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<h1><a href="dataproc_v1.html">Cloud Dataproc API</a> . <a href="dataproc_v1.projects.html">projects</a> . <a href="dataproc_v1.projects.locations.html">locations</a> . <a href="dataproc_v1.projects.locations.sessions.html">sessions</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
<code><a href="dataproc_v1.projects.locations.sessions.sparkApplications.html">sparkApplications()</a></code>
</p>
<p class="firstline">Returns the sparkApplications Resource.</p>
<p class="toc_element">
<code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
<code><a href="#create">create(parent, body=None, requestId=None, sessionId=None, x__xgafv=None)</a></code></p>
<p class="firstline">Create an interactive session asynchronously.</p>
<p class="toc_element">
<code><a href="#delete">delete(name, requestId=None, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes the interactive session resource. If the session is not in terminal state, it is terminated, and then deleted.</p>
<p class="toc_element">
<code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Gets the resource representation for an interactive session.</p>
<p class="toc_element">
<code><a href="#list">list(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists interactive sessions.</p>
<p class="toc_element">
<code><a href="#list_next">list_next()</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<p class="toc_element">
<code><a href="#terminate">terminate(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Terminates the interactive session.</p>
<h3>Method Details</h3>
<div class="method">
<code class="details" id="close">close()</code>
<pre>Close httplib2 connections.</pre>
</div>
<div class="method">
<code class="details" id="create">create(parent, body=None, requestId=None, sessionId=None, x__xgafv=None)</code>
<pre>Create an interactive session asynchronously.
Args:
parent: string, Required. The parent resource where this session will be created. (required)
body: object, The request body.
The object takes the form of:
{ # A representation of a session.
"createTime": "A String", # Output only. The time when the session was created.
"creator": "A String", # Output only. The email address of the user who created the session.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for the session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"authenticationConfig": { # Authentication configuration for a workload is used to set the default identity for the workload execution. The config specifies the type of identity (service account or user) that will be used by workloads to access resources on the project(s). # Optional. Authentication configuration used to set the default identity for the workload execution. The config specifies the type of identity (service account or user) that will be used by workloads to access resources on the project(s).
"userWorkloadAuthenticationType": "A String", # Optional. Authentication type for the user workload running in containers.
},
"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. The labels to associate with the session. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must 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", # Identifier. The resource name of the session.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for the 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.
},
"runtimeInfo": { # Runtime information about workload execution. # Output only. Runtime information about session execution.
"approximateUsage": { # Usage metrics represent approximate total resources consumed by a workload. # Output only. Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
"acceleratorType": "A String", # Optional. Accelerator type being used, if any
"milliAcceleratorSeconds": "A String", # Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliDcuSeconds": "A String", # Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliSlotSeconds": "A String", # Optional. Slot usage in (milliSlot x seconds).
"shuffleStorageGbSeconds": "A String", # Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"updateTime": "A String", # Optional. The timestamp of the usage metrics.
},
"currentUsage": { # The usage snapshot represents the resources consumed by a workload at a specified time. # Output only. Snapshot of current workload resource usage.
"acceleratorType": "A String", # Optional. Accelerator type being used, if any
"milliAccelerator": "A String", # Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"milliDcu": "A String", # Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliDcuPremium": "A String", # Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliSlot": "A String", # Optional. Milli (one-thousandth) Slot usage of the workload.
"shuffleStorageGb": "A String", # Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"shuffleStorageGbPremium": "A String", # Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"snapshotTime": "A String", # Optional. The timestamp of the usage snapshot.
},
"diagnosticOutputUri": "A String", # Output only. A URI pointing to the location of the diagnostics tarball.
"endpoints": { # Output only. Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
"a_key": "A String",
},
"outputUri": "A String", # Output only. A URI pointing to the location of the stdout and stderr of the workload.
"propertiesInfo": { # Properties of the workload organized by origin. # Optional. Properties of the workload organized by origin.
"autotuningProperties": { # Output only. Properties set by autotuning engine.
"a_key": { # Annotatated property value.
"annotation": "A String", # Annotation, comment or explanation why the property was set.
"overriddenValue": "A String", # Optional. Value which was replaced by the corresponding component.
"value": "A String", # Property value.
},
},
},
},
"sessionTemplate": "A String", # Optional. The session template used by the session.Only resource names, including project ID and location, are valid.Example: * https://www.googleapis.com/compute/v1/projects/[project_id]/locations/[dataproc_region]/sessionTemplates/[template_id] * projects/[project_id]/locations/[dataproc_region]/sessionTemplates/[template_id]The template must be in the same project and Dataproc region as the session.
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"state": "A String", # Output only. A state of the session.
"stateHistory": [ # Output only. Historical state information for the session.
{ # Historical state information.
"state": "A String", # Output only. The state of the session at this point in the session history.
"stateMessage": "A String", # Output only. Details about the state at this point in the session history.
"stateStartTime": "A String", # Output only. The time when the session entered the historical state.
},
],
"stateMessage": "A String", # Output only. Session state details, such as the failure description if the state is FAILED.
"stateTime": "A String", # Output only. The time when the session entered the current state.
"user": "A String", # Optional. The email address of the user who owns the session.
"uuid": "A String", # Output only. A session UUID (Unique Universal Identifier). The service generates this value when it creates the session.
}
requestId: string, Optional. A unique ID used to identify the request. If the service receives two CreateSessionRequests (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.CreateSessionRequest)s with the same ID, the second request is ignored, and the first Session is created and stored in the backend.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
sessionId: string, Required. The ID to use for the session, which becomes the final component of the session's resource name.This value must be 4-63 characters. Valid characters are /a-z-/.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is false, it means the operation is still in progress. If true, the operation is completed, and either error or response is available.
"error": { # The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC (https://github.com/grpc). Each Status message contains three pieces of data: error code, error message, and error details.You can find out more about this error model and how to work with it in the API Design Guide (https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the name should be a resource name ending with operations/{unique_id}.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as Delete, the response is google.protobuf.Empty. If the original method is standard Get/Create/Update, the response should be the resource. For other methods, the response should have the type XxxResponse, where Xxx is the original method name. For example, if the original method name is TakeSnapshot(), the inferred response type is TakeSnapshotResponse.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}</pre>
</div>
<div class="method">
<code class="details" id="delete">delete(name, requestId=None, x__xgafv=None)</code>
<pre>Deletes the interactive session resource. If the session is not in terminal state, it is terminated, and then deleted.
Args:
name: string, Required. The name of the session resource to delete. (required)
requestId: string, Optional. A unique ID used to identify the request. If the service receives two DeleteSessionRequest (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.DeleteSessionRequest)s with the same ID, the second request is ignored.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is false, it means the operation is still in progress. If true, the operation is completed, and either error or response is available.
"error": { # The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC (https://github.com/grpc). Each Status message contains three pieces of data: error code, error message, and error details.You can find out more about this error model and how to work with it in the API Design Guide (https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the name should be a resource name ending with operations/{unique_id}.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as Delete, the response is google.protobuf.Empty. If the original method is standard Get/Create/Update, the response should be the resource. For other methods, the response should have the type XxxResponse, where Xxx is the original method name. For example, if the original method name is TakeSnapshot(), the inferred response type is TakeSnapshotResponse.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}</pre>
</div>
<div class="method">
<code class="details" id="get">get(name, x__xgafv=None)</code>
<pre>Gets the resource representation for an interactive session.
Args:
name: string, Required. The name of the session 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.
"createTime": "A String", # Output only. The time when the session was created.
"creator": "A String", # Output only. The email address of the user who created the session.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for the session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"authenticationConfig": { # Authentication configuration for a workload is used to set the default identity for the workload execution. The config specifies the type of identity (service account or user) that will be used by workloads to access resources on the project(s). # Optional. Authentication configuration used to set the default identity for the workload execution. The config specifies the type of identity (service account or user) that will be used by workloads to access resources on the project(s).
"userWorkloadAuthenticationType": "A String", # Optional. Authentication type for the user workload running in containers.
},
"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. The labels to associate with the session. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must 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", # Identifier. The resource name of the session.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for the 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.
},
"runtimeInfo": { # Runtime information about workload execution. # Output only. Runtime information about session execution.
"approximateUsage": { # Usage metrics represent approximate total resources consumed by a workload. # Output only. Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
"acceleratorType": "A String", # Optional. Accelerator type being used, if any
"milliAcceleratorSeconds": "A String", # Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliDcuSeconds": "A String", # Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliSlotSeconds": "A String", # Optional. Slot usage in (milliSlot x seconds).
"shuffleStorageGbSeconds": "A String", # Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"updateTime": "A String", # Optional. The timestamp of the usage metrics.
},
"currentUsage": { # The usage snapshot represents the resources consumed by a workload at a specified time. # Output only. Snapshot of current workload resource usage.
"acceleratorType": "A String", # Optional. Accelerator type being used, if any
"milliAccelerator": "A String", # Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"milliDcu": "A String", # Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliDcuPremium": "A String", # Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliSlot": "A String", # Optional. Milli (one-thousandth) Slot usage of the workload.
"shuffleStorageGb": "A String", # Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"shuffleStorageGbPremium": "A String", # Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"snapshotTime": "A String", # Optional. The timestamp of the usage snapshot.
},
"diagnosticOutputUri": "A String", # Output only. A URI pointing to the location of the diagnostics tarball.
"endpoints": { # Output only. Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
"a_key": "A String",
},
"outputUri": "A String", # Output only. A URI pointing to the location of the stdout and stderr of the workload.
"propertiesInfo": { # Properties of the workload organized by origin. # Optional. Properties of the workload organized by origin.
"autotuningProperties": { # Output only. Properties set by autotuning engine.
"a_key": { # Annotatated property value.
"annotation": "A String", # Annotation, comment or explanation why the property was set.
"overriddenValue": "A String", # Optional. Value which was replaced by the corresponding component.
"value": "A String", # Property value.
},
},
},
},
"sessionTemplate": "A String", # Optional. The session template used by the session.Only resource names, including project ID and location, are valid.Example: * https://www.googleapis.com/compute/v1/projects/[project_id]/locations/[dataproc_region]/sessionTemplates/[template_id] * projects/[project_id]/locations/[dataproc_region]/sessionTemplates/[template_id]The template must be in the same project and Dataproc region as the session.
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"state": "A String", # Output only. A state of the session.
"stateHistory": [ # Output only. Historical state information for the session.
{ # Historical state information.
"state": "A String", # Output only. The state of the session at this point in the session history.
"stateMessage": "A String", # Output only. Details about the state at this point in the session history.
"stateStartTime": "A String", # Output only. The time when the session entered the historical state.
},
],
"stateMessage": "A String", # Output only. Session state details, such as the failure description if the state is FAILED.
"stateTime": "A String", # Output only. The time when the session entered the current state.
"user": "A String", # Optional. The email address of the user who owns the session.
"uuid": "A String", # Output only. A session UUID (Unique Universal Identifier). The service generates this value when it creates the session.
}</pre>
</div>
<div class="method">
<code class="details" id="list">list(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)</code>
<pre>Lists interactive sessions.
Args:
parent: string, Required. The parent, which owns this collection of sessions. (required)
filter: string, Optional. A filter for the sessions to return in the response.A filter is a logical expression constraining the values of various fields in each session resource. Filters are case sensitive, and may contain multiple clauses combined with logical operators (AND, OR). Supported fields are session_id, session_uuid, state, create_time, and labels.Example: state = ACTIVE and create_time < "2023-01-01T00:00:00Z" is a filter for sessions in an ACTIVE state that were created before 2023-01-01. state = ACTIVE and labels.environment=production is a filter for sessions in an ACTIVE state that have a production environment label.See https://google.aip.dev/assets/misc/ebnf-filtering.txt for a detailed description of the filter syntax and a list of supported comparators.
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 interactive sessions.
"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.
"sessions": [ # Output only. The sessions from the specified collection.
{ # A representation of a session.
"createTime": "A String", # Output only. The time when the session was created.
"creator": "A String", # Output only. The email address of the user who created the session.
"environmentConfig": { # Environment configuration for a workload. # Optional. Environment configuration for the session execution.
"executionConfig": { # Execution configuration for a workload. # Optional. Execution configuration for a workload.
"authenticationConfig": { # Authentication configuration for a workload is used to set the default identity for the workload execution. The config specifies the type of identity (service account or user) that will be used by workloads to access resources on the project(s). # Optional. Authentication configuration used to set the default identity for the workload execution. The config specifies the type of identity (service account or user) that will be used by workloads to access resources on the project(s).
"userWorkloadAuthenticationType": "A String", # Optional. Authentication type for the user workload running in containers.
},
"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. The labels to associate with the session. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must 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", # Identifier. The resource name of the session.
"runtimeConfig": { # Runtime configuration for a workload. # Optional. Runtime configuration for the 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.
},
"runtimeInfo": { # Runtime information about workload execution. # Output only. Runtime information about session execution.
"approximateUsage": { # Usage metrics represent approximate total resources consumed by a workload. # Output only. Approximate workload resource usage, calculated when the workload completes (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).Note: This metric calculation may change in the future, for example, to capture cumulative workload resource consumption during workload execution (see the Dataproc Serverless release notes (https://cloud.google.com/dataproc-serverless/docs/release-notes) for announcements, changes, fixes and other Dataproc developments).
"acceleratorType": "A String", # Optional. Accelerator type being used, if any
"milliAcceleratorSeconds": "A String", # Optional. Accelerator usage in (milliAccelerator x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliDcuSeconds": "A String", # Optional. DCU (Dataproc Compute Units) usage in (milliDCU x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliSlotSeconds": "A String", # Optional. Slot usage in (milliSlot x seconds).
"shuffleStorageGbSeconds": "A String", # Optional. Shuffle storage usage in (GB x seconds) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"updateTime": "A String", # Optional. The timestamp of the usage metrics.
},
"currentUsage": { # The usage snapshot represents the resources consumed by a workload at a specified time. # Output only. Snapshot of current workload resource usage.
"acceleratorType": "A String", # Optional. Accelerator type being used, if any
"milliAccelerator": "A String", # Optional. Milli (one-thousandth) accelerator. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"milliDcu": "A String", # Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliDcuPremium": "A String", # Optional. Milli (one-thousandth) Dataproc Compute Units (DCUs) charged at premium tier (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing)).
"milliSlot": "A String", # Optional. Milli (one-thousandth) Slot usage of the workload.
"shuffleStorageGb": "A String", # Optional. Shuffle Storage in gigabytes (GB). (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"shuffleStorageGbPremium": "A String", # Optional. Shuffle Storage in gigabytes (GB) charged at premium tier. (see Dataproc Serverless pricing (https://cloud.google.com/dataproc-serverless/pricing))
"snapshotTime": "A String", # Optional. The timestamp of the usage snapshot.
},
"diagnosticOutputUri": "A String", # Output only. A URI pointing to the location of the diagnostics tarball.
"endpoints": { # Output only. Map of remote access endpoints (such as web interfaces and APIs) to their URIs.
"a_key": "A String",
},
"outputUri": "A String", # Output only. A URI pointing to the location of the stdout and stderr of the workload.
"propertiesInfo": { # Properties of the workload organized by origin. # Optional. Properties of the workload organized by origin.
"autotuningProperties": { # Output only. Properties set by autotuning engine.
"a_key": { # Annotatated property value.
"annotation": "A String", # Annotation, comment or explanation why the property was set.
"overriddenValue": "A String", # Optional. Value which was replaced by the corresponding component.
"value": "A String", # Property value.
},
},
},
},
"sessionTemplate": "A String", # Optional. The session template used by the session.Only resource names, including project ID and location, are valid.Example: * https://www.googleapis.com/compute/v1/projects/[project_id]/locations/[dataproc_region]/sessionTemplates/[template_id] * projects/[project_id]/locations/[dataproc_region]/sessionTemplates/[template_id]The template must be in the same project and Dataproc region as the session.
"sparkConnectSession": { # Spark connect configuration for an interactive session. # Optional. Spark connect session config.
},
"state": "A String", # Output only. A state of the session.
"stateHistory": [ # Output only. Historical state information for the session.
{ # Historical state information.
"state": "A String", # Output only. The state of the session at this point in the session history.
"stateMessage": "A String", # Output only. Details about the state at this point in the session history.
"stateStartTime": "A String", # Output only. The time when the session entered the historical state.
},
],
"stateMessage": "A String", # Output only. Session state details, such as the failure description if the state is FAILED.
"stateTime": "A String", # Output only. The time when the session entered the current state.
"user": "A String", # Optional. The email address of the user who owns the session.
"uuid": "A String", # Output only. A session UUID (Unique Universal Identifier). The service generates this value when it creates the session.
},
],
}</pre>
</div>
<div class="method">
<code class="details" id="list_next">list_next()</code>
<pre>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.
</pre>
</div>
<div class="method">
<code class="details" id="terminate">terminate(name, body=None, x__xgafv=None)</code>
<pre>Terminates the interactive session.
Args:
name: string, Required. The name of the session resource to terminate. (required)
body: object, The request body.
The object takes the form of:
{ # A request to terminate an interactive session.
"requestId": "A String", # Optional. A unique ID used to identify the request. If the service receives two TerminateSessionRequest (https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.TerminateSessionRequest)s with the same ID, the second request is ignored.Recommendation: Set this value to a UUID (https://en.wikipedia.org/wiki/Universally_unique_identifier).The value must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), and hyphens (-). The maximum length is 40 characters.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is false, it means the operation is still in progress. If true, the operation is completed, and either error or response is available.
"error": { # The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC (https://github.com/grpc). Each Status message contains three pieces of data: error code, error message, and error details.You can find out more about this error model and how to work with it in the API Design Guide (https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the name should be a resource name ending with operations/{unique_id}.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as Delete, the response is google.protobuf.Empty. If the original method is standard Get/Create/Update, the response should be the resource. For other methods, the response should have the type XxxResponse, where Xxx is the original method name. For example, if the original method name is TakeSnapshot(), the inferred response type is TakeSnapshotResponse.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}</pre>
</div>
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