was last updated.
"uuid": "A String", # Output only. A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.
},
],
}

list_next()

Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call 'execute()' on to request the next
          page. Returns None if there are no more items in the collection.

patch(name, body=None, x__xgafv=None)

Updates the session template synchronously.

Args:
name: string, Required. The resource name of the session template. (required)
body: object, The request body.
The object takes the form of:

{ # A representation of a session template.
"createTime": "A String", # Output only. The time when the template was created.
"creator": "A String", # Output only. The email address of the user who created the template.
"description": "A String", # Optional. Brief description of the template.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"idleTtl": "A String", # Optional. Applies to sessions only. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 1 hour if not set. If both ttl and idle_ttl are specified for an interactive session, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
"kmsKey": "A String", # Optional. The Cloud KMS key to use for encryption.
"networkTags": [ # Optional. Tags used for network traffic control.
"A String",
],
"networkUri": "A String", # Optional. Network URI to connect workload to.
"serviceAccount": "A String", # Optional. Service account that used to execute workload.
"stagingBucket": "A String", # Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
"subnetworkUri": "A String", # Optional. Subnetwork URI to connect workload to.
"ttl": "A String", # Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
},
"peripheralsConfig": { # Auxiliary services configuration for a workload. # Optional. Peripherals configuration that workload has access to.
"metastoreService": "A String", # Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
"sparkHistoryServerConfig": { # Spark History Server configuration for the workload. # Optional. The Spark History Server configuration for the workload.
"dataprocCluster": "A String", # Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]
},
},
},
"jupyterSession": { # Jupyter configuration for an interactive session. # Optional. Jupyter session config.
"displayName": "A String", # Optional. Display name, shown in the Jupyter kernelspec card.
"kernel": "A String", # Optional. Kernel
},
"labels": { # Optional. Labels to associate with sessions created using this template. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values can be empty, but, if present, must contain 1 to 63 characters and conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a session.
"a_key": "A String",
},
"name": "A String", # Required. The resource name of the session template.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for session execution.
"autotuningConfig": { # Autotuning configuration of the workload. # Optional. Autotuning configuration of the workload.
"scenarios": [ # Optional. Scenarios for which tunings are applied.
"A String",
],
},
"cohort": "A String", # Optional. Cohort identifier. Identifies families of the workloads having the same shape, e.g. daily ETL jobs.
"containerImage": "A String", # Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
"properties": { # Optional. A mapping of property names to values, which are used to configure workload execution.
"a_key": "A String",
},
"repositoryConfig": { # Configuration for dependency repositories # Optional. Dependency repository configuration.
"pypiRepositoryConfig": { # Configuration for PyPi repository # Optional. Configuration for PyPi repository.
"pypiRepository": "A String", # Optional. PyPi repository address
},
},
"version": "A String", # Optional. Version of the batch runtime.
},
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"updateTime": "A String", # Output only. The time the template was last updated.
"uuid": "A String", # Output only. A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.
}

x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # A representation of a session template.
"createTime": "A String", # Output only. The time when the template was created.
"creator": "A String", # Output only. The email address of the user who created the template.
"description": "A String", # Optional. Brief description of the template.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"idleTtl": "A String", # Optional. Applies to sessions only. The duration to keep the session alive while it's idling. Exceeding this threshold causes the session to terminate. This field cannot be set on a batch workload. Minimum value is 10 minutes; maximum value is 14 days (see JSON representation of Duration (https://developers.google.com/protocol-buffers/docs/proto3#json)). Defaults to 1 hour if not set. If both ttl and idle_ttl are specified for an interactive session, the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
"kmsKey": "A String", # Optional. The Cloud KMS key to use for encryption.
"networkTags": [ # Optional. Tags used for network traffic control.
"A String",
],
"networkUri": "A String", # Optional. Network URI to connect workload to.
"serviceAccount": "A String", # Optional. Service account that used to execute workload.
"stagingBucket": "A String", # Optional. A Cloud Storage bucket used to stage workload dependencies, config files, and store workload output and other ephemeral data, such as Spark history files. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location according to the region where your workload is running, and then create and manage project-level, per-location staging and temporary buckets. This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.
"subnetworkUri": "A String", # Optional. Subnetwork URI to connect workload to.
"ttl": "A String", # Optional. The duration after which the workload will be terminated, specified as the JSON representation for Duration (https://protobuf.dev/programming-guides/proto3/#json). When the workload exceeds this duration, it will be unconditionally terminated without waiting for ongoing work to finish. If ttl is not specified for a batch workload, the workload will be allowed to run until it exits naturally (or run forever without exiting). If ttl is not specified for an interactive session, it defaults to 24 hours. If ttl is not specified for a batch that uses 2.1+ runtime version, it defaults to 4 hours. Minimum value is 10 minutes; maximum value is 14 days. If both ttl and idle_ttl are specified (for an interactive session), the conditions are treated as OR conditions: the workload will be terminated when it has been idle for idle_ttl or when ttl has been exceeded, whichever occurs first.
},
"peripheralsConfig": { # Auxiliary services configuration for a workload. # Optional. Peripherals configuration that workload has access to.
"metastoreService": "A String", # Optional. Resource name of an existing Dataproc Metastore service.Example: projects/[project_id]/locations/[region]/services/[service_id]
"sparkHistoryServerConfig": { # Spark History Server configuration for the workload. # Optional. The Spark History Server configuration for the workload.
"dataprocCluster": "A String", # Optional. Resource name of an existing Dataproc Cluster to act as a Spark History Server for the workload.Example: projects/[project_id]/regions/[region]/clusters/[cluster_name]
},
},
},
"jupyterSession": { # Jupyter configuration for an interactive session. # Optional. Jupyter session config.
"displayName": "A String", # Optional. Display name, shown in the Jupyter kernelspec card.
"kernel": "A String", # Optional. Kernel
},
"labels": { # Optional. Labels to associate with sessions created using this template. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values can be empty, but, if present, must contain 1 to 63 characters and conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a session.
"a_key": "A String",
},
"name": "A String", # Required. The resource name of the session template.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for session execution.
"autotuningConfig": { # Autotuning configuration of the workload. # Optional. Autotuning configuration of the workload.
"scenarios": [ # Optional. Scenarios for which tunings are applied.
"A String",
],
},
"cohort": "A String", # Optional. Cohort identifier. Identifies families of the workloads having the same shape, e.g. daily ETL jobs.
"containerImage": "A String", # Optional. Optional custom container image for the job runtime environment. If not specified, a default container image will be used.
"properties": { # Optional. A mapping of property names to values, which are used to configure workload execution.
"a_key": "A String",
},
"repositoryConfig": { # Configuration for dependency repositories # Optional. Dependency repository configuration.
"pypiRepositoryConfig": { # Configuration for PyPi repository # Optional. Configuration for PyPi repository.
"pypiRepository": "A String", # Optional. PyPi repository address
},
},
"version": "A String", # Optional. Version of the batch runtime.
},
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"updateTime": "A String", # Output only. The time the template was last updated.
"uuid": "A String", # Output only. A session template UUID (Unique Universal Identifier). The service generates this value when it creates the session template.
}

Cloud Dataproc API . projects . locations . sessionTemplates

Instance Methods

Method Details